Evaluation of Irrigation Methods in Soke Plain With Hf-Ahp Ii Hybrid Mcdm Method

Abstract

Soke Plain (Turkey) is one of the two plains where cotton production is the highest in Turkey, the leading country for cotton production in the Mediterranean Basin. The cropping pattern in Soke Plain is dominated by cotton with a ratio of 97%. The overall irrigation scheme is equipped with conventional systems (i.e., surface, furrow) whose efficiency is approximately 50% due to high evaporation and physical losses. Water efficiency improve-ment in cotton irrigation necessitates a thorough evaluation of the agricultural water management for Soke Plain, a water-scarce region under drought threat. In this paper, a hybrid multi-criteria decision making (MCDM) method is presented for the evaluation and selection of irrigation methods. This process involves various potentially conflicting qualitative and quantitative criteria, therefore, a hybrid MCDM method such as HF-AHP-PROMETHEE II is needed to make decisions. In HF-AHP-PROMETHEE II, Hesitant Fuzzy Analytic Hierarchy Process (HF-AHP) is first implemented to determine importance weights of criteria and then Hesitant Fuzzy Preference Ranking Organization Method for Enriching Evaluations II (HF-PROMETHEE II) is utilized to assess and rank the irrigation method alternatives. For comparison analysis, HF-AHP-TOPSIS (HF-AHP-Technique for Order Preference by Similarity to Ideal Solution) method is also implemented to the same problem. A case study is presented where five irrigation method alternatives in Soke Plain are assessed by five expert decision-makers (DMs), based on fifteen evaluation criteria. Sprinkler is found to be the first ranked irrigation method among five alternatives with both HF-AHP-PROMETHEE II and HF-AHP-TOPSIS resulting in the same ranking. The selection of this irrigation technique by the expert DMs is compliant with prevailing regional features related to hydro-logic, climatic, environmental conditions and with regard to cotton, one of the highest water-consuming crops.