Ganga River Basin Research Articles

Factors influencing the adoption of organic farming: a case of Middle Ganga River basin, India

Factors influencing the adoption of organic farming: a case of Middle Ganga River basin, India

Impact of Forestry Interventions on Groundwater Recharge and Sediment Control in the Ganga River Basin

Water related services of natural infrastructure will help to combat the risk of water crisis, and nature-based solutions involve the management of ecosystems to mimic or optimize the natural processes for the provision and regulation of water. Forested areas provide environmental stability and supply a high proportion of the world’s accessible freshwater for domestic, agricultural, industrial and ecological needs. The present work on “Forestry Interventions for Ganga” to rejuvenate the river is one of the steps toward the Ganga River rejuvenation programme in the country. The consequences of forestry interventions for Ganga will be determined on the basis of water quantity and water quality in the Ganga River. The study conservatively estimated the water savings and sedimentation reduction of the riverscape management in the Ganga basin using the Soil Conservation Service Curve Number (SCS-CN) & GEC, 2015 and Trimble, 1999 & CWC, 2019 methodologies, respectively. Forestry plantations and soil and moisture conservation measures devised in the programme to rejuvenate the Ganga River are expected to increase water recharge and decrease sedimentation load by 231.011 MCM·yr-1 and 1119.6 cubic m·yr-1 or 395.20 tons·yr-1, respectively, in delineated riverscape area of 83,946 km2 in Ganga basin due to these interventions. The role of trees and forests in improving hydrologic cycles, soil infiltration and ground water recharge in Ganga basin seems to be the reason for this change. Forest plantations and other bioengineering techniques can help to keep rivers perennial, increase precipitation, prevent soil erosion and mitigate floods, drought & climate change. The bioengineering techniques could be a feasible tool to enhance rivers’ self-purification as well as to make river perennial. The results will give momentum to the National Mission of Clean Ganga (NMCG) and its Namami Gange programme including other important rivers in the country and provide inputs in understanding the linkages among forest structure, function, and streamflow.

Spatio-temporal variation of trace elements distributed over surface water of Upper Ganga River Basin in Western Himalayan Region

Spatio-temporal variation of trace elements distributed over surface water of Upper Ganga River Basin in Western Himalayan Region

Flood susceptibility prediction using multi criteria decision analysis and bivariate statistical models: a case study of Lower Kosi River Basin, Ganga River Basin, India

Flood susceptibility prediction using multi criteria decision analysis and bivariate statistical models: a case study of Lower Kosi River Basin, Ganga River Basin, India

Heavy metal distribution in various environmental matrices and their risk assessment in Ganga River Basin, India

This study focuses on heavy metals distribution and their ecological risk in river water, bed sediment, and suspended particulate matter (SPM) along the Ganga River basin. Overall abundance of the metals followed the sequence, Fe > Al > Mn > Pb > Ni > Cd > Cr > Zn > Co in water, Al > Fe > Mn > Zn > Cr > Cu > Ni > Co > Pb > Cd in bed sediment, while Al > Fe > Mn > Cr > Zn > Ni > Cu > Pb > Co > Cd in SPM. Among the abundant metals, Fe and Mn average concentrations exceeded BIS and WHO limits in river water. Similarly, Fe, Cd, and Zn, and most metals exceeded local background concentrations in bed sediment and SPM, respectively. Major ion chemistry in water signified carbonate weathering dominance during the time of sampling. Generally, Mn, Ni, Cu, Cr, and Co were derived from natural weathering and erosion, while Zn, Cd, and Pb were derived from both natural and anthropogenic sources. Metal index (MI) for river water showed that 27% of the locations were anthropogenically affected, whereas contamination factor and ecological risk assessment indicated highest contamination and risk from Cr and Cd in suspended sediments around urban centers in the middle basin. Furthermore, the confluence of Chambal and Yamuna increased heavy metal load in Yamuna and Ganga, respectively. The study highlighted the role of the water–sediment interaction indicating SPM is acting as a sink for metals followed by bed sediment.

Spatial connections in extreme precipitation events obtained from NWP forecasts: A complex network approach

Understanding the spatial variability of extreme precipitation events (EPEs) has always been a challenging task, with climate change further complicating the issue. Many studies have looked into the spatiotemporal characteristics of EPEs and the possibility of them being connected. Most of these studies are based on observation data products which inform about the events after they have occurred. Various Quantitative Precipitation Forecasts (QPFs) obtained from the Numerical Weather Prediction (NWP) models such as those of the European Centre for Medium-range Weather Forecasts (ECMWF), Japan Meteorological Agency (JMA), National Centre for Medium-Range Weather Forecasting (NCMRWF), and UK Met Office (UKMO) are available which inform about the precipitation events before they have occurred. In this study, we inter-evaluate four gridded (deterministic) QPFs over the Ganga River basin of India for their ability to detect the spatial connections among EPEs during the monsoon months, i.e., June, July, August and September (JJAS). Several experimental runs are performed in multiple time periods (13, 6 and 4 years) at various percentile thresholds (85th, 90th and 95th percentile) at two spatial resolutions of 25 and 50-km. Moreover, we also evaluate the forecast patterns of the QPF obtained from the national agency of India, i.e., NCMRWF and analyse its performance with respect to the other three selected QPFs from international agencies. For the observation/reference dataset, the gridded Indian Meteorological Department (IMD) dataset is selected. We first use the deterministic and dichotomous error statistics to evaluate the performance of NWP forecasts. Further, we employ the theory of complex networks to create networks of extreme precipitation at each grid. With this work, we aim to answer (a) can the theory of complex networks be a feasible tool for evaluating the performance of NWP forecasts in detecting extreme precipitation behaviour; (b) does the change in temporal length of the NWP forecasts influence the spatial structure of extreme precipitation as observed before, and (c) can a global NWP model, larger in length, be used as a potential substitute to the NCMRWF model. The ECMWF model performs well with respect to IMD as the average CC for TP_13 is 0.42 while they are 0.31 and 0.34 for TP_6 and TP_4, respectively. Also, we find that ECMWF can be a suitable substitute for the NCMRWF model. The identification of a substitute precipitation forecast, larger in temporal length, can be beneficial as input in hydrological models for streamflow forecasting and estimating parameters for bias correction of precipitation, among others.

Prioritising river stretches using multi-modelling habitat suitability of Gangetic dolphin (Platanista gangetica) as a flagship species for aquatic biodiversity conservation in the Ganga River Basin, India

Globally, the river ecosystems are threatened due to human-driven exploitation and indiscriminate resource use. The rate of species loss is a magnitude higher in these ecosystems, hence, identifying conservation priority areas as refugia, using the flagship-cum-indicator species approach can aid in long-term conservation of multiple species and ensure uninterrupted functioning of ecological processes. For effective conservation planning, we derived the site occupancy and abundance of Gangetic dolphin (Platanista gangetica) as a flagship species in the Ganga River Basin, and modelled their distribution vis-à-vis river conditions for identifying Conservation Priority Stretches (CPS). The study incorporates the first-ever basin-wide (4635 km river) Gangetic dolphin (GD) sightings to estimate range decline, abundance, and identify CPS of select rivers in the Basin. A total of 2151 sightings of surfacing dolphins with mean encounter rate of 0.55 ± 0.09 sightings/km of the river was observed from the surveyed stretch. The GD encounter rate varied significantly across the surveyed rivers (Analysis of Variance, F = 3.08, p < 0.001). We estimated 24.37 % decline in the dolphin distribution range in the basin since 19th Century. The estimated population size of the dolphin in the Basin was 3330 individuals ± 620 individuals (Confidence Interval 95 % = 2304–4668; Coefficient of Variance = 18.61) which varied across the river. The site occupancy and abundance were best predicted by channel depth (β = 0.82 ± 0.46), meanders (β = 02.56 ± 0.87) and individual rivers, whereas channel width (β = 0.11 ± 0.08) and survey efforts influenced detection probabilities. Further, we identified 610 km (12.2 %) of river stretches as high CPS in the Basin based on the prediction probability (≥0.70) of GD. Protection of these stretches is likely to ensure sustained reproduction of GD and provide refugia for other threatened species of the Ganga River and its tributaries, which is under increasing anthropogenic pressure.

Biogeochemical appraisal of carbon fractions and carbon stock in riparian soils of the Ganga River basin

The farmers are approaching river/reservoir beds to produce crops and vegetables during the lean periods, especially post-monsoon, winter, and summer, for their livelihood in changing climatic scenarios. Comparing C fractions, C stocks, and microbial indices between the terrestrial (conventional agricultural land: CAL) and riparian zones (reservoir riparian zones: RSRZ and river riparian zones: RRZ) reveals that cultivating riparian zones is environmentally stressful and climatically vulnerable to livelihood practices. The moist riverbed conditions for cultivation result in the accumulation of residual biomass and the burial of soil organic matter. The C fractions showed decreasing trends as CAL > RSRZ > RRZ. The mean TOC stock was found high in the CAL soils (45.04 Mg C ha−1) than in the RRZ (40.65 Mg C ha−1) and RSRZ soils (38.01 Mg C ha−1). The labile C fraction (KMnO4-C) varied from 2.34 to 3.29 % of TOC, and the RSRZ and RRZ soils showed 14.50 % and 40.32 % less KMnO4-C than the CAL soils. The relationship between KMnO4-C and mineralizable C (Cmin) showed high potential for organic carbon stabilization in riparian soils. The microbial biomass carbon (MBC) and basal soil respiration (BSR) values were nearly half of the CAL in the RRZ soils indicating limited carbon substrate availability to the microbial decomposition. Low mineralization quotient (qM) and high metabolic quotient (qCO2) indicated stressful microbial utilization of labile TOC in the RRZ soils. The high carbon management index (CMI) showed the potential to store and sequester TOC in riparian soils. The artificial neural networks (ANN) were used to examine the impact of soil properties on the prediction efficiency of TOC stocks in the three farming zones.

Assessment of the natural flow regime and its variability in a tributary of Ganga River: Impact of land use and land cover change

Accurate assessment of hydrological processes in a catchment including the estimation of virgin or natural flow regime of the rivers is critical to maintaining healthy river ecosystems, particularly in the developing nations that currently face the challenges of limited quantity and poor quality of available water. In this work, we aim to estimate the natural river flow and its variability due to land use and land cover (LULC) alterations over a period of ∼43 years (1970–2013–14) in the Ramganga River Basin (RRB), a sub-basin of the most fertile and densely populated basin in the world i.e., the Ganga River Basin. Hydrological modeling of the RRB was performed using the Soil and Water Assessment Tool (SWAT) and its performance was evaluated by performing statistical analysis (e.g. coefficient of determination and Nash–Sutcliffe efficiencies). The simulated flows exhibited good agreement with the observed flows at the three flow monitoring stations in the RRB - Katghar, Chaubari, and Dabri. Upon achieving a good model performance, the natural flows for the 2013-14 LULC scenario were estimated by removing all existing flow interventions (e.g. dams and barrages) and irrigation usage. Average annual natural flows were observed to be higher by at least ∼40% than the average annual existing flows (i.e., flows estimated with current managed conditions) for the three stations. Historical LULC information for the basin was obtained from the object-based image classification of CORONA satellite images (1970). The annual average natural flows for the 1970 scenario were observed to be lower (3–12%) than the 2013-14 scenario which could be attributed to a significant increase in urban settlements and a reduction in the area coverage by barren land and shrubs and bushes. Overall, our work provides valuable insights into the natural flow regime and its variability due to anthropogenic activities and long-term LULC alterations in the RRB which may inform future strategies for sustainable water resources management in the basin.

Prediction of Surface Water Quality of Upper Ganga in Uttar Pradesh

Abstract: With an increase in population and accelerated pace of industrialization, water quality is going to degrade day-by-day. The main source of water in India is from rivers. The Ganga River Basin is the world’s most populated and is home to half of India’s population, including two-thirds of the nation’s poor. This paper highlights the utility of statistical techniques for evaluating, interpreting complex data sets and recognizing spatial differences in water quality for effective management of river water quality. The Autoregressive Integrated Moving Average (ARIMA) model uses time-series data and statistical analysis to interpret the data and make future predictions. 6 water quality parameters Dissolved Oxygen, BOD, pH, Temperature, Electrical Conductivity and Total Coliform are analysed and predicted. In this work 4 monitoring station is taken for the prediction analysis and data is taken from the CPCB. In this work ARIMA model is giving the better prediction of temperature, total coliform and conductivity in compare of other water quality parameter pH, BOD and DO. The max value for correlation coefficient for Dissolved Oxygen, BOD, pH, Temperature, Electrical Conductivity and Total Coliform are respectively 0.73, 0.76, 0.79, 0.83, 0.84 and 0.85.

Moisture source identification for precipitation associated with tropical cyclone development over the Indian Ocean: a Lagrangian approach

In this study, we investigated the moisture sources for precipitation through a Lagrangian approach during the genesis, intensification, and dissipation phases of all tropical cyclones (TCs) that occurred over the two hemispheric sub-basins of the Indian Ocean (IO) from 1980 to 2018. In the North IO (NIO), TCs formed and reached their maximum intensity on both sides of the Indian Peninsula, to the east in the Bay of Bengal (BoB), and to the west in the Arabian Sea (AS). The oceanic areas where TCs occurred were their main moisture sources for precipitation associated with TCs. Additionally, for TCs over the BoB, continental sources from the Ganges River basin and the South China Sea also played a notable role; for TCs over the AS, the Somali Low-Level jet (along the African coast in a northerly direction) also acted as an essential moisture transport. In the South IO (SIO), the western, central, and eastern basins were identified as the preferred areas for the genesis and development of TCs. During TC activity, the central IO and the Wharton and Perth basins mostly supplied atmospheric moisture. The Mascarene High circulation was the main moisture transport mechanism for the precipitation of TCs formed in the SIO basin. In both basins, during their intensification process, TCs gained more moisture (even more intensely when reaching the hurricane category) than during the genesis or dissipation stages. Additionally, the modulation during monsoonal seasons of the moisture contribution to the TCs was more noticeable over the NIO basin than for the SIO. Overall, the moisture uptake for precipitation from the sources for TCs occurred slightly faster in the NIO basin than in the SIO basin.

Challenges in Understanding the Variability of the Cryosphere in the Himalaya and Its Impact on Regional Water Resources

The Himalaya plays a vital role in regulating the freshwater availability for nearly a billion people living in the Indus, Ganga, and Brahmaputra River basins. Due to climate change and constantly evolving human-hydrosphere interactions, including land use/cover changes, groundwater extraction, reservoir or dam construction, water availability has undergone significant change, and is expected to change further in the future. Therefore, understanding the spatiotemporal evolution of the hydrological cycle over the Himalaya and its river basins has been one of the most critical exercises toward ensuring regional water security. However, due to the lack of extensivein-situmeasurements, complex hydro-climatic environment, and limited collaborative efforts, large gaps in our understanding exist. Moreover, there are several significant issues with available studies, such as lack of consistent hydro-meteorological datasets, very few attempts at integrating different data types, limited spatiotemporal sampling of hydro-meteorological measurements, lack of open access toin-situdatasets, poorly accounted anthropogenic climate feedbacks, and limited understanding of the hydro-meteorological drivers over the region. These factors result in large uncertainties in our estimates of current and future water availability over the Himalaya, which constraints the development of sustainable water management strategies for its river catchments hampering our preparedness for the current and future changes in hydro-climate. To address these issues, a partnership development workshop entitled “Water sEcurity assessment in rIvers oriGinating from Himalaya (WEIGH),” was conducted between the 07th and 11th September 2020. Based on the intense discussions and deliberations among the participants, the most important and urgent research questions were identified. This white paper synthesizes the current understanding, highlights, and the most significant research gaps and research priorities for studying water availability in the Himalaya.

Multi-faceted analyses of seasonal trends and drivers of land surface variables in Indo-Gangetic river basins

The Indo-Gangetic river basins feature a wide range of climatic, topographic, and land cover characteristics providing a suitable setting for the exploration of multivariate time series. Here, we collocated a comprehensive feature space for these river basins including Earth observation time series on the normalized difference vegetation index (NDVI), surface water area (SWA), and snow cover area (SCA) in combination with driving variables between December 2002 and November 2020. First, we evaluated changes using multi-faceted trend analyses. Second, we employed the causal discovery algorithm Peter and Clark Momentary Conditional Independence (PCMCI) to disentangle interactions within the feature space. PCMCI quantifies direct and indirect relationships between variables and has been rarely applied to remote sensing applications. The results showed that vegetation greening continues significantly. Irrigated croplands in the Indus basin indicated the highest trend magnitude (0.042 NDVI/decade−1). At annual and basin scale, positive trends were also identified for SWA in the Indus (837 km2/decade−1) and Ganges basin (677 km2/decade−1). Annual trends in SCA were insignificant at basin scale. Considering elevation zones, negative SCA trends were found in high altitudes of the Ganges and Brahmaputra river basins. Similarly, NDVI and SWA showed positive trends in high elevations. Furthermore, the causal analysis revealed that NDVI was controlled by water availability. SWA was directly influenced by river discharge and indirectly by precipitation. In high altitudes, SWA was controlled by SCA and temperature. Precipitation and temperature were identified as important drivers of SCA with spatio-temporal variations. With amplified climate change, the joint exploitation of time series will be of increasing importance to further enhance the understanding of land surface change and complex interplays across the spheres of the Earth system. The insights of this study and used methods could greatly support the development of climate change adaptation strategies for the investigated region.

Climate change and water scarcity will increase risk of nuclear catastrophe in South Asia

ABSTRACT Climate change poses grave challenges to global peace and stability. Nowhere is the relation between the climate crisis and the increased threat of nuclear war clearer than in South Asia, where approximately 700 million people in India, Pakistan, China, and Bangladesh depend on the shared waters of the Indus, Ganges, and Brahmaputra river basins. These river systems, fed by Himalayan glaciers, are diminishing markedly due to climate change. As geopolitical tensions in the region intensify, it becomes even more crucial to address and eliminate the two intertwined existential threats of water scarcity (caused by climate change) and the risk of nuclear war. This paper analyses the Indus River conflict and the Brahmaputra conflict in turn and offers effective strategies and recommendations for dealing with the threats.

Are there any effects of eco-climatic factors on freshwater prawn reproduction: a study on monsoon river prawn, Macrobrachium malcolmsonii.

Prawns are regarded as delicious food items and a source of income as it is the salient exportable fishery item of Bangladesh and a number of other countries. Climate change may inhibit the general physiological activity of prawns. This study explored the eco-climatic effects on reproduction, including size at first sexual maturity (Lm), spawning season, and fecundity of monsoon river prawn, Macrobrachium malcolmsonii (Milne-Edwards, 1844). The study was carried out in the Ganges (Padma) River basin, northwestern Bangladesh, from January to December 2014. Seven hundred fifty-seven specimens ranging from 0.80 to 18.27g BW (body weight) with TLs (total length) of 4.20 to 11.52cm were analyzed. The Lm was estimated as 6.2-6.6cm. Total fecundity was higher than earlier studies and ranged from 2743 to 122,165 with a mean value of 6715 ± 2437. The spawning season was estimated from April to October with a peak in July. Significant correlation was found between rainfall and the presence of ovigerous females, i.e., spawning season. The number of ovigerous females increased in ≥ 100mm average rainfall, and the maximum ovigerous female spawned at 250-320mm rainfall. Spawning season of M. malcolmsonii may have shifted with shifting rainy season as a result of climate change. The findings of our investigation would be useful for sustainable management of the fishery of M. malcolmsonii and other prawn species in the Ganges River, Bangladesh, and adjoining countries with similar eco-climatic factors.

Influence of Hydrology and Sanitation on Groundwater Coliform Contamination in Some Parts of Western Bengal Basin: Implication to Safe Drinking Water

Access to clean water has been identified as one of the primary Sustainable Development Goals. Rapid urbanization is going on in developing nations creating additional pressure on water resources in most of these places which in turn also affects individuals which is largely reliant on proper sanitation and drinking water quality. In addition, open sanitation practice is becoming major public health problem in rural and in some urban areas in India. Groundwater contamination by pathogenic bacteria sourced from both sanitation system and surface water is becoming one of the major concerns now-a-days. The residents of the Ganges river basin in India are already stressed with natural arsenic pollution as well as other various types of water pollution, and microbial pollution from sanitation is a new addition to it. A field-based hydrogeological investigation with the identification of sanitation sites (surface and subsurface) was conducted in some parts of the Ganges basin, in and around a lower order distributary river, River Churni in West Bengal state, to identify the natural and human influences on sanitation drinking water pollution in a highly populated part of South Asia. Groundwater was found to be contaminated severely with total (TC) and fecal (FC) coliform bacteria. The abundance of TC was found to be the highest in monsoon season (78%) than in pre-monsoon (48%) and post-monsoon (29%) seasons. The results revealed that the groundwater samples from shallow depths and close to sanitation sites were highly contaminated with coliform bacteria than the deeper and higher distant (&amp;gt;30 m distance) ones. Shallow groundwater samples near to surface water (River Churni) source, other than sanitation sites, showed elevated TC levels. The occurrence of coliform bacteria in studied groundwater samples was observed to be positively correlated with conductivity, TDS, TOC, chloride, and sulfate, while the abundance was restricted by pH and temperature of groundwater. Thus, improper sanitation systems and contaminated surface water were identified as one of the major sources of pathogenic contamination of groundwater-sourced drinking water in the studied area, whereas improper human practices further complicate the scenario which needs to be managed properly.

Toward SDGs: Forest, Market and Human Wellbeing Nexus in Indian Western Himalayas

The wellbeing of mountain communities is determined by the availability and accessibility of ecosystem goods and services. We assessed the relationship between forest quality and wellbeing of local communities of Nanda Devi Biosphere Reserve (NDBR) in the Upper Ganga River Basin, Western Himalayas, India. We used 14 relevant Sustainable Development Goals of the United Nations as indicators to assess wellbeing. Data on these indicators were collected in 22 villages that were selected based on secondary demographic information, remoteness, and the state of the forest resources, which we classified into degraded and less-degraded. Semi-structured questionnaire-based interviews were conducted in randomly selected households (n = 764). The households located close to forests scored higher on wellbeing indicators than the households located further away from forests as they have better accessibility to forest resources and freshwater, which provides alternatives to market and agricultural products. Households with access to less-degraded resources also had access to wild fruits, vegetables, and medicinal plants adding to their food and health security. Our study found that the combination of climate change, declining forest resources, and the expansion of the market-based economy is leading to shifts in traditional cropping patterns and hence the nutritional status and forest use patterns of local people, making them vulnerable to diseases and hunger. Accessibility to an intact forest patch near a village contributes to the wellbeing of people and increases their resilience in the face of climate change and the changes dictated by the market forces.

Hydrogeochemical and health risk assessment in and around a Ramsar-designated wetland, the Ganges River Basin, India: Implications for natural and human interactions.

Wetlands are the most productive and dynamic ecosystems, which have continuously been influenced by social and economic development. As a result, the pollution of wetland surface water and groundwater in adjacent regions has become an emerging global issue that requires constant monitoring and assessment. The current study investigates the natural and anthropogenic processes that influence surface and groundwater chemistry in and around Saman wetland (a Ramsar site) in the Ganges River Basin, India. Various physicochemical parameters are analyzed, and different hydrochemical indices are utilized to evaluate surface and groundwater quality for domestic and irrigation purposes. It is observed that the waters are alkaline in nature and dominated by moderately hard to hard types. An increase in the concentration of nitrate (NO3-) in Saman wetland water is noted, which is possibly due to the leaching of nitrogen ions primarily from fertilizers, pesticides, animal and human waste, and wastewater drained from brick and other factories. The elevated fluoride (F-) content in studied groundwater samples is mainly governed by geogenic processes. Furthermore, surface and groundwater chemistry are mainly controlled by weathering reaction (rock-water interaction), excluding a few wetland surface water samples that are placed outside the boomerang-shaped boundaries of Gibb's diagram, which suggests evaporated dominance. Water Quality Index (WQI) estimation suggests that around 57% of groundwater samples have poor groundwater quality for drinking purposes. Estimation of irrigation water quality indices suggests that surface water of Saman wetland is permissible for irrigation purposes; however, none of the samples have excellent and good class as per sodium (alkali) hazard. Furthermore, health risk assessment showed that NO3- and F- levels in the groundwater pose noncarcinogenic health effects, preferably to children, and thus is unfit for drinking purposes. For long-term water resource management and conservation of the Saman wetland, this study suggests proper awareness, appropriate remedial measures, and regular monitoring of the surface as well as groundwater quality monitoring in the study region.

Spatiotemporal heterogeneity and driving mechanisms of Himalayan glacier mass change in the early 21st century

Glaciers in the Himalayan mountain ranges contain huge amounts of water and are essential for the water security of their downstream basins. Due to the spatiotemporal heterogeneity and uncertainty of the glacier mass change (GMC) in the Himalayas, more refined and deeper investigations on the GMC and its driving forces are needed to complement the current research. We present the mass balance of Himalayan glaciers during 2000 to 2013 using the latest global digital elevation models; this method focuses on establishing a high-coverage result of the GMC and resolving the problems of timestamps and penetration uncertainties. The GMC of the entire Himalayas is −0.32 ± 0.15 m w.e.yr − 1; most of the lost mass drains into the Indus and Ganges river basins. Glacier mass loss gradually decreases from east to west, with the East and Central Himalayas exhibiting the highest heterogeneity in the vertical and horizontal directions, respectively. We propose two multivariate regression models with 12 potential driving factors that explain 63% to 89% of the GMC across different regions of the Himalayas. Precipitation significantly influences changes in glacier mass throughout the Himalayas, whereas debris coverage and glacier size have insignificant effects on changing the glacier mass. Our analysis reveals that seasonal climate-driven changes in the glacier mass of the Himalayas may threaten the downstream water supply.

Spatiotemporal dependence of soil moisture and precipitation over India

Anthropogenic climate change has impacted almost all phases of the global water cycle. Growing consensus asserts that extreme precipitation events will only rise in the years to come. However, an increase in extreme precipitation events does not necessarily correspond to higher flood risk. Much onus lies on the antecedent conditions before the storm events. Despite the importance of Soil Moisture (SM) – Precipitation (P) dependence in runoff generation, relatively few studies have unraveled the SM – P dependence. Previous studies were constrained by the direct trivial relationship existing between SM and P, and hence there is a need to understand direction and dynamical interdependency. We employed Event Coincidence Analysis (ECA) to identify and quantify the preconditioning of P extremes by soil moisture (SM) anomalies. High precursor coincidence rate (greater than45%) was obtained for traditional flash flood-prone areas over India - Ganga river basin, West-flowing rivers of Kutch and Saurashtra including Luni, inland drainage of Rajasthan and Narmada river basin, indicating the robustness of the approach. The trigger coincidence rate reveals strong SM-P coupling over central India. Our results indicate the applicability of ECA in characterizing the spatiotemporal patterns of SM-P dependence over India.