Abstract
The potential of several predictive models including multiple model-artificial neural network (MM-ANN), multivariate adaptive regression spline (MARS), support vector machine (SVM), multi-gene genetic programming (MGGP), and ‘M5Tree’ were assessed to simulate the pan evaporation in monthly scale (EPm) at two stations (e.g. Ranichauri and Pantnagar) in India. Monthly climatological information were used for simulating the pan evaporation. The utmost effective input-variables for the MM-ANN, MGGP, MARS, SVM, and M5Tree were determined using the Gamma test (GT). The predictive models were compared to each other using several statistical criteria (e.g. mean absolute percentage error (MAPE), Willmott's Index of agreement (WI), root mean squared error (RMSE), Nash-Sutcliffe efficiency (NSE), and Legate and McCabe’s Index (LM)) and visual inspection. The results showed that the MM-ANN-1 and MGGP-1 models (NSE, WI, LM, RMSE, MAPE are 0.954, 0.988, 0.801, 0.536 mm/month, 9.988% at Pantnagar station, and 0.911, 0.975, 0.724, and 0.364 mm/month, 12.297% at Ranichauri station, respectively) with input variables equal to six were more successful than the other techniques during testing period to simulate the monthly pan evaporation at both Ranichauri and Pantnagar stations. Thus, the results of proposed MM-ANN-1 and MGGP-1 models will help to the local stakeholders in terms of water resources management.
Highlights
Evaporation plays the main role in environmental studies and water resources management
Numerous studies reported the determination of the pan evaporation applying some empirical and semi-empirical formulations based on various meteorological information (Griffiths, 1966; Penman, 1948; Priestley & Taylor, 1972)
The recorded meteorological information was collected from the Crop Research Centres in Uttarakhand, India are the monthly minimum (Tmin) and maximum temperatures (Tmax), the wind speed (Sw), the hours of sunshine (Hss), the monthly pan evaporation (EPm), and the morning and afternoon relative humidity (RH1 and RH2)
Summary
Evaporation plays the main role in environmental studies and water resources management. The most effective meteorological factors on evaporation rate are relative humidity, air temperature, vapor pressure deficit, atmospheric pressure, vapor pressure, wind speed, and sunshine hours (Yaseen et al, 2019). Evaporation is generally measured using two methods: (i) direct methods such as Class A panevaporimeter and (ii) indirect methods include empirical equations (Ghorbani, Deo, Yaseen, Kashani, & Mohammadi, 2017). Numerous studies reported the determination of the pan evaporation applying some empirical and semi-empirical formulations based on various meteorological information (Griffiths, 1966; Penman, 1948; Priestley & Taylor, 1972). Alternative methods, which require less meteorological data are needed to predict the evaporation (Kisi, 2015; Kisi, Genc, Dinc, & Zounemat-Kermani, 2016)
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