An Interval Two-Stage Stochastic Programming Model for Flood Resources Allocation under Ecological Benefits as a Constraint Combined with Ecological Compensation Concept

How to Price Ecosystem Water Yield Service and Determine the Amount of Compensation?—The Wei River Basin in China as an Example

Determining the price of water yield service is the core of watershed compensation. This is necessary to establish a reasonable and scientific compensation mechanism and achieve the efficient management of water. Unlike previous studies, this study establishes a theoretical model of pricing and a compensation mechanism for achieving a balance between the supply and demand of water yield service. A panel threshold model is used to estimate the production elasticity of water for pricing water yield service. Then, we analyze the spatial and temporal changes of the price and the compensation amounts of water yield service in the Wei River basin, China. The results show that: (1) The water marginal contribution to regional GDP meets the law of diminishing marginal return in the form of the threshold effect. When water input amounts (logarithm) are on both sides of 9.449, the marginal contribution is significantly different. (2) The price of water yield service shows an increasing trend. It was CNY 47.27/m3 in 2015, increasing by 472.94% compared with 2000 (CNY 8.24/m3). The spatial distribution was “high in the southeast and low in the northwest”. (3) Total payment amounts increased from CNY 33.1955 billion in 2000 to CNY 227.1302 billion in 2015 and were mainly distributed in relatively developed areas. The acceptance areas were concentrated in relatively undeveloped areas. Total acceptance amounts increased from CNY 2922.2 million in 2000 to CNY 16,398.6 million in 2015. This study can provide scientific basis for ecological compensation practices and promote high-quality development of the socio-economy of the watershed.

Can Carbon Offset Policies Be Effectively Implemented in All Regions of China? An Evolutionary Game Analysis of Decision-Making Dynamics of Local Governments

Carbon offset policies are an effective means of coordinating regional ecological conservation, promoting environmentally friendly economic development, and achieving carbon neutrality; they are being gradually implemented in all regions of China. This study analyzed the decision-making behavior of local governments before and after the introduction of incentive and restraint mechanisms. To this end, it constructed a dynamic evolutionary game model for local governments with a carbon surplus and those with a carbon deficit. The results indicate that it is difficult to implement carbon offset policies between regions without the intervention of the central government. They also show that the effects of different incentive and restraint mechanisms vary significantly. Specifically, a mechanism that targets both carbon surplus and carbon deficit local governments and a unilateral mechanism that targets only carbon deficit local governments are shown to be effective. Finally, the results indicate that the implementation costs of incentive and restraint mechanisms differ, and their implementation intensity affects the time required for carbon offset policies to be rolled out in all regions. Based on these findings, we propose policy recommendations for promoting the implementation of carbon offset policies in all regions of China and alleviating carbon emission pressure.

Monitoring Water Quality of the Haihe River Based on Ground-Based Hyperspectral Remote Sensing

The Haihe River is a typical sluice-controlled river in the north of China. The construction and operation of sluice dams change the flow and other hydrological factors of rivers, which have adverse effects on water, making it difficult to study the characteristics of water quality change and water environment control in northern rivers. In recent years, remote sensing has been widely used in water quality monitoring. However, due to the low signal-to-noise ratio (SNR) and the limitation of instrument resolution, satellite remote sensing is still a challenge to inland water quality monitoring. Ground-based hyperspectral remote sensing has a high temporal-spatial resolution and can be simply fixed in the water edge to achieve real-time continuous detection. A combination of hyperspectral remote sensing devices and BP neural networks is used in the current research to invert water quality parameters. The measured values and remote sensing reflectance of eight water quality parameters (chlorophyll-a (Chl-a), phycocyanin (PC), total suspended sediments (TSS), total nitrogen (TN), total phosphorus (TP), ammonia nitrogen (NH4-N), nitrate-nitrogen (NO3-N), and pH) were modeled and verified. The results show that the performance R2 of the training model is above 80%, and the performance R2 of the verification model is above 70%. In the training model, the highest fitting degree is TN (R2 = 1, RMSE = 0.0012 mg/L), and the lowest fitting degree is PC (R2 = 0.87, RMSE = 0.0011 mg/L). Therefore, the application of hyperspectral remote sensing technology to water quality detection in the Haihe River is a feasible method. The model built in the hyperspectral remote sensing equipment can help decision-makers to easily understand the real-time changes of water quality parameters.

Multi-Objective Optimal Allocation of Water Resources Based on the NSGA-2 Algorithm While Considering Intergenerational Equity: A Case Study of the Middle and Upper Reaches of Huaihe River Basin, China

With the rapid development of society and the economy, the demand for water resources is increasing. This, combined with the increasing competition for water resources between current and future generations, hinders the sustainable development of society. To alleviate prominent water resources problems, achieve sustainable utilization of water resources and the sustainable development of society and economy, a multi-objective optimal water resources allocation model is proposed, in which different water sources and different water departments are considered to achieve the maximum social and economic benefits of the study area on the premise of water resources sustainability. To meet the needs of future generations, the discount value is introduced to measure intergenerational equity. A case study from seven cities in the upper and middle reaches of the Huaihe River Basin is given to verify the practicality and viability of the model. The non-dominated sorting Genetic Algorithms-2(NSGA-2) was used to find optimal water resources allocation schemes in 2020 and 2050 under the condition of a hydrological drought year (inflow guarantee rate p = 75%). Compared with previous models, the intergenerational equity model considers the sustainability of water resources, has higher social and economic benefits, and ensures the fair distribution of water resources among generations. According to the results, under balanced weight, the water shortage ratio of the seven cities will decrease from 5.24% in 2050 to 1.58% in 2020, and the economic benefit will increase from 79.46(10¹⁰CNY) to 168.3(10¹⁰CNY), respectively. In addition, the discount value of economic benefit in 2050 is 80.23(10¹⁰CNY), which is still higher than that in 2020. This shows that the water resource allocation scheme can eliminate the disparity between supply and demand for water resources and achieve intergenerational equity. Therefore, the intergenerational equity model can alleviate the contradiction of water resources and realize intergenerational equity.

Application of an Interval Two-Stage Robust (ITSR) Optimization Model for Optimization of Water Resource Distribution in the Yinma River Basin, Jilin Province, China

The present study is based on the application of an interval two-stage stochastic programming (ITSP) model in the Yinma River Basin. A robust method based on interval two-stage robust (ITSR) optimization is introduced to construct an optimization model of water resource distribution in order to solve the problems of water shortage in low-income and high-income areas caused by the unreasonable distribution of water resources. The model would help in reducing the system risk in the Yinma River Basin caused by an excessive pursuit of economic benefits. The model simulations show that the amount of water required for the water resource distribution is significantly reduced after balancing the risks and the water resource distribution of the water use departments is reduced by up to 20%. In addition, the situation of water scarcity of various water use departments shows a decreasing trend. There is no scarcity of water use in Panshi, Yongji, Shuangyang and Jiutai areas. The water shortage of water use departments in other areas is reduced by up to 97%. The allocation of reused water to ecological and environmental departments with higher water demand further solved the water shortage problem in low-income departments in the interval-two-stage planning model. In this study, after the introduction of the robust optimization method in the Yinma River Basin, the stability of the water resources distribution system is significantly improved. In addition, the risk of water use system in the interval-two-stage stochastic model can be avoided.

Optimization of Ecological Water Supplement Scheme for Improved Suitable Habitat Area for Rare Migratory Birds in Nature Reserves Using Interval-Parameter Fuzzy Two-Stage Stochastic Programming Model

The optimization of ecological water supplement scheme in Momoge National Nature Reserve (MNNR), using an interval-parameter two-stage stochastic programming model (IPTSP), still experiences problems with fuzzy uncertainties and the wide scope of the obtained optimization schemes. These two limitations pose a high risk of system failure causing high decision risk for decision-makers and render it difficult to further undertake optimization schemes respectively. Therefore, an interval-parameter fuzzy two-stage stochastic programming (IPFTSP) model derived from an IPTSP model was constructed to address the random variable, the interval uncertainties and the fuzzy uncertainties in the water management system in the present study, to reduce decision risk and narrow down the scope of the optimization schemes. The constructed IPFTSP model was subsequently applied to the optimization of the ecological water supplement scheme of MNNR under different scenarios, to maximize the recovered habitat area and the carrying capacity for rare migratory water birds. As per the results of the IPFTSP model, the recovered habitat areas for rare migratory birds under low, medium and high flood flow scenarios were (14.06, 17.88) × 103, (14.92, 18.96) × 103 and (15.83, 19.43) × 103 ha, respectively, and the target value was (14.60, 18.47) × 103 ha with a fuzzy membership of (0.01, 0.83). Fuzzy membership reflects the possibility level that the model solutions satisfy the target value and the corresponding decision risk. We further observed that the habitat area recovered by the optimization schemes of the IPFTSP model was significantly increased compared to the recommended scheme, and the increases observed were (5.22%, 33.78%), (11.62%, 41.88%) and (18.44%, 45.39%). In addition, the interval widths of the recovered habitat areas in the IPFTSP model were reduced by 17.15%, 17.98% and 23.86%, in comparison to those from the IPTSP model. It was revealed that the IPFTSP model, besides generating the optimal decision schemes under different scenarios for decision-makers to select and providing decision space to adjust the decision schemes, also shortened the decision range, thereby reducing the decision risk and the difficulty of undertaking decision schemes. In addition, the fuzzy membership obtained from the IPFTSP model, reflecting the relationship among the possibility level, the target value, and the decision risk, assists the decision-makers in planning the ecological water supplement scheme with a preference for target value and decision risk.

Interval-Parameter Two-Stage Stochastic Programming (IPTSP) Model of Ecological Water Replenishment Scheme in the National Nature Reserve for Improved Suitable Habitat for Rare and Endangered Migrant Birds

In this work, an interval-parameter two-stage stochastic programming (IPTSP) model of water resources allocation was established for maximizing the restored habitat area of large, rare, and endangered water birds by adjusting the recommended scheme of water replenishment under different scenarios and constraints. The established model can efficiently deal with the uncertainties, such as the interval parameters and random variables, in the management system of water resources simultaneously. A case study was conducted in the Momoge National Nature Reserve (MNNR) in northeast China to maximize the restored habitat area of large, rare and endangered water birds based on limited water resources. According to the previous studies, a water area with a depth of 0–40 cm is a suitable habitat area in the MNNR for the Siberian crane, oriental stork, and red-crowned crane. The results of the present work show that the habitat area restored by water replenishment schemes under low, medium, and high flood flow scenarios after optimization increased in comparison to 13.36 × 103 ha of the recommended scheme, with an increase of [0.62, 5.23], [1.49, 6.42], and [2.43, 7.17] × 103 ha, respectively (the two numbers within each bracket represent the lower and upper bounds of the restored habitat areas). As a result, the carrying capacity of suitable habitat areas increased by [0.82, 6.88], [1.96, 8.45], and [3.21, 9.43] × 103 birds, correspondingly. The restored wetland area of the project recommendation scheme was 34.23 × 103 ha, and that of the optimal water replenishment schemes was [29.35, 41.01], [31.02, 44.13], and [33.88, 46.04] × 103 ha, respectively under the three flood flow scenarios. The results reveal that the model constructed in this work realizes the optimization and adjustment of the initial scheme to an increased restored wetland and habitat area with an increase in the flow level. Here, the upper bound of the interval value mentioned above is significantly higher than the lower bound value, which indicates that a feasible decision space was provided for decision makers to optimize and adjust the recommended scheme on the basis of the actual situation. The model-optimized schemes significantly improved the utilization of limited water resources. The results of this study can provide valuable theoretical support for the restoration and protection of rare and endangered water bird habitats and planning and management of water resources.

A Machine Learning Ensemble Approach Based on Random Forest and Radial Basis Function Neural Network for Risk Evaluation of Regional Flood Disaster: A Case Study of the Yangtze River Delta, China

The Yangtze River Delta (YRD) is one of the most developed regions in China. This is also a flood-prone area where flood disasters are frequently experienced; the situations between the people-land nexus and the people-water nexus are very complicated. Therefore, the accurate assessment of flood risk is of great significance to regional development. The paper took the YRD urban agglomeration as the research case. The driving force, pressure, state, impact and response (DPSIR) conceptual framework was established to analyze the indexes of flood disasters. The random forest (RF) algorithm was used to screen important indexes of floods risk, and a risk assessment model based on the radial basis function (RBF) neural network was constructed to evaluate the flood risk level in this region from 2009 to 2018. The risk map showed the I-V level of flood risk in the YRD urban agglomeration from 2016 to 2018 by using the geographic information system (GIS). Further analysis indicated that the indexes such as flood season rainfall, urban impervious area ratio, gross domestic product (GDP) per square kilometer of land, water area ratio, population density and emergency rescue capacity of public administration departments have important influence on flood risk. The flood risk has been increasing in the YRD urban agglomeration during the past ten years under the urbanization background, and economic development status showed a significant positive correlation with flood risks. In addition, there were serious differences in the rising rate of flood risks and the status quo among provinces. There are still a few cities that have stabilized at a better flood-risk level through urban flood control measures from 2016 to 2018. These results were basically in line with the actual situation, which validated the effectiveness of the model. Finally, countermeasures and suggestions for reducing the urban flood risk in the YRD region were proposed, in order to provide decision support for flood control, disaster reduction and emergency management in the YRD region.