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Accurate forecast of daily streamflow of the major Himalayan rivers is crucial for understanding changes in their hydrological regimes caused by precipitation variability, as well as their potential implications for hydropower generation and flood management in the downstream region. However, the study pertaining to daily streamflow forecasting in the western Himalayas is lacking, primarily due to the limited availability and accessibility of long-term daily gauged data. In this study, four machine learning (ML) models, namely support vector machine, random forest, deep neural networks, and bi-directional long-short-term memory (BLSTM), were employed to forecast daily streamflow in the Sutlej river basin. The models were trained (11 years) and tested (2 years) using publicly accessible earth observation and reanalysis datasets for a period of 13 hydrological years, grouped into four distinct scenarios, denoted as M1, M2, M3, and M4. In each scenario, feature parameters were generated from the pool of six hydro-meteorological variables namely- precipitation (P), air temperature ( T a ), evapotranspiration (ET), snowfall, snow cover area (SCA), and discharge. The optimal feature combinations (e.g., scenarios) were identified using the time lag cross correlation technique. All of the ML models demonstrated reasonable performance (NSE > 0.82, R > 0.91, and RMSE < 101.2 m3/s) in simulating streamflow during testing period, the BLSTM model showed a slightly superior level of accuracy across all scenarios (NSE = 0.97, R = 0.99 and RMSE = 42.7 m3/s for M4). The BLSTM was further used to reconstruct daily timeseries discharge for the period 2012–2021. The variability in T a , ET, and P exerts a greater influence on streamflow generation in the glacierized catchment in comparison to snowfall. The observed phenomenon can be ascribed to the dampening effect of snowfall on discharge, as their effects become apparent within a timeframe of five to seven days. [ABSTRACT FROM AUTHOR]

This study examines the proportional contribution of snow/ice melt, rainfall, and groundwater to Sutlej River discharge at various locations. Sutlej River is a major tributary of the Indus River system and an important water supply source for irrigation through the canal network in northwest India. Here, we used hydrograph separation and associated uncertainty and applied the snowmelt runoff model (SNOWMOD) to estimate the contribution from different water sources to the Sutlej River. We used δ18O and electrical conductivity values of different waters for the hydrograph-separation approach. The first-order Gaussian error propagation and Monte-Carlo simulation are used to assess the accuracy. The estimated contribution at Rampur is ~ 62.7% (snow/ice melt), 18.7% (rainfall), and ~ 18.4% (groundwater); for Ropar is 59 ± 2% (snow/ice melt), 23 ± 2% (rainfall), and 18 ± 2% (groundwater); and for Yusufpur, 25 ± 3% (snow/ice melt), 39 ± 3% (rainfall), and 36 ± 2% (groundwater) during July–December 2013. The findings from the hydrograph-separation and SNOWMOD analysis established a fundamental understanding of the hydrological processes in the Sutlej River system, providing valuable baseline data essential for developing sustainable water resource management strategies. [ABSTRACT FROM AUTHOR]

Glacier-associated hazards are becoming a common and serious challenge to the high mountainous regions of the world. Glacial lake outburst floods (GLOFs) are one of the most serious unanticipated glacier hazards, with the potential to release a huge amount of water and debris in a short span of time, resulting in the loss of lives, property, and severe damage to downstream valleys. The present study used multi-temporal Landsat and Google earth imageries to analyze the spatio-temporal dynamism of the selected glacial lake (moraine-dammed) in the Satluj basin of Western Himalayas. Furthermore, GLOF susceptibility of the lake was assessed using a multi-criteria decision-based method. The results show that the lake area has increased from 0.11 to 0.26 km2 over the past 28 years from 1990 to 2018. The susceptibility index value for the lake was calculated as 0.75, which indicates that the lake is highly susceptible to the GLOF. The depth and volume of the lake were estimated to be 16 m and 57 × 105 m3, respectively, using an empirical formula. HEC-RAS, HECGeo-RAS, and Arc-GIS software were utilized in this study to perform unsteady flow analysis and to determine the GLOF impact on the downstream area. The worst-case GLOF scenario (breach width of 75 m) was revealed during an overtopping failure of the moraine dam, resulted in a peak discharge of 4060 m3/s and releasing a total water volume of 57 × 105 m3. The breach hydrograph has been routed to calculate the spatial and temporal distribution of peak flood, inundation depth, velocity, water surface elevation, and flood peak arrival time along the river channel. The analysis further reveals that the routed flood waves reach the nearest settlement, i.e., Rajpur town, situated at a distance of 102 km in the downstream valley of the lake at 6 h after the beginning of the lake breach event with a peak discharge/flood of 1757 m3/s and maximum flow velocity of 1.5 m/s. With the ongoing climate warming and glacier retreat, moraine-dammed lakes are becoming more hazardous and thus increasing the total threat. Therefore, it is mandatory to monitor and assess such lakes at regular intervals of time to lessen the disastrous impacts of GLOFs on the livelihood and infrastructure in the downstream valleys. The findings of this study will aid in the creation of risk management plans, preparatory tactics, and risk reduction techniques for GLOF hazards in the region. [ABSTRACT FROM AUTHOR]

In the Himalayan Mountain region, a large number of glacial lakes have developed in the recent past due to glacier recession under the influence of climate change. In this study, we used high resolution satellite data such as Indian Remote Sensing (IRS) LISS-IV (5.8 m) and Google earth images supplemented with field survey to generate an updated glacial lake inventory of Upper Jhelum Basin (UJB) of Kashmir Himalaya. The Sentinel-2A (10 m), Landsat-OLI (30 m) and MSS (60 m), and Cartosat-DEM (30 m) were additional data sources used for glacial lake mapping and change detection analysis. A total of 393 glacial lakes covering an area of 21.55 ± 3.8km² were identified, mapped and inventoried. The lake inventory includes 102 proglacial lakes, 13 supraglacial lakes and 278 unconnected glacial lakes. Using the weighted index-based method, 21 glacial lakes were found as Potentially Dangerous Glacial Lakes (PDGLs). Out of these, 7 lakes were classified as High, 9 as Medium and 5 as Low hazard glacial lakes as per the hazard assessment. Change detection analysis of PDGLs from 1980 to 2020 revealed an increase in area from 5.92 km² to 8.46 km² thereby, indicating a growth of 2.51 ±0.9 km² (30%) at a rate of 0.063 km²/year. The formation and growth of glacial lakes in this area is attributed to continuous glacier recession under the warming trend of temperature and declining nature of precipitation. In this study, the findings showed that Tavg and Tmin are rising significantly at a rate of 0.004°C/year and 0.013°C/year respectively. This study provides an important database for future GLOF studies in the region. [ABSTRACT FROM AUTHOR]

Climate warming-induced glacier recession has resulted in the development and rapid expansion of glacial lakes in the Himalayan region. The increased melting has enhanced the susceptibility for Glacial Lake Outburst Floods (GLOFs) in the region. The catastrophic failure of potentially dangerous glacial lakes could be detrimental to human life and infrastructure in the adjacent low-lying areas. This study attempts to assess the GLOF hazard of Gangabal lake, located in the Upper Jhelum basin of Kashmir Himalaya, using the combined approaches of remote sensing, GIS, and dam break modeling. The parameters, such as area change, ice thickness, mass balance, and surface velocity of the Harmukh glacier, which feeds Gangabal lake, were also assessed using multitemporal satellite data, GlabTop-2, and the Cosi–Corr model. In the worst-case scenario, 100% volume (73 × 106 m3) of water was considered to be released from the lake with a breach formation time (bf) of 40 min, breach width (bw) of 60 m, and producing peak discharge of 16,601.03 m3/s. Our results reveal that the lake area has increased from 1.42 km2 in 1972 to 1.46 km2 in 1981, 1.58 km2 in 1992, 1.61 km2 in 2001, 1.64 km2 in 2010, and 1.66 km2 in 2020. The lake area experienced 17 ± 2% growth from 1972 to 2020 at an annual rate of 0.005 km2. The feeding glacier (Harmukh) contrarily indicated a significant area loss of 0.7 ± 0.03 km2 from 1990 (3.36 km2) to 2020 (2.9 km2). The glacier has a maximum, minimum, and average depth of 85, 7.3, and 23.46 m, respectively. In contrast, the average velocity was estimated to be 3.2 m/yr with a maximum of 7 m/yr. The results obtained from DEM differencing show an average ice thickness loss of 11.04 ± 4.8 m for Harmukh glacier at the rate of 0.92 ± 0.40 m/yr between 2000 and 2012. Assessment of GLOF propagation in the worst-case scenario (scenario-1) revealed that the maximum flood depth varies between 3.87 and 68 m, the maximum flow velocity between 4 and 75 m/s, and the maximum water surface elevation varies between 1548 and 3536 m. The resultant flood wave in the worst-case scenario will reach the nearest location (Naranaag temple) within 90 min after breach initiation with a maximum discharge of 12,896.52 m3 s−1 and maximum flood depth and velocity of 10.54 m and 10.05 m/s, respectively. After evaluation of GLOF impacts on surrounding areas, the area under each inundated landuse class was estimated through the LULC map generated for both scenarios 1 and 2. In scenario 1, the total potentially inundated area was estimated as 5.3 km2, which is somewhat larger than 3.46 km2 in scenario 2. We suggest a location-specific comprehensive investigation of Gangbal lake and Harmukh glacier by applying the advanced hazard and risk assessment models/methods for better predicting a probable future GLOF event. [ABSTRACT FROM AUTHOR]

A catastrophic debris flow in the Rishiganga and Dhauliganga rivers in Uttarakhand, India, on 7 February 2021 left a trail of disaster. Around 100–150 people lost their lives according to Uttarakhand Chief Secretary statement given to ANI news portal, two hydropower projects were badly damaged and a bridge across the Rishiganga River was washed off in the event. Study shows that the debris flow is caused due to detachment of 0.59 km2 right lobe of a hanging glacier and resultant ice-rock avalanche. This right lobe of the glacier was located over a mountain slope having an average slope of 35° at 4700–5555 m a.s.l. and travelled 12.4 km before hitting the infrastructure projects. Role of precipitation, snow cover, land surface temperature, and permafrost processes were investigated for identifying causes of the event. Since 2012, monsoon precipitation and mean annual land surface temperature (LST) showed significant increasing trend. Snow cover during monsoon months showed increasing trend and September, October and November experienced decreasing trend at glacier elevations. Mean annual LST increased from − 0.3 °C in 2012 to a peak of 0.4 °C in 2016. Central lobe of the glacier advanced during this period and eventually fell off in 2016 suggesting that the LST warming forced reduction of frictional drag at the interface facilitating it advancement and eventual dislodgement. Permafrost modelling suggests warm permafrost below 50 m and conditions favourable for intense frost cracking up to 10–15 m. At ~ 40 m depth, the delayed response of 2012–2016 warming produced peak positive temperature conditions by December and probably facilitated the formation of thin film of water at the deeper layers acting as a lubricant for glacier sliding. It is also suggested that the increase in summer precipitation might have forced thickening of the accumulation area and thereby increasing the shear stress for sliding of the glacier. It is proposed that the recent change in the weather conditions in the region is primarily responsible for this event through geological, glaciological, and permafrost processes. Flood modelling study suggests a flood volume of ~ 10 MCM generating 24.5 m flow depth at the bridge site with 12.7 m/s flow velocity. The event highlighted the need for improved monitoring of the cryosphere areas of the Himalaya to capture the early warning signs for better preparedness. [ABSTRACT FROM AUTHOR]

In this study, remote sensing-based algorithm, METRIC is used to estimate evapotranspiration (ET) over a mountainous watershed in the lesser Himalayas in Uttarakhand, India. ET estimates of METRIC are compared with the ET values determined by using FAO Penman-Monteith equation and crop coefficients. In its original form, METRIC underestimated the ET values considerably with mean absolute error (MAE) of 0.95 mm/day. A modification is incorporated in METRIC for better representation of the effect of rainfall on the ET process. The proposed modification estimates ET at the hot pixel using daily rainfall and meteorological data. Using the modification, the MAE is reduced to 0.44 mm/day and underestimation of ET is reduced from 20.9% to 8.4%. This study contributes to the better understanding of ET in the lesser Himalayas of Uttarakhand. It also underlines the importance of accurate assignment of ET to the hot pixel for accurate estimation of ET using METRIC. [ABSTRACT FROM AUTHOR]

This research paper proposes a new five-step protocol to enhance the result of existing cloud removal algorithms using Moderate Resolution Imaging Spectroradiometer (MODIS) daily snow cover products (SCPs). The study has been carried out for the upper Bhagirathi basin (up to Maneri Hydropower Project) located in the Western Himalaya. Gafurov and Bárdossy test employed to validate the performance of the proposed method, followed by comparing with the field observed snow cover duration (SCD) data. The result shows that the mean overall accuracy of the proposed method for cloud removal is about ∼95%. However, the cloud removal method by Gafurov and Bardossy also achieved similar mean overall accuracy but with the higher variability within the individual images as compared with the variability within the results obtained by the proposed method. SCD computed from cloud removed SCPs matched significantly with the field observed SCD for a point location, supporting the accuracy achieved by the cloud removal method. This study also examines the spatiotemporal variability of the snow cover in the study area during the past 18 years (2000–2018). During the observation period, no specific trend was observed for annual maximum snow cover, while yearly minimum snow cover in the basin showed an increasing trend since 2010. Seasonally, December and June month witnessed significant changes. December experienced a declining trend in snow cover between 3000–6000 m a.s.l. covering 88% of the basin area, whereas, June showed an increasing trend between 4500 to 6000 m (a.s.l.). This elevation range covers 61% of the basin area, including core 86% of the glacier area within the basin. September and October experienced the highest inter-annual snow cover variability. Maximum snow cover month of February and minimum snow cover month of August experienced the least variability. The present study suggests significant elevation-dependent increasing as well as the decreasing trend in the snow cover with seasonal contrast, which may affect the glaciers as well as the hydrological behavior of the basin. [ABSTRACT FROM AUTHOR]

We present a long-term assessment (1965–2018) of recessional and area change patterns as well as the recent decade surface velocity ( υ ‾ , 2000–2001 and 2017–2018) and elevation change ( d h / d t , 2003–2016) of the Parvati Glacier, north-western Himalaya. Multi-temporal high (Corona, Hexagon, and PlanetScope) to medium (Land Remote-Sensing Satellite (System, Landsat) Thematic Mapper (TM)/Enhanced Thematic Mapper+ (ETM+)/Operational Land Imager (OLI), Sentinel 2A- Multispectral Instrument (MSI), and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER)) resolution images from 1965 to 2018 were analysed to evaluate multi-parameters of glacier dynamics. We estimated an average annual recessional rate of 37.5 ± 0.5 m and total area loss of 2.2 ± 0.01 km2 for the Parvati Glacier over the past half-century (i.e. 1965–2018). During 1973–1989, the Parvati Glacier experienced a significant recession (70.9 ± 3.1 m a−1) that resultant into disintegrated of the glacier in two separate glaciers between 1981 and 1989. We observed a higher average recession rate (28.4 ± 1.6 m a−1) of the detached glacier after its disintegrated from the Parvati Glacier (18.7 ± 1.6 m a−1) between 1989 and 2018. However, the debris-covered ice area of the Parvati Glacier (about 12%) increased twice that of the detached glacier (about 6.1%) during 1994–2018. The estimated υ ‾ reveals a substantial slowdown by about 27.7% and about 20% for the Parvati and detached glacier, respectively, during 2000–2001 and 2017–2018. Overall the annual average surface lowering rate (−0.7 ± 0.5 m a−1) for both the glacier has been almost similar during 2003–2016 but varied significantly at altitudinal. Our study shows inconsistency in previously reported recessional rate and observed advance phases in 1976–1989 and 2009–2013 for the Parvati Glacier during almost the same duration of the study. It is mainly ascribed to the misinterpretation of glacier boundaries using the Survey of India (SoI) topographic map of 1962 where glacier boundaries more generalized and by using coarser resolution of Landsat Multispectral Scanner (MSS) images (1970s), particularly for the debris-covered area. Overall, the Parvati Glacier shows a significant recession and frontal area change; and in the recent decades, extensive surface lowering, along with an observable slowdown in glacier υ ‾ and appearance of ice-cliffs in the ablation area collectively point towards substantial glacier degeneration over the period of our analysis. [ABSTRACT FROM AUTHOR]

Using high-resolution Google EarthTM images in conjunction with Landsat images, the glaciers and lakes in the Baspa basin are classified to explore the recent changes. A total number of 109 glaciers (187 ± 3.7 km2) are mapped and subsequently classified as compound valley glaciers, simple valley glaciers, cirques, niches, glacieretes and ice aprons. The compound and simple valley glaciers contribute 67.1 ± 1.3% and 19.8 ± 0.3% to the total glacier cover of the basin. Similarly, a total number of 129 glacial lakes (0.360 ± 0.007 km2) are identified. From 1976 to 2011, the compound valley glaciers have lost a small area of 10.3 ± 0.03% at a rate of 0.41 ± 0.002 km2 a-1, whereas the niche glaciers have lost higher area of 40.1 ± 0.001% at a rate of 0.04 ± 0.0001 km2 a-1. Change detection of two benchmark glacial lakes revealed a progressive expansion during recent decades. The Baspa Bamak proglacial lake has expanded from 0.020 ± 0.0004 km2 (2000) to 0.069 ± 0.001 km2 (2011). Due to the complete loss of source ice, another glacial lake has expanded from 0.09 ± 0.001 km2 (1994) to 0.10 ± 0.002 km2 (2011). During the study period, the mean annual temperature that is Tavg, Tmin and Tmax have increased significantly at the 95% confidence level by 1.5 oC (0.070 °C a-1), 1.8 oC (0.076 °C a-1) and 1.6 oC (0.0071 °C a-1) from 1985 to 2008. However, the precipitation has decreased significantly from 1976 and 1985 to 2008. [ABSTRACT FROM AUTHOR]

This study assesses the impact of glacier changes and their effects on glacier melt runoff over three different Himalayan river basins located in western Himalaya (i.e. Baspa and Ganga) and eastern Himalaya (Teesta). For computation of glacier melt runoff, a fully distributed snow-glacier melt runoff model viz. SPHY has been used. The glacier area changes have been computed by preparing the glacier maps for different years for all selected river basins viz. Baspa (for year 2000 & 2018), Ganga (for year 1990, 2000, 2010 and 2020) and Teesta (for year 2000 and 2020). Results showed that the glacier areas have noticeably reduced for all Himalayan river basins viz. Baspa (∼19.8%), Ganga (∼5.01%) and Teesta (∼5%). It has been observed that smaller glaciers have more significantly reduced than large glaciers. The strength of the glacier melt induced runoff computation has been evaluated with reference to observed discharge at different gauges in all selected river basins, which showed a reliable agreement between modeled and observed runoff (R2 > 0.7). To see the behavior of runoff for different glacier sized watersheds, the three basins have been divided into a number of watersheds. In Baspa four watersheds while for Ganga and Teesta basins, six watersheds have finally selected depending on quantum of glacier. As per the decadal computation of glacier melt scenarios for all river basins viz. Baspa (i.e. 2003–2010 and 2011–2018), Ganga (1986–1995, 1996–2005, 2006–2015, and 2011–2020) and Teesta (1996–2010 and 2006–2020), observations showed that watersheds having large glaciers, the melt runoff has increased, while in cases of the watersheds having small glaciers, the melt runoff has decreased due to reduced glacier cover. In case of Baspa basin, glacier melt runoff has decreased by 5% while for Ganga and Teesta basins it has increased by 1%. Similarly, for Baspa basin, snowmelt runoff has increased by 6% and for Ganga and Teesta it has decreased by 3%. • This study demonstrates the comparative assessment of glacier changes and their impacts on melt runoff. • Separation of snowmelt runoff and glacier melt runoff from the total runoff. • Analysis of the behavior of runoff for different glacier sized watersheds under varying glacier characteristics. • Glacier melt runoff and snowmelt runoff change assessment at different stations using varying degree-day factors. [ABSTRACT FROM AUTHOR]

Himalayan glaciers are normally difficult to monitor through field observations because of highly rugged and extremely inaccessible mountainous terrain. Thus, using Landsat data (MSS, ETM+ and TM), changes in glacier area, length, and debris cover have been delineated in the Baspa basin, which is a highly glacierized sub-basin of the Satluj River in the western Himalaya. Out of the total 109 glaciers inventoried through Landsat TM imagery (2011), 36 glaciers were found to be heavily debris covered (32.5 ± 2.0%). A shrinkage in glacier area of 41.2 ± 10.5 km2 (i.e., 18.1 ± 4.1%) at a rate of 1.18 ± 0.3 km2 a-1 from 1976 (227.4 ± 9.4 km2) to 2011 (186.2 ± 3.7 km2) has been recorded. The overall glacier retreat studied for 33 glaciers varied from 3.3 ± 0.03%, that is, 0.87 ± 0.06 km at a rate of 17.2 ± 1 m a-1 to 30 ± 6.6%, that is, 0.60 ± 0.04 km at a rate of 24.8 ± 0.2 m a-1. Consequently, the debris cover has increased by 23.5 ± 1.4 km2 (16.3 ± 3.8%) from 1976 to 2011. Overall, the clean, small sized, low-altitude glaciers with south to southwest aspect and relatively steep slope have lost maximum area, which indicated a major control of these factors on the glacier changes. Simultaneously, a trend estimation of observed climatic data (1976/1985-2008) of three meteorological stations (Sangla, Rakcham, and Chitkul) using Mann Kendall test, Sen's Slope estimator and linear regression test revealed an increase in temperature and rainfall while a decline in snowfall. Importantly, the T min has increased significantly at 95% confidence level during all the studied periods. The mean annual T min and T max indicated a rising trend at a rate of 0.076 and 0.071 °C a-1. Thus, the changes in temperature and precipitation may be the major causes of accelerating the glacier ablation. The higher area changes (53.0 ± 0.4%), of small glaciers <0.5 km2 mark their sensitivity to climatic changes especially rising temperature. Under the warming climate, formation and progressive expansion of glacial lakes is expected because of the glacier recession in the basin. For instance, the Baspa Bamak Proglacial Lake at the snout of Baspa Bamak glacier has expanded continuously from 2000 onward. [ABSTRACT FROM AUTHOR]

Snow is important for hydrological studies and is a variable very sensitive to climatic variations. In the present study, the variability of snow-covered areas (SCAs) obtained through Moderate Resolution Imaging Spectroradiometer (MODIS) snow data products was analysed using the Mann–Kendall test and Sen’s slope estimator in the Sutlej basin, Western Himalayas, India. However, due to the limitations of long time-series snow cover data, the study has been carried out for a time period from 2000 to 2009. Before trend analysis, the estimated SCA was validated using the ground-based snowfall data. A simple linear regression test was applied to analyse the relationship between the variation in SCA and snowfall. The relationship between the mean annual snowfall and SCA indicated a highly significant correlation (R2 = 0.95). In order to have a better insight into the relationship, the regression test was also carried out for six elevation zones. The coefficient of determination (R2) varied from 0.78 at the 1500–2000 m asl zone to 0.96 at the 3000–3500 m asl zone. The trend analysis indicated reduction in SCA with significant negative behaviour for annual, winter, and post-monsoon seasons and for November and December months. The negative trend was observed for an elevation of <2500 m asl in the basin. Moreover, during the same period (2000–2009), the temperature (TmaxandTmin) increased while there was a decrease in snowfall. The trend analysis of temperature from 1984 to 2009 revealed positive trends with significant trend inTminas determined by using the Mann–Kendall statistical test. The reduction in SCA was, therefore, attributed to the increasing trends in temperature, particularlyTmin, associated with reduction in snowfall. These SCA variations have significant implications for water resources managers in the area as some of these observed trends, if continue, may result in changes in hydrological/ecological balance of the Sutlej basin. [ABSTRACT FROM AUTHOR]

Snow is an essential resource present in the Himalaya. Therefore, monitoring of the snowfall changes over a time period is important for hydrological and climatological purposes. In this study, variability of snowfall from 1976-2008 were analysed and compared with variability in temperature ( T and T) from 1984-2008 using simple linear regression analysis and Mann-Kendall test in the Satluj Basin. The annual, seasonal, and monthly analyses of average values of snowfall and temperature ( T and T) have been carried out. The study also consists an analysis of average values of annual snowfall and temperature over six elevation zones (<1500 to >4000 m amsl). During the study, it was observed that the snowfall exhibited declining trends in the basin. The snowfall trends are more sensitive to the climate change below an elevation of 4000 m amsl. Over the elevation zones of 3000-3500 and 4000-4500 m amsl, positive trends of mean annual values of snowfall were observed that may be due to higher precipitation as snowfall at these higher elevations. Although, both negative and positive snowfall trends were statistically insignificant, however, if this decreasing trend in snowfall continues, it may result in significant however, changes in future. Furthermore, the T is also increasing with statistically significant positive trend at 95% confidence level for November, winter season, annually as well as for the elevation zones of 2500-3000, 3000-3500, and 3500-4000 m amsl. There are dominantly increasing trends in T with negative trends for February, June-September, monsoon season, and for elevation zone <1500 m amls. It is important to state that in the present basin, during the months of winter season, most of the precipitation is produced as snowfall by the westerly weather disturbances. Thus, the declining nature in snowfall is concurrent with the positive trends in temperature particularly T, therefore, reflecting that the positive trends in T may be the dominant factor besides T in controlling the snowfall trends. The snowfall data were also compared with SCA and this showed a highly positive correlation of 0.95% which validates the utilisation of time series of snowfall for the trend analysis. [ABSTRACT FROM AUTHOR]

A wide range of methods for detection of glacial lakes and their expansions using multi-temporal remote sensing images have been employed in the past. This paper presents a framework for semiautomatic detection of glacial lakes and estimation of its expansion in Chamkhar Chu Basin, Hindukush Himalaya, Bhutan, with the help of ASTER multispectral image classifications. Lakes in the glacierized area tend to have a varying spectral response ranging from light blue or green to almost black which makes them difficult to be differentiated from shadows in the region. Detection of glacial lakes has been performed using NDWI technique and support vector machine image classification approach and results were compared. An integrated thermal-optical dataset was generated for applying SVM technique, and results showed that the lakes under cast shadow were accurately detected. Water spread extent of the lake has been estimated and it was observed that the present expansion rate of glacial lake has increased by twofolds from its previous rate in the last decade. The formations, deformations around glacial lake and related geomorphological variations occurring around lake were employed in defining the expansion mechanism of the lake. This study also demonstrates that ASTER data provide the possibility of accurate detections and estimation of water spread of glacial lake without simultaneous field observations. [ABSTRACT FROM AUTHOR]

Glaciers are widely recognized as key indicators of climate change, and melt water obtained from them is an important source of fresh water and for hydropower generation. Regular monitoring of a large number of Himalayan glaciers is important for improving our knowledge of glacier response to climate change. In the present study, Survey of India topographical maps (1966) and Landsat datasets as ETM+ (2000, 2006) and TM (2011) have been used to study glacier fluctuations in Tirungkhad basin. A deglaciation of 26.1% (29.1 km2) in terms of area from 1966 to 2011 was observed. Lower altitude small glaciers (area < 1 km2) lost more ice (34%), while glaciers with an area <10 km2lost less (20%). The percentage of change in glacier length was 26% (31.9 km) from 1966 to 2011. The south-facing glaciers showed high percentages of loss. From 2000 to 2011, debris cover has increased by 1.34%. The analysis of the trend in meteorological data collected from Kalpa and Purbani stations was carried out by Mann Kendall non-parametric method. During the last two decades, the mean annual temperature (TmaxandTmin) has increased significantly, accompanied with a fall in snow water equivalent (SWE) and rainfall. The increasing trend in temperature and decreasing trend in SWE were significant at 95% confidence level. This observation shows that the warming of the climate is probably one of the major reasons for the glacier change in the basin. [ABSTRACT FROM AUTHOR]

lmost every year in the winter months (December-February), the vast Indo-Gangetic Plain south of the Himalaya is affected by dense fog. This fog is considered as radiational fog, and sometime it becomes smog (when it mixes with smoke). The typical meteorological, topographic and increasing pollution conditions over the Indo-Gangetic Plain are perhaps the common contributing factors for fog formation. In the present study, the North Indian fog has been successfully mapped and analysed using NOAA-AVHRR satellite data. In the winter seasons of 2005-06, 2006-07 and 2007-08, the fog-affected area has been found to cover about 575,800 km, 594,100 km and 478,000 km, respectively. Less fog in 2007-08 may be the consequence of high fluctuations in the meteorological parameters like temperature, relative humidity and wind speed as related to the prevailing synoptic regime for that season. The dissipation and migration pattern of fog in the study area has also been interpreted on the basis of the analysis of both meteorological and satellite data. Further analysis of the fog-affected area allowed identifying more fog-prone regions. Analysis of past fog-affected days and corresponding meteorological conditions enabled us to identify favourable conditions for fog formation viz. air temperature 3-13°C, relative humidity >87%, wind speed <2 m/s and elevation <300 m. Based on the observations of past fog formation and corresponding governing parameters, fog for few selected days could be predicted in hind-sight and later verified with NOAA images. [ABSTRACT FROM AUTHOR]

Runoff regimes in Himalayan basins are controlled mainly by melting of snow and ice cover. The air temperature is the principal variable to estimate the importance of the melting of the snow cover when using snowmelt runoff model. Changes in temperature will ultimately affect stream flow and snow/ice melt runoff in particular. Global atmospheric general circulation models (GCMs) have been developed to simulate the present climate and used to predict future climatic changes and its effect. These GCMs have certain disadvantages, therefore another simple approach of hypothetical scenarios have been developed and successfully demonstrated in this study to investigate the effect of changes in temperature. Adopted plausible climate scenarios included three temperature scenarios (T + 1, T + 2, T + 3°C). The effect of these changes has been studied on the stream flow which has contribution from snowmelt, rainfall and base flow in the Satluj basin. It was observed that with the increase in temperature there is not much change in total stream flow, but the distribution of stream flow have changed. More snowmelt runoff occurred earlier due to increased snow melting however, reduced in the monsoon months. [ABSTRACT FROM AUTHOR]

Snow is a dynamic natural element, the distribution of which is largely controlled by latitude and altitude. In the tropical country like India, snow distribution is mostly controlled by altitude. The present study aims to identify the relationship between snow accumulation with elevation and aspect in rugged terrain in the Himalayan region. The river basins of four tributaries of the River Indus i.e. Satluj, Chenab, Ravi and Beas located in the western Himalaya were considered for study. Snow covered area was estimated for a period of 2 years (01 Jan 2003 to 17 Dec 2004) using MODIS 8 days' maximum snow cover products. Aspect and classified relief maps were prepared using the USGS DEM. The interrelationship between aspect, elevation and snow cover area was determined for all the four river basins and comparative analysis has been made. A 2 years average shows that Satluj has the minimum snow covered area 23%, while Chenab has the highest snow covered area i.e. 42%, Ravi and Beas has 33% and 38% respectively. The minimum elevation from where snow covered area appears has been calculated and it has been observed that in case of Satluj, snow appears at a higher elevation (1,369 m) while in Chenab snow appears at an elevation of 834 m, followed by Ravi (1,058 m) and Beas (1,264 m). It was found that aspect has a major impact on snow accumulation in the lower elevations in all the basins as compared to higher elevations. Snow accumulates most in the northwest and northeast aspect. The rate of change in snow cover with elevation is determined for all the river basins and it has been concluded that Satluj has the lowest rate of change of snow cover with elevation (1.3% per 100 m), Chenab 1.8% per 100 m, followed by Ravi 2% per 100 m and Beas (2% per 100 m). [ABSTRACT FROM AUTHOR]

• To study the effect of snow and glacier changes on glacier and snowmelt runoff. • Incorporation of real time snow cover and glacier maps derived from Satellite data. • Use of variable degree-day factors coupling with temperature index model. • Analyzing temporal variations in snow and glacier melt runoff in Himalayas. • Comparison of SPHY modeled snow cover with satellite derived snow cover. Monitoring the changes in glaciers and their impact on melt runoff is significant to assess the availability of water resources in the Himalayan basins. In this study, the spatial processes in Hydrology (SPHY) model has been incorporated with variable degree-day factors coupled with temperature index model in the Baspa river basin, a major tributary of Satluj River, located in Western Himalaya. The temporal glacier maps derived from the LANDSAT satellite sensors and Moderate Resolution Imaging Spectroradiometer (MODIS) derived snow covered area (SCA) maps have been used to compute the snow and glacier melt runoff separately. The SCA maps generated through the model were found comparable to the MODIS derived SCA maps for the years 2010 and 2018. Model simulation results showed that SPHY based computed flow at the outlet i.e. Sangla gauge was found satisfactory when compared to the observed flow and R2 computed >0.7. The contribution from Glacier melt has been found to be reduced from 18 to 12% while Snow melt contribution increased from 58 to 64% from 2000 to 2018. On the basis of analysis of the 17 watersheds (i.e. dominated by snow and glaciers) out of 30 watersheds created in the basin, the flow from Glacier melt in glacier dominated watersheds is increasing while in other watersheds it is reducing due to reduced glacier cover. On an average, Glacier melt has decreased 14% and 44%, Snow melt increased 24 and 42% and Rain flow (rainfall induced runoff) 31 and 40% for the year 2011 to 2018 with respect to the year 2003 from these 17 watersheds. As per SPHY, corresponding to glacier map of the year 2000, the glacier ice volume has been computed around 13.41 km3, while for the glacier map of 2018, it has been reduced around 10.99 km3. [ABSTRACT FROM AUTHOR]

Global change is expected to have a strong impact in the Himalayan region. The climatic and orographic conditions result in unique modelling challenges and requirements. This paper critically appraises recent hydrological modelling applications in Himalayan river basins, focusing on their utility to analyse the impacts of future climate and socio-economic changes on water resource availability in the region. Results show that the latter are only represented by land use change. Distributed, process-based hydrological models coupled with temperature-index melt models are predominant. The choice of spatial discretisation is critical for model performance due to the strong influence of elevation on meteorological variables and snow/ice accumulation and melt. However, the sparsity and limited reliability of point weather data, and the biases and low resolution of gridded datasets, hinder the representation of the meteorological complexity. These data limitations often limit the selection of models and the quality of the outputs by forcing the exclusion of processes that are significant to the local hydrology. The absence of observations for water stores and fluxes other than river flows prevents multi-variable calibration and increases the risk of equifinality. The uncertainties arising from these limitations are amplified in climate change analyses and, thus, systematic assessment of uncertainty propagation is required. Based on these insights, transferable recommendations are made on directions for future data collection and model applications that may enhance realism within models and advance the ability of global change impact assessments to inform adaptation planning in this globally important region. [ABSTRACT FROM AUTHOR]