Multi Criteria Decision Making Results Integration with Borda, Copeland, and Averaging Methods in Precise ET0 Method Determination

Demand control in agriculture enhances water efficiency by optimizing resource utilization. Among the primary causes of water loss are evaporation and transpiration, making their accurate estimation crucial for effective water management. This study aims to determine the most precise potential evaporation and transpiration (ET0) estimation method using data from 18 synoptic stations. The methods evaluated include Ivanov, Thornthwaite, Blaney-Criddle (BC), Priestley-Taylor, Makkink, Turc, and Hargreaves- Samani (HS). Two analytical approaches were employed: evaluation criteria and multi-criteria decision-making (MCDM) techniques, incorporating the Analytic Hierarchy Process (AHP), VIKOR, and Shannon entropy methods. The rankings derived from these methods were further refined through integration techniques such as averaging, Copeland, and Borda methods. Among the evaluated methods, HS and BC performed best based on evaluation criteria. The relative root mean square error (RMSE) reduction from HS to other methods was 82.92% for Ivanov, 72.45% for Thornthwaite, 39.16% for BC, 37.39% for Priestley-Taylor, 26.64% for Makkink, and 68.54% for Turc. Notably, the Shannon entropy and AHP rankings aligned, consistently placing BC and HS at the top. In integrated ranking approaches, the Copeland and Borda methods yielded identical results, with BC, HS, Makkink, and Turc achieving high rankings. Priestley-Taylor and Ivanov were ranked equally in the averaging method, whereas Thornthwaite ranked lowest. The Ivanov method consistently placed last in Copeland and Borda rankings. Considering similarity criteria values exceeding 0.8, the BC method is particularly effective in wet and semi-arid climates, while the HS method demonstrates reliability across all three climate zones studied.