Predictive simulation and optimal allocation of surface water resources in reservoir basins under climate change

Predicting and allocating surface water resources are becoming increasingly important tasks for addressing the risk of water shortages and challenges of climate change,especially in reservoir basins.However,surface water resource management includes many systematic uncertainties and complexities that are difficult to address.Thus,advanced models must be developed to support predictive simulations and optimal allocations of surface water resources,which are urgently required to ensure regional water supply security and sustainable socioeconomic development.In this study,a soil and water assessment tool-based interval linear multi-objective programming(SWAT-ILMP)model was developed and integrated with climate change scenarios,SWAT,interval parameter programming,and multi-objective programming.The developed model was applied to the Xinfengjiang Reservoir basin in South China and was able to identify optimal allocation schemes for water resources under different climate change scenarios.In the forecast year 2025,the optimal water quantity for power generation would be the highest and account for∼60%of all water resources,the optimal water quantity for water supply would account for∼35%,while the optimal surplus water released from the reservoir would be the lowest at≤5%.In addition,climate change and reservoir initial storage would greatly affect the surplus water quantity but not the power generation or water supply quantity.In general,the SWAT-ILMP model is applicable and effective for water resource prediction and management systems.The results from different scenarios can provide multiple alternatives to support rational water resource allocation in the study area.

Urban energy consumption and related carbon emission estimation： a study at the sector scale

With rapid economic development and energy consumption growth, China has become the largest energy consumer in the world. Impelled by extensive international concern, there is an urgent need to analyze the character- istics of energy consumption and related carbon emission, with the objective of saving energy, reducing carbon emission, and lessening environmental impact. Focusing on urban ecosystems, the biggest energy consumer, a method for estimating energy consumption and related carbon emission was established at the urban sector scale in this paper. Based on data for 1996-2010, the proposed method was applied to Beijing in a case study to analyze the consumption of different energy resources （i.e., coal, oil, gas, and electricity） and related carbon emission in different sectors （i.e., agriculture, industry, construction, transportation, household, and service sectors）. The results showed that coal and oil contributed most to energy consumption and carbon emission among different energy resources during the study period, while the industrial sector consumed the most energy and emitted the most carbon among different sectors. Suggestions were put forward for energy conservation and emission reduction in Beijing. The analysis of energy consumption and related carbon emission at the sector scale is helpful for practical energy saving and emission reduction in urban ecosystems.

Numerical simulation of hydrodynamic and water quality effects of shoreline changes in Bohai Bay

This study uses the HD and Ecolab modules of MIKE to simulate the hydrodynamic and water quality and predict the influence of shoreline changes in Bohai Bay, China. The study shows that shoreline changes weaken the residual current and generate a counter-clockwise circulation south of Huanghua Port, thereby resulting in weak water exchange capacity and low pollutant-diffusing capacity. Shoreline changes reduce the area of Bohai Bay, resulting in a smaller tidal prism and further weakening the water exchange capacity. This situation is not conducive to the diffusion of pollutants, and therefore may lead to increased water pollution in the bay. Shoreline changes hinder the spread of runoff, weaken the dilution effect of the river on seawater, and block the spread of coastal residual Current, thereby resulting in increased salinity near the reclamation area. Shoreline changes lead to an increase in PO4-P concentration and decrease in DIN concentration. The value of N/P near the project decreases, thereby weakening the phosphorus-limited effect.

Network analysis of eight industrial symbiosis systems

Industrial symbiosis is the quintessential characteristic of an eco-industrial park. To divide parks into different types, previous studies mostly focused on qualitative judgments, and failed to use metrics to conduct quantitative research on the intemal structural or functional characteristics of a park. To analyze a park＇s structural attributes, a range of metrics from network analysis have been applied, but few researchers have compared two or more symbioses using multiple metrics. In this study, we used two metrics （density and network degree centraliza- tion） to compare the degrees of completeness and dependence of eight diverse but representative industrial symbiosis networks. Through the combination of the two metrics, we divided the networks into three types： weak completeness, and two forms of strong completeness, namely ＂anchor tenant＂ mutualism and ＂equality-oriented＂ mutualism. The results showed that the networks with a weak degree of completeness were sparse and had few connections among nodes; for ＂anchor tenant＂ mutualism, the degree of completeness was relatively high, but the affiliated members were too dependent on core members; and the members in ＂equality-oriented＂ mutualism had equal roles, with diverse and flexible symbiotic paths. These results revealed some of the systems＇ internal structure and how different structures influenced the exchanges of materials, energy, and knowledge among members of a system, thereby providing insights into threats that may destabilize the network. Based on this analysis, we provide examples of the advantages and effectiveness of recent improvement projects in a typical Chinese eco-industrial park （Shandong Lubei）.