Assessment of sustainable groundwater resources management using integrated environmental index: Case studies across Iran.

Assessing environmentally sustainable GW management (ESGM) needs a deep knowledge of the present and the projected status of GW (GW) quantity and quality. Translations of these data into policy relevant information are usually done through quantitative indices. Despite the availability of a dozen GW sustainability indicators, defining an integrated index based on internationally accepted scientific standards indicators is required. To fill this gap, an in-depth review on the developed indicators/index for evaluation of GW sustainable management (GWSM) from an environmental viewpoint at aquifer scales is provided in this study. Thirteen environmentally related quantitative indicators are adopted for assessment of GWSM, especially in arid regions, depending upon data availability, and relevance of indicators. An integrated ESGM index (ESGMI) is developed based on weighted aggregation of thirteen adopted indicators through multi criteria decision making (MCDM) methods. ESGMI value ranged between 0 and 100, zero value denotes to the worst state or unsustainable GW management (GWM) and 100 indicates the ideal state or GWM is sustainable. Thirty important aquifers across Iran are chosen to implement the ESGMI at the national scale of a country known to be the fifth largest global GW user. ESGMI values for thirty of Iran's aquifers are obtained in the range 15.40 to 68.50 (on average, 49.96). This reveals the unsustainable status of GWM in this country. The results of this study demonstrate that the ESGMI is a promising tool to determine the current state of GW quantity and quality, reveals the effect of policy actions and plans, and contributes to the development and operation of effective sustainable management policies for GW resources. Due to uncertainties and spatio-temporal variabilities of key controlling variables in GW management, sustainability evaluation should be understood as a dynamic and iterative process, requiring persistent monitoring, analysis, prioritization, and modification. Crown