Assessing the Response of Ecosystem Water Use Efficiency to Drought During and after Drought Events across Central Asia The frequency and intensity of drought are expected to increase worldwide in the future. However, it is still unclear how ecosystems respond to drought. Ecosystem water use efficiency (WUE) is an essential ecological index used to measure the global carbonxe2x80x93water cycles, and is defined as the carbon absorbed per unit of water lost by the ecosystem. In this study, we applied gross primary productivity (GPP), evapotranspiration (ET), land surface temperature (LST), and normalized difference vegetation index (NDVI) data to calculate the WUE and drought index (temperature vegetation dryness index (TVDI)), all of which were retrieved from moderate resolution imaging spectroradiometer (MODIS) data. We compared the mean WUE across different vegetation types, drought classifications, and countries. The temporal and spatial changes in WUE and drought were analyzed. The correlation between drought and WUE was calculated and compared across different vegetation types, and the differences in WUE between drought and postdrought periods were compared. The results showed that (1) ecosystems with a low (high) productivity had a high (low) WUE, and the mean ecosystem WUE of Central Asia showed vast differences across various drought levels, countries, and vegetation types. (2) The WUE in Central Asia exhibited an increasing trend from 2000 to 2014, and Central Asia experienced both drought (from 2000 to 2010) and postdrought (from 2011 to 2014) periods. (3) The WUE showed a negative correlation with drought during the drought period, and an obvious drought legacy effect was found, in which severe drought affected the ecosystem WUE over the following two years, while a positive correlation between WUE and drought was found in the postdrought period. (4) A significant increase in ecosystem WUE was found after drought, which revealed that arid ecosystems exhibit high resilience to drought stress. Our results can provide a specific reference for understanding how ecosystems will respond to climate change.

An objectbased image analysis approach to assess irrigationwater consumption from MODIS products in Ethiopia Abstract   Efficient waterresource management is essential with regard to food security, growing populations and climate change. This is especially important for low and middleincome (LMC) countries where food is often locally produced by traditional smallholder farming. Detailed knowledge of the spatiotemporal distribution of irrigationwater consumption provides valuable information to anticipate local food shortages and water scarcity as a result of climate variability. Yet, adequate techniques to quantify irrigationwater consumption at field level over large areas are lacking. Irrigation estimates generally have a coarse resolution making them inadequate for fieldlevel assessments.  This study developed a remotesensingbased approach to quantify spatiotemporal patterns of irrigationwater consumption at field level using the MODIS evapotranspiration product (MOD16A2) and existing landuse maps on the spatiotemporal distribution of irrigated agriculture. Objectbased image analysis was used to establish local evapotranspiration differences between irrigated and rainfed fields on a monthly basis, which are the irrigationwater consumption rates of the irrigated fields. This novel method was applied to a study area in the Central Rift Valley in Ethiopia where smallholder farming is dominant and only a few largescale farms are present. Comparison with irrigationwaterconsumption values of a local irrigation scheme showed that the monthly temporal dynamics were captured quite well, but lower values were calculated compared to the schemeu0027s field data. Comparison with two validated remotesensing based studies in Africa showed good agreement as irrigationwaterconsumption estimates were in the same order of magnitude. Irrigationwater consumption follows the temporal rainfall pattern, i.e. irrigation practices intensify with increased water availability. Surface water is commonly used for irrigation in the study area.  Our study shows that smallholder practices have a lower irrigationwater consumption compared to modern largescale farms by approximately a factor 3. Irrigationwater consumption in the area is considerable, especially during the dry season. On average 32 % of excess water (precipitation xe2x80x93 evapotranspiration) is consumed for irrigation. For smallholder irrigation and largescale irrigation specifically this is 28 % and 63 % respectively.  The objectbased approach presented here is an operational mapping method for fieldlevel irrigationwaterconsumption over large areas. MOD16A2 is a global opensource readilyavailable evapotranspiration product used here although an evapotranspiration product with a higher spatial resolution might be preferred. Our approach can provide irrigationwaterconsumption estimates over large areas in datapoor regions, which will increase the understanding of spatiotemporal patterns of smallholder irrigation and provide information to optimize water use.