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Abstract: Crop models often simulate drought impacts with full and no irrigation scenarios, while planners are more interested in whether the current available irrigation water can cope with the future more serious droughts. This paper addresses a key constraint common to modeling studies: the limited representation of actual irrigation water supply. We present a data-driven approach to identify a benchmark for agronomic drought risk levels as defined by water availability thresholds at the baseline climate (1980–2008) using reported crop yields, climate and irrigation statistics. Then, holding the current irrigation supplies, we adopted Bayesian formula to estimate magnitude of the future water availability and the associated probability of crops yields being decreased to rainfall-deficiency under climate conditions in 2030s (2020–2040) based on the RegCM3 climate model output driven by IPCC SRES A1B scenario. Results reveal that future drought stress would overwhelm the irrigation capacity of current supplies in northern and western China, while drought remains at baseline climate levels in the central, eastern and southern regions. The largest increases in the probability of projected drought risk were in northeast and southwest, ranging from 14% to 28% above baseline climate. Regional drought impacts for grain self sufficiency are discussed. [Copyright &y& Elsevier]

• Spatial and temporal ET dynamics are evaluated using GLEAM, PML and MTE products • The environmental drivers of ET variability in the semi-arid Sahel are identified • Global ET products are consistent with measured in the water-limited zones • Results show significant rising trend and high ET variability in the Western Sahel • Wavelet coherence results confirm strong coupling between ET and rainfall in the Sahel This paper evaluates the atmospheric controls contributing to actual evapotranspiration (ET) variability and trends across the ecological zones in the data-scarce region of West Africa. Spatial and temporal ET dynamics in the region were analysed using three selected prognostic- and machine learning-based global ET over 1983 to 2012. In addition, the responses of annual actual ET to changes in annual rainfall, atmospheric evaporative demand (AED) and incident solar radiation were evaluated using joint time-frequency wavelet decomposition method and pixel-wise partial correlation analysis. Based on the Mann-Kendall statistics, results from the Global Land Evaporation Amsterdam Model (GLEAM) data revealed high variability (> 70 mm yr−1) and significant rising trends (> 5 mm yr−1) in annual ET in the Western Sahel. In contrast, results from CSIRO Penman-Monteith Leuning (PML) ET data showed declining trends by more than 4 mm yr−1 in some parts of the Savannah zone during the study period. Results also showed some similarities in the coupling between annual ET, rainfall and AED, particularly along the Sahelian belt time-frequency domain. This implies that these atmospheric variables largely explain the signals in ET variations across the zones. However, the atmospheric variables have different modulating powers on the ET variations in the region. Additionally, we find that other non-climatic factors may have also influenced the variations in ET during the study period. This could serve as a pointer to focusing on other non-climatic drivers, potentially affecting ET trend and variability in the study area. Therefore, the study highlights the importance of providing essential and robust information on ET variability and trend as affected by different atmospheric drivers and its potential impacts on water resources, particularly in the Sahelian zone where agricultural biomes are often threatened by water stress and drought. [ABSTRACT FROM AUTHOR]