a case study of uttarakhand

Flash Flood in Himalayan Region of Uttrakhand (A Case Study of Kedarnath Flood 2013 and Rishi Ganga Flash Flood, Reini Village 2021)

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• First Online: 22 July 2022
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• Nitesh Sharma 7 ,
• Kanchan Deoli Bahukhandi 8 &
• Siddiqui Nihal Anwar 8  

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The climate change significantly affect the glacial of Himalayan region. The flash floods are one of the most perilous climate-related disastrous events in the Himalayan region. Such floods grow under six hours after the rainfall that prompted risky circumstances for individuals and cause loss of life, property and environment. Just about seven years after such flash floods attacked the Kedarnath valley in Uttarakhand, around 5000 individuals were killed, and the scientists have cautioned that conditions were creating for a comparative misfortune going to happen in the district again. The cloudburst situation on every next day had occurred mainly in the Uttarakhand caused decimating floods and landslides turning into the nation’s most exceedingly awful natural disaster event since the tsunami in the year of 2004, which was about 375% more than the benchmark rainfall during an ordinary rainstorm. Aside from the social, political, and affordable misfortunes, such natural disasters adjust the prior landscape of Kedarnath region. This paper provided the satellite data for the year 2007, 2013, and 2019. The information and data are compared with before the event of the flash flood and after the flash flood and its impact caused alongside. The comparative analysis have also been carried out by using the GIS and Remote Sensing techniques by comparing before and after flash flood event.

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Sharma, N., Bahukhandi, K.D., Anwar, S.N. (2022). Flash Flood in Himalayan Region of Uttrakhand (A Case Study of Kedarnath Flood 2013 and Rishi Ganga Flash Flood, Reini Village 2021). In: Bahukhandi, K.D., Kamboj, N., Kamboj, V. (eds) Environmental Pollution and Natural Resource Management . Springer Proceedings in Earth and Environmental Sciences. Springer, Cham. https://doi.org/10.1007/978-3-031-05335-1_19

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Role of Tourism on Disaster Recovery: A Case Study of Uttarakhand, India

29 Pages Posted: 17 Jan 2023

Shivani Chouhan

Indian Institute of Technology (IIT), Roorkee

Annegret H. Thieken

University of Potsdam

Philip Bubeck

Mahua mukherjee.

The Indian Himalayan Region (IHR) is a tectonically active region, making it susceptible to natural and man-made disasters. The Himalayan state of Uttarakhand has a history of disasters that cause huge loss of life and property every year. Tourism plays an imperative role in the state's economy due to its natural resources and pilgrimage sites. To foster tourism, the Government of India proposed the Char-Dham National Highway project to connect the four major pilgrimage sites with other tourist destinations. However, development projects related to tourism, such as road construction, blasting, muck disposal, deforestation, etc., may even increase the frequency of disasters. Hence, this study examines how tourism contributes to disaster impact and recovery. A survey of 716 households was conducted in 32 villages in Uttarakhand where major disasters happened in the past decade. Using the MannWhitney U test, differences between households on-touristic and off-touristic routes are highlighted. The findings revealed that people in both categories have suffered the same harsh effect of disasters, but their socioeconomic conditions are significantly different. Overall, disaster recovery in off-touristic route villages appears to be slower than in on-touristic route villages because of a lack of livelihood opportunities, alternative income sources, poverty, and a lack of disaster coping skills. A special recovery assistance is needed for off-touristic route villages as they are more vulnerable to hazards. Thus, developing sustainable tourism solutions with resilient planning is an important step in improving disaster resilience of hill communities.

Keywords: tourism, Disaster Recovery, Disaster Impact, Indian Himalayas, MultiHazards

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Shivani Chouhan (Contact Author)

Indian institute of technology (iit), roorkee ( email ).

DOMS Indian Institute of Technology Roorkee Roorkee India

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• Published: 25 March 2024

Understanding flash flooding in the Himalayan Region: a case study

• Katukotta Nagamani 1 ,
• Anoop Kumar Mishra 1 , 2 ,
• Mohammad Suhail Meer 1 &
• Jayanta Das 3  

Scientific Reports volume  14 , Article number:  7060 ( 2024 ) Cite this article

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• Climate sciences
• Cryospheric science
• Natural hazards

The Himalayan region, characterized by its substantial topographical scale and elevation, exhibits vulnerability to flash floods and landslides induced by natural and anthropogenic influences. The study focuses on the Himalayan region, emphasizing the pivotal role of geographical and atmospheric parameters in flash flood occurrences. Specifically, the investigation delves into the intricate interactions between atmospheric and surface parameters to elucidate their collective contribution to flash flooding within the Nainital region of Uttarakhand in the Himalayan terrain. Pre-flood parameters, including total aerosol optical depth, cloud cover thickness, and total precipitable water vapor, were systematically analyzed, revealing a noteworthy correlation with flash flooding event transpiring on October 17th, 18th, and 19th, 2021. Which resulted in a huge loss of life and property in the study area. Contrasting the October 2021 heavy rainfall with the time series data (2000–2021), the historical pattern indicates flash flooding predominantly during June to September. The rare occurrence of October flash flooding suggests a potential shift in the area's precipitation pattern, possibly influenced by climate change. Robust statistical analyses, specifically employing non-parametric tests including the Autocorrelation function (ACF), Mann–Kendall (MK) test, Modified Mann–Kendall, and Sen's slope (q) estimator, were applied to discern extreme precipitation characteristics from 2000 to 201. The findings revealed a general non-significant increasing trend, except for July, which exhibited a non-significant decreasing trend. Moreover, the results elucidate the application of Meteosat-8 data and remote sensing applications to analyze flash flood dynamics. Furthermore, the research extensively explores the substantial roles played by pre and post-atmospheric parameters with geographic parameters in heavy rainfall events that resulted flash flooding, presenting a comprehensive discussion. The findings describe the role of real time remote sensing and satellite and underscore the need for comprehensive approaches to tackle flash flooding, including mitigation. The study also highlights the significance of monitoring weather patterns and rainfall trends to improve disaster preparedness and minimize the impact of flash floods in the Himalayan region.

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Introduction.

The most significant challenges affecting a country's long-term social, economic, and environmental well-being stem from natural disasters. This includes extreme hydro-meteorological events like cloudbursts and excessive rainfall, which, due to their severe complications and intensity, have become a focal point of research, particularly in mountainous areas. The exploration of these events is crucial for developing strategies to mitigate their impact for mountainous region 1 . In the Himalayan context, the discernment of topographical intricacies assumes paramount importance due to their potential rapid escalation into calamitous events 2 . Consequently, a comprehensive understanding of hydrological challenges and water resource resilience becomes imperative, as these phenomena manifest in diverse catastrophic forms 3 . To delineate and analyze these hydrological challenges and resilience, hydrological modeling emerges as a crucial tool. The efficacy of such modeling is contingent upon the utilization of high-resolution geospatial data, particularly within the Soil and Water Assessment Tool (SWAT) framework. This integration enhances precision in water resource management, addressing the intricacies posed by the challenging Himalayan terrain 4 . This aligns with the study of Patel et al. 2022 5 , who concentrate on the 2013 Uttarakhand flash floods, underlining the importance of hydrological assessments and the development of disaster preparedness strategies in the region. The catastrophic nature of flash floods caused by cloud bursts and landslides in mountainous regions is highlighted as the most devastating natural disaster 6 . Instances of such disasters precipitate multifaceted consequences, encompassing loss of life, infrastructural degradation, and disruption of financial operations. Mitigating these adversities necessitates the systematic monitoring and analysis of flood events. A historical examination underscores the pivotal role of floods, emerging as the foremost impactful natural calamity, with an annual average impact on over 80 million individuals globally over the past few decades. The substantial global impact, as evidenced by floods contributing to annual economic losses exceeding US$11 million worldwide 7 , is further underscored by the difficulty in collecting information on land use, topography, and hydro-meteorological conditions. Anticipating an increased frequency of precipitation extremes and associated flooding in Asia, Africa, and Southeast Asia in the coming decades, this challenge has prompted a debate on the necessary adaptations in flood management policies to address this evolving reality 8 . India, facing the highest flood-related fatalities among Asian countries 9 , 10 , encounters heightened vulnerability to disaster threats. This susceptibility is further exacerbated by the country's extensive geographic variability, making the development and implementation of a climate response strategy considerably more challenging 11 .

The Indian Himalayan Region, being crucial to the national water, energy, and food linkage due to its variety of political, economic, social, and environmental systems, is uniquely vulnerable to hydro-meteorological catastrophes, including floods, cloudbursts, glacier lake eruptions, and landslides 12 , 13 , 14 , 15 . During monsoon season the cloud burst is increasing in the Himalayan region.This phenomenon is closely tied to the unique climatic conditions prevalent in the Himalayas during this period. Monsoons in this region bring intense and sustained rainfall, characterized by the convergence of moisture-laden air masses, especially from the Bay of Bengal, attributing to landslides, debris flows, and flash flooding 16 . These result in significant loss of life, property, infrastructure, agriculture, forest cover, and communication systems 17 . In 2013, the Himalayan state of Uttarakhand experienced devastating floods and landslides due to multiple heavy rainfall spells 17 , 18 . On February 7th, 2021, a portion of the Nanda Devi glacier in Uttarakhand's Chamoli district broke off, causing an unanticipated flood 19 , 20 , 21 . During this sudden flood, 15 people were killed, and 150 went missing. These disasters have disrupted the Himalayan ecology in several states, including Uttarakhand, and the cause and magnitude of these disasters have been made worse by human activities, including building highways, dams, and deforestation 22 . When we check the flood record of Uttarakhand, Himalaya, the area has experienced catastrophes during 1970, 1986, 1991, 1998, 2001, 2002, 2004, 2005, 2008, 2009, 2010, 2012, 2013, 2016, 2017, 2019, 2020, and 2021, making them among the most significant natural disasters to have struck Uttarakhand 16 , 21 .

The rising trend of the synoptic scale of Western Disturbance (WD) activity and precipitation extremes over the Western Himalayan (WH) region during the last few decades is the result of human-induced climate change, and these changes cannot be fully explained by natural forcing alone. This phenomenon is observed over the large expanse of the high-elevation eastern Tibetan Plateau, where a higher surface warming in response to climate change is noted compared to the western side 22 , 23 . Since the Industrial Revolution, the Himalaya and the Tibetan plateau have warmed at an increased rate of 0.2 degrees each decade (1951–2014) 24 . In the Himalayan region, the mean surface temperature has increased by almost 0.5˚C during 2000–2014. This alteration in climate (temperature) has resulted in a decrease in the amount of apples produced in low-altitude portions of the Himalaya. The warming of the planet is directly responsible for these effects. The Himalayan region has experienced a decline in pre-monsoon precipitation towards the end of the century, leading to new societal challenges for local farmers due to the socioeconomic shifts that have taken place 25 . Simultaneously, there has been an increase in the highest recorded temperature observed throughout the monsoon season. In tandem with heightened levels of precipitation, an elevation in the maximum attainable temperature has the potential to amplify the occurrence of torrential rainfall events during the monsoon season 26 . This long-term change in atmospheric parameters, known as climate change, may affect river hydrology and biodiversity. The associated shifts in climate pose a significant risk to hydropower plants if certain climate change scenarios materialize. As part of this broader context, the dilemma of spring disappearance should be thoroughly analyzed to provide scientific, long-term remedies and mitigation strategies for potential hydrogeological disasters. This is crucial due to the observed increase in the frequency of landslides, avalanches, and flash floods in recent years 24 .

El Niño–Southern Oscillation (ENSO) and Equatorial Indian Ocean Oscillation (EQUINOO) play a crucial role in the teleconnection of India's Monsoon, as well as in determining rainfall patterns and the occurrence of flash floods across different regions of India. At a regional level, a study was conducted to examine the impact of various types of climatic fluctuations on the onset dates of the monsoon. Northern India, specifically northern northwest India, referred to as SR15, consistently experiences a delayed start to its seasons, regardless of the climatic phase 27 . The occurrence of significant anomalies in sea surface temperatures (SST) in the tropical Pacific region, associated with ENSO and EQUINOO, is accompanied by large-scale tropical Sea Level Pressure (SLP) anomalies related to the Southern Oscillation (SO) 28 , 29 . The Equatorial Indian Ocean Oscillation (EIO) represents the oscillation between these two states, manifested in pressure gradients and wind patterns along the equator (EQUINOO).

The negative anomaly of the zonal component of surface wind in the equatorial Indian Ocean region (60°–90°, 2.5° S—2.5° N) is the foundation for the EQUINOO index 30 . Additionally, they demonstrated that between 1979 and 2002, any season with excessive rainfall or drought could be "explained" in terms of the favorable or unfavorable phase of either the EQUINOO, the ENSO, or both. For instance, in 1994, EQUINOO was favorable, but ENSO was negative, resulting in above-average rainfall in India. Conversely, ENSO was favorable, EQUINOO was unfavorable between 1979 and 1985, and India saw below-average rainfall. They, therefore, proposed that by combining those two climate indices, it would be possible to increase the predictability of rainfall during the Indian monsoon. The quantity of rainfall throughout a storm event that might cause a significant discharge in a particular river segment is known as a "rainfall threshold" 31 , 32 . Different techniques, indicators, and predictor variables can be used to derive rainfall thresholds. There are four categories of methodology: empirical, hydrological/hydrodynamic, probabilistic, and compound approaches. Empirical rainfall thresholds are among the most popular methods for constructing EWS in local, regional, and national areas 33 , 34 , 35 . Empirical methods use historical flood reports and rainfall amounts to perform a correlation analysis linking the frequency of event to the amount and length of essential precipitation 36 , 37 , 38 . Several empirical rainfall threshold curves may be found in literature from various countries 32 , 39 , 40 , 41 . Although this research concentrated on various shallow landslides and mudflows, flash flood risk systems can be set using actual rainfall thresholds 42 . Similarly, the principles of the Flood Risk Guideline (FFG) method serve as the foundation for hydrogeological precipitation limits 30 , 41 , 43 , 44 . The fundamental concept of FFG is to use reverse hydrologic modelling to identify the precipitation that produces the slightest flood flow at the basin outlet. Alerts are sent out whenever the threshold is exceeded for a specific time for the real-time actual daily rainfall or the precipitation forecast. This method needs data on precipitation collected using radar or real-time rainfall sensors 45 , 46 . Other threshold approaches for rainfall, however, require the same data. The modelling of various synthetic photographs, regionally dispersed models, and the prior soil moisture status have all been incorporated into the FFG, which is widely used worldwide 46 . Hydraulic models have been developed recently, allowing the threshold to be determined by the canal design, features, and the link between the achieved water table and the inundated area 47 , 48 .

Recent flood events underscore the inadequacy of relying solely on structural safeguards for comprehensive protection against such catastrophes. The imperative for an effective flood management approach becomes paramount to preemptively mitigate these calamities and ensure sustainable safety measures. The present study generates rainfall product that uses real-time satellite data from Meteosat-8 to summarize the significant short-lived localised multiple rainfall events that result flash flooding in the Nainital, Uttrakhand, during October 2021 48 . This method was utilized to investigate the flood events over J&K 2014 49 . Rajasthan in 2019 50 and Bihar and Assam in 2019 51 . This study introduces a pioneering approach by precisely measuring the peak rainfall hours and correlating them with daily rainfall, elucidating their direct correlation with flash flooding in the study area. A distinctive feature of this research is its integration of time series rainfall data with socioeconomic metrics to underscore the significant damage caused by a major flash flood incident. The exploration of the role of sheer slope in flooding provides a unique angle to flood dynamics. Additionally, the study delves into pre-atmospheric parameters specific to the study area that played a pivotal role in initiating flash flooding. By shedding light on these intricate details, this study establishes itself as a trailblazer in disaster mitigation strategies, emphasizing its pivotal role in advancing our understanding of flash flood dynamics and fortifying disaster response frameworks.

The economic and climatic conditions of India are intricately linked to the region of Himalaya, renowned for its delicate ecosystems and geological intricacies 52 . Spanning a vast area, the Indian, Himalaya is among the recent mountain ranges on the surface of earth, marked by the study delves into the vulnerability of the region of Himalaya, examining the intricate interplay of geographical and atmospheric parameters in flash flood occurrences. The area has susceptibility to geological hazards, topographical nuances, biodiversity, and water resource dynamics 53 . Geographically positioned between latitudes 28.44° to 31.28°N and longitudes 77.35° to 81.01°E, with elevations ranging from 7409 to 174 m, Uttarakhand, depicted in Fig.  1 , covers 53,483 square kilometers. Approximately 64% of the land is forested, and 93% is mountainous terrain, bordered by Himachal Pradesh, Uttar Pradesh, China, and Nepal. Serving as the source of major rivers, the state encompasses six significant basins: Yamuna, Alaknanda, Ganga, Kali, Bhagirathi, and Ramganga. Data analysis utilized Shuttle Radar Topographic Mission information obtained from Earth Explorer ( https://earthexplorer.usgs.gov ) via Arc GIS Version 10.5, as shown in Fig.  1 .

( a ) Showing Uttarakhand North western Himalayan state of India ( b ) Nainital district of Uttarakhand with Digital elevation model.

Climate characteristics

The climate of study area exhibits notable variations, ranging from humid subtropical conditions in the Terai region to tundra-like environments in the Greater Himalaya. Substantial transformations occur across the landscape, with high altitudes housing glaciers and lower elevations supporting subtropical forests. Annual precipitation contributes nourishing snowfall to the Himalaya, particularly above 3000 meters 54 . Temperature variations are influenced by elevation, geographical position, slope, and topographical factors. In March and April, southern areas experience average maximum temperature between 34 °C and 38 °C, with average minimum temperatures ranging from 20 °C to 24 °C. Temperatures peak in May and June, reaching up to 42 °C in the lowlands and around 30 °C at elevations exceeding two kilometers. A decline in temperatures begins in late September, reaching their lowest points in January and early February, with January being the coldest month. Southern regions and river valleys witness an average maximum temperature of approximately 20 °C and an average minimum temperature of about 6 °C, while elevation of 2 km above sea level range from 10 °C to 12 °C 55 .

Materials and methodology

Radar is used to collect the rainfall observation remotely. A rain gauge is a conventional method located on the ground for recording rainfall depth in millimeters. Radar systems and rain gauges are standard equipment for tracking significant rainfall events. If there is a widespread, uniform network of rain gauges, it is possible to monitor rainfall accurately unfortunately, there is no such system in Nainital, Uttarakhand, or other parts of India. With the diverse topography of Nainital, Uttrakhand, it is challenging to observe accuracy for extreme rainfall events using radar and rain gauge stations. Satellite observation is the only tool available for monitoring these events. The extreme rainfall event over Nainital, Uttarakhand, was tracked in this study using hourly measurements of rainfall from Meteosat-8 geostationary satellite data. Hourly rainfall measurement was estimated at five kilometres by integrating observation from the Meteosat-8 satellite with space-borne precipitation Radar (PR) from the tropical rainfall measuring mission (TRMM). To estimate rainfall using Meteosat-8 IR and water vapour (WV) channels at 5 km resolution, we have employed the rain index-based technique created by Mishra, 2012 48 . The techniques use TRMM (Tropical rainfall Measuring Mission), space-borne precipitation radar (PR), and Meteosat-8 multispectral satellite data to create the rain analysis. The technique uses Infrared and water vapour observation from Meteosat-8 on 17, 18 and 19 October 2021 to estimate the amount of rainfall over the Nainital, Uttarakhand. By using the infrared (IR) and water vapour (WV) channel observations from Meteosat-8, a new rain index (RI) was computed. The procedure for calculating the rain index is as follows. Non-rainy clouds are filtered out using spatial and temporal gradient approach and brightness temperature from thermal Infrared (TIR) and WV are collocated against rainfall from precipitation radar (PR) to derive non-rainy thresholds of brightness temperature from TIR and WV channels. Now TIR and WV rain coefficient is computed by dividing the brightness temperature from TIR and WV channels with non-rainy thresholds. The TIR ad WV, rain coefficient product, is defined as the rain index (RI). RI is collocated against rainfall from PR to develop a relationship between rainfall and RI using large data sets of heavy rainfall events during the monsoon season of multiple years. The following equation is developed between rain rate (RR) and RI:

Finally, the rainfall rate (RR) is calculated using Eq. ( 1 ). For the Indian subcontinent, a, b, and c are calculated as a = 8.4969, b = 2.7362, and c = 4.27. Using RI generated from Meteosat-8 measurements, this model may be used to estimate hourly rainfall.

The current equation (I) was verified using observations from a strong network of ground-based rain gauges. Hourly rain gauge readings over India during the south-west monsoon season were observed to have a correlation coefficient of 0.70, a bias of 1.37 mm/h, a root mean square error of 3.98 mm/h, a chance of detection of 0.87, a false alarm ratio of 0.13, and a skill score of 0.22 48 . The method used by Mishra 48 outperformed other methods for examining the diurnal aspects of heavy rain over India compared to currently available worldwide rainfall statistics. If both satellite spectral responses to the channels used to produce the rain signatures are similar, the equation developed to estimate rainfall using the rain signature from one satellite can also be used to estimate rainfall using the rain signature from another satellite.

Within the framework of this investigation, Meteosat-8 Second Generation (MSG) measurements were harnessed to scrutinize rainfall characteristics with a heightened focus on fine geographical and temporal scales. Employing the mentioned technique facilitated the calculation of spatial rainfall distribution, as well as the meticulous quantification of hourly and daily rainfall. Subsequently, a comprehensive analysis of cumulative rainfall was conducted, unraveling nuanced patterns and trends within the meteorological data. Following an in-depth examination of intense rainfall episodes, the atmospheric datasets, incorporating cloud optical thickness, total precipitable water vapor, and aerosol optical depth, were procured from Modern-Era Retrospective Analysis for Research and Applications, the National Centers for Environmental Prediction (NCEP), and the National Centre for Atmospheric Research (NCAR). These datasets underwent meticulous scrutiny to unravel the intricate interconnections between atmospheric parameters and heavy rainfall, specifically flash flooding, across the study area. The central objective was to decipher the meteorological conditions catalyzing the genesis of a low-pressure system, subsequently triggering heightened convective activities. To comprehend the dynamics of aerosols within the study domain, trajectory analysis through HYSPLIT was implemented, elucidating trajectories and dispersion patterns of aerosols for comprehensive insights. To comprehensively comprehend episodes of heavy rainfall in the Nainital region of Uttarakhand, particularly during the flash flooding events of October 2021, this study systematically delves into pre-flood parameters. The investigation focuses on Nainital and systematically analyzes time series rainfall data (Modern-Era Retrospective Analysis for Research and Applications) spanning from 2000 to 2021. Monthly rainfall for each year and the long-term mean (accumulated rainfall) were meticulously calculated. Robust statistical tests applied to the time series data unveiled trends, indicating a non-significant increase overall, except for a notable decrease in July. The study further integrates Shuttle Radar Topography Mission (SRTM) topographic data and the total number of cloud burst events ( https://dehradun.nic.in/ ) to elucidate the role of elevation in cloud burst occurrences. Exploring the relationship between elevation, annual rainfall, and maximum temperature, the research establishes critical links between heavy rainfall episodes, flash flooding, and associated loss of lives from 2010 to 2022. The study strategically correlates these aspects with time-series data, presenting instances of heavy rainfall and rapid-onset flooding. Utilizing Meteosat-8 data and remote sensing, our research pioneers dynamic flash flood analysis, shedding light on the pivotal roles played by atmospheric and geographic parameters. The time series precipitation data, spanning from 2001 to 2021, underwent rigorous trend analysis employing statistical methodologies, including Autocorrelation function (ACF), Mann–Kendall (MK) test, Modified Mann–Kendall test, and Sen's slope (q) estimator. These analyses were conducted to elucidate and characterize the prevailing trends within the rainfall dataset over the specified temporal interval.

Autocorrelation function (ACF)

Autocorrelation or serial dependency is one of the severe drawbacks for analyzing and detecting trends of time series data. The existence of autocorrelation in the time series data may affect MK test statistic variance (S) 56 , 57 . Hence, the ACF at lag-1 was calculated using the following equation.

where, \({r}_{k}\) denotes the ACF (autocorrelation function) at lag k, \({x}_{t}\) and \({x}_{p}\) is the utilized rainfall data, \(\overline{x}\) denotes the mean of utilized data \(\left({x}_{p}\right)\) , \(N\) signify the total length of the time-series ( \({x}_{p})\) , k refers to the maximum lag.

Mann–Kendall (MK) test

In hydroclimatic investigations, the MK test is extensively employed for evaluating trends 58 , 59 , 60 . The-MK test 61 , 62 was conferred by the World-Meteorological-Organization (WMO), which has a number of benefits 63 . The following equations can be used to construct MK test-statistic

In Eq. ( 5 ), n denotes the size of the sample, whereas \({x}_{p}\) and- \({x}_{q}\) denote consecutive data within a series.

The variance of \(S\) is assessed in the following way

whereas \({t}_{p}\) and \(q\) denotes the number of ties for the \({p}^{th}\) value. Equation ( 9 ) shows how to calculate Z statistic, the standardized-test for the MK test-(Z)

The trend's direction is indicated by the letter Z. A negative Z value specifies a diminishing trend and vice versa. The null hypothesis of no trend will be rejected when the absolute value of Z would be greater than 2.576 and 1.960 at 1% and 5% significant level.

Modified Mann–Kendall test

Hamed and Rao (1998) 64 introduced the modified MK test for auto-correlated data. In the case of auto-correlated data, variance (s) is underestimated 65 ; hence, the following correction factor \(\left(\frac{n}{{n}_{e}^{*}}\right)\) is proposed to deal with serially dependency data.

where \(n\) is the total number of observations and \({\rho }_{e}\left(f\right)\) denotes the autocorrelation function of the time series, and it is estimated using the following equation

Sen's slope (q) estimator

Sen 66 proposed the non-parametric technique to obtain the quantity of trends in the data series. The Sen’s slope estimator can calculate in the time series from N pairs of data using this formula

where \({Q}_{i}\) refers to the Sen’s slope estimator, \({x}_{n}\) and \({x}_{m}\) are scores of times \(n\) and \(m\) , respectively.

Results and discussion

The Himalaya, renowned for their massive size and elevated altitude, possess distinctive geological characteristics that render them vulnerable to sudden and intense floods 67 . These rapid floods are the outcome of a combination of natural and human factors, including geological movements, glacial lakes, steep topography, deforestation, alterations in land usage, and the monsoon season 68 . In the Himalayan region, the primary trigger for these abrupt floods is often linked to instances of cloud bursts accompanied by heavy rainfall episodes 69 . This study aims to provide insight into historical and recent instances of significant rainfall that have resulted in flash floods, while also examining the relationship between these events with atmospheric and other relevant factors. The study also elaborates on the discussion on flash flooding on the 17th, 18 and 19 October 2021. In Fig.  2 we have illustrated the elevation and cloud burst events that occurred between 2020 and 2021 across different districts in Uttarakhand, Himalaya. The elevation map (Fig.  2 ), was generated by Arc GIS 10.5. Using cloud burst data from ( https://dehradun.nic.in/ ). After statistical analyses, the same data was imported to Arc GIS 10.5 and was shown in the form of Fig.  2 . The figure underscores that the northern areas, located within the central portion of Uttarakhand, witnessed a higher frequency of cloud bursts compared to the southern areas. The observed divergence, attributed to steeper slopes in the northern region as opposed to the southern region, is further complemented by an intriguing revelation in our study 70 . Specifically, we noted significantly fewer cloud burst events in the areas of both lower and sharply higher elevations during the period of 2020–2021, particularly when compared with the occurrences at medium elevations from (1000 to 2500)m illustrated in Fig.  2 . Thus, emphasizing a noteworthy and substantiated relationship between cloud bursts and elevation 70 .

Location map of cloudbursts hit area from 2020 to 2021 over Uttrakhand.

Within the specified timeframe, a total of 30 significant cloudburst incidents were documented during 2020–2021, with 17 of these incidents transpiring in 2021. Among the districts, Uttarkashi recorded the highest number of cloudburst occurrences (07), trailed by Chamoli with 05 incidents, while Dehradun and Pithoragarh each registered 04 instances. Rudraprayag accounted for 03 incidents, whereas Tehri, Almora, and Bageshwar each reported 01 cloudburst occurrence, according to reports from the Dehradun District Administration and the India Meteorological Department in 2021.

Due to high topography, the area has faced many flash flood events in history. Figure  3 presents a graphical representation of the total monthly rainfall data for the Nainital district in Uttarakhand from 2000 to 2021. The graph reveals the amount of rainfall received each month throughout this period. A noteworthy observation from the graph is that most of the years between 2000 and 2021 experienced substantial rainfall, with the majority surpassing 300 mm. However, 2010 is an exceptional case of rainfall in the Nainital area. The region received an astounding 500 mm monthly rainfall during this particular year. This extraordinary amount of rainfall was unprecedented and broke the records of the last few decades. Such a significant monthly rainfall level had not been observed in the region for quite some time. The spike in rainfall during 2010 might have considerably impacted the local environment, water bodies, and overall hydrological conditions in the area. Given the intensity of the rainfall, It could have caused flooding, landslides, and other related hazards. The data presented in Fig.  3 is crucial for understanding the long-term trends and patterns of rainfall in Nainital over the past two decades. In Fig.  3 , another intriguing aspect emerges, shedding light on the fact that the South-west monsoon exhibits its peak rainfall during the months of June, July, August, and September across the study area.( https://mausam.imd.gov.in/Forecast/mcmarq/mcmarq_data/SW_MONS OON_2022_UK.pdf).The region could be subject to recurring heavy rainfall episodes, potentially resulting in flash flooding over specific temporal intervals.

Time series monthly rainfall of study area. J(January),F(February),M(March),A(April),M(May),Ju(June)Jl(July),Ag(August), S(September),Oc(October), N(November), D(December).

Figure  4 offers a visual representation of the long-term average of monthly recorded rainfall data in the study area from 2000 to 2021 to gain insight into the average rainfall during the same timeframe. The graph illustrates a significant rise in the average long-term rainfall within the study area. This increase is particularly notable during the months spanning from June to September. Notably, the figure underscores that during the years 2000 to 2021, the months of July and August in the area witnessed multiple heavy rainfall episodes due to monsoon. For these two months, the long-term average surpasses the 300 mm mark. In our results and discussion, we unravel the ramifications of persistent and substantial rainfall throughout these crucial months. The enduring deluge sets in motion a series of impactful consequences, ranging from escalated surface runoff and heightened river discharge to the looming specter of rapid flooding and landslides. This intricate web of effects intricately influences the stability of the soil, the vitality of vegetation, and the delicate balance within local ecosystems 71 . The findings highlighted in Fig. (3 and 4) underscore the critical significance of examining monthly rainfall data to comprehend the relationship with average monthly rainfall trends from (2000–2021) in the Himalayan region. The figure specifically draws attention to the months characterized by substantial rainfall, which may have result in disasters such as flash flooding and landslides. So we have concluded the study area may have received flash flooding by heavy rainfall during June to September (2000–2021).The daily rainfall data from 2001 to 2021 was allowed for non parametric trend analyses using Mann–Kendall test, Sen’s slope analysis. Modified Mann–Kendall and autocorrelation function for trend analysis.

Accumulated rainfall (Long-term mean) over the Study area.

Our analysis delved into daily rainfall data, downloaded from (ww.nasa.giovanni.com). We aimed to discern trends in key parameters, including monthly rainfall during the monsoon season (June to September), monsoon season data, annual rainfall, heavy rainfall events (> 50 mm/Day), and the number of wet days (> 2.5 mm/Day). Table 1 provides a comprehensive analysis of rainfall trends and extreme rainfall events from 2000 to 2021. In June, a negative autocorrelation was observed, and the findings are statistically significant at a 95% confidence level, so we considered modified MK test instead of original MK test. Employing the non-parametric Mann–Kendall test (MK/mMK) for trend analysis, our findings revealed a general non-significant increasing trend, with the exception of July, which exhibited a non-significant decreasing trend. Noteworthy was the significant increase in the number of wet days at a 0.05% significance level. Sen’s slope analysis further emphasized an annual increase in rainfall at a rate of 4.558 mm. These results provide valuable insights into the evolving rainfall patterns in the studied region, with implications for understanding climate variations.

Topographic influence on rainfall and temperature over the study area

Exploring the realm of abundant rainfall at lofty Himalayan elevations delves into the captivating interplay between topography and the dynamic shifts in atmospheric parameters. Our investigation ventures beyond the surface, intricately analyzing the elevations across diverse districts within our study area. Figure  5 serves as a visual gateway, unraveling the fascinating discourse on how these elevational nuances weave a compelling narrative of change, orchestrating the dance between rainfall patterns and temperature shifts across our meticulously examined landscape. Using Fig.  5 , we can correlate the significant relationship between the amount of rainfall and the topography over the Himalayan region of Uttarakhand. The figure distinctly delineates various districts of Uttarakhand, such as Bageshwar, Chamoli, Nainital, Pithoragarh, Rudraprayag, and Tehri Garhwal, positioned at elevations surpassing 7000 m. The presented data establishes a conspicuous correlation between the received rainfall and the elevated nature of these districts, showcasing those areas above 7000 m experience substantial annual rainfall exceeding 1500 mm. This correlation underscores the notable influence of elevation on the precipitation patterns in the Himalayan region. Higher elevations tend to attract more moisture from the atmosphere, leading to increased rainfall 72 .

Topographic influence on the atmospheric parameter (Temperature and rainfall).

Figure  5 , in conjunction with the citation of Rafiq et al. 2016 73 , emphasizes the significant connection between mean maximum temperature and elevation within the Himalayan region. The figure illustrates that as elevation increases, there is a corresponding decline in mean maximum temperature. This well-known phenomenon is called the "lapse rate," which describes the temperature decrease with rising altitude. Areas above 7000 m experience notably lower temperatures than those at lower elevations. The lapse rate is a fundamental climatic characteristic particularly relevant in mountainous terrains like the Himalaya. As air ascends along the slopes, it cools down due to decreasing atmospheric pressure, forming clouds through condensation. These clouds subsequently contribute to rainfall, as discussed in the study by Wang Keyi et al. 72 . Higher elevations experience a more pronounced temperature decrease, resulting in elevated rainfall levels.

The steep slopes in the Himalayan region significantly correlate with the number of casualties resulting from cloud bursts, landslides, and flash floods caused by heavy rainfall events. The presence of steep gradients exacerbates the impact of sudden and intense rainfall, leading to flash floods and landslides. Topography is crucial in disasters, particularly flash flooding and landslides, commonly observed in the Himalayan region 2 . These natural disasters have resulted in substantial loss of life and livelihood, as depicted in Fig.  6 .  Over 300 casualties were reported due to landslides, flash flooding, and cloud bursts in Uttarakhand during 2021. From 2010 and 2013, the loss was restricted to nearly 230 causalities each year. The Himalayan steep gradients are especially vulnerable to the effects of rainfall and climate change 74 .

Number of human lives lost during heavy rainfall episodes in Uttrakhand.

Moreover, these mountainous regions' ecological and socioeconomic systems are becoming increasingly vulnerable due to the rising human population 2 . These disasters cause severe damage to infrastructure, properties, human lives, and the environment. Furthermore, they can exacerbate other hardships, including the spread of diseases, financial instability, environmental degradation, and social conflicts 74 .

In summary, the steep slopes in the Himalayan region play a critical role in the occurrence and severity of disasters such as flash floods and landslides. The susceptibility of these areas to heavy rainfall and climate impacts poses significant challenges for ecological and socioeconomic systems, particularly with the increasing human population. The aftermath of these disasters is far-reaching and extends beyond the immediate loss of life and property, affecting various aspects of human life and the environment in the region.

Flash flood event during October 2021

As delineated in Fig. 7 , our investigation reveals a distinctive pattern in precipitation dynamics. Traditionally, the region encounters heightened rainfall exclusively from June to September, aligning with the monsoon season. Flash flooding, consequently, primarily manifests during this period. However, the anomalous occurrence in October 2021 is unprecedented in our dataset. For the first time, our analysis, depicted in Fig.  7 , captures the manifestation of intense rainfall episodes leading to flash flooding in the Nainital region, Uttarakhand. As this was the rare case the study area has received heavy raifnall during month of october 2021. This may be due to western distribuance that area very rarely is receiving. The infrequency of such events in the area may be attributed to the rarity of western disturbances impacting the region. Utilizing the technique developed by Mishra 48 , we conducted the study to map daily monthly and spatial distribution of rainfall amount using Meteosat-8 data. The study employs real-time monitoring to track and analyze flash flooding, shedding light on the atmospheric parameters that contributed to the occurrence of this unique episode.

During October 2021, the region of Nainital, Uttarakhand experienced a series of rainfall events. From 12 to 15 September 2021, the area witnessed the development of low-pressure systems from the Bay of Bengal, as documented in the IMD Report 2021. This convergence of low-pressure systems led to several episodes of heavy rainfall over the Himalayan region 74 . Unfortunately, the consequences of these multiple rainfall episodes were severe, causing flash flooding and triggering landslides in various parts of the Indian Himalaya. Over the past few decades, there has been a noticeable upward trend in flash flooding incidents, particularly in the Himalayan region, which can be attributed to the effects of climate change 75 . As global temperatures rise and weather patterns become more erratic, the delicate balance of the Himalayan ecosystem is being disrupted, leading to intensified rainfall events and a higher risk of natural disasters like flash floods and landslides. These alarming changes underscore the urgent need for climate action and measures to address the impacts of climate change on vulnerable regions like the Himalaya. In October 2021, Nainital, Uttarakhand experienced an unusual and devastating flood event, an occurrence that is typically rare during this particular month. The torrential floodwaters swept away numerous homes and disrupted transportation networks, leaving the region in turmoil. In response to this calamity, various defence groups, such as the army and national defense forces, were promptly deployed to the Himalayan state to conduct rescue operations for residents and tourists. The impact of the flood was further exacerbated by landslides, which severed many districts from the rest of the region, as roads were blocked by mud and debris. The region's vulnerability to such natural disasters can be traced back to historical records, as it has been experiencing substantial rainfall since as early as 1857 76 . During 17th, 18th, and 19th of October 2021 a series of heavy rainfall episodes in Nainital, Uttarakhand, leading to flash flooding and landslides. The dire consequences resulted in widespread destruction of both lives and livelihoods 2 . Figure  7 highlights the visual representation of rainfall distribution over three days. The illustration provides valuable insights into the amount and pattern of rainfall that occurred during this critical period. Notably, the data reveals a remarkable occurrence on the 18th and 19th of October, where the study area experienced an abrupt 270 mm of rainfall. This substantial rainfall in just two days is an alarming and unprecedented event, signifying the intensity and severity of the weather system that hit the region. Moreover, it is essential to note that the 270 mm rainfall figure is not solely confined to those two days but is the cumulative result of heavy rainfall from multiple rainy spells that persisted during the specified period. The confluence of these rain events led to an overwhelming deluge, which became a primary driver of the extreme flooding that engulfed Nainital, Uttarakhand.

Time series heavy rainfall episodes over the Study area.

The analysis of near real-time monitoring of flash flooding in the area involved examining pre-flood atmospheric data related to aerosol optical depth, cloud optical thickness and total perceptible water vapour over the study area, as depicted in Fig.  8 b,c,d. The study revealed a significant correlation between the pre-flood atmospheric data and the occurrence of extreme and multiple rainfall episodes in the region. This indicates that cloud formation and the presence of moisture are closely linked to the presence of aerosol particles 77 . The analysis of aerosol data in the study area revealed a significant presence of aerosol content in the atmosphere before the flood. This observation was particularly evident from the data recorded between the 5th and 8th of October 2021, as depicted in Fig.  8 . The aerosol optical depth during this period was measured to be around 0.8, a noteworthy value for its potential impact in inducing heavy rainfall and flash flooding 78 , 79 . Aerosols are tiny particles suspended in the air, which can have important implications for weather and climate patterns 80 .  High aerosol optical depth, as indicated by the measurement of 0.8, suggests a relatively dense concentration of aerosol particles in the atmosphere during the specified timeframe. Such high aerosol levels can act as cloud condensation nuclei, providing necessary sites for water vapour to condense and form cloud droplets. This phenomenon is crucial for cloud formation and rainfall processes 81 .  The significance of aerosols in cloud formation lies in their ability to serve as nuclei for the aggregation of water vapour, leading to the development of clouds. This thick cloud cover resulted in considerable precipitable water vapour from the 17th to 19th of October, as shown in Fig.  8 82 , 83 . These atmospheric parameters resulted in favorable conditions for extreme with multiple rainfall episodes over the study area from 17 to 19th October 2021,finally, the extreme rainfall episodes attributed to flash flooding over the Nainital, Uttarakhand.

( a ) Cumulative rainfall over the Nanital Utrankhand, ( b ) Aerosol optical depth over the Nanital Utrankhand, ( c ) Cloud optical thickness over the Nanital Utrankhand, ( d ) Total Perceptible water Vapor over the Nanital Utrankhand.

When moisture condenses around aerosol particles, it contributes to the formation of larger cloud droplets. These larger droplets can result in more intense rainfall events, potentially leading to flash flooding under certain conditions 82 , 83 . Furthermore, the HYSPLIT trajectory analysis revealed a profound influence of air masses originating or passing through western regions on the Himalayan radiation budget. This suggests that atmospheric dynamics from these areas significantly impact the weather patterns and climate in the Himalayan region. To gain deeper insights into the role of aerosols in the Himalayan radiation budget, the study also examined the Atmospheric Radiative Forcing (ARF) 14 . In the investigation of aerosol data, a backward trajectory analysis was conducted depicted in Fig.  9 , focusing on the 17th and 18th of October 2021. The analysis aimed to trace the movement and direction of aerosols in the atmosphere 48 h before reaching the target area encircled in Fig.  9 . The findings of figure demonstrated journey of aerosol during these days, shedding light on their movement and behavior in the study area. Specifically, on the 17th of October, the source of aerosols was observed at an altitude of 3500 m above Mean Sea Level (MSL). The tracked trajectory of aerosols reveals a gradual descent from an initial altitude of 3500 m above Mean Sea Level (MSL), ultimately reaching the research target at 1096 m MSL. This horizontal movement of aerosols suggests a potential influential role in the occurrence of heavy rainfall that result flash flooding over the study area by providing the favorable atmospheric conditions.

Backward trajectory of Aerosol during 17th, 18th and 19th October 2021 over the study area source encircled.

The comprehensive analysis conducted in this study has significantly advanced our understanding of the intricate interactions between various atmospheric parameters, aerosols, and rainfall patterns, all of which collectively contribute to heavy with multiple rainfall episodes that resulted flash flooding event in the Nainital region of Uttarakhand. The severity of such flash floods is starkly evident from the tragic loss of fifty lives and the extensive damage to property and infrastructure.

A key highlight of this study is the application of remote sensing data, including total aerosol optical depth, cloud cover thickness, total precipitable water vapour, and rainfall product (Meteosat-8), for real-time monitoring of flash floods. The use of cutting-edge satellite technology and geospatial data has proven to be pivotal in closely monitoring and tracking flash floods, enabling timely and efficient responses to mitigate the impact of these disasters. The findings of this research underscore the vital importance of leveraging advanced technology and scientific research to address the challenges posed by flash flooding in the Himalayan region. To effectively combat these challenges, a comprehensive and multi-faceted approach is imperative. This may encompass implementing measures to counteract the impact of climate change on weather patterns, advocating for sustainable land use practices to reduce vulnerability, and bolstering the resilience of critical infrastructure to withstand the impacts of extreme weather events like flash floods.

Furthermore, the study presents a unique occurrence in the Nainital region of Uttarakhand, Himalaya, wherein heavy rainfall, marked by multiple episodes, led to flash flooding during October 2021, an unusual event when compared to the time series precipitation analyzed in the study. The investigation emphasizes the significant role of elevation in influencing rainfall and temperature variations in the region. The study emphasizes the significance of continuous scientific research and monitoring efforts to gain invaluable insights into the underlying patterns and drivers of flash flooding in the Himalaya. Armed with this knowledge, authorities can formulate robust strategies and policies to minimize the impact of future flash floods and safeguard the lives and livelihoods of the communities residing in the region. This study reaffirms the crucial role that satellite data and geospatial technology play in effective disaster management. It underscores the urgency of adopting proactive measures to address the mounting risks of flash floods in vulnerable regions like Nainital, Uttarakhand. By synergizing scientific research, advanced monitoring techniques, and community engagement, authorities can work towards building a more resilient future, better equipped to respond to and mitigate the repercussions of flash flooding events.

With their immense size and unique geological features, the Himalaya are prone to flash flooding incidents that pose significant risks to human life and infrastructure. Natural factors, such as tectonic activities and glacial lakes, and human-induced changes, including deforestation and land use alterations, influence these flash floods. In the Nainital region of Uttarakhand, the primary cause of flash floods is often attributed to cloud bursts accompanied by heavy rainfall episodes. The study highlights the crucial role of rainfall product and remote sensing data including total aerosol optical depth, cloud cover thickness and total precipitable water vapour, in real-time short-lived flash flood monitoring. The study emphasizes the significant role of elevation in influencing rainfall and temperature variations in the region. The application of satellite technology and geospatial data has proven to be instrumental in promptly tracking and responding to flash flood events. A comprehensive approach is necessary to address the challenges of flash flooding in the Himalaya. This may involve implementing measures to mitigate the impact of climate change, promoting sustainable land use practices, and enhancing infrastructure resilience. The study highlights a significant shift in precipitation patterns of Nainital, with usual heightened rainfall and flash floods. The rarity of such events in the region may be linked to infrequent western disturbances.

The research contributes valuable historical data and insights into the patterns of heavy rainfall and flash floods in the region. It underscores the alteration in precipitation patterns attributed to variations in atmospheric parameters over the study area. The findings demonstrate continuous monitoring and scientific research are critical for developing effective strategies to mitigate the impact of flash floods and safeguard communities in vulnerable regions like Nainital Uttarakhand. Overall, this study emphasizes the urgent need for climate action and proactive measures to address the rising risks of flash floods. By integrating advanced technology, scientific research, and community engagement, authorities can work towards building a more resilient future and better preparedness to tackle extreme weather events ( Supplementary Information ).

Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.

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Nagamani, K., Mishra, A.K., Meer, M.S. et al. Understanding flash flooding in the Himalayan Region: a case study. Sci Rep 14 , 7060 (2024). https://doi.org/10.1038/s41598-024-53535-w

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Understanding the Chamoli flood: Cause, process, impacts, and context of rapid infrastructure development

23 mins Read

Prepared by: Arun B. Shrestha , Jakob Steiner , Santosh Nepal , Sudan B. Maharjan , Miriam Jackson , Ghulam Rasul , and Birendra Bajracharya

1. Background

Disaster struck Uttarakhand’s Chamoli District on 7 February 2021, when a massive flash flood ravaged through the valleys of the Rishi Ganga, Dhauliganga and Alaknanda rivers. More than 70 people have been confirmed dead and another 134 people reported missing . The flood swept away the unfinished Tapovan Vishnugad Hydropower Project and inflicted substantial damage on the Rishi Ganga Hydropower Project. Even as rescue and relief efforts were underway, a glacial lake outburst flood (GLOF) was suggested as the reason for the flood, possibly triggered by glacier collapse. Some reports even used the term “glacier burst”, possibly referring to a GLOF. In the immediate aftermath of the event, ICIMOD decided not to comment on the cause of the flood for two reasons. Firstly, while understanding the cause is important to identify possibilities of similar hazards in this and other areas, the priority in the first few days and weeks should be rescue and relief. Secondly, as a regional knowledge institution, we felt it important to verify and corroborate all available information to come up with a credible reason for the flood. Now, two weeks after the event, we have adequate information to present our understanding of this flood event. The purpose of this report is to share our understanding of the cause and downstream propagation of the flood. The report also touches upon the cascading nature of floods, the challenges to infrastructre development, and the need to consider environmental sustainability while planning infrastructure development in fragile mountain environments.

Key messages

• The Chamoli flood was not caused by a GLOF as there were no significant glacial lakes in the area
• The flood was triggered by a massive rockslide just below Ronti peak, of ~22 mio m 3 of rock mixed with ice and snow
• The energy of the fall melted the ice creating the source of flood. This remobilized the debris and ice on the valley floor deposited by previous events, pushed the stream water and created an excessive flood wave.
• A couple of days prior to this, a strong western disturbance resulted in heavy precipitation in the area, which increased the flood magnitude downstream
• Comprehensive monitoring of mountain environments is recommended
• Infrastructure in the flood path, particularly hydropower projects, exacerbated the impact of the flood. Infrastructure development in fragile mountain environments should consider a sustainability framework, including environmental sustainability

2. General description of the area

The flood event took place in the Tapovan area of Joshimath in Chamoli District, Uttarakhand State. The region consists of high mountain ranges with steep topography, including the second highest peak in India, Nanda Devi (7816 masl; Fig. 1). The mountain ranges are made up of high grade metamorphic and volcanic rocks . The Lower Himalaya Range to the south is composed of sedimentary and low-grade metamorphic rocks. The Chamoli flood occurred in an area about 60 km northeast of where the devastating Uttarakhand flash flood occurred in 2013 . The Chamoli flood took place on the Rishi Ganga River on the northern side of Nanda Ghumti peak (7050 masl). The Rishi Ganga is a tributary of the Dhauliganga River, which originates from the Raikhana Glacier (5375 masl) to the north and meets the Alaknanda River further downstream. The high-altitude area consists of glaciers and snow peaks which melt during the spring and summer season and provide meltwater to downstream areas. Because of the perennial sources of water and steep topography, hydropower plants have been constructed across many tributaries. Presently, about 3900 MW of hydroelectricity is generated in Uttarakhand, out of its estimated hydropower potential of 20,000 MW (Agrawal et al. 2017), with several under construction projects expected to add another 3200 MW .

Figure 1: (a) Location map showing rockslide origin and flood path along the Ronti Gad, Rishi Ganga, Dhauliganga and Alaknanda rivers. (b) Longitudinal profile of flow path including rockslide source area.

Figure 2: Average monthly temperature and precipitation of the area (1980-2019). Data source: ERA5 reanalysis

The climate of the area is characterised by warm-wet summers (June-September) and cold-wet winters (December-February). The difference between average monthly maximum and minimum temperature is about 20 o C, which is higher in the winter season compared to summer (Fig. 2). The area receives precipitation from both westerlies and the summer monsoon, with annual average precipitation around 1000 mm; of this, winter precipitation due to western disturbances contributes 28% and summer precipitation 42%.

3. The source of the flood

Figure 3: 3D view of the origin of the rockslide and the debris flow captured on a satellite image (CubeSat) at 10:30 IST, just before it reached the Tapovan Hydropower Project site (dotted black line shows the sediment deposited on the adjacent slopes of the river valley). The release zone of the rockslide is marked in red.

Figure 4: Pre (left) and post (right) event images showing scarp of the rockslide origin and its sliding surface along the joint plane, including directly impacted and sediment deposited area along the Ronti Gad River valley. The rockslide has an approximate width of 550 m at the upper edge at 5,500 masl (Images from Maxar portal accessed through the USAID SERVIR Programme; the post event image is from 10 February 2021).

a. Initial suggestions about the flood and counter arguments

As news and videos of the debris flow that hit the Tapovan Hydropower Project site around 10:30 IST on 7 February surfaced, initial suggestions were that a glacial lake must have burst . As the upstream areas from the location of the first videos were investigated, it quickly became clear that no lakes were present in the catchment prior to the event. Some media outlets even called it a “glacier burst” , a term not recognized by the scientific community. As the first high resolution images (taken by coincidence just as the debris flow passed the valley; see Figure 3) became available, approximately 7 hours after the event, it was clear that an avalanche, landslide or rockfall had happened approximately 22 km upstream of the hydropower site, just below Ronti peak in the Nanda Devi massif. The location of the source was clearly identifiable from the imagery (Figure 3) while no other source (flood paths, emptied lake, or avalanche scour) could be identified.

b. What we now think is the source of the flood

Based on available imagery and relying on published data, we are able to make approximate calculations of the mass movements that have taken place. We examined pre- and post-event imagery and found that a crack had formed prior to the event (Fig. 4 and 5) at the site where the rock detachment followed by a rockslide happened (Fig. 4). This failure eventually propagated along a 550 m wide crest starting at an elevation of 5500 masl reaching down to nearly 4500 masl. Analysis of elevation models pre- and post-event suggests that the scarp left by the rockslide is 150 m deep, 100 m on average and consists largely of rock and relatively little ice (Fig. 4). It is 39 ° steep, 1060 m long and has an area of ~ 350,000 m 2 . This results in an approximate volume of 22 mio m 3 , which corresponds with the DEM differencing that puts it at 25 mio m 3 . Relying on modelled glacier thickness (21 to 25 m for the three glacierettes in the inventory, which corresponds to typical heights of such hanging glaciers; Farinotti et al. 2019), we can estimate the fraction of rock to be 85% and ice 15% and calculate a total mass of ~52 * 10 9 kg. With a straight slide line of 1.6 km (5500 to 3900 masl), this results in total potential energy of 8.24 * 10 14 J.  This energy is converted to kinetic energy during the fall and dissipated as enough heat to melt 2.7 * 10 6 m 3 of ice (with 335 kJ per kg of ice necessary at 0 ° C). Considering that not all the mass was converted into energy during the fall, this number is likely a lot lower (Huggel et al. 2005). As Huggel et al. (2005) argue and has been conclusively shown in experiments (Arakawa 1999) and for a large co-seismic event (Eberhart-Phillips et al. 2003), fluidization can also happen simply from a very large impact on present ice, which possibly happened in this case.

Fig 5: A crack is visible at the top of the failure zone on 6 February, one day before the event. There is substantial snow on 6 February, but much of this had melted by 10 February, three days after the event.

During an ice avalanche in 2016, a volume of ~ 7.2 * 10 6 m 3 of ice was dislodged to the west of the rockslide in 2021, taking bed rock with it along the way, resulting in a mixed ice-debris deposit of ~1.5 * 10 7 m 3 . Sentinel-2 Imagery from 2 December 2020, when the area was not snow covered yet, shows that a large part of this deposit was still present in the valley below when the event on 7 February 2021 happened (Fig. 6). In a similar case in Langtang Valley in Nepal, a co-seismic avalanche resulted in a large compound deposit of ice, snow, and debris. As debris settles on top during the fall (as in the case here), ice was protected from melt by a debris layer of several metres thickness (Fujita et al. 2017; Kargel et al. 2016). A big part of the ice body is still present in Langtang even today, nearly 6 years later. As some of this ice body was still present just after the event below Ronti peak in 2021 (Fig. 5), we can conclude that a fraction of this previous deposit (< 7.2 * 10 6 m 3 ), was fluidized by the available energy. There are also reports from observers of the event of a pungent smell, suggesting water-saturated sediments were mobilised and added to the fluid content of the debris flow.

Figure 6: Location of the impact site of both the 2016 and 2021 events, on an image from 10 February 2021. On the right, between two small lakes, a body of ice is still visible covered in fresh debris. Note that the tongue of this glacier is many hundreds of metres upstream and therefore this ice is not connected to the main glacier body in the valley.

From the 200 to 400 m high surge of debris (h) on the adjacent headwalls below, we can estimate the velocity of the fall at between 60 and 90 m s -1 (Chow 1959; Evans et al. 2001, 1989; Pierson 1985). Assuming an average velocity for the resulting debris flow of ~20 m s -1 the debris flow took about 18 minutes to reach the Tapovan Hydropower Project site and was able to move ~1000 m 3 s -1 of water, assuming that only 75% of the energy from the rockslide was used to fluidize the deposited ice below. This would explain to a large part, how such a strong flood wave was able to reach downstream areas without a previous body of water being present.

c. What triggered the rockslide?

i. Precedent weather conditions A strong western disturbance passed across Kashmir and northwest India from 4 to 6 February 2021. It was fully charged with convective instability that may have contributed to the heavy precipitation. This unfortunate event occurred on 7 February. Numerical simulation of some of the attributes have been carried out which depict strong evidence of heavy precipitation contributing to high flows downstream. The analysis of wind pattern and geopotential height contours at 500hPa level indicate that the trough of an active westerly wave was passing over Kashmir and northwestern latitudes of India with a strong vorticity and convergence combination at the leading edge of the westerly. The trough of this western disturbance showed great potential of convective instability as severe Convective Available Potential Energy (CAPE) conditions were found on the rear end of the low pressure area. The numerical simulation on 4 February is presented in Figure 7 which shows heavy precipitation over that region. The western disturbance travelled with relatively slower speed and its stagnancy produced concentrated precipitation.

Figure 7: Precipitation on 4 February, 18:00 UTC (Source: WRF – 5 km numerical simulation by Pakistan Meteorological Department )

Precipitation data derived from Global Precipitation Measurement (GPM) Mission suggests that there were continuous precipitation events from 3 to 5 February which resulted in approximately 58 mm of cumulative precipitation(Fig. 7). Most of the precipitation in the high altitude areas of Chamoli would have occurred as snowfall.

ii. Climate change

Maximum temperature in the Chamoli area has increased at the rate of 0.032 o C per year between 1980 and 2018 which is statistically significant at 99.9% confidence level, compared to minimum temperature which has increased at 0.024 o C per year at 90% confidence level (Fig. 8).The trends were analysed using Mann–Kendall (MK) and Sen slope estimation (Kendall 1975; Mann 1945; Sen 1968). Furthermore, January 2021 was the warmest January on record in Uttarakhand for six decades. Note also the dramatic reduction in snow cover between 6 and 10 February as shown in Figure 4. While a hazard event like the flood at Chamoli cannot be directly attributed to climatic changes, the increased thaw-freeze cycle of permafrost could have partially contributed to the event.

Figure 8: Maximum temperature trends in the Chamoli area (Data source: ERA5 reanalysis data, 1980-2019).

iii. Other factors

At the same headwall, a large ice avalanche was previously released somewhere between 19 September and 9 October 2016, which deposited ~1.5 * 10 7 m 3 of ice and more bedrock in the valley below (Figure 9). The resulting destabilization of the rock due to the lack of ice cover (glacial debuttressing, stress-release fracturing), and increased exposure to solar radiation and hence an increased freeze thaw cycle, in combination with a large snowfall event preceding the event of 7 February 2021 and rapid melt water production, may have favoured the fracturing of rock. This can however not explain the depth of the fracture (~150 m), which must have evolved over a longer period of time. Fracture zones at the runout of the rockslide visible before the event suggest that such detachments have happened at the same location previously. Permafrost thaw and frost cracking has been used to explain increased rockfall activity in the Alps (Deline et al. 2015; Gruber and Haeberli 2007); however, that generally only applies for the first ~10 m of bedrock.

Figure 9: The ice avalanche breakoff between 19 September and 9 October 2016 (solid red outline on top) with the area covered by resulting deposits along the Ronti Gad River valley (dotted pink line) and flow surface (dotted yellow line). The green outline shows the present rockslide scarp.

As the debris moved downstream, it pushed running river water ahead of it, including water from small ponding structures along the river path. Besides, the water stored in the 60 metre long diversion dam of the Rishi Ganga Hydropower Project, including in its desilting chamber, should also have contributed to the flood water which was seen before the debris flow in the videos posted on social media.

4. Cascading impacts and environmental sustainability

The event and related debris flow/flood caused damage to four hydropower projects along the Rishi Ganga, Dhauliganga and Alaknanda river path (Table 1). The Rishi Ganga Hydropower Project (13.2 MW) near Raini village, located 14 km downstream from the impact site (Figure 10), was the first to be hit by the debris after the rockslide. The unfinished Tapovan Vishnugad Hydropower Project (520 MW) (Fig. 11), 8 km downsteam from Rishi Ganga Hydropower Project, was the second hydropower plant hit by the flood. The diversion dam of this run-of-the river type project faced massive damage from sedimentation and the dam was filled with debris, which can be seen in the remote sensing images taken before and after the event (Fig. 10 and 11).

Figure 10: Pre and post images from the MAXAR portal shows the Rishi Ganga Hydropower Project and bridge 700 m downstream of the hydropower site completely washed away (Images accessed through the USAID SERVIR Programme; the post event image is dated 10 February 2021)

Figure 11: Tapovan Vishnugad Hydropower dam site before and after the flood (10 February 2010). The dam is fully covered by debris. (Images accessed through the USAID SERVIR Programme)

Table 1: Hydropower projects affected by the Chamoli flood

As highlighted by the IPCC 2019 report (Hock et al. 2019), the mountainous regions are exposed to many cryosphere-related hazards. The frequency, magnitude and areas of these hazards are projected to change as the cryosphere continues to decline. The escalation of cascading hazards to a cascading disaster is a common phenomenon observed in the Hindu Kush Himalaya region (Cutter 2018; Vaidya et al. 2019). One of the prominent recent examples is the Uttarakhand flood of 2013, which started with heavy rainfall and caused a chain of events including landslides, flash floods, and the Chorabari lake outburst and debris flow, which killed more than 6,000 people and damaged roads, bridges, and buildings (Allen et al. 2016; Ray et al. 2016). Similar hazard events or in combination with other geophysical processes can damage several hydropower stations, which can be further exacerbated with future floods in the context of global climate change (Nie et al. 2021). Hock et al (2019) also suggest that snow avalanches involving wet snow even in winter will occur more frequently in the mountainous regions. Nie et al. (2021) reported 105 existing hydropower projects (HP) (≥ 40 MW) with an installed capacity of 37 GW, 61 projects (≥40 MW) currently under construction (39 GW) and 890 projects (≥10 MW) in various stages of planning (242 GW) in the Karakoram-Himalaya region. Most of the existing hydropower projects were built in the past two to three decades, mainly starting from the downstream sections. Now these projects are gradually moving upstream where the exposure to mountain hazards is high, the chances of multiple hazards happening in combination and occurring more frequently, and cascading effects can create compounding impacts on the system. Hydropower projects are particularly at risk because of the proximity of their infrastructure (such as diversion dams/reservoirs) to the river network where water-related hazards occur (Kumar and Katoch 2016). Many hydropower projects have been damaged by events like the Chamoli flood. For example, the Dig Tsho 1985 GLOF event in the Everest region, the 2015 earthquake, the 2014 Jure landslides, the 2013 Uttarkhand flood, and the 2016 Bhote Koshi GLOF (Nepal) damaged hydropower plants in Nepal and India (Vaidya et al. 2021). Conversely, hydropower infrastructure also impacts the local environment, causing changes in natural flow regimes and environmental flows, alteration of aquatic ecosystems, and deterioration of water quality, among others.

5. Conclusion and recommendations

The rockslide-triggered flash flood in Chamoli is one of many possible hazards in the HKH mountains. Mountain hazards like glacial lake outburst floods, torrential floods, debris flows, landslides, and avalanches, especially caused by the coupling of avalanches, glacier movement, snow melt, and extreme precipitation are common in this region. While this event cannot be directly attributed to climate change, it is well known that climate change can lead to increase in the frequency and severity of mountain hazards (Krishnan et al. 2019; Vaidya et al. 2019; Hock et al. 2019). It is necessary to carry out quantitative studies on the status of mountains, understand their formation mechanism, and monitor dynamic processes in order to have advance knowledge of impending hazard events and improve preparedness. These should be done through ground based research, analysis of geospatial information, and modelling. All these need sustained investments from national agencies including establishment of environmental monitoring, analysis and information systems. Collaborative efforts between institutions within the region and with international institutions can help in building robust systems and capacity within the region. The HKH is a multi-hazard environment. Often these hazards are of a cascading nature with multiple hazards interconnected with a primary hazard trigger and a chain of secondary and tertiary hazards. Human interference in the mountain environment is rapidly increasing. Mountain settlements are increasing in size and land use patterns are changing. Infrastructure such as roads and hydropower projects are rapidly penetrating mountain landscapes. The interplay between natural hazards with human settlements and infrastructure is an important aspect, which can significantly escalate the impacts of event like the Chamoli flood. Disaster risk management therefore needs to incorporate a multi-hazard risk assessment approach. In the aftermath of recent disaster events, the role of infrastructure, especially hydropower and its interplay with natural hazards has emerged as a topic of strong debate. These events have raised the question: Is hydropower a boon or bane? With the need to green the energy sector and the challenges with solar and wind energy, hydropower seemed to be a viable option. However, hydropower development faces multiple challenges. Apart from financial and technical challenges, it faces strong environmental and social challenges. On the environmental front, hydropower development impacts environmental flows, water quality, and the health of aquatic and terrestrial ecosystems. At the same time the physical environment poses many challenges to hydropower development and sustainability. Climate change related flow variations, extreme events, erosion and sedimentation, and GLOF/LDOFs, are some of the environmental challenges to hydropower. A comprehensive sustainability  framework considering financial, environmental and social sustainability can help make hydropower a viable energy option. Vaidya et al. (2021) argue that for the sustainability of hydropower in the HKH region, environmental threats need to be minimized by mitigating risk through both structural (e.g. erosion protection work) and non-structural measures (e.g. operating rules). Besides this, mitigating the risk of climate change and flow variability is of paramount importance for future energy security for which a better understanding of future climate projections and water availability is needed. That understanding can be reflected in the design and location consideration of future hydropower projects in the region.

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Arun B. Shrestha

Jakob Steiner

Santosh Nepal

Sudan B. Maharjan

Miriam Jackson

Ghulam Rasul

Birendra Bajracharya

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A Case Study Of Forest Fires In Uttarakhand And Adjoining Areas In India

https://doi.org/10.51514/JSTR.3.3.2021.62-70

Arin Gaur, Sapan Kumar, Vandita Srivastava, Sanjeev Kumar, Karan singh and Alok Sagar Gautam

Forest fires have been regular in Uttarakhand for a long time. This is one of the major disasters occur in the time of summers.   We had studied the fire activity for a period of two years and three months (i.e. JAN 2019 to MAR 2021). We have collected satellite data through GIOVANNI and FIRMS NASA using VIIRS, OMI and AIRS aboard Soumi NPP, Aura and Aqua satellites, respectively, for forest fire counts and their respective brightness, NO 2 , SO 2 , Ozone, and air temperature, for the rectangular area covered between coordinates 77.583E, 28.733N, 81.016E, 31.466N enclosing Uttarakhand state of India. We observed the year 2019 was a relatively quiet year as far as forest fire incidents are concerned. Fire events were detected in the months of May and June in 2019 but with a very high fire counts of nearly 2000 on some days. On the other hand, due to COVID-19 lockdown in the year 2020, with less human interventions, there are a less number of forest fires in summer. instead more fire events observed in winter due to an instant increase in the variables causing the fire, that continued in 2021 as well. These forest fires affect our atmosphere by releasing various pollutants such as NO 2 and SO 2 in addition to increasing the air temperature of the surrounding. We tried to understand the causes and the effects of forest fires along with their high activity period in the hilly areas of Uttarakhand having dense forest area that faces a high number of fires annually, either naturally occurring or of anthropogenic. It will help authorities and disaster management group to plan and prevent such events.

Keywords : Forest Fire, SO 2 , NO 2 , Ozone, Air Temperature, Covid-19, Uttarakhand .

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• Open access
• Published: 24 February 2022

Environmental and economic impact of cloudburst-triggered debris flows and flash floods in Uttarakhand Himalaya: a case study

• Vishwambhar Prasad Sati   ORCID: orcid.org/0000-0001-6423-3119 1 &
• Saurav Kumar 1  

Geoenvironmental Disasters volume  9 , Article number:  5 ( 2022 ) Cite this article

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This paper examines the environmental and economic impact of cloudburst-triggered debris flow and flash flood in four villages of Uttarkashi district, Uttarakhand Himalaya. On 18th July 2021 at 8:30 p.m., a cloudburst took place on the top of the Hari Maharaj Parvat, which triggered a huge debris flows and flash floods, affecting 143 households of four villages of downstream areas. Immediately after the cloudburst occurred, the authors visited four affected villages—Nirakot, Mando, Kankrari, and Siror. A structured questionnaire was constructed and questions were framed and asked from 143 heads of affected households on the impact of debris flows and flash floods on people’s life, settlements, cowsheds, bridges, trees, forests, and arable land in and around the villages. The volume of debris, boulders, pebbles, gravels, and mud was assessed. It was noticed that all four villages got lots of destructions in terms of loss of life—people and animals, and property damage—land, crops, and infrastructural facilities. This study shows that the location of the settlements along with the proximity of the streams, which are very violent during the monsoon season, has led to the high impact of debris flow on the affected villages. We suggest that the old inhabited areas, which are located in the risk zones, can be relocated and the new settlements can be constructed in safe places using suitability analyses.

Introduction

Cloudburst, a geo-hydrological hazard, refers to a sudden and heavy rainfall that takes place within a short span of time and a particular space (Sati 2013 ). The intensity of rainfall is often more than 100 mm/h (Das et al. 2006 ). The disruptive events, cloudbursts occur during the monsoon season in the Himalaya and trigger debris flows, flash floods, landslides, and mass movements (Fig.  1 ). Fragile landscape, rough and rugged terrain, and precipitous slope accentuate the magnitude of geo-hydrological hazards. Cloudburst-triggered debris flows, flash floods, landslides, and mass movements have become more intensive and frequent worldwide, mainly in the mountainous regions, causing large-scale destruction of people, land, and property (Houghton et al. 1996 ; Wang et al. 2014 ; Mayowa et al. 2015 ; Malla et al. 2020 ; Sim et al. 2022 ). Similarly, the Himalayan region is prone to the occurrences of cloudburst-triggered hazards, causing huge loss of life and property and degradation of forest and arable lands (Bohra et al. 2006 ; Allen et al. 2013 ; Balakrishnan 2015 ; Ruiz-Villanueva et al. 2017 ).

Cloudburst-triggered hazards in the Uttarakhand Himalaya

The Uttarakhand Himalaya, one of the integrated parts of the Himalaya, is the most fragile landscape and prone to geo-hydrological hazards—cloudbursts, avalanches, and glacier bursts (Sati 2019 ). It receives many hazards mainly cloudburst-triggered debris flows, flash floods, landslides, and mass movements during the monsoon season every year. The intensity, frequency, and severity of these hazards have been observed to increase during the recent past. Devi ( 2015 ) stated that the changing monsoon patterns and increasing precipitation in the Himalaya are associated with catastrophic natural hazards. However, these hazards are the least understood because of the remoteness of the areas and lacking meteorological stations (Thayyen et al. 2013 ).

The Uttarakhand Himalaya has many eco-sensitive zones, vulnerable to natural hazards mainly for geo-hydrological hazards. Every year, many cloudburst events occur here, cause to roadblocks, land degradation, forest and cropland loss, and losses of life and infrastructural facilities. One of the most devastating cloudburst-triggered debris flow events of this century occurred on the night of 16th and 17th June 2013 in the famous Hindu pilgrimage ‘Kedarnath’, which killed more than 10,000 people and devastated the entire Mandakini and Alaknanda river valleys (Upadhyay 2014 ; Sati 2013 ). The entire region had received 16 major geo-hydrological and terrestrial hazards within the last 50 years (Bhambri et al. 2016 ). Some of the devastating cloudburst-triggered debris flows and flash floods that occurred in the Uttarakhand Himalaya are Rudraprayag on 14th September 2012, Munsiyari on 18th August 2010, Kapkot on 19th August 2010, Nachni on 7th August 2009, Malpa and Ukhimath on 17th August 1998, Badrinath on 24th July 2004, and the Alaknanda River valley on 1970. About 20,000 people died and a huge loss of property took place due to these calamities (Das 2015 ). It has been noticed that these catastrophic events occurred mainly during the three months of the monsoon season—July, August, and September.

Debris flows and flash floods caused by glacier-bursts incidences were although not much frequent and intensive yet, during the recent past, their number has increased owing to changes in the climatic conditions. The increasing number of infrastructural facilities on the valley bottom has accelerated damages owing to exposed elements in risk-prone areas (Sati 2014 ; ICIMOD 2007a , b ; Chalise and Khanal 2001 ; Bhandari 1994 ; Uttarakhand 2017 ). Many drivers exist, which affect the severity of cloudburst-triggered hazards in the Uttarakhand Himalaya. Growing population and the construction of settlements and infrastructural facilities on the fragile slopes and along the river valleys have also caused severe hazards. The Uttarakhand region is home to world-famous pilgrimages and natural tourism. Mass tourism during the rainy season enhances the intensity of disasters.

Several studies have been carried out on glacier-bursts and cloudburst-triggered debris flows and flash floods in the Himalaya (Shugar et al. 2021 ; Byers et al. 2018 ; Cook et al. 2018 ; Asthana and Sah 2007 ; Bhatt 1998 ; Joshi and Maikhuri 1997 ; NIDM 2015 ; IMD 2013 ; Khanduri et al. 2018 ; Sati 2006 , 2007 , 2009 , 2011 , 2018a , b , 2020 ; Naithani et al. 2011 ). These studies were conducted from broader perspectives, mostly covering the entire Himalaya. However, the present paper looks into the case study of four villages of the Uttarakhand Himalaya, which were severely affected and damaged by cloudburst-triggered debris flows and flash floods, which occurred on July 18th, 2021. It analyses the environmental impact of cloudbursts in terms of forest and fruit trees dislocation, land degradation, and soil erosion—arable, forests, and barren land of the four affected villages. It also evaluates the human and economic losses like the killing of people, loss of existing crops, and damage of houses and cowsheds, respectively. The study suggests policy measures to risk reduction and rehabilitation of settlements from danger zones to safer areas after suitability analysis.

The Uttarakhand Himalaya is located in the north of India and south of the Himalaya. It is also called the Indian Central Himalayan Region. Out of the total 93% mountainous area, 16% is snow-capped, called the Greater Himalaya. The terrain is undulating and precipitous and the landscape is fragile, vulnerable to natural hazards. This catastrophic event occurred in the four villages of Uttarkashi district. The Uttarkashi town lies about 10 km downstream of the affected villages. A National Highway number 108, connecting Haridwar and Gangotri, is passing through Uttarkashi town. The four affected villages—Nirakot, Mando, Kankrari, and Siror are located in the upper Bhagirathi catchment, which is prone to geo-hydrological hazards. The slope gradient of these villages varies from 15° to 70°. Indravati is a perennial stream, a tributary of the Bhagirathi River that meets Bhagirathi from its left bank. All three Gadheras (streams)—Mando, Diya, and Siror are seasonal but violent during the monsoon season. Nirakot (1530 m) village is located in the middle altitude of the Hari Maharaj Parvat (2350 m) in a steep slope, Mando village (1180 m) is located on the left bank of the Bhagirathi River along the Mando Gadhera with gentle to a steep slope, Kankrari (1620 m) village is located on the moderate to the gentle slope on the bank of the Diya Gadhera, and Siror village (1280 m) is situated on the left bank of both Bhagirathi and Siror Gadhera with gentle to the steep slope (Fig.  2 ). One of the prominent eco-sensitive zones of the Uttarakhand Himalaya, the ‘Bhagirathi Eco-Sensitive Zone’ is 120 km long, spanning from Uttarkashi to Gaumukh, along the Bhagirathi River valley (Sati 2018a , b ). The rural people depend on the output of the traditional farming systems, often face intensive natural hazards. The settlements are located either on the fragile and steep slopes or on the banks of streams, which are very violent during the monsoon season when a heavy downpour occurs. Therefore, heavy losses of life and property in these areas are common, taking place every year.

Location map of cloudburst source and hit areas and their surroundings

Methodology

This study was empirically tested and a qualitative approach was employed to describe data. A structured questionnaire was constructed. The main questions framed and asked from the heads of households were—human and animal death, damage to self property—houses and cowsheds, and existing crops—cereals, fruits, and vegetables. Loss to public properties such as bridges, public institutions, and forest land was assessed. Based on the questions framed, we surveyed 143 heads of households of four villages, which were partially or fully affected due to cloudburst-triggered debris flow. These villages are Nirakot, Mando, Kankrari, and Siror. To assess the debris and the damaging areas, the authors travelled from the source areas to the depositional zones and measured the volume of debris—boulders, pebbles, sands, and soils using a formula; circumference = 2πR and area = π * R 2 . The slope gradient, accessibility, economic conditions, and climate of the villages were assessed and based on which, the susceptibility analysis of the villages was carried out. The villages were divided into very high susceptibility, high susceptibility, and moderate susceptibility levels. Both environmental degradation and economic losses in four villages were assessed. We used Geographical Positioning System (GPS) to obtain the data of altitude, longitude, and latitude. Two maps—case study villages and the major cloudburst incidences—2020 and 2021 were prepared and data were also presented using graphs. Photographs of four villages were used to present the destruction of villages due to the cloudburst event.

Results and analysis

Major cloudburst incidences in the uttarakhand himalaya.

Past incidences depict that the Uttarakhand Himalaya suffered tremendously due to cloudburst-triggered calamities. We gathered data on the major cloudburst incidences in Uttarakhand in the monsoon seasons of 2020 and 2021 from the state disaster relief force (SDRF), Dehradun. From May to September 2020, 13 major cloudburst incidences were noticed in Uttarakhand (Table 1 ). These incidences resulted in the death of 22 people and 77 animals, and 19 houses were fully damaged. Similarly, from May to September 2021, 17 major cloudburst incidences were occurred in the Uttarakhand Himalaya, resulting in the death of 34 people and 144 animals, and 106 houses were buried. Besides, it caused a huge loss to public property and landscape degradation.

The economic losses in 2021 were much higher than the losses in 2020 (Fig.  3 ). In 2021, the frequency and intensity of cloudburst-triggered calamities were also higher. The loss of animals was quite high both the years. Houses that collapsed due to calamity were six times higher in 2021 than in 2020. The loss of human life was substantial in both years. Several bridges were washed away.

Loss of human lives, livestock, houses and bridges due to cloudburst in Uttarakhand during the 2020 and 2021

District-wise major cloudburst events of 2020–2021 are shown in the map of the Uttarakhand Himalaya (Fig.  4 ). A total of 30 major cloudburst incidences were recorded, out of which, 17 occurred in 2021. The Uttarkashi district received the highest incidences (07), followed by the Chamoli district (05). Dehradun and Pithoragarh districts have recorded 04 incidences each. Rudraprayag 03 and Tehri, Almora, Bageshwar have recorded 01 each. It has been observed that cloudburst-triggered incidences mainly occurred in remote places along the fragile river valleys and middle slopes.

Location map of cloudbursts hit areas in 2020 and 2021

Case study of affected villages

On July 18, 2021, a cloudburst hits the Hari Maharaj Parvat (hilltop) at an altitude of 2350 m at 8:30 p.m., which triggered huge debris flows and flash floods. The four villages—Nirakot, Mando, Kankrari, and Siror of Uttarkashi district, located down slopes of the hilltop and close to the Uttarkashi town, were severely affected due to debris flow (Table 2 ). At the cloudburst hit area, it formed three gullies, which later on merged into three streams, along which these villages are located. Debris, from the source i.e. hilltop of Hari Maharaj Parvat, equally flew in three directions. Since the cloudburst event occurred at 8:30 p.m., the people did not have time to move with their movable property and therefore, the magnitude of damage was enormous.

The villages are located from the altitudes of 1180 m (lowest) to 1620 m (highest). Mando village is located at 1180 m, Kankrari village at 1620 m, Nirakot at 1530 m, and Siror has 1280 m altitude. The two villages—Nirakot and Mando have west-facing slopes, Kankrari has a south-facing slope, and Siror has a north-facing slope. These villages are located along the tributaries of the Bhagirathi River, with 2 to 5 km distance from the road. The intensity and volume of debris were different in different villages, therefore, the casualties and losses were also varied. The villages are surrounded by agricultural and forestlands. The farmers mainly grow subsistence cereal crops—paddy, wheat, pulses, oilseeds, fruits, and vegetables. Forest types comprise pine (sub-tropical) and oak and coniferous forests (temperate), used for fodder, firewood, and wild fruits.

Located at the high-risk zones, these villages face several disaster incidences every year. Out of the total 143 heads of households surveyed, more than 80% of heads were in favour of rehabilitating them in the safer areas. They wanted to relocate their houses and cowshed within the village territory with financial assistance from the state government. The streams, along which the settlements are constructed, are fragile and highly vulnerable to landslide hazards. Further, the cloudburst incidences are increasing due to climate change, the heads of households perceived.

Figure  5 shows four villages—Nirakot, Mando, Kankrari, and Siror, which were severely affected by cloudburst-triggered debris flow and flash flood. The volume of debris and boulders can be seen in all the villages. These villages are surrounded by dense sub-tropical and temperate forests that vary from pine to mixed-oak and deodar. Kharif crops were growing in the arable land whereas a large cropland has been washed away.

Cloudburst affected villages a Nirakot, b Mando, c Kankrari, d Siror; Photo: by authors

Impact of cloudburst-triggered debris flow and flash flood

Environmental impact.

The environmental impact of cloudburst-triggered debris flow and flash flood in four villages of Uttarkashi district was analyzed (Table 3 ). The major variables were the number of forest trees dislocated, total land degradation, land degradation under existing crops, number of fruit trees dislocated, land degradation under arable land, number of buildings were damaged, number of bridges damaged, and boulders’ volume. Forest trees, which dislocated were pine in the middle altitude and mixed-oak and deodar in the higher altitude. A total of 770 forest trees were dislocated from all four villages, out of which, 500 were from the Kankrari village (highest). The lowest trees dislocated were from Siror village (70). The total land degradation from the cloudburst hit areas to the affected areas was huge, however, we have measured the land which was within and surrounding each village. The total land degradation was 52.5 acres with the highest in Kankrari (45 acres) and the lowest in Siror (0.5 acres). The land degradation under existing crops was 22.6 acres in all four villages, varying from 0.1 acres in Siror to 20.6 acres in Kankrari. The total number of fruit trees dislocated was 486. Land degradation under arable land was 22.6 acres. It includes the area under existing crops both agriculture and horticulture. A total of 19 buildings were damaged whereas a total of 14 bridges, connecting the affected villages were washed away.

Economic impact

The economic impact due to cloudburst calamity was tremendous in the forms of a household affected, loss of human and animal life, building loss, forest loss, loss of existing crops including fruits, loss of arable land, and loss of bridges (Table 4 ). The value of all these assets was calculated in Indian Rupees (INR) at the current price. The total number of households affected was 143, of which, 100 households belonged to the Kankrari village (highest) and three households (lowest) were from Siror village. Four people died due to the calamity—three women from Mando village and 1 man from Kankrari village. Two cows from Mando village died. The total loss from the collapse of the building was 1.7 million INR, with the highest (1.1 million INR) from Kankrari village. A total of 0.77 million INR was lost due to forest loss, and the loss from existing crops was 3.35 million INR. Loss from dislocation of fruit trees was noted high, which was about 0.5 million INR. A large portion of arable land was flown which value was 11.3 million INR. About 14 million INR was lost due to the collapse of bridges. As a whole, about 31.62 million INR was lost due to cloudburst calamity. Per household loss by the cloudburst calamity was noted 0.22 million INR.

Average circumference, area, and volume of boulders

We calculated the average circumference, area, and volume of boulders in the case study villages using a formula: circumference = 2πR; Area = π * R 2 ; volume = length × width × depth (Table 5 ). We noticed that the highest average area of boulders was in Mando village, which is 28.3 m 2 followed by Kankrari 19.6 m 2 , Nirakot 12.57 m 2 , and Siror 7.1 m 2 . In terms of the total volume of debris, it was the highest in Kankrari village, followed by Mando, Nirakot, and Siror villages.

Figure  6 shows the average diameter of boulders in the cloudburst-affected villages. We drew the figure with a scale of 1 cm is equal to 1 m. The average biggest diameter of boulders was found in Mando village (6 m), followed by Kankrari (5 m) and Nirakot (4 m) villages. The average smallest diameter of boulders was found in Siror village (3 m).

Village-wise average diameter of boulders

Susceptibility analysis

Based on the above description, susceptibility analysis of the case study villages was carried out (Table 6 ). The main variables of susceptibility were slope gradient, accessibility of villages, economic conditions of households, and climatic conditions. We noticed that Nirakot village has very high susceptibility, Kankrari has high, and Siror and Mando have moderate susceptibility.

The Uttarakhand Himalaya is highly vulnerable to geo-hydrological disasters because of its geological formation (Vaidya 2019 ). It is an ecologically fragile, geologically sensitive, and tectonically and seismically very active mountain range (Sati 2019 ). The geo-hydrological events—cloudbursts and glacier bursts-triggered catastrophes are very common and devastating. The monsoon season poses severe threats to natural hazards because of heavy downpours. About 93% of the Uttarakhand Himalaya is mountainous mainland, of which 16% is snow-capped. The undulating and precipitous terrain and remoteness are the most vulnerable for disaster risks.

This study reveals that most of the cloudbursts incidences in 2020–21 occurred mainly in the remote mountainous districts of the Uttarakhand Himalaya. The villages in the Uttarakhand Himalaya are located on the sloppy land and along the river valleys, which are fragile and very vulnerable to disasters. The rivers flow above danger marks during the monsoon season cause threats to rural settlements. The roads of Uttarakhand are constructed along the river banks and on fragile lands. These roads lead to the highland and river valley pilgrimages where the number of tourists and pilgrims visit every year mainly during the monsoon season. There are many locations along the river valleys where the houses are constructed on the debris, deposited by rivers during debris flow events. Therefore, the environmental and economic losses due to debris flows and flash floods are high. The construction of hydropower projects along the river valleys without using sufficient technology further accentuates the vulnerability of debris flows and flash floods. One of the recent examples is the Rishi Ganga tragedy in Chamoli district where more than 200 people died with a huge loss to property (Sati 2021 ). We observed that the cloudburst triggered calamity in 2021 was higher than in 2020. The trend of occurring natural hazards has been increasing. Similarly, the intensity and frequency of natural hazards were observed high.

The present study shows that the environmental and economic loss in the four villages of the Bhagirathi River valley was huge due to cloudburst-triggered debris flows and flash floods. Almost every household of the villages were affected by cloudburst calamity. There were large forest and arable land degradation, forest and fruit trees were dislocated, loss of life—human and animal, and the houses and bridges were collapsed. The calamity also poses threat to the future, in terms of, the large deposition of debris including boulders, pebbles, and gravels in the villages along the streams and gullies. The rural people are poor and their livelihood is dependent on practicing subsistence agriculture. Many of them are living below the poverty line in these villages. Because the existing crops have been lost, they are facing food insecurity. Further, the psychological problems are immense. The fear of another calamity is always there in the mind of people as all villages are situated in very high to moderate susceptible areas. The national highway is passing through the right bank of the Bhagirathi River and the affected villages are situated on the left bank. The connectivity problem is immense all the time in these villages. The entire rural areas of the Uttarakhand Himalaya are facing similar problems.

Cloudburst-triggered debris flows and flash floods are natural calamities in the Himalayan regions. They occur naturally and cannot be stopped. The losses—environmental and economic are also huge. However, the severity of these natural calamities can be minimized. For example, the high impact of cloudburst-triggered debris flow on the four study villages was mainly due to their location along the streams and on the fragile slopes. This can be avoided by constructing the settlements in safer places generally away from the violent streams. In the disaster risk zones, scenario analysis can be carried out under which, identifying driving forces of disaster risks is the first step. Then, the critical uncertainties are to be identified, and finally, a possible scenario can be developed. Nature-based eco-disaster risk reduction can be adopted to prevent further disaster risks. A large-scale plantation drive in the degraded land will restore the fragile landscape. Both pre and post-disaster risk reduction measures can be adopted to reduce the economic and environmental impact of debris flows. There must be policies implementation programmes for providing immediate relief packages for the affected people in terms of food and shelters. In a long run, susceptibility analyses should be carried out to understand the risk to the settlements so that the settlements can be replaced on the safer side if needed. A special budget can be allocated to hazard-prone villages during adverse situations.

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Sati, V.P., Kumar, S. Environmental and economic impact of cloudburst-triggered debris flows and flash floods in Uttarakhand Himalaya: a case study. Geoenviron Disasters 9 , 5 (2022). https://doi.org/10.1186/s40677-022-00208-3

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Uttarakhand nurse reported missing in July found dead in UP, cops confirm rape

The nurse was reported missing by her sister on july 31. her body was found in uttar pradesh's bilaspur on august 8..

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• Woman reported missing on July 31, body found on August 8
• Woman strangled, body dumped in bushes in UP
• CCTV footage and mobile surveillance helped identify suspect

A nurse from Uttarakhand was raped and murdered, and her body was found in Uttar Pradesh days later. The nurse was reported missing on July 31. Her body was recovered by the police on August 8. A couple has been arrested from Rajasthan in connection with the case.

The victim's sister filed a missing person report at Rudrapur Kotwali on July 31. The police launched an investigation immediately. On August 8, the woman's decomposed body was found in the bushes in Uttar Pradesh's Bilaspur town.

The post-mortem report confirmed that the nurse had been raped and strangled to death.

The woman, who worked at a private hospital in Rudrapur, was last seen on CCTV footage on July 30 while returning from work. The footage showed her in the Dibdiba area of Bilaspur, a town near Rudrapur.

Following this lead, the police deployed multiple teams and also put her mobile number under surveillance.

After analysing CCTV footage near the crime scene, the police identified a suspicious man following the woman on the fateful day. The investigation led them to Bareilly district in Uttar Pradesh. However, the suspect had fled by the time the police arrived.

The police then expanded their search to Haryana and Rajasthan. Eventually, the suspect, identified as Dharmendra, was located in Jodhpur, Rajasthan. The police arrested him along with his wife and brought them to Rudrapur for questioning.

During interrogation, Dharmendra confessed to the crime. He admitted that on the evening of July 30, he saw the nurse walking alone on the roads. Taking advantage of the darkness, he forcibly dragged her into the bushes.

When the victim resisted his attempt to rape her, Dharmendra violently slammed her head against the road and eventually strangled her with a scarf. After committing the crime, he dumped her body in the bushes and fled with her mobile phone and Rs 30,000 in cash, the accused confessed.

Senior Superintendent of Police (SSP) Manjunath TC confirmed the details of the crime and assured that the accused would face strict legal action. (Inputs by Ramesh Chandra) Published By: Anuja Jha Published On: Aug 15, 2024

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Uttarakhand nurse raped, murdered while returning from hospital; 1 arrested

A nurse was raped and murdered while returning home from hospital after her duty, and a daily wage labourer was arrested..

A man was arrested for allegedly raping and killing a nurse in Uttarakhand while she was returning home from the hospital two weeks ago. The horrific incident took place in Uttarakhand’s Udham Singh Nagar district, reported The Indian Express and the accused was arrested on August 14.

The nurse worked at a private hospital in Nainital and her body was found in an empty plot in Uttar Pradesh’s Rampur district. The incident took place on July 30, the report said.

The accused in the case, Dharmendra Kumar, belongs to Bareilly and is a daily wage labourer. Kumar allegedly sexually assaulted and murdered the nurse while she was heading home from the hospital.

Click here for LIVE updates on Kolkata rape-murder case

On July 31, the victim's sister filed a missing person report with the local police after she did not come home the previous night. The nurse's body was found by the police on August 8.

According to the police, the accused first dragged her to the bushes where he raped her and strangled her to death. He then robbed her, took her jewellery, and fled. The police arrested the man from Rajasthan after they tracked the victim's phone to the location.

“The accused is a (drug) addict and does not know the woman. On the day of the incident, he saw the woman going alone. As per our information, he stopped the woman, who fought back fiercely. She was, however, overpowered and… strangled her to death. He also sexually assaulted her. After the murder, he took the woman’s belongings and escaped,” SSP Manjunath T C told Express.

This comes as the healthcare community called a strike after a junior doctor was raped and murdered on the premises of the RG Kar Medical College in Kolkata on August 9. Opposition leaders and doctors' associations alleged a “cover-up” by the Kolkata Police as the parents of the victim were initially informed that their daughter committed suicide.

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• Anger in Uttarakhand as nurse raped & killed

Anger in Uttarakhand as nurse raped & killed

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Disaster Management: A Case Study of Uttarakhand

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ISBN No. 978-93-82715-98-6 of Seminar Proceedings in Mount Carmel College, Bangalore

Nataraja T.C

Carmalites with ISBN No. 978-93-82715-98-6 of Seminar Proceedings in Mount Carmel College, Bangalore.

Journal of Tourism Futures

Sofia Wijaya

Ramjit Singh

The paper critically reviews the research available on crisis and disaster management strategies for tourist destinations as published in tourism and travel related journals adopting a narrative analysis approach. A total of 74 research papers published on the subject in widely recognized top tier tourism and management journals, between January 2000 and September 2018, have all been incorporated into this study. The studies covered the various type of natural disasters and other events like terrorist attacks, pandemics and political upheaval. The study found the key themes including media sensitization, destination reputation and image, effectiveness and speedy response to a disaster and the importance of relationship marketing/collaboration and communication strategies etc are all critical after crises and disasters occur. Abundant opportunities exist to further expand the theory in this study area through future research and the construction of a theoretical framework, greater em...

Amitabh Upadhya

The role of Destination Management Organizations (DMO) has traditionally been more of promotion of the destination that got expanded to facilitation and coordination of tourism services for the inbound tourists to the destination. On the other hand any crisis situation was left to other national organizations (such as disaster management team) to deal with, and the DMO would later take up the damage control exercise of stemming the decline of numbers at the destination once the crisis was over or managed. The two have been in most cases worked independently of each other as tourism is generally not a priority of governments at the time of crisis despite the fact that the biggest causality of the crisis in most cases has been the tourism industries. Not much literature is available on how the DMO/NTO should handle the situation and actively mitigates the effect of the crisis or where does the DMO fit-in the disaster management mechanism either of the government agencies or that of the industry. The concerted effort of all organizations will help maintain the image of the destination which gets irreparable beating if the crisis has received wide spread media coverage which it does, given the advancement in information communication technology (ICT). Recent researches though, have attempted to define and assign an active role to DMOs in situations of crisis but being incident specific many of those studies have not been able to suggest a wider and effective frame-work for dealing with crisis situations that negatively impact the destination image and tourist mobility. The present study is a conceptual approach to expand, elaborate, and ascribe a role to the DMO that fits within the scope of its definition as regards crisis and its aftermath. The focus of this study is to review recent crisis situations in the Middle East and North Africa (MENA) region and asses its impact on tourism of the region. The study also suggests a model of destination management that includes crisis management as an essential component.

Bindi Varghese

Tourism is a strategic economic activity in Karnataka, but the uniqueness of the governing bodies accentuates on integrated planning pioneering with several distinguishing features. The urban and territorial changes caused by tourism are well introspected areas in contemporary scientific literature. This research adopts an integrative approach with a framework connecting scientific traditions of destination management and competitiveness with a case study examining in-depth reliability of Destination Management Organizations (DMOs) in destination governance and narrates upon the essentiality of stakeholder participation in destination decision making process. Most pertinent functions of the Destination Management Organization (DMO) are to facilitate the corporation and collaboration of stakeholder within the destination. Primarily in times of crisis where collaboration and collective decision making is a priority; many destinations today are not equipped to combat such crisis which consecutively take a toll on the destination and unfavourably affect the tourists visiting the destination leaving behind a negative impression which can adversely affect the tourism integrity of the destination.

Mutinta Chitumba

An Overview of Disaster Management is designed to introduce the subject of disaster management to an audience of UN organization professionals who form disaster management teams, as well as to government counterpart agencies, NGOs, and donors. The training is designed to increase the audience’s awareness of the nature and management of disasters. This should lead to better performance in disaster preparedness and response. By questioning the “inevitability” of disasters, we hope you can begin to see mitigation of disasters as a component of development, and disasters as opportunities to further development goals. In this course we take a broad view of disasters. We will not try to separate out problems rooted in environmental degradation as a distinct set of responsibilities. It also includes emergencies which encompass the need to provide assistance to large populations displaced by the forces of civil conflict or other emergencies. Mush of the course’s content is based on the UNDP/UNDRO Disaster Manual and follows its principles, procedures, and terminology.

Management review quarterly

Kyoo-Man Ha

TIJ's Research Journal of Social Science & Management - RJSSM

Seemin Mushir

Kedarnath is one of the oldest and most important worshipping place for the people of hindu religion located in Uttarakhand state of India. During 2013, Okhimath area of Rudrapratap has also met unprecedented damage to the life and property, infrastructure and landscape during 16th to 17th of June due to pouring rainfall and cloud burst accident. The complete area, which accommodated around 100 to 150 shops and five hotels, to serve the needs of the pilgrims, was wholly washed away leaving no trace of them. This research paper is an analysis on the impact of Uttarkashi flood on the tourism of Uttarkhand. Four principal questions were attempted to be answered: the impacts of the Uttarkashi on pilgrimage visitors and how they affected the tourism economy; the recovery efforts undertaken and their effectiveness; other actions that, if taken, might have improved preparedness and made recovery efforts more effective; and how pilgrimage centers might be made more resilient to natural disa...

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Uttarakhand nurse rape-murder: UP man arrested from Rajasthan by tracking victim's stolen phone

The Bareilly native said he strangled the nurse to death after raping her at a plot

A shocking crime from Uttarakhand has come to the fore amid the ongoing nationwide protests over the rape and murder of a doctor at Kolkata's RG Kar Medical College hospital. In Rudrapur of Uttarakhand's Udham Singh Nagar district, a nurse was allegedly raped and murdered by a migrant labourer. The crime took place on July 30 and the police finally cracked the case by pursuing the mobile phone that was stolen from the victim.

The woman, 33, was a nurse at a private hospital in Nainital. The mother of an 11-year-old girl, they were living in in Udham Singh Nagar's Bilaspur Colony. The police started the probe as a man-missing complaint when the sibling of the victim filed a complaint on July 31 claiming that her sister never came home on July 30, Tuesday. 

The cops couldn't make any breakthrough until her body was found in an empty plot in Uttar Pradesh’s Dibdiba over a week later, reports said. The autopsy report confirmed that she was sexually assaulted before being murdered.

ALSO READ | Kolkata doctor rape and murder: Roy's mobile paired to headset found at crime scene

The investigation team then tried tracking the victim's mobile phone. As expected, it was stolen from her after the murder by the accused -- Dharmendra of Uttar Pradesh's Bareilly. The cops picked him up from Rajasthan’s Jodhpur, TV 18 said in a report. 

According to the police, Dharmendra confessed to having committed the crime during interrogation. He followed and attacked the nurse on the way inside the Basundhara Apartment at Kashipur Road in Udham Singh Nagar. He wanted to rob the woman of her valuables and dragged her to the isolated plot when he raped and strangled her to death, the TV18 report added. He fled Uttarakhand with her jewellery, mobile phone and cash inside her purse, the police said. 

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Case Study: Ulta Beauty and VARGO

Are you curious about how Ulta Beauty, the largest beauty retailer in the U.S., revolutionized their distribution centers?

Read this case study to uncover how Ulta Beauty partnered with VARGO® to implement Locus Robotics’ LocusBots and improve their supply chain operations. By listening to their associates and addressing key challenges, Ulta Beauty enhanced efficiency and productivity across their facilities.

In this case study, you'll learn:

• How Ulta Beauty's new Greenfield facility in Greer, SC, became a model of efficiency
• The significant improvements in productivity and accuracy achieved through automation
• The impact of seasonal peak scalability with doubled bots and reduced training time

Explore the innovative steps Ulta Beauty took to stay ahead in the competitive beauty retail industry.

Read the full case study now and get inspired!

Please CLICK HERE to download the Case Study.

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Saturday, 17 August 2024

Agenda - The Sunday magazine

• Cover Story

Substance abuse crisis threatens the future of Uttarakhand youth

Once confined to older adults, drug addiction is now entangling school-aged children, causing alarm and fear among families

The tranquil village of Ganigaon, nestled among the Himalayan mountains of Uttarakhand, is facing a growing menace that threatens its future—substance abuse among its youth.

This issue, once limited to older individuals, has begun to trap even the youngest members of the community, leading to a wave of fear and concern among residents. “In my school, some boys often come after using drugs. They even bring substances to share with others,” says Anita (name changed), a 17-year-old student from Ganigaon. “When teachers try to counsel them, they don't listen and sometimes even threaten them. This behavior is not only disrupting their education but also instilling fear among the girls, whose parents are now hesitant to send them to school.”

Anita’s story is not an isolated case. Ganigaon, located 54 km from Bageshwar district and 32 km from Garur block, is a picturesque village with a population of approximately 1,746 people.

However, the beauty of the landscape belies the growing darkness within the community. Substance abuse, which has already taken hold of many adults, is now spreading rapidly among children and adolescents, affecting their education and futures.Devaki (name changed), a 44-year-old resident, echoes these concerns: "We send our boys to school hoping they'll study and build a better future. But instead, they are ruining their lives with drugs.

This behavior is also disturbing the peace at home. If this continues, how will they study? How will they find employment?”

The impact of this growing trend is felt deeply within the families of Ganigaon. Malti Devi (name changed), 55, shares how this vice has gripped her family: "My husband used to come home intoxicated, creating a tense environment. Now, my sons have picked up the same habit. They skip school and engage in substance abuse.

Despite my efforts to counsel them, they continue down this dangerous path, even resorting to stealing money from home to feed their addiction. I’m at a loss about how to save them.” The village head, Hema Devi, expresses her alarm over the situation: "Substance abuse is increasing rapidly in our village. People are selling cannabis and making homemade liquor, which is affecting everyone’s health, but they won't stop.

Now, even children are falling prey to this. It’s leading to more violence, with women bearing the brunt of it. Men spend all their money on alcohol, forcing women to work in others' fields to make up for the financial shortfall.” Recognising the severity of the problem, Hema Devi mentions that the panchayat is working on launching a campaign to combat substance abuse. Social worker Neelam Grundy emphasizes the urgency of the situation: “The rise of substance abuse in the village is a dangerous trend. What started with the elderly has now spread to the youth and even school-aged children.

 We need a comprehensive campaign to tackle this issue, but it can't just be the responsibility of the government. The elders in the village need to lead by example and give up this vice so that the younger generation can break free from its grip.”

The Uttarakhand government, recognizing the growing issue, has launched a campaign to make the state drug-free by 2025.

At the administrative level, efforts are being made to curb the spread of this menace. Between 2019 and 2023, over 119 kilograms of charas were seized in 89 cases in Bageshwar district alone, alongside 58 cases of smack trafficking.

These figures show the administration's commitment to tackling the issue, but society must also take responsibility. Only through a combined effort can the future of Uttarakhand’s youth be safeguarded, and the state be freed from the clutches of this growing evil.

(The writer is a student of Class 10th from Ganigaon Village, Bageshwar. Views expressed are personal. Charkha Features)

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