Xueliang Cai, Wim Bastiaanssen Remote sensing based crop water productivity for investment in and management of mega irrigation systems in Asia Xueliang Cai, Wim Bastiaanssen
Background Water productivity concept is widely accepted and the remote sensing approach produces beautiful maps. …So what? How water productivity can be operationalized to help make better investment and management decisions?
Background Asian Development Bank (ADB) is working with many countries to invest hundred of millions USD in irrigation; But how should the irrigation performance be measured? And how this measurement can lead to improved investments and management?
Performance indicator Our method pySEBAL: a crop water productivity tool to convert satellite images to water use, soil moisture, crop growth, and water productivity Remote sensing (Crop biomass, leaf area index, nitrogen, yield) Crop water productivity (ETa, ET deficit, Evaporation, Transpiration, soil moisture) Diagnostic analysis Performance indicator
India, Rice Water productivity maps for performance assessment Good CWP (average 1.47 kg/m3) Moderate variability (CV = 0.14)
Factors affecting water use, yield, and WP Distance to the main dam
Factors affecting water use, yield, and WP Soil type
Factors affecting water use, yield, and WP Crop calendar and intensity
Factors affecting water use, yield, and WP Fertilizer (type and rate)
Factors affecting water use, yield, and WP Seed
Establishing the investment target Assessing potential BC = Ta / ETa Big and uneven potential for on-farm water management improvement
Establishing the investment target Determining priority
Remote sensing works better with ground information Final remarks Crop water productivity needs to move beyond being research and policy concept Operationalization of CWP requires looking at the elements contributing to CWP (crop, water, and biophysical and managerial factors) Remote sensing approach is mostly used for monitoring and performance assessment, but it can also be a powerful diagnostic tool for planning and management Remote sensing works better with ground information
Dank ye! x.cai@un-ihe.org