Development of groundwater poverty index focusing on agricultural and industrial perspectives in West Azerbaijan Province, Iran

Groundwater resources play an important role in meeting the water needs of agriculture and industry. Therefore, identifying the factors affecting the potential challenges of groundwater resources can be key to proper implementation and management, considered the main goal of the current research. In this study, agricultural groundwater poverty index (AGPI) and industrial groundwater poverty index (IGPI) were developed based on General, Effective, and Data mining methods for the study period 2012-2020 in the West Azerbaijan Province, Iran. Both agricultural and industrial sectors were classified into five categories with 17 and 15 associated variables, respectively. The total scores of AGPI and IGPI were obtained (48.63, 47.80, 49.67) and (33.35, 33.60, 33.37), respectively, for General, Effective, and Data mining methods in the West Azerbaijan Province. In 2012-2020, the qualitative classification of the sustainability status of groundwater resources for the agriculture and industry sectors was at a good and very good level. The crop cultivation patterns of Pea, Beans, and Lentils products require management reforms to avoid the relative unsustainability in groundwater resources. Also, Production of Food and Beverages, Tobacco products, Production of Coke fuel, Oil refineries, and Nuclear fuels, Chemical Products, Rubber and Plastic products, and Non-Metallic Mineral Products could face management challenges in the West Azerbaijan Province. As the agricultural sector puts more pressure on groundwater resources than the industrial sector, it is expected that the southern part of the province will be more affected by water crises in the future. Also, the countries' internal management plans and international relations, such as the Joint Comprehensive Plan of Action (JCPOA), could have a significant impact on the status of their water resources. Due to saving time and money, it is highly recommended to use the Data mining method to develop the AGPI and IGPI in practical projects. The results of current study will have a critical impact on improving and optimizing the performance of implemented groundwater resource management projects in various temporal-spatial levels.