Abstract
Accurate and reliable estimations of reference evapotranspiration (ET0) are imperative in irrigation scheduling and water resource planning. This study aims to analyze the spatiotemporal trends of the monthly ET0 calculated by the Penman–Monteith FAO-56 (PMF-56) model in the Huai River Basin (HRB), eastern China. However, the use of the PMF-56 model is limited by the insufficiency of climatic input parameters in various sites, and the alternative is to employ simple empirical models. In this study, the performances of 13 empirical models were evaluated against the PMF-56 model by using three common statistical approaches: relative root-mean-square error (RRMSE), mean absolute error (MAE), and the Nash–Sutcliffe coefficient (NS). Additionally, a linear regression model was adopted to calibrate and validate the performances of the empirical models during the 1961–2000 and 2001–2014 time periods, respectively. The results showed that the ETPMF increased initially and then decreased on a monthly timescale. On a daily timescale, the Valiantzas3 (VA3) was the best alternative model for estimating the ET0, while the Penman (PEN), WMO, Trabert (TRA), and Jensen-Haise (JH) models showed poor results with large errors. Before calibration, the determination coefficients of the temperature-based, radiation-based, and combined models showed the opposite changing trends compared to the mass transfer-based models. After calibration, the performance of each empirical model in each month improved greatly except for the PEN model. If the comprehensive climatic datasets were available, the VA3 would be the recommended model because it had a simple computation procedure and was also very well correlated linearly to the PMF-56 model. Given the data availability, the temperature-based, radiation-based, Valiantzas1 (VA1) and Valiantzas2 (VA2) models were recommended during April–October in the HRB and other similar regions, and also, the mass transfer-based models were applicable in other months.
Highlights
Under the background of global warming, reference evapotranspiration (ET0 ) has become a crucial agrometeorological variable for meteorological and hydrological process studies, as well as forWater 2018, 10, 493; doi:10.3390/w10040493 www.mdpi.com/journal/waterWater 2018, 10, 493 irrigation scheduling and management, which plays a vital role in the atmosphere, hydrosphere, and biosphere
Similar monthly trends of the estimated by the PMF-56 model (ETPMF) could be detected in other regions of China, such as the Yellow River Basin [49], northwest China [50], and the Sanjiang Plain in northeast China [51]
The spatial distribution of the ETPMF results showed a similar tendency of temporal distribution in the Huai River Basin (HRB) (Figure 3)
Summary
Under the background of global warming, reference evapotranspiration (ET0 ) has become a crucial agrometeorological variable for meteorological and hydrological process studies, as well as forWater 2018, 10, 493; doi:10.3390/w10040493 www.mdpi.com/journal/waterWater 2018, 10, 493 irrigation scheduling and management, which plays a vital role in the atmosphere, hydrosphere, and biosphere. The PMF-56 model has two advantages compared with other models [2,7] It is used globally without any calibrations because of its biophysical basis. The main shortcoming of the PMF-56 model is the requirement of large datasets, including the air mean, maximum and minimum temperature, relative humidity, wind speed, and solar radiation. Records of these meteorological input parameters are often with debatable quality or are unavailable for a specific site, especially in some developing countries [1]. In the areas where the observed large meteorological data are difficult to obtain, the PMF-56 model is not the best option
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