Distribution and storage of soil organic and inorganic carbon under different ecological zones in Xinjiang, China

The Chinese government set up a redline for water resources in 2011, mandating water withdrawals and management criteria to the year 2030. ‘How much water is required to produce sufficient crop to feed a 1.6 billion population in 2030?’ becomes a crucial question to be addressed. The objectives of this study are to: (1) document crop water use and productivity from 1998 to 2017 and (2) define the redline water withdrawal for crop use (REWCU) to 2030. The study inversely inferred REWCU from broadly-defined available water for crop use (BAWCU) and associated parameters. Of all BAWCU, 66.3% had been consumed by crops, in which rainfall-derived water consumption accounted for 71.7% of it, while the irrigation-derived water consumption represented the remaining 28.2%. Of all the rainfall that was available for crop use, 72.1%, or the rainfall depletion rate, had been actually consumed by crop evapotranspiration (ET). Likewise, 55.2%, or the irrigation depletion rate, had been consumed by crops. Crop water productivity (CWP) measured by crop yield per unit ET was computed for six major crop categories. Five broad scenarios have been formulated—business as usual, optimistic, deliberative optimistic, pessimistic, and deliberative pessimistic—under lower, higher, and average population and crop projections, respectively. The projected REWCU was 4166.30 × 10⁸ m³, and the projected agricultural water withdrawal was 4629.22 × 10⁸ m³ to 2030, representing 66.1% of the projected nationwide redline total water withdrawal (RETWW) of 7000 × 10⁸ m³. The study used CWP and BAWCU to inversely infer REWCU since they reflect diverse biophysical and management factors and can be used as reliable proxies. Both methodology and research results may offer references and support when making nation- and region-wide water-for-food decisions by crop and water administrations.

In this study, Python Surface Energy Balance System (PySEBS) software was developed in the Python 2.7 programming language for continuous calculation of actual evapotranspiration (ET_a) at regional scales. The software is based on the Surface Energy Balance System (SEBS) model, which uses basic meteorological data, MODIS remote sensing data, and Digital Elevation Model (DEM) data as the original input data and finally outputs daily-scale ET_a in the form of raster data with a spatial resolution of 1 km × 1 km. To verify the reliability of the PySEBS model, the ET_a of spring maize during the growing season in Jilin Province, China, from 2001 to 2020 was calculated and analyzed in this study and compared with the results of similar studies by others. The findings showed that the PySEBS model has a reasonable accuracy in estimating ET_a within ±15% and is a robust model that can achieve the continuous calculation of ET_a at a regional scale. Therefore, PySEBS software is a useful tool for regional irrigation scheduling and water resources management.