Remote Sensing and Statistical Crop Yield Integration for Assessing Water Use Efficiency: Case Study of Zhambyl Region, Kazakhstan

Abstract

This study assesses water use efficiency in Kazakhstan’s Zhambyl region using satellite-based remote sensing and publicly available statistical data. The region’s semi-arid climate, heavy dependence on irrigation, limited water resources, with the added complexity of upstream transboundary water system make it well suited for assessing water productivity under water-scarce conditions. The overarching goal of the research is to compare remote-sensing-based and statistically derived WUE estimates to determine their reliability and applicability for regional water management. Satellite-based water use efficiency estimation was conducted using Net Primary Production and evapotranspiration metrics, offering district-level insights into water productivity. In 2023, satellite-based WUE was 0.81 gC/m2/mm, a value that falls within typical ranges reported for dry semi-humid regions (approximately 0.88 gC/m2/mm) and higher than those characteristics of arid zones (around 0.22 gC/m2/mm). These results indicate relatively high vegetation water-use efficiency under local climatic conditions. Water use efficiency derived from secondary statistical data yielded substantially higher values than global averages (5.79–7.30 kg/m3), reflecting the methodological limitations of aggregated regional statistics rather than actual field-level performance. The discrepancy underscores the need for primary, farm-level data collection to improve the accuracy of statistical approaches. Overall, the study demonstrates the value of remote sensing as a robust and scalable tool for evaluating water use efficiency in arid and semi-arid regions, while highlighting the need for precise field-based measurements to improve the verification and accuracy of such assessments.