This 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.
Optimization of irrigation water is an important issue in agricultural production for maximizing the return from the limited water availability. The current study proposes a simulation-optimization framework for developing optimal irrigation schedules for rice crop (Oryza sativa) under water deficit conditions. The framework utilizes a rice crop growth simulation model to identify the critical periods of growth that are highly sensitive to the reduction in final crop yield, and a genetic algorithm based optimizer develops the optimal water allocations during the crop growing period. The model ORYZA2000, which is employed as the crop growth simulation model, is calibrated and validated using field experimental data prior to incorporating in the proposed framework. The proposed framework was applied to a real world case study of a command area in southern India, and it was found that significant improvement in total yield can be achieved by the model compared to other water saving irrigation methods. The results of the study were highly encouraging and suggest that by employing a calibrated crop growth model combined with an optimization algorithm can lead to achieve maximum water use efficiency.
The COVID-19 pandemic has disrupted daily activities across multiple sectors globally. The extent of its impact on the global economy and its key sectors, especially water, wastewater, and associated sectors such as agriculture, is still unclear. In this paper, the preliminary impacts of COVID-19 on water resources of India, especially on the river water quality, water usage in domestic and commercial sectors, wastewater treatment sector, and agriculture sector, are discussed. The limitations in the functioning of the existing system and management of water resources are identified. The need for improvements to strengthen the water resources monitoring and developing process-based models are highlighted. This paper also discusses the need for further investigation to identify the extent of impact and contributing factors to improve our understanding of the natural system for preparing, monitoring, and implementing the policies to manage the water resources during any pandemic/epidemics in the future.
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