Modeling Water Management and Food Security in India under Climate Change

Climate change and variability will impact water availability and the food security of India. Trend analyses of historical data indicate an increase in temperature and changes in rainfall pattern in different parts of the country. The general circulation models (GCMs) also project increased warming and changes in precipitation patterns over India. This chapter presents examples of model applications in water management and crop yield simulation in India, focusing on climate change impact assessment. Simulation models have been successfully applied for rotational water allocation, deficit irrigation scheduling, etc. in different canal commands. Application of a universal soil loss equation in a distributed parametric modeling approach by partitioning watershed into erosion response units suggests that by treating only 14% of the watershed area, a 47% reduction in soil loss can be achieved. Simulation studies conducted using different hydrological models with different climate change projections and downscaling approaches showed varied hydrological responses of different river basins to the future climate change scenarios, depending on the hydrological model, climate change scenarios, and downscaling approaches used. Crop yield modeling showed decreases in irrigated and rainfed rice (Oryza sativa L.) yields under the future climate change scenarios, but the decrease is marginal for rainfed rice. Maize (Zea mays L.) yields in monsoon may be adversely affected by a rise in atmospheric temperature, but increased rain can partly offset those losses. Wheat (Triticum aestivum L.) yields are likely to be reduced by 6 to 23% and 15 to 25% during the 2050s and 2080s, respectively. A combined bottom-up participatory process and top-down integrated modeling tool could provide valuable information for locally relevant climate change adaptation planning.

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Bibliographic Details
Main Authors: Islam A, Shirsath, Paresh Bhaskar, Kumer SN, Subash N, Sikka, Alok Kumar, Aggarwal, Pramod K.
Format: Book Chapter biblioteca
Language:English
Published: Wiley 2014
Subjects:climate change, agriculture, food security, water availability, crop yield, water management,
Online Access:https://hdl.handle.net/10568/68149
https://doi.org/10.2134/advagricsystmodel5.c11
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Summary:Climate change and variability will impact water availability and the food security of India. Trend analyses of historical data indicate an increase in temperature and changes in rainfall pattern in different parts of the country. The general circulation models (GCMs) also project increased warming and changes in precipitation patterns over India. This chapter presents examples of model applications in water management and crop yield simulation in India, focusing on climate change impact assessment. Simulation models have been successfully applied for rotational water allocation, deficit irrigation scheduling, etc. in different canal commands. Application of a universal soil loss equation in a distributed parametric modeling approach by partitioning watershed into erosion response units suggests that by treating only 14% of the watershed area, a 47% reduction in soil loss can be achieved. Simulation studies conducted using different hydrological models with different climate change projections and downscaling approaches showed varied hydrological responses of different river basins to the future climate change scenarios, depending on the hydrological model, climate change scenarios, and downscaling approaches used. Crop yield modeling showed decreases in irrigated and rainfed rice (Oryza sativa L.) yields under the future climate change scenarios, but the decrease is marginal for rainfed rice. Maize (Zea mays L.) yields in monsoon may be adversely affected by a rise in atmospheric temperature, but increased rain can partly offset those losses. Wheat (Triticum aestivum L.) yields are likely to be reduced by 6 to 23% and 15 to 25% during the 2050s and 2080s, respectively. A combined bottom-up participatory process and top-down integrated modeling tool could provide valuable information for locally relevant climate change adaptation planning.