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Modeling Rainwater Storage in Distributed Reservoir Systems in Humid Subtropical and Tropical Savannah Regions

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  • Pramod Pandey
  • Michelle Soupir
  • Vijay Singh
  • Sudhindra Panda
  • Vinay Pandey

Abstract

Using a hydrologic model this study estimated rainwater storages in field-scale on-farm reservoir (OFR) systems at two locations: (1) Fort Worth, Texas, US; (2) Kharagpur, West Bengal, India. The water storages were estimated for variable OFR sizes: 1%, 5%, 10%, 15%, and 25% of the farm area. Water losses through seepage and evaporation were estimated using variable saturated hydraulic conductivity conditions: 0.33, 0.64, 1.3, 5 cm/h, which corresponded to the ranges of hydraulic conductivity of loam, sandy loam, loamy sand, and sandy soils, respectively. Results indicated that the water loss through evaporation was dominant at the first location, while seepage was at the second location. Changing the OFR sizes captured 5 to 28% of the total rainfall received in the farm area of the first location and 20–40% at the second location. Finally, a comparative economic analysis was made between a distributed OFR system and a centralized large reservoir that indicated that the distributed OFR system benefits exceeded the benefits of a large reservoir. Copyright Springer Science+Business Media B.V. 2011

Suggested Citation

  • Pramod Pandey & Michelle Soupir & Vijay Singh & Sudhindra Panda & Vinay Pandey, 2011. "Modeling Rainwater Storage in Distributed Reservoir Systems in Humid Subtropical and Tropical Savannah Regions," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 25(13), pages 3091-3111, October.
    • Handle: RePEc:spr:waterr:v:25:y:2011:i:13:p:3091-3111
    DOI: 10.1007/s11269-011-9847-5
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    2. Chen, Shu & Shao, Dongguo & Gu, Wenquan & Xu, Baoli & Li, Haoxin & Fang, Longzhang, 2017. "An interval multistage water allocation model for crop different growth stages under inputs uncertainty," Agricultural Water Management, Elsevier, vol. 186(C), pages 86-97.
    3. Yue, Qiong & Guo, Ping & Wu, Hui & Wang, Youzhi & Zhang, Chenglong, 2022. "Towards sustainable circular agriculture: An integrated optimization framework for crop-livestock-biogas-crop recycling system management under uncertainty," Agricultural Systems, Elsevier, vol. 196(C).
    4. Hashim, H. & Hudzori, A. & Yusop, Z. & Ho, W.S., 2013. "Simulation based programming for optimization of large-scale rainwater harvesting system: Malaysia case study," Resources, Conservation & Recycling, Elsevier, vol. 80(C), pages 1-9.
    5. Shu Chen & Dongguo Shao & Xudong Li & Caixiu Lei, 2016. "Simulation-Optimization Modeling of Conjunctive Operation of Reservoirs and Ponds for Irrigation of Multiple Crops Using an Improved Artificial Bee Colony Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(9), pages 2887-2905, July.
    6. Pramod Pandey & Pieter Zaag & Michelle Soupir & Vijay Singh, 2013. "A New Model for Simulating Supplemental Irrigation and the Hydro-Economic Potential of a Rainwater Harvesting System in Humid Subtropical Climates," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(8), pages 3145-3164, June.
    7. Yue, Qiong & Guo, Ping, 2021. "Managing agricultural water-energy-food-environment nexus considering water footprint and carbon footprint under uncertainty," Agricultural Water Management, Elsevier, vol. 252(C).

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