Agricultural Irrigation Water Requirement and Its Response to Climatic Factors Based on Remote Sensing and Single Crop Coefficient Method

Jiaxin Sun, Liwen Chen, Peng Qi () and Guangxin Zhang
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Jiaxin Sun: Chinese Academy of Sciences
Liwen Chen: Jilin Jianzhu University
Peng Qi: Chinese Academy of Sciences
Guangxin Zhang: Chinese Academy of Sciences

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2024, vol. 38, issue 13, No 14, 5215-5233

Abstract: Abstract Precise calculation of the water required for agricultural irrigation is important for efficient use of water resources and maintenance of food security. However, the amount of water required for agricultural irrigation is significantly uncertain at different time scales under the influence of climate change. Therefore, in this study, one of major grain producing area, Youyi Farm in the Sanjiang Plain, was selected to simulate the agricultural irrigation water requirement for the Rice, Maize, and Soybean based on remote sensing data and single crop coefficient method. Meanwhile, their response to climatic factors was analyzed by the method of generalized additive model (GAM). The results showed that the multi-year average irrigation water requirement of Rice, Maize, and Soybean during 2010 ~ 2019 was 2.98 × 108m3, 0.25 × 108m3, and 0.04 × 108m3, respectively. A fluctuating decreasing trend was shown for each crops’ water requirement. For Rice, the initial growth period accounts for the largest proportion of irrigation water requirement (34%). For Maize and Soybean, the middle growth period has the highest proportion of irrigation water requirement (45% and 52%). In addition, from 2000 to 2019, the three main climatic factors with the greatest impact on irrigation water requirement were precipitation, vapor pressure deficit, and photoperiod, in that order. Irrigation water requirement was positively correlated with wind speed, photoperiod, maximum temperature and vapor pressure deficit. Precipitation is negatively correlated with irrigation water requirement, and minimum temperature is non-linearly correlated with irrigation water requirement, first positively and then negatively.

Keywords: Irrigation water requirement; remote sensing; single crop coefficient method; GAM model (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s11269-024-03910-z

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