Application of improved set pair analysis model for evaluation of water resources carrying capacity

Li, Fanxiu

doi:10.1109/rsete.2011.5964224

Cited by 3 publications

(1 citation statement)

References 8 publications

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“…The continuous over exploitation of groundwater for irrigation has led to the depletion of groundwater resources year after year. Irrigation water use efficiency is low, which directly leads to unnecessary waste of water resources and reduction of crop yields (Li, 2011). Therefore, to address the above problems, the advantages of this paper lie firstly in correcting the crop coefficients according to the crop cultivation habits in the study area to improve the accuracy of the water requirement calculation results.…”

Section: Introductionmentioning

confidence: 99%

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

Sun,

Chen,

et al. 2024

Water Resour Manage

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Section: Introductionmentioning

confidence: 99%

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

Sun,

Chen,

et al. 2024

Water Resour Manage

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Development and application of a new water-carbon-economy coupling model (WCECM) for optimal allocation of agricultural water and land resources

Sun,

Yang,

et al. 2024

Agricultural Water Management

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

Sun,

Chen,

et al. 2024

Preprint

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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. 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 on the Google Earth Engine (GEE) platform sensing 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. The requirement for irrigation water at different stages of crop growth varies significantly due to different climatic conditions in different years. 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.

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Application of improved set pair analysis model for evaluation of water resources carrying capacity

Cited by 3 publications

References 8 publications

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

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

Development and application of a new water-carbon-economy coupling model (WCECM) for optimal allocation of agricultural water and land resources

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

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