Browsing by Author "Adeloye, Adebayo J."
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Item Open Access Adaptation by Himalayan water resource system under a sustainable socioeconomic pathway in a high-emission context(ASCE, 2021-01-13) Dau, Quan V.; Momblanch, Andrea; Adeloye, Adebayo J.Climate change in the Indian Himalayan region is being manifested in the loss of glaciers and altered patterns of monsoon rainfall. Simultaneously, rapid population growth together with economic development are increasing sectoral water demands and changing land use patterns. This study investigated the impact of this complex interplay on water resources in the Beas-Sutlej water resources system. The GFDL-CM3 model was used to describe RCP8.5 future meteorological conditions throughout the 21st century. Population and land use changes were projected under the Shared Socioeconomic Pathway-1 (SSP1). The water evaluation and planning (WEAP) system was applied for assessing sectoral water demands. The results showed increasing runoff during the premonsoon and monsoon seasons due to increased glaciers melting and more rainfall, respectively. It also emerged that irrigation water demand decreased moderately in Punjab (8%–13%) and Haryana (1%–9%); however, the situation was reversed in Rajasthan where it increased by 14%. Adaptation strategies were proposed including increased water allocation to Rajasthan and converting lands to cultivating more staple crops in Punjab and HaryanaItem Open Access Bias correction of high-resolution regional climate model precipitation output gives the best estimates of precipitation in Himalayan catchments(American Geophysical Union (AGU), 2019-12-14) Bannister, Daniel; Orr, Andrew; Jain, Sanjay K.; Holman, Ian P.; Momblanch, Andrea; Phillips, Tony; Adeloye, Adebayo J.; Snapir, Boris; Waine, Toby W.; Hosking, J. Scott; Allen‐Sader, ClareThe need to provide accurate estimates of precipitation over catchments in the Hindu Kush, Karakoram, and Himalaya mountain ranges for hydrological and water resource systems assessments is widely recognised, as is identifying precipitation extremes for assessing hydro‐meteorological hazards. Here, we investigate the ability of bias‐corrected Weather Research and Forecasting model output at 5 km grid spacing to reproduce the spatiotemporal variability of precipitation for the Beas and Sutlej river basins in the Himalaya, measured by 44 stations spread over the period 1980 to 2012. For the Sutlej basin, we find that the raw (uncorrected) model output generally underestimated annual, monthly, and (particularly low‐intensity) daily precipitation amounts. For the Beas basin, the model performance was better, although biases still existed. It is speculated that the cause of the dry bias over the Sutlej basin is a failure of the model to represent an early‐morning maximum in precipitation during the monsoon period, which is related to excessive precipitation falling upwind. However, applying a non‐linear bias‐correction method to the model output resulted in much better results, which were superior to precipitation estimates from reanalysis and two gridded datasets. These findings highlight the difficulty in using current gridded datasets as input for hydrological modelling in Himalayan catchments, suggesting that bias‐corrected high‐resolution regional climate model output is in fact necessary. Moreover, precipitation extremes over the Beas and Sutlej basins were considerably under‐represented in the gridded datasets, suggesting that bias‐corrected regional climate model output is also necessary for hydro‐meteorological risk assessments in Himalayan catchments.Item Open Access Effect of Hedging-Integrated Rule Curves on the Performance of the Pong Reservoir (India) During Scenario-Neutral Climate Change Perturbations(Springer, 2015-11-10) Adeloye, Adebayo J.; Soundharajan, Bankaru Swamy; Ojha, C. S. P.; Remesan, RenjiThis study has evaluated the effects of improved, hedging-integrated reservoir rule curves on the current and climate-change-perturbed future performances of the Pong reservoir, India. The Pong reservoir was formed by impounding the snow- and glacial-dominated Beas River in Himachal Pradesh. Simulated historic and climate-change runoff series by the HYSIM rainfall-runoff model formed the basis of the analysis. The climate perturbations used delta changes in temperature (from 0° to +2 °C) and rainfall (from −10 to +10 % of annual rainfall). Reservoir simulations were then carried out, forced with the simulated runoff scenarios, guided by rule curves derived by a coupled sequent peak algorithm and genetic algorithms optimiser. Reservoir performance was summarised in terms of reliability, resilience, vulnerability and sustainability. The results show that the historic vulnerability reduced from 61 % (no hedging) to 20 % (with hedging), i.e., better than the 25 % vulnerability often assumed tolerable for most water consumers. Climate change perturbations in the rainfall produced the expected outcomes for the runoff, with higher rainfall resulting in more runoff inflow and vice-versa. Reduced runoff caused the vulnerability to worsen to 66 % without hedging; this was improved to 26 % with hedging. The fact that improved operational practices involving hedging can effectively eliminate the impacts of water shortage caused by climate change is a significant outcome of this study.Item Open Access Evaluating the variability in surface water reservoir planning characteristics during climate change impacts assessment(Elsevier, 2016-04-25) Soundharajan, Bankaru Swamy; Adeloye, Adebayo J.; Remesan, RenjiThis study employed a Monte-Carlo simulation approach to characterise the uncertainties in climate change induced variations in storage requirements and performance (reliability (time- and volume-based), resilience, vulnerability and sustainability) of surface water reservoirs. Using a calibrated rainfall–runoff (R–R) model, the baseline runoff scenario was first simulated. The R–R inputs (rainfall and temperature) were then perturbed using plausible delta-changes to produce simulated climate change runoff scenarios. Stochastic models of the runoff were developed and used to generate ensembles of both the current and climate-change-perturbed future runoff scenarios. The resulting runoff ensembles were used to force simulation models of the behaviour of the reservoir to produce ‘populations’ of required reservoir storage capacity to meet demands, and the performance. Comparing these parameters between the current and the perturbed provided the population of climate change effects which was then analysed to determine the variability in the impacts. The methodology was applied to the Pong reservoir on the Beas River in northern India. The reservoir serves irrigation and hydropower needs and the hydrology of the catchment is highly influenced by Himalayan seasonal snow and glaciers, and Monsoon rainfall, both of which are predicted to change due to climate change. The results show that required reservoir capacity is highly variable with a coefficient of variation (CV) as high as 0.3 as the future climate becomes drier. Of the performance indices, the vulnerability recorded the highest variability (CV up to 0.5) while the volume-based reliability was the least variable. Such variabilities or uncertainties will, no doubt, complicate the development of climate change adaptation measures; however, knowledge of their sheer magnitudes as obtained in this study will help in the formulation of appropriate policy and technical interventions for sustaining and possibly enhancing water security for irrigation and other uses served by Pong reservoir.Item Open Access Untangling the water-food-energy-environment nexus for global change adaptation in a complex Himalayan water resource system(Elsevier, 2018-11-08) Momblanch, Andrea; Papadimitriou, Lamprini; Jain, Sanjay K.; Ojha, Chandra S. P.; Adeloye, Adebayo J.; Holman, Ian P.Holistic water management approaches are essential under future climate and socio-economic changes, especially while trying to achieve inter-disciplinary societal goals such as the Sustainable Development Goals (SDGs) of clean water, hunger eradication, clean energy and life on land. Assessing water resources within a water-food-energy-environment nexus approach enables the relationships between water-related sectors to be untangled while incorporating impacts of societal changes. We use a systems modelling approach to explore global change impacts on the nexus in the mid-21st century in a complex western Himalayan water resource system in India, considering a range of climate change and alternative socio-economic development scenarios. Results show that future socio-economic changes will have a much stronger impact on the nexus compared to climate change. Hydropower generation and environmental protection represent the major opportunities and limitations for adaptation in the studied system and should, thereby, be the focus for actions and systemic transformations in pursue of the SDGs. The emergence of scenario-specific synergies and trade-offs between nexus component indicators demonstrates the benefits that water resource systems models can make to designing better responses to the complex nexus challenges associated with future global change.