A resilience-based framework for evaluating the carrying capacity of water and environmental resources under the climate change.

This paper proposes a new framework for evaluating water and environmental resources carrying capacity (WERCC) based on the concept of resilience under uncertainty. First, several quantitative and qualitative criteria based on the seven principles of resilience and the Pressure-Support-State (PSS) framework are defined to incorporate the positive and negative impacts of human interventions and natural factors on water resources and the environment. The resilience principles include redundancy and diversity, managing connectivity, managing slow variables and their feedbacks, fostering complex adaptive system (CAS) thinking, encouraging learning, broadening participation, and promoting polycentric governance. After evaluating the values of the criteria and sub-criteria using a two-point evidential reasoning (TPER) approach and considering the existing uncertainties, the monthly time series of WERCC with uncertainty bands are calculated. The proposed methodology is then used to evaluate the WERCC in the Zarrinehrud river basin in Iran for a given historical period (1991-2012), and the period of 2020 to 2049 under different climate change scenarios. The results of this analysis demonstrate the inadequacy of the WERCC during the historical period and indicate that the continuation of the existing trend (base scenario, MSC) will cause many environmental issues. Hence, several water and environmental resources management (WERM) scenarios are proposed to enhance the WERCC. These scenarios are evaluated using a multi-agent-multi-criteria decision-making method to identify the preferable WERM scenario (MSC). This scenario, which encompasses various projects (e.g., development and enhancement of water transfer networks and upgrading cultivation methods), improves the average value of the WERCC by 26 %. The results of the proposed methodology are compared with those of a traditional decision-making method, which considers three criteria of average WERCC, the pressure-support index, and the implementation cost. The results demonstrate that the multi-agent-multi-criteria decision-making approach provides a more cost-effective management scenario, with 30 % less cost, leading to only 3 % less carrying capacity.