Investigating the Accuracy and Efficiency of Hydrological Re-Analyzed Models in Estimating the Evaporation Rate from Dam Reservoirs (Case Study: Yamchi Dam, Ardabil)

In this study, the efficiency of hydrological re-analyzed models SWBM, HTESSEL, HBV-SIMREG, Ensemble, and LISFLOOD in estimating the rate of evaporation from the reservoir of Yamchi dam in Ardabil was investigated. The evaporation values obtained from the re-analyzed models were validated using the findings of Penman's analytical equation and the values of eight experimental models. In addition to the methods, the accuracy of re-analyzed models was evaluated using the feed forward neural network. The resulting feed forward neural network was designed in two stages with two and three hidden layers and each was evaluated in three different combinations of network inputs. According to the findings, the values generated from the Penman analytical model had a correlation coefficient of 0.9 with the data received from studied area's evaporation pan. Among the hydrological re-analyzed models, the highest correlation with received data from study area's evaporation pan was related to LISFLOOD model with a value of 0.87 and RMSE equal to 1.37 mm per day. The obtained results showed that the mean absolute error for the LISFLOOD model with the data provided from the study area's evaporation pan was 1.14 mm per day, on a daily time scale. The results showed that in the absence of area data, re-analyzed hydrological model can readily offer the best estimate of evaporation from the reservoirs’ free surface on a monthly scale.