http://117.252.14.250:8080/jspui/handle/123456789/1761 2026-04-05T17:53:56Z http://117.252.14.250:8080/jspui/handle/123456789/7962 Large-scale modeling of solar water pumps using machine learning Zuffinetti, Guillaume; Meunier, Simon; Hudelot, Celine; John MacAllister, Donald; Krishan, Gopali; Lutton, Evelyne; Bhattacharya, Prosun; Kitanidis, Peter K.; MacDonald, Alan M. Photovoltaic Groundwater Pumping Systems (PVGWPSs) have experienced growing interest, particularly in two key regions. In Africa, they offer a means to improve water availability for millions. In northern India, they could help decarbonize the agricultural sector. However, large-scale deployment must be approached carefully to avoid risks such as groundwater overextraction or widespread unmet irrigation demand. To support informed deployment, a large-scale, physics-based, dynamic PVGWPS model is introduced, that simulates pumping ca pacities of PVGWPS. Given the computational intensity of this model, machine learning-based emulators are explored to replicate its results more efficiently without significant loss in accuracy. The emulator operates in two stages. First, it predicts whether the motor-pump will stop due to water level dropping below the operational threshold. Among the models tested, the Gradient Boosting Classifier model performed best. Second, when no stoppage is predicted, the emulator estimates the pumping capacity of the PVGWPS. Among the models tested for this second task, the Random Forest Regressor gave the most accurate results. Applied to datasets from Africa and the Indo-Gangetic Basin within India, the emulator achieved high accuracy (R 2 ≥ 0.99, NRMSE ≤ 5 %) while reducing computation time by more than a factor of 1500. The emulators thus offer high computational speed and sufficient accuracy to open the way to addressing large-scale dispatch problems, such as the optimal positioning and pre-sizing of PVGWPSs at regional, national, or even continental scales while considering a large number of possible climate scenarios. Coupled with sustainability analyses (not explored in this study), they could serve as powerful upstream decision-support tools for PVGWPSs planning, complementing more detailed, site-specific analyses . 2026-01-01T00:00:00Z http://117.252.14.250:8080/jspui/handle/123456789/7961 Analysing flood resilience in the anthropocene: Integrated insights from a multi-scalar extreme event in the himalayas Pathania, Ashish; Raaj, Saran; Krishan, Gopal; Lapworth, Dan; Brauns, Bentje; MacDonald, Alan; Gupta, Vivek; John MacAllister, Donald Extreme precipitation events are intensifying globally due to climate change, often leading to unprecedented f lood risks and challenges in water resource management. In August 2023, Punjab, India, experienced cata strophic flooding, impacting approximately 12,000 villages and resulting in 65 reported fatalities. The flood highlighted the need to understand better the multifaceted drivers of such extreme events, especially in regions dependent on major dams. This study analyzes the hydrometeorological drivers, dam operations, hydrological responses, and socioeconomic impacts associated with the event. A detailed spatiotemporal meteorological analysis demonstrates that heavy and very heavy rainfall events in July significantly elevated antecedent soil moisture levels, heightening the region's flood susceptibility in August despite seasonal rainfall deficits. Using HEC-RAS hydrodynamic modeling coupled with high-resolution demographic data, the study demonstrates the Pong Dam's critical role in mitigating flood impacts, reducing population exposure by approximately 80 % compared to unregulated conditions. A deterministic population exposure assessment was carried out using 2011 village-level census data. The results showed disproportionate impacts on vulnerable groups, with flood exposure rising from August 15–17 by ~49 % among children, ~46 % among women, and ~47 % among non-working populations. Genetic Algorithm-based optimization with a piecewise penalty function improved the balance between flood mitigation and water conservation. It underscores the importance of integrating real-time hydrological data to enable adaptive reservoir management. The study recommends that policymakers prioritize advanced flood forecasting systems incorporating soil moisture data, high-resolution rainfall forecasts, and demographic vulnerability indices, while addressing the critical operational challenges of data availability, monitoring density, and institutional capacity. 2025-12-01T00:00:00Z http://117.252.14.250:8080/jspui/handle/123456789/7953 Springs outflows in diverse geology and geomorphology of Seti Khola watershed, Western Nepal Pokhrel, Gunanidhi; Rijal, Moti Lal; Krishan, Gopal Springs are crucial for supporting life and balancing ecosystems and vary in outflow from place to place. A study was conducted in the mid-hill region of western Nepal, which spans between carbonate (44%) and non-carbonate (56%) lithology. A field survey identified 175 perennial springs, which were categorized based on their outflows using methods such as bucket-stopwatch, weir, and float techniques. Springs were grouped into minimum 0.1-10 liter per minute (lpm), intermediate 10-60 lpm, and maximum outflow 60-300 lpm categories. This study assessed the characteristics of springs, focusing on their lithology, elevation, landforms, and land cover. Springs in carbonate-dominant areas consistently exhibited higher outflows than those in non-carbonate areas. Intermediate outflow was the most frequent, particularly in forested areas. The occurrence of springs is significantly influenced by the underlying geology, fractured networks, conduits, and resulting topography. Soil types, especially eutric cambisols, supported higher outflow in intermediate and maximal, whereas gleyic cambisols had minimal outflows. Springs with intermediate outflows were crucial for local water needs, whereas maximal, although rare, were vital for ecosystem health and larger water supply. These findings underscore the importance of spring conservation and sustainable watershed management in maintaining spring outflow and mitigating water scarcity. 2025-01-01T00:00:00Z http://117.252.14.250:8080/jspui/handle/123456789/7724 The Wet and Dry Spells across India during 1951–2007 Singh, Nityanand; Ranade, Ashwini Characteristics of wet spells (WSs) and intervening dry spells (DSs) are extremely useful for water-related sectors. The information takes on greater significance in the wake of global climate change and climate-change scenario projections. The features of 40 parameters of the rainfall time distribution as well as their extremes have been studied for two wet and dry spells for19 subregions across India using gridded daily rainfall available on 18 latitude 3 18 longitude spatial resolution for the period 1951–2007. In a low-frequency-mode, intra annual rainfall variation, WS (DS) is identified as a ‘‘continuous period with daily rainfall equal to or greater than (less than) daily mean rainfall (DMR) of climatological monsoon period over the area of interest.’’ The DMRshowssignificantspatialvariationfrom 2.6 mm day21overtheextremesoutheastpeninsula (ESEP)to 20.2 mm day21 over the southern-central west coast (SCWC). Climatologically, the number of WSs (DSs) decreases from 11 (10) over the extreme south peninsula to 4 (3) over northwestern India as a result of a decrease in tropical and oceanic influences. The total duration of WSs (DSs) decreases from 101 (173) to 45 (29) days, and the duration of individual WS(DS)from12(18)to7(11)days following similar spatial patterns. Broadly, the total rainfall of wet and dry spells, and rainfall amount and rainfall intensity of actual and extreme wet and dry spells, are high over orographic regions and low over the peninsula, Indo-Gangetic plains, and northwest dry province. The rainfall due to WSs (DSs) contributes ;68% (;17%) to the respective annual total. The start of the first wet spell is earlier (19 March) over ESEP and later (22 June) over northwestern India, and the end of the last wet spell occurs in reverse, that is, earlier (12 September) from northwestern India and later(16December)from ESEP. In recent years/decades, actual and extreme WSs are slightly shorter and their rainfall intensity higher over a majority of the subregions, whereas actual and extreme DSs are slightly(not significantly) longer and their rainfall intensity weaker. There is a tendency for the first WS to start approximately six days earlier across the country and the last WS to end approximately two days earlier, giving rise to longer duration of rainfall activities by approximately four days. However, a spatially coherent, robust, long-term trend (1951–2007) is not seen in any of the 40 WS/DS parameters examined in the present study. 2010-01-01T00:00:00Z