College of New Energy and Environment, Jilin University, Changchun 130012, China.
Northeast Asian Studies College, Jilin University, Changchun 130012, China.
Int J Environ Res Public Health. 2021 Dec 23;19(1):149. doi: 10.3390/ijerph19010149.
In this work, based on the upper line of water resources utilization and the bottom line of water environmental quality of "Three Lines, Single Project", a fuzzy optimization method was introduced into the Tingjiang River water resources optimal allocation and eco-compensation mechanism model, which is based on the interval two-stage (ITS) stochastic programming method. In addition, a Tingjiang River water resources allocation and eco-compensation mechanism model based on the interval fuzzy two-stage (IFTS) optimization method was also constructed. The objective functions of both models were to maximize the economic benefits of the Tingjiang River. The available water resources in the basin, the water environmental quality requirements, and regional development requirements were used as constraints, and under the five hydrological scenarios of extreme dryness, dryness, normal flow, abundance, and extreme abundance, the water resources allocation plan of various sectors (industry, municipal, agriculture, and ecology) in the Tingjiang River was optimized, and an eco-compensation mechanism was developed. In this work, the uncertainty of the maximum available water resources in each region and the whole basin was considered. If the maximum available water resources were too high, it would lead to a large waste of water resources, whereas if the maximum available water resources were too low, regional economic development would be limited. Therefore, the above two parameters were set as fuzzy parameters in the optimization model construction in this work. The simulation results from the IFTS model showed that the amount of water available in the river basin directly affects the water usage by various departments, thereby affecting the economic benefits of the river basin and the amount of eco-compensation paid by the downstream areas. The average economic benefit of the Tingjiang River after the optimization of the IFTS model simulation was [3868.51, 5748.99] × 10 CNY, which is an increase of [1.67%, 51.9%] compared to the economic benefit of the basin announced by the government in 2018. Compared to the ITS model, the economic benefit interval of the five hydrological scenarios of extreme dryness, dryness, normal flow, abundance, and extreme abundance was reduced by 28.54%, 44.9%, 31.49%, 40.37%, and 36.43%, respectively, which can improve the economic benefits of the basin and provide more accurate decision-making schemes. In addition, the IFTS simulation showed that the eco-compensation quota paid by downstream Guangdong Province to upstream Fujian Province is [28,116.4, 30,738.6] × 10 CNY, which is a reduction of [8461.404, 110,836] × 10 CNY compared to the 2018 compensation scheme of the government. Compared to the ITS model, the range of eco-compensation values was observed to increase by 9.94%, 54.81%, 15.85%, 50.31%, and 82.90%, respectively, under the five hydrological scenarios, which reduces the burden of ecological expenditure downstream and provides a broader decision-making space for decision-makers and thus enables improved decision-making efficiency. At the same time, after the optimization of the IFTS model, the additional water consumption of the second stage of the Tingjiang River during the extremely dry year decreased by 62.11% compared to the results of the ITS model. The additional water consumption of the industrial sector decreased by 68.39%, the municipal sector decreased by 59.27%, and in the first phase of water resources allocation for 14 districts and counties in the Tingjiang River, industrial and municipal sectors are the main two sectors. After introducing the fuzzy method into the IFTS model, the difference in the water consumption by these two sectors in the basin under different hydrological scenarios can be alleviated, and the waste of water resources caused by too low water allocation or excessive water allocation can be avoided. The national and local (the downstream region) eco-compensation quotas can be indirectly reduced, and the risk of water resources allocation and eco-compensation decision-making in the basin can be effectively reduced.
在这项工作中，基于“三线一单”的水资源利用上线和水环境质量底线，引入模糊优化方法到基于区间两阶段（ITS）随机规划方法的汀江流域水资源优化配置和生态补偿机制模型中。此外，还构建了基于区间模糊两阶段（IFTS）优化方法的汀江流域水资源分配和生态补偿机制模型。两个模型的目标函数都是最大化汀江的经济效益。流域的可用水资源、水环境质量要求和区域发展要求作为约束条件，在极端干旱、干旱、正常流量、丰沛和极度丰沛五种水文情景下，优化汀江流域各部门（工业、市政、农业和生态）的水资源分配方案，并制定生态补偿机制。在这项工作中，考虑了每个区域和整个流域最大可用水资源的不确定性。如果最大可用水资源过高，将导致水资源大量浪费，而如果最大可用水资源过低，将限制区域经济发展。因此，在优化模型构建中，将上述两个参数设置为模糊参数。IFTS 模型的模拟结果表明，流域的可用水量直接影响各部门的用水量，从而影响流域的经济效益和下游地区支付的生态补偿金额。IFTS 模型模拟优化后的汀江平均经济效益为[3868.51,5748.99]×10 CNY，比 2018 年政府公布的流域经济效益增加了[1.67%,51.9%]。与 ITS 模型相比，极端干旱、干旱、正常流量、丰沛和极度丰沛五种水文情景的经济效益区间分别减少了 28.54%、44.9%、31.49%、40.37%和 36.43%，可以提高流域的经济效益，提供更准确的决策方案。此外，IFTS 模拟显示，下游广东省向上游福建省支付的生态补偿额度为[28,116.4,30,738.6]×10 CNY，比 2018 年政府补偿方案减少了[8461.404,110,836]×10 CNY。与 ITS 模型相比，在五种水文情景下，生态补偿值范围分别增加了 9.94%、54.81%、15.85%、50.31%和 82.90%，降低了下游生态支出的负担，为决策者提供了更广阔的决策空间，从而提高了决策效率。同时，在 IFTS 模型优化后，汀江在极旱年份的第二阶段的额外用水量与 ITS 模型相比减少了 62.11%。工业部门的额外用水量减少了 68.39%，市政部门减少了 59.27%，在汀江 14 个县区的水资源分配第一阶段，工业和市政部门是主要的两个部门。在引入模糊方法到 IFTS 模型后，可以缓解流域不同水文情景下这两个部门的用水量差异，避免因水资源配置过低或过高而造成的水资源浪费。可以间接减少流域水资源分配和生态补偿决策的国家和地方（下游地区）生态补偿额度，有效降低流域水资源分配和生态补偿决策的风险。
