Efficient irrigation water management for an 18,000 ha sugarcane plantation in Xinavane in southern Mozambique is a challenge. Sugarcane is an irrigation intensive crop and its productivity is sensitive to water stress. Options to adopt field water management best practices and proper irrigation scheduling are limited due to the lack of plot-level information on the actual crop water use and stress levels throughout the growing season. Due to heterogeneity in cropping calendar within the sugarcane plantation, at a certain point of time, different plots are at different growth stages. This makes scheme level irrigation scheduling complex and calls for frequent crop water use information. To fill this gap, this study presents a novel approach where a combination of satellite imagery with local weather data is used to provide daily evaporation rates. The Priestley-Taylor equation is applied to quantify evaporation (soil evaporation + transpiration) using radiation and temperature data from a meteorological station and spatial albedo estimates derived from the Sentinel-2 satellites. The results show 20 meter resolution maximum crop evaporation estimates can be derived with the proposed methodology. Additionally, the results show NDVI in the last two crop stages is able to distinguish between poor and good performing fields. Therefore, NDVI can be a useful index to estimate actual evaporation. First, the evaporation estimates were corrected for the crop stage using NDVI proxies and an additional stress indicator was used to calculate the actual evaporation flux spatially. The spatial evaporation estimates provide the water manager with information on actual crop water use and biomass development, which is relevant to both crop monitoring and irrigation management water management when drought-related stress is filtered.

莫桑比克南部Xinavane的18,000公顷甘蔗种植园的有效灌溉水管理是一个挑战。甘蔗是灌溉密集型作物，其生产力对水分胁迫敏感。由于缺乏有关整个生长期的实际作物用水量和压力水平的地块级信息，采用田间水管理最佳实践和适当灌溉计划的选择受到限制。由于甘蔗种植园中种植日历的异质性，在某个时间点，不同的地块处于不同的生长阶段。这使计划级灌溉计划变得复杂，并需要频繁的作物用水信息。为了填补这一空白，本研究提出了一种新颖的方法，其中结合使用卫星图像和本地天气数据来提供每日蒸发率。利用来自气象站的辐射和温度数据以及从Sentinel-2卫星获得的空间反照率估算值，将Priestley-Taylor方程应用于量化蒸发（土壤蒸发+蒸腾作用）。结果表明，采用建议的方法可以得出20米分辨率的最大农作物蒸发量估算值。此外，结果表明，在最后两个作物阶段，NDVI能够区分效果欠佳的田地。因此，NDVI是评估实际蒸发量的有用指标。首先，使用NDVI代理对作物阶段的蒸发估计值进行校正，并使用附加的应力指标在空间上计算实际的蒸发通量。