Selection of alternate reference evapotranspiration models based on multi-criteria decision ranking for semiarid climate

• Published in: Environment, development and sustainability development and sustainability, 2024-05, Vol.26 (5), p.11171-11216
• Main Authors: Rajput, Jitendra, Singh, Man, Lal, Khajanchi, Khanna, Manoj, Sarangi, Arjamadutta, Mukherjee, Joydeep, Singh, Shrawan
• Format: Article
• Language: English
• Subjects: Agricultural management; Agriculture; Atmospheric models; Climate; Datasets; Decision making; Earth and Environmental Science; Ecology; Economic Geology; Economic Growth; Entropy; Environment; Environmental Economics; Environmental Management; Evapotranspiration; Hydrologic cycle; Hydrology; Irrigation; Irrigation efficiency; Irrigation scheduling; Irrigation water; Mass transfer; Meteorological data; Multiple criterion; Observatories; Performance evaluation; Radiation; Ranking; Ratings & rankings; Resource management; Resource scheduling; Semi arid environments; Semiarid climates; Semiarid environments; Sustainable Development; Water management; Water resources management; Water supply; Water use
• ISSN: 1573-2975; 1387-585X; 1573-2975
• DOI: 10.1007/s10668-023-03234-9

The hydrologic cycle’s fundamental component, evapotranspiration, is a crucial parameter for research on climate, hydrology, and water use in agriculture. Efficient water management in agriculture requires an accurate assessment of reference evapotranspiration (ET o ). The Food and Agriculture Organization recommended Penman–Monteith (PM) approach is among the most precise models for computing ET o . Nevertheless, this technique requires a comprehensive climate dataset, typically only accessible at a few meteorological observatories. As a result, estimating ET o using a small climatic dataset may be an alternative for water management aspects. Thus, in the current study, 12 temperature, ten radiation, and seven mass transfer-based models were assessed using 31 years of meteorological data (1990–2020) and compared with the traditional PM approach in the semiarid environment of Central Delhi, India. Moreover, ranking different models in data-limited situations was attempted using multi-criteria decision-making (MCDM) techniques viz ., TOPSIS (technique for order performance by similarity to ideal solution) and entropy. Results showed that the Priestley–Taylor (PRTY) and Blaney–Criddle (BLCD) models were found to be the most appropriate alternatives to the PM model, with Pearson’s coefficient of correlation (r) values of 0.93 and 0.96, respectively, and mean absolute percentage error (MAPE) values of 13.30 and 21.11%. According to the performance evaluation indices, the performance of the radiation-based models was superior to that of the temperature and mass transfer models. Nevertheless, this ranking would aid in precisely estimating ETo with minimal data, resulting in efficient irrigation scheduling and water resource management.