School of Civil Engineering, College of Engineering, University of Tehran, Tehran, Iran.
School of Civil Engineering, College of Engineering, University of Tehran, Tehran, Iran.
J Environ Manage. 2022 Jan 1;301:113900. doi: 10.1016/j.jenvman.2021.113900. Epub 2021 Oct 9.
This paper introduces a new framework to evaluate the resilience of lakes under climatic and anthropogenic droughts. The proposed hierarchical structure of criteria for assessing lake's resilience has four levels. The first level includes several indices such as long-term resilience, reliability, and implementation cost. In the second to fourth levels, four main resilience-based criteria (i.e. robustness, resourcefulness, redundancy, and rapidity) and some qualitative and quantitative sub-criteria are defined considering the factors affecting the ecological condition of lakes. To quantify the time series of the sub-criteria, a coupled SWAT-MODSIM-based simulation model has been applied. Also, the values of criteria and sub-criteria have been aggregated using the Evidential Reasoning (ER) approach. After estimating the annual resilience time series, three resilience indices, namely the recovery time (Tr), loss of resilience (LOR), and final resilience (Res), have been calculated. The normalized values of these indices and reliability criteria have been aggregated to evaluate the overall performance of lake restoration scenarios. To show the applicability of the proposed methodology, the Zarrinehrud river basin and Lake Urmia have been selected as the case study. As one of the largest hypersaline lakes globally, Lake Urmia suffers from drastic changes in its water body and a high level of salinization. Also, the Zarrinehrud river basin, located in the southeastern of Urmia Lake, is the most significant sub-basin of the lake and is responsible for supplying 41% of the total annual inflow of the lake. The restoration scenarios of Lake Urmia have been assessed from 2019 to 2049. Eventually, the most effective scenario, which has an average overall performance of 0.72, the implementation cost of 17.1 million dollars, and the uncertainty band of 0.05, has been selected.
本文提出了一个新的框架来评估湖泊在气候和人为干旱下的弹性。所提出的评估湖泊弹性的标准层次结构有四个层次。第一级包括几个指标，如长期弹性、可靠性和实施成本。在第二到第四级，定义了四个主要基于弹性的标准（即稳健性、灵活性、冗余性和快速性）以及一些考虑影响湖泊生态条件的因素的定性和定量子标准。为了量化子标准的时间序列，应用了一个基于 SWAT-MODSIM 的耦合模拟模型。此外，还使用证据推理（ER）方法对标准和子标准的值进行了聚合。在估计了年度弹性时间序列后，计算了三个弹性指数，即恢复时间（Tr）、弹性损失（LOR）和最终弹性（Res）。这些指数和可靠性标准的归一化值被聚合在一起，以评估湖泊恢复方案的整体性能。为了展示所提出方法的适用性，选择扎林胡德河流域和乌尔米亚湖作为案例研究。作为全球最大的咸水湖之一，乌尔米亚湖的水体发生了剧烈变化，盐度水平很高。此外，位于乌尔米亚湖东南部的扎林胡德河流域是该湖最重要的子流域，负责供应该湖 41%的年总流入量。评估了从 2019 年到 2049 年的乌尔米亚湖恢复方案。最终，选择了最有效的方案，其总体性能平均为 0.72，实施成本为 1710 万美元，不确定性带为 0.05。
