Calibration and validation of ET0 through an R-CRAN code in agricultural lands of south-east Spain

Currently, water demands from urban and agricultural use are increasing, especially in arid and semi-arid regions, such as the Mediterranean. This situation is expected to become worse with the climate change projections for the region, increasing the pressure, in both quantity and quality, on fresh water resources. Evapotranspiration (ET0) is a hydrologic variable with high uncertainty and considered incorrect in water balance estimations. However, its accurate assessment is essential to obtain the real value of available water to satisfy water demands, especially in extended agricultural areas such as the south-east of Spain. ET0 can be obtained using different equations with different levels of input data requirements, among them the Penman–Monteith option is the one recommended by the FAO (PMFAO), but its input data requirements are high. On the other hand, there are simpler options, such as the Hargreaves equation (ET0,HG), but there is not such a big agreement about its accuracy in the scientific literature. The main objection to the use of PMFAO is the lack of some of the required meteorological variables in most climate stations, forcing the use of simpler alternatives. This paper presents an R-CRAN code where the ET0,HG, parameterized by Samani, is calibrated and validated with the Allen model considering 18 statistical contrasts. Both ET0,HG results (pre- and post-calibrated) are compared with daily, monthly and annual results of the PMFAO. All meteorological data was provided by the CA52 Cartagena La Aljorra weather station, managed by the Agricultural Information System of the Murcia region (SE Spain). The main results show that daily, monthly and annual ET0,HG results after the Allen calibration and validation are similar to the PMFAO. However, a moderate underestimation of ET0,HG compared to PMFAO was identified. To sum up, the presented R-CRAN code provides an alternative to apply the ET0,HG method with few meteorological input requirements and, once calibrated, can be applied to extended data networks in other regions.This work was partially supported by the project GRE17-12 of the University of Alicante. Antonio Jodar-Abellan acknowledges financial support received from the Spanish FPU scholarship for the training of university teachers. In the same way, this work has been conducted within the Cátedra del Agua of the University of Alicante (https://catedradelaguaua.org/)