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Mismatch between crop water requirements and irrigation in Heihe River Basin, Northwestern China

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Abstract

Heihe Inland River Basin is the second largest in China. Water use for agriculture in the middle section of the basin accounts for over 90% of total usage; this leads to lake shrinkage, river blanking, and desertification of the downstream basin. Crop water requirements within the Ganzhou district of the Heihe River Basin in Northwestern China were modeled using a parameter calibration of the CROPWAT model, based on household survey data on crop coefficients and water usage, taking into account effective precipitation. The results show that modeled evapotranspiration for seed maize was consistent with evapotranspiration determined from observed data based on eddy covariance, as adjusted R2 values approached 0.73 (P < 0.001). Vast differences were observed between actual irrigation and water requirements across the study area. Excessive water was used for irrigation, particularly in the case of maize, where mismatches in dates were widespread between actual irrigation and water requirements. Thus, to save water and increase yield, a set schedule for irrigation was recommended.

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Acknowledgements

The authors gratefully acknowledge the financial support of National Natural Science Foundation of Chin (Project number: 91325302) and Strategic Priority Research Program of Chinese Academy of Sciences, Pan-Third Pole Environment Study for a Green Silk Road (Project number: XDA20040400).

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Authors and Affiliations

  1. Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research (IGSNRR), Chinese Academy of Sciences (CAS), Beijing, 100101, China

    Minghong Tan

  2. International College, University of Chinese Academy of Sciences, Beijing, 100190, China

    Minghong Tan

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  1. Minghong Tan
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Correspondence to Minghong Tan.

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Communicated by I. Kisekka.

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Tan, M. Mismatch between crop water requirements and irrigation in Heihe River Basin, Northwestern China. Irrig Sci 37, 95–103 (2019). https://doi.org/10.1007/s00271-018-0608-6

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  • DOI: https://doi.org/10.1007/s00271-018-0608-6

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