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Traditional blue water resources assessment and management may not meet the needs of sustainable water resource utilization; ignoring the number of green water resources will underestimate the availability of water resources. To rationally allocate and scientifically manage the limited water resources, it is necessary to divide the rich and poor flow situation of blue water and green water. The MIKE SHE-MIKE HYDRO integrated coupled model was selected and used in the Yalong River basin to ascertain the blue and green water in the hydrological cycle. The model was calibrated by matching simulated discharge against observed streamflow discharge at the Tongziling Station. At the same time, the research analyzed the component of green water and the total amount of blue water or green water on a temporal scale. The set pair analysis (SPA) was introduced to classify blue water and green water, which can not only understand the amount and distribution characteristics of water resources in the Yalong River Basin but also rationally allocate the total of water resources in the basin from the perspective of the regional water cycle. Furthermore, according to the situation of blue water and green water in the basin, the related policies are formulated to realize the efficient utilization of water resources in the Yalong River basin.

Understanding the changes in hydrological process is a key subject for water resource management of a high-diversity watershed. In this paper, through an establishment of a SWAT-based model, the effects of climate change and its induced vegetation change on hydrological process were analyzed in the East River Basin. The model could well simulate the hydrological processes of the basin including surface runoff (SURQ), groundwater (GWQ), lateral flow (LATQ), total water yield (WYLD), actual evapotranspiration (ET), and groundwater recharge (PERC). Under the vegetation change induced by temperature increase, the effects of the vegetation change on hydrological process were larger than that of the temperature change. Under the vegetation change caused by the increase of temperature and precipitation, the vegetation change enhanced the effects of climate change on annual SURQ, LATQ, GWQ, WYLD, and PERC of the basin. Under spatial scale, when the temperature and precipitation changed simultaneously, the increase of precipitation could promote the increase of annual ET in sub-watersheds. Also, the annual SURQ, WYLD, GWQ and ET in western sub-watersheds were more sensitive to the cumulative changes of vegetation and climate. This work can provide useful information to decision makers in water resource management of watersheds.

As the total water resources consumption control and carbon mitigation continuous improvement, the weak water-carbon incorporate management is increasingly exposed. In this study, a water-carbon nexus assessment framework is proposed to analyze the nexus relationship between water consumption and carbon emission, and distinguishes the coupled water-carbon transmission intensity and the transfer paths under regional and industrial scales. According to the practical input-output table, water consumption, and carbon emission information, the framework is applied to Beijing-Tianjin-Hebei urban agglomeration (BTHUA), a population, resource, and trade intensive area of China. Inter-regional/intra-regional water consumption and carbon emission transfer fluxes between sectors, the pairwise ecological relationship, and the water-carbon nexus were analyzed. Results indicated that the water-carbon transfer indexes from Hebei to Beijing and Tianjin were 161.85 kg/m

Commonalities and asynchronous experiences of realizing zero-waste of water, energy, and food resources between the world and China have critical global importance to support sustainable development, especially for Guangdong-Hong Kong-Macao Greater Bay Area (GBA) urban agglomeration. In this study, a comprehensive assessment framework for the zero-waste city was proposed to evaluate zero-waste construction in the world (e.g., San Francisco, New York, and Tokyo) and China (e.g., Beijing, Shanghai, and GBA) from the perspective of water, energy, and food. The results showed that the zero-waste construction level of the GBA cities was weaker than that of the benchmark city and other world-class cities. The average score of the GBA cities was the lowest, 2.5% lower than the benchmark city and 11.8% lower than other world-class cities. Macao had apparent advantages in the social-economic and ecological-environment system, while the Pearl River Delta cities were considerably better than Macao and Hong Kong in the water and food systems. Future work could improve the level of zero-waste construction by learning from foreign zero-waste cities’ advanced experience, increasing efforts to promote the implementation of a circular economy, and building an all-around government sharing mechanism with public participation.

Microplastic deposition in subtropical lakes and the influences of human activities remain to be deeply and fully understood. Owing to the intensification of urban construction and population growth, urban lakes serving as significant freshwater resources for sustainable development of the regional economy are becoming degraded, especially due to microplastic pollution. To understand the deposition characteristics of microplastics in lake sediments from the China's subtropical city, six sediment core samples were collected from Xinghu Lake of Guangdong Province. Here, we analyzed the morphological characteristics of microplastics from the perspective of microstructure, and investigated the temporal and spatial distribution patterns of microplastics on the macroscopic scale. The deposition characteristics of microplastics in the past 64 years and the influence of socio-economic factors on the accumulation of microplastics were further clarified through the isotope composition of cesium-137 and lead-210 in the subtropical urban area with intense human activities. The results showed that the microplastic concentration of sediment cores in Xinghu Lake was 523 ± 140 particles/kg. The average sizes of microplastics in the five sub-lakes (i.e., Bohai, Zhongxin, Li, Qinglian, and Xiannü Lakes) of Xinghu Lake were 668, 642, 727, 708 and 646 μm, respectively. There were 25 polymers in sediment cores of Xinghu Lake. Rayon, polypropylene, polyethylene terephthalate and polypropylene-polyethylene copolymer were the main types, and the microplastics have the aging phenomenon or mechanical abrasion. The average deposition rates of sediment and microplastics were 0.6 cm/a and 106 particles/(kg·a) in Xinghu Lake, respectively. Meanwhile, the urban expansion and economic growth, as indicated by the increase in the urban area, population and gross domestic product, all played an essential role in the accelerated accumulation of microplastics in sediment cores of Xinghu Lake.

Water and land are crucial natural resources for agricultural development. It is necessary to allocate water and land resources effectively in order to achieve the maximum economic profits and the minimum environmental costs. In this research, an inexact two-stage fractional programming model was developed for the allocation of water and land resources, which is integrated interval-parameters (IPP), two-stage stochastic programming (TSP), fractional programming (FP). This model could optimally allocate water and land resources at the same time under the scenario of the maximum economic profit and the minimum environmental cost; it was proved to be beneficial in (1) dealing with the conflicts between economic development and environmental protection and give insights in trade-off among the agricultural system; (2) allocating water and land resources for five crops under multiple flow level simultaneously; and (3) describing the uncertain inputs as interval-parameters to reduce model uncertainties. The developed model was applied to the northeast region of China. The optimal allocation schemes of water and land resources, the maximum economic profits, and the minimum environmental costs were obtained. The results showed that economic profits in the agricultural system in the northeast region of China would not definitely be connected with the allocation of water and land resources, and solid waste pollution would bear the largest environmental cost. The developed model could help decision-makers to get a deeper understanding of the agricultural system and manage water and land resources in an efficient and environment-friendly way.

In this paper, a hybrid method integrated unbiased grey model (UGM) and artificial neural network (ANN) into an interval two-stage fuzzy credibility-constrained programming (ITFCP) framework is proposed for water resources allocation of the Yalong River research area. Through the grey correlation analysis and the eXtreme Gradient Boosting (XGboost) algorithm, the economic and social indicators are related to the water demands of different water sectors in different regions can be obtained for building water demand prediction model. According to the unbiased grey prediction of the socio-economic development data of each region in the Yalong River Basin (YRB), water demand prediction models are constructed by using neural network. The establishment of a hybrid two-stage interval fuzzy credibility-constrained programming model can analyze the uncertainties existing in the process of water resources allocation. Taking 2020, 2025, and 2030 as the planning years, the developed model studies and reveals the system benefits at different credibility levels, the water shortage of each user in sub-regions and the water resources allocation situation to provide suggestion for managers to optimize the allocation of water resources. Compared to the previous methods, this integrated model can help decision-makers set management policies more sustainably and profitably.

To facilitate regional water resources allocation, an integrated bi-level multi-objective programming (IBMP) model with dual random fuzzy variables was developed in this research The proposed model was derived through incorporating dual random fuzzy variables, multi-objective programming, and interval parameter programming within a bi-level optimization framework. This approach improved upon the previous bi-level programming methods and had two advantages. Firstly, it was capable of reflecting tradeoffs among multiple conflict preferences for water related bi-level hierarchical decision-making processes. Secondly, random fuzzy variables were used to tackle the dual uncertainties in both sides of the constraints, which were characterize as probability density functions and discrete intervals. Then, a real-world water resources planning problem was employed for illustrating feasibility of the application of IBMP model in Dongjiang river watershed of south China. Results reflected the alternative decisions for water allocation schemes under a set of probability levels and fuzzy α - cut levels, which can support in-depth analysis of tradeoffs among multiple levels and objective values. Moreover, modeling comparison analysis was undertaken to illustrate the performances of the proposed model.

In this research, an interval two-stage stochastic fuzzy-interval credibility constraint programming (ISFICP) method was developed for water resources allocation among multiple water users under complexities and uncertainties. The method could reflect the multiple complexities of water resources management, also trade-offs between the system benefits and violation risks. Dongjiang River (DJR) Basin, which supplies water to several core cities in south China such as Guangzhou, Shenzhen, and Hong Kong, was applied as the real demonstrative case. The water resources system of DJR Basin is particularly complex due to it is the primary source water for Guangdong-Hong Kong-Macao Greater Bay Area (GBA). Through considering multiple complexities and uncertainties of the water resources system, such as natural, economic, and social conditions, ISFICP was developed to obtain potential water-allocation schemes. Probabilistic distribution, fuzzy-interval sets (FIS), and discrete intervals were introduced to represent the multiple uncertainties associated with the multiple complexities. The results indicated that the model could provide practical schemes for local decision-makers under multiple scenarios such as flow levels, credibility levels, and recycling rates.

Headwater streams are a hotspot of freshwater biodiversity, carrying indispensable resource pools of aquatic species. However, up to now, there remain many challenges to accurately and efficiently characterize the responses of this vulnerable ecosystem to human-induced changes. Here, we collected macroinvertebrate data from 12 different headwater streams in the Liao River of northeast China by DNA metabarcoding approach, to reveal biodiversity changes and ecological thresholds affected by human beings. Our data showed that the community composition and structure of headwater streams had unique and significant differences under human impacts, and 5-day biological oxygen demand (BOD

Socioeconomic development, leading to significant changes in land-use patterns, has further influenced the output of regional nonpoint-source (NPS) pollution. Multiple uncertainties exist in the processes of land-use changes and NPS pollution export. These uncertainties can deeply affect the management of regional land-use patterns and control of NPS pollution. In this research, an integrated land-use prediction and optimization (ILUPO) model based on system dynamics, export coefficient, interval linear programming, and fuzzy parameter programming models was proposed. The ILUPO model can provide future land-use patterns and NPS pollution loads, and also help optimize the patterns under multiple pollution reduction scenarios. Interval and fuzzy uncertainties in the processes of land-use changes and NPS pollution output can be effectively addressed. The developed model was applied to a water source area in the central part of northern Guangdong Province in South China. For the prediction period 2020-2030 under the high-speed development scenario, results show that cropland area would decrease, while grassland and waterbody areas would increase. In contrast, these three types of land-use would show opposite variation trends under the low-speed development scenario. Construction land area would decrease, while forestland area would increase under both the low-speed and high-speed development scenarios. Variation of the predicted land-use patterns would lead to an increase of total nitrogen loads under each of the scenario, while the total phosphorus loads would show relatively complex variation trends. Regional land-use patterns should be further optimized to mitigate NPS pollution. However, the pollution loads in the study area cannot be reduced by5% through land-use adjustment. Because cropland would still be the critical source of NPS pollution after optimization, strictly controlling the areas of cropland would be important for the management of such pollution in the research area. In addition, certain areas of grassland and waterbody would need to be converted into cropland and construction land to balance the economic benefit of the system and NPS pollution control. Multiple results obtained from the model under different scenarios of pollution reduction targets and α-cut levels can provide decision-making supports for the local policy makers. The developed ILUPO model can yield insights useful for the planning and adjustment of regional land-use patterns while considering NPS pollution control under conditions of uncertainty.

Production, consumption, and disposal of plastics are associated with the generation of a large amount of greenhouse gas (GHG). Polyethylene terephthalate (PET) is one of the most widely used plastics, which is mainly produced and consumed by China and causing increasing concerns. The Previous studies mainly focused on material flows and stocks of PET. Detailed information on GHG emissions for the entire life cycle of PET in China is limited. Particularly, the key paths of emission reduction for life-cycle PET considering carbon neutrality are unknown. In this research, a network analysis system and model of GHG emissions were developed for PET in China and helping explore characteristics of GHG emissions over the three development periods of the PET industry. The results showed that the most potential stage of carbon neutrality for PET was from the exploitation of raw materials to the end of PET chips production, accounting for approximately 74.9% over 2000 to 2018. The manufacturing process of PET fibers and bottles would have a major contribution to GHG emissions. At the same time, GHG emissions from the mechanical recovery process should not be ignored. The plastic restriction order for PET and the waste treatment ways of low-carbon would have a significant contribution to emission reduction. According to the results, this study identified the most potential key process of carbon neutrality in the PET life cycle and proposed policies to reduce GHG emissions, which would provide scientific support for the PET industry to achieve the goal of carbon neutrality in China.

The pursuit of the sustainable agriculture often ignores to consider the ecological benefits. To achieve this goal, it is necessary to evaluate the ecological impacts related to the sustainable development. Therefore, to assess the overall ecological impact of crop production in 31 provinces in China, this study proposes to set up a non-monetary framework and indicators based on Emergy theory. Further analysis focuses on sustainable ecosystem under three different planting scenarios to identify the driving factors. The results demonstrated that the ecosystem disservice of crop production processes is greater than the services. The total emergy inputs, fertilizers used and R%, all of these can affect the ecological benefits. Furthermore, simply changing the cultivation pattern cannot achieve a balance between ecology and economy, there is no doubt that other method needed are needed. These findings provide valuable insights for developing appropriate policies for decision makers.