Maps of reference evapotranspiration for the irrigation project in Brazil

The maximum daily evapotranspiration data set for a project (ETproject) for Brazil. It has a spatial resolution of <strong>30 seconds (~ 1 km²)</strong>. The data set grid is in <strong>GeoTIFF format</strong> and corresponds perfectly to WorldClim. It uses the <strong>geographic coordinate</strong> reference system, with <strong>WGS84 projection (EPSG: 4326)</strong>. The objective study is to estimate and provide evapotranspiration values of monthly reference and the maximum of twelve months, for dimensioning irrigation systems throughout the Brazilian territory. With the meteorological data of two hundred and fifty-nine conventional INMET stations, the daily reference evapotranspiration (ETo) for 15 years was calculated. For each weather station, the data was grouped by month and the ETo for the irrigation project (ETproject) was determined to meet the eighty percent probability of occurrence, following the recommendations of FAO24. In parallel, monthly images of 15 years of ETo were acquired for Brazil, and the climatic variables of WorldClim. Using the ET values of the stations design, it was modeled for the rest of Brazil, using machine learning algorithms and the covariates. After modeling, the following performances were achieved: mean square error of 0.306 mm / d, mean bias error of -0.004 mm / d, mean absolute error of 0.227 mm / d, determination coefficient of 0.938 and efficiency of Nash-Sutcliffe 0.937. ETo values for irrigation projects were similar to several others reported in the literature when compared at a given point. With this research it was possible to determine the monthly and annual ETo for irrigation projects throughout the Brazilian territory. The article has been submitted for publication.巴西某项目的逐日最大蒸散发数据集（ETproject），空间分辨率为**30弧秒（约1 km²）**。该数据集网格采用GeoTIFF格式，且与WorldClim数据集完全匹配，使用地理坐标参考系统，采用WGS84投影（EPSG: 4326）。本研究的目标为估算并提供逐月参考蒸散发值与全年十二个月的最大值，用于巴西全境灌溉系统的规划选型。 研究依托259个常规巴西国家气象研究院（INMET）站点的气象数据，计算了15年间的逐日参考蒸散发（ETo）。针对每个气象站点，将数据按月分组，并依据FAO24的相关建议，确定满足80%保证率的灌溉项目专用蒸散发（ETproject）值。 同步获取了巴西全境15年间的逐月ETo影像与WorldClim气候变量数据。依托各站点推导得到的设计ET值，结合机器学习算法与协变量，对巴西其余区域开展空间建模。建模完成后取得如下性能指标：均方误差0.306 mm/d，平均偏差误差-0.004 mm/d，平均绝对误差0.227 mm/d，决定系数0.938，纳什-舒特克利夫效率（Nash-Sutcliffe Efficiency）0.937。 将本数据集的灌溉项目专用蒸散发值与文献中已报道的同类值进行单点对比，结果显示二者具有较好的一致性。通过本研究，可确定巴西全境的逐月及年度灌溉项目专用蒸散发值。本论文已提交待刊。