Environmental Water Management Research Articles

Water Quality Prediction Based on LSTM and Attention Mechanism: A Case Study of the Burnett River, Australia

Prediction of water quality is a critical aspect of water pollution control and prevention. The trend of water quality can be predicted using historical data collected from water quality monitoring and management of water environment. The present study aims to develop a long short-term memory (LSTM) network and its attention-based (AT-LSTM) model to achieve the prediction of water quality in the Burnett River of Australia. The models developed in this study introduced an attention mechanism after feature extraction of water quality data in the section of Burnett River considering the effect of the sequences on the prediction results at different moments to enhance the influence of key features on the prediction results. This study provides one-step-ahead forecasting and multistep forward forecasting of dissolved oxygen (DO) of the Burnett River utilizing LSTM and AT-LSTM models and the comparison of the results. The research outcomes demonstrated that the inclusion of the attention mechanism improves the prediction performance of the LSTM model. Therefore, the AT-LSTM-based water quality forecasting model, developed in this study, demonstrated its stronger capability than the LSTM model for informing the Water Quality Improvement Plan of Queensland, Australia, to accurately predict water quality in the Burnett River.

Analysis of the Management of Small and Medium Rivers in Urban Area Based on Ecological Civilization Construction of Waters

Water is the soul of the city, people in the early construction of the city is based on water, all the major cities today are river through. Rivers are closely related to the development of towns. As one of the indispensable and important substances for the survival and development of human beings, the study of water resources plays a great role in the construction of ecological civilization in cities. However, the problem of sewage discharge is still prevalent in small and medium-sized cities. Even though the country has spent a lot of money in recent years to deal with water pollution and implement measures to treat rivers whose ecological environment has been destroyed, the problem of sewage discharge cannot be solved fundamentally. Based on the research on moon lake in Chizhou, Anhui province, this paper holds that the restoration of urban small and medium-sized rivers should be based on the restoration of high-quality water resources, put forward the strategy of systematic management, ecological priority, improve the comprehensive benefits of urban small and medium-sized rivers, give full play to the role of effective supervision by residents, and build a new ecological civilization in the water areas. Based on the shortcomings and experience gained from the treatment of moon-lake sewage in Chizhou city, we will popularize the treatment of urban river wastewater from small to large, take the improvement of water environment as an important part of ecological management, find out the problems in the process of water environmental management and put forward corresponding measures to establish scientific and efficient protection mechanism.

Numerical Modeling of COD Transportation in Liaodong Bay: Impact of COD Loads from Rivers Flowing into the Sea

Pollution loads pose a major threat to the health of the marine environment and the long-term viability of the coastal economy. The present study developed a coupling model to simulate the chemical oxygen demand (COD) transport in upper rivers (1D) and subsequent diffusion in the coastal zone (2D) in Liaodong Bay, based on the HydroInfo system. Three main seagoing rivers, including Daliao, Liao, and Daling Rivers, were selected and investigated for hydrodynamic and hydrochemical analyses. The mathematical model was evaluated by monitoring data from state-controlled cross-sections scattered along the three rivers, and the observation data showed good agreement with simulated values, confirming the model’s accuracy in terms of spatial and temporal distribution. The transport and propagation process of COD in inlet rivers, such as Daliao, Liao, and Daling, including the sea area of Liaodong Bay, were simulated and analyzed. Simulated results revealed that the pollution range of COD in Liaodong Bay was 258–391 km2 in different seasons. The pollutant leakage scenarios for the three rivers entering the sea were simulated utilizing the developed mathematical model. The study simulated and predicted that, in the event of a sudden water pollution accident (e.g., sneak discharge and leakage at various sections of sea-entering rivers, such as Daliao, Liao, and Daling), pollutants might take 2–11 days to reach the sea-entering mouth, and the sea area would take 8–32 days to reach the maximum pollution range. Our numerical modeling may be used to analyze and make decisions on pollution control in Liaodong Bay and major sea-entry rivers, and be useful to water environment management in sea-entry rivers and Liaodong Bay, and water pollution emergency responses.

Quantitative analysis of self-purification capacity of non-point source pollutants in watersheds based on SWAT model

• Based on SWAT model and different self-purifying capacity expression indicators. • Quantitative identification of the self-purifying capacity of the watershed. • Analysis of the causes of change over time and under different land uses. • Quantitative analysis of the self-purifying capacity of the watershed for non-point source pollutants. • The conclusion is of great significance for future ecological protection. It is of great value to reveal the self-purification capacity of surface-sourced nutrients in the watershed and its change pattern, which is important to enrich the study of self-purification capacity of rivers and provide scientific basis for river water environment management. Based on the SWAT model and different self-purification capacity expression indicators, the self-purification capacity of non-point source pollutant nutrients and its change pattern in each river section of the Yiluo River basin from 2018 to 2021 were analyzed, and the physical significance of each indicator, its influence factor and its use range were systematically discussed. The results show that the self-purification of TN and TP in the Yiluo River exceeds 50% of the self-purification of the whole water system, but the self-purification rate is smaller than that of the Yiluo and Luo Rivers; the self-purification of TN and TP is the largest during the abundant water period and the smallest during the dry water period. The self-purification capacity expressed by the indicators of self-purification amount RL and area self-purification amount RA increases with the increase of hydrological variables such as flow (including water depth and velocity), river morphological parameters such as river width and length, and pollutant load; The self-cleaning ability expressed by the self-cleaning coefficient Kx/Kt, self-cleaning length SL, self-cleaning rate Re and load weight self-cleaning rate RLw is opposite; The self-purification rate Vf of the river only increases with the increase of water temperature. From the perspective of differences in application, the two indicators of self-purification speed Vf and area self-purification amount RA should be used for spatial comparison; The other six indicators should be used for the comparison of the same river at different times, of which the self-purification length SL can be used to reflect the influence of hydrological conditions on the self-purification process because of its sensitivity to changes in hydrological conditions.

TLT: Recurrent fine-tuning transfer learning for water quality long-term prediction

The water quality long-term prediction is essential to water environment management decisions. In recent years, although water quality prediction methods based on deep learning have achieved excellent performance in short-term prediction, these methods are unsuitable for long-term prediction because the accumulation use of short-term prediction will easily introduce noise. Furthermore, The long-term prediction task requires a large amount of data to train the model to obtain accurate prediction results. For some monitoring stations with limited historical data, it is challenging to fully exploit the performance of deep learning models. To this end, we introduce a transfer learning framework into water quality prediction to improve the prediction performance in data-constrained scenarios. We propose a deep Transfer Learning based on Transformer (TLT) model to enable time dependency perception and facilitate long-term water quality prediction. In TLT, we innovatively introduce a recurrent fine-tuning transfer learning method, which can transfer the knowledge learned from source monitoring stations to the target station, while preventing the deep learning model from overfitting the source data during the pre-training phase. So, TLT can fully exert the performance of deep learning models with limited samples. We conduct experiments on data from 120 monitoring stations in major rivers and lakes in China to verify the effectiveness of TLT. The results show that TLT can effectively improve the long-term prediction accuracy of four water quality indicators (pH, DO, NH3-N, and CODMn) from monitoring stations with limited samples.

The application of water conservancy project in the comprehensive management of water environment in Taihu Lake Basin

After the outbreak of cyanobacterial water pollution crisis in Taihu Lake Basin, it not only affected the normal life and production activities of local residents, but also attracted extensive attention from the media at home and abroad. When the governments at all levels from the central to the local level attach great importance to the comprehensive water environment management in the Taihu basin, they start from the perspectives of land, science and technology, farmers, water conservancy, construction and environmental protection, and put forward a large number of engineering and non-engineering measures. Therefore, on the basis of clarifying the significance of water conservancy project construction and the current situation of water environment management in Taihu Lake basin, this paper deeply discusses how to apply water conservancy project in the comprehensive water environment management of Taihu Lake basin, and makes a comparative analysis of the benefits obtained from it. The final results show that hydraulic engineering plays an active role in the comprehensive treatment of water environment.

The application of water conservancy project in the comprehensive management of water environment in Taihu Lake Basin

After the outbreak of cyanobacterial water pollution crisis in Taihu Lake Basin, it not only affected the normal life and production activities of local residents, but also attracted extensive attention from the media at home and abroad. When the governments at all levels from the central to the local level attach great importance to the comprehensive water environment management in the Taihu basin, they start from the perspectives of land, science and technology, farmers, water conservancy, construction and environmental protection, and put forward a large number of engineering and non-engineering measures. Therefore, on the basis of clarifying the significance of water conservancy project construction and the current situation of water environment management in Taihu Lake basin, this paper deeply discusses how to apply water conservancy project in the comprehensive water environment management of Taihu Lake basin, and makes a comparative analysis of the benefits obtained from it. The final results show that hydraulic engineering plays an active role in the comprehensive treatment of water environment.

Development and Path of Reclaimed Water Utilization Policy in China: Visual Analysis Based on CNKI and WOS.

In this paper, CiteSpace and NVivo software were used for the knowledge graph visualization and content analysis of highly cited papers in the research literature on reclaimed water utilization policy in CNKI and WOS. The results showed the following: there was an upward trend in the number of papers on reclaimed water policy, papers in both databases attached great importance to research on this topic, and the research prospects for this topic are broad. The UK, Greece, Italy, the United States, and France have great influence in the field of reclaimed water utilization policy research. The international influence of China’s research on the topic needs to be improved. There is a lack of communication and cooperation among the subjects of reclaimed water utilization policy research, and a cooperative network with close and benign interactions has not yet been formed. The research hotspots of the topic in China are mainly focused on regional governance, with insufficient attention paid to policy and management, while foreign countries pay more attention to policy and management. Behavior guidance policy and black and smelly water will become research hotspots for domestic policies, while public perception, demand, drinking water, and carbon will become research hotspots for international policies. Domestic research on reclaimed water use policy in highly cited papers focused on water environment and ecological security management, while international research focused on the background of reclaimed water use policy and its implementation, with the main intention of optimizing the ascension path and making international research policies thematically stronger. The attitudes of domestic and foreign researchers regarding reclaimed water utilization policies are mainly rational and emotional, indicating that current policies have a degree of applicability. However, there are also obvious problems that will need to be addressed and improved, and there are substantial development prospects. In the future, research on reclaimed water utilization policies in China should strengthen top-level design, improve the policy system, and increase the supervision of policies to achieve optimization.

Water-Quality Assessment and Pollution-Risk Early-Warning System Based on Web Crawler Technology and LSTM.

The openly released and measured data from automatic hydrological and water quality stations in China provide strong data support for water environmental protection management and scientific research. However, current public data on hydrology and water quality only provide real-time data through data tables in a shared page. To excavate the supporting effect of these data on water environmental protection, this paper designs a water-quality-prediction and pollution-risk early-warning system. In this system, crawler technology was used for data collection from public real-time data. Additionally, a modified long short-term memory (LSTM) was adopted to predict the water quality and provide an early warning for pollution risks. According to geographic information technology, this system can show the process of spatial and temporal variations of hydrology and water quality in China. At the same time, the current and future water quality of important monitoring sites can be quickly evaluated and predicted, together with the pollution-risk early warning. The data collected and the water-quality-prediction technique in the system can be shared and used for supporting hydrology and in water quality research and management.

Deep Learning-Based Water Quality Retrieval in an Impounded Lake Using Landsat 8 Imagery: An Application in Dongping Lake

Attempts have been made to incorporate remote sensing techniques and in situ observations for enhanced water quality assessments. Estimations of nonoptical indicators sensitive to water environment changes, however, have not been fully studied, mainly due to complex nonlinear relationships between the observed values and surface reflectance. In this study, we applied a novel deep learning approach driven by a range of spectral properties to retrieve 6-year changes in water quality variables, i.e., Chl-a, BOD, TN, CODMn, NH3-N, and TP, on a monthly basis between 2013 and 2018 at Dongping Lake, an impounded lake located in the Yellow River in China. Band arithmetic was used to compute 26 predictors from Landsat 8 OLI imagery for model inputs. The results showed generally strong agreement between in situ and ConvLSTM-derived lake variables, generating R2 of 0.92, 0.88, 0.84, 0.80, 0.83, and 0.77 for TN, NH3-N, CODMn, Chl-a, TP, and BOD, which suggest good performance of the developed model. We then used statistical analysis to identify the spatial and temporal heterogeneity. The framework established in this study has applications in effective water quality monitoring and serves as an alarming tool for water-environment management in the complex inland lake waters.

Flood susceptibility assessment using hybrid machine learning and remote sensing in Quang Tri province, Vietnam

AbstractFlooding is the most dangerous of all environmental hazards and leads to significant impacts both on the environment and on human life. Environmental protection and water management can be achieved by modeling flood susceptibility, to inform strategy that will reduce flood damage. The aim of this study is to develop novel hybrid models based on a radial basis functions neural network (RBFNN), arithmetic optimization algorithm (AOA), artificial bee colony (ABC), and ant lion optimizer (ALO), to build flood susceptibility maps in the Quang Tri province of Vietnam. The obtained models were trained and validated using 1511 flood points and 14 conditioning factors. Various statistical indices were used to assess the performance of the models, namely root mean square error, receiver operation characteristics (ROC), area under the receiver operating characteristic curve (AUC), and the coefficient of determination (R2). The comparison analysis highlights that the RBFNN‐ABC model was better than other models with an AUC of 0.98, followed by RBFNN‐AOA, support vector machine, and random forest, all with an AUC value of 0.96, and finally RBFNN‐ALO, with an AUC of 0.95. From the flood susceptibility map, it can be seen that the eastern areas of the study area have high and very high flood susceptibility, that requires local government attention. The approach and results of this study can support national and local authorities, decision‐makers, and other planners in the construction of appropriate strategies to reduce potential damage in the future.

Combined effects of damming and drought on nitrogen dynamics in an ephemeral river of North China

Damming and drought have dramatically altered water cycle dynamics in rivers, which further affects nitrogen biogeochemical cycles; however, their combined effects have rarely been studied, especially for ephemeral rivers with variable water flows. Taking the Dagu River of North China as the study area, we examined the spatiotemporal variability of nitrogen in river water and its relation to damming and drought. The total nitrogen (TN), dissolved inorganic nitrogen (DIN) and NO3‾ concentrations varied significantly in space and time, but the NH4+ and NO2‾ concentrations changed little. Spatially, compared with the upper reaches, the TN, DIN and NO3‾ concentrations in the lower reaches decreased by 71%, 81% and 85%, respectively, which was concurrent with the isotopic enrichment of nitrate. Temporally, their concentrations in dry seasons were more than twice of wet seasons, and increased from 2018 (normal year) to 2019 (dry year). The cascade dams may promote the NO3‾ removal towards the lower reaches through assimilation, which combined with nitrification and strong evaporation to enhance δ18O–NO3‾ enrichment and disproportionate δ15N–NO3‾/δ18O–NO3‾ ratio. Further, the damming effects can be aggravated by droughts because of no flow, extended nitrogen residence time and increased groundwater discharge with higher nitrogen contents, which jointly elevated the nitrogen level. Hence, the combined effects of damming and drought should be fully considered for management of water environment and resources in regions with ephemeral rivers.

How Well Do Multisatellite Products Capture the Space–Time Dynamics of Precipitation? Part II: Building an Error Model through Spectral System Identification

Abstract Satellite precipitation products, as all quantitative estimates, come with some inherent degree of uncertainty. To associate a quantitative value of the uncertainty to each individual estimate, error modeling is necessary. Most of the error models proposed so far compute the uncertainty as a function of precipitation intensity only, and only at one specific spatiotemporal scale. We propose a spectral error model that accounts for the neighboring space–time dynamics of precipitation into the uncertainty quantification. Systematic distortions of the precipitation signal and random errors are characterized distinctively in every frequency–wavenumber band in the Fourier domain, to accurately characterize error across scales. The systematic distortions are represented as a deterministic space–time linear filtering term. The random errors are represented as a nonstationary additive noise. The spectral error model is applied to the IMERG multisatellite precipitation product, and its parameters are estimated empirically through a system identification approach using the GV-MRMS gauge–radar measurements as reference (“truth”) over the eastern United States. The filtering term is found to be essentially low-pass (attenuating the fine-scale variability). While traditional error models attribute most of the error variance to random errors, it is found here that the systematic filtering term explains 48% of the error variance at the native resolution of IMERG. This fact confirms that, at high resolution, filtering effects in satellite precipitation products cannot be ignored, and that the error cannot be represented as a purely random additive or multiplicative term. An important consequence is that precipitation estimates derived from different sources shall not be expected to automatically have statistically independent errors. Significance Statement Satellite precipitation products are nowadays widely used for climate and environmental research, water management, risk analysis, and decision support at the local, regional, and global scales. For all these applications, knowledge about the accuracy of the products is critical for their usability. However, products are not systematically provided with a quantitative measure of the uncertainty associated with each individual estimate. Various parametric error models have been proposed for uncertainty quantification, mostly assuming that the uncertainty is only a function of the precipitation intensity at the pixel and time of interest. By projecting satellite precipitation fields and their retrieval errors into the Fourier frequency–wavenumber domain, we show that we can explicitly take into account the neighboring space–time multiscale dynamics of precipitation and compute a scale-dependent uncertainty.

Sustainable Innovation on Urban Landscape Construction and Ecological Water Environment Governance Process

Abstract In recent years, various cities have continued to build urban landscapes with typical characteristics, but most of the urban landscape constructions are too similar. There is even a problem that the urban landscape is not recognised by the local people, and the same is true for the problem of ecological water governance. This article aims to study the sustainable innovation of urban landscape construction and ecological water environment governance process. To this end, this article proposes fuzzy comprehensive evaluation criteria and goals, through this evaluation system to evaluate the urban landscape construction and ecological water environment management process, and at the same time design experiments to investigate. The experimental results of this paper show that the evaluation system can help improve the urban landscape construction and ecological water environment management. At the same time, the analysis results show that under this evaluation system, urban residents’ satisfaction with the urban landscape has increased by 47 %. At the same time, the effect of water treatment has also been improved, with an improvement effect of 31 %. For the actual governance process, the effect is huge.

Research on the Compilation Ability of Technicians in Construction Enterprises for Innovative Data

In order to study the participation of front-line technicians in construction enterprises in technological innovation activities of enterprises, the cognition of innovation data compilation, the method of each element of innovation data writing, the ability of literature retrieval and the difficulties encountered in the process of writing. In this paper, the questionnaire survey is used to investigate the first-line general contracting project departments of large-scale central enterprises whose main business is energy and power, water resources and environmental engineering, infrastructure construction, design, supervision, investment, and operation management in the past five years. 23 professional and technical personnel with intermediate professional titles were surveyed. The research results show that: 23% of technicians are aware of innovation activities and actively participate in them; 77% of technicians are not aware of innovation activities and have not been guided to participate by the organization, so they do not know much about technological innovation activities; from the perspective of individual technicians, 45% of technicians believe that participation in innovation is optional and has little impact on themselves; 36% of technicians believe that it is necessary to participate in technological innovation activities, but completing their own work is more important and more in line with their actual benefits.

Zoning Strategy for Basin Land Use Optimization for Reducing Nitrogen and Phosphorus Pollution in Guizhou Karst Watershed

Eutrophication caused by excessive total nitrogen (TN) and total phosphorus (TP) emissions is of wide concern for society at large. Studies have revealed certain relationships among land use, TN, and TP. However, the relationships among land use compound topographic position, TP, and TN have seldom been studied. Therefore, the objectives of this paper are to construct optimal zoning of land use and reduce the nutrient load of lakes. Spearman correlation and redundancy analyses were used to reveal the relationship between land use comprehensive topographic position and TN and TP in the lakes of Guizhou Plateau. The results show that the nutritional state of the research area is medium. The trophic level index (TLI) value and TN concentration were high during flood periods, while TP concentration was high in dry periods. The TN concentration in the tributaries was higher than that in the reservoir area. Construction land and valley were the sources of the pollution, whereas forest land and gentle slope were the sink. According to the ”source–sink” effect, once the optimal zoning of land use is completed, the governance of urban land pollution governed areas should be strengthened next. This paper can provide decision support for water environment management and sustainable development decision-making.

Stream water quality optimized prediction based on human activity intensity and landscape metrics with regional heterogeneity in Taihu Basin, China.

The driving effects of landscape metrics on water quality have been acknowledged widely, however, the guiding significance of human activity intensity and landscape metrics based on reference conditions for water environment management remains to be explored. Thus, we used the self-organized map, long- and short-term memory (LSTM) algorithm, and geographic detectors to simulate the response of human activity intensity and landscape metrics to water quality in Taihu Lake Basin, China. Fitting results of LSTM displayed that the accuracy was acceptable, and scenario 2 (regional heterogeneity) was more efficient than scenario 1 (regional consistent) in the improvement of water quality. In the driving analysis for the reference conditions, clusters I and II (urban agglomeration areas) were mainly affected by the amount of production wastewater per unit of developed land and the amount of livelihood wastewater per unit of developed land, respectively. Their optimal values were 0.09 × 103 t/km2 (reduction of 35.71%) and 0.2 × 103 t/km2 (reduction of 4.76%). Cluster III (agricultural production areas) was mainly affected by interference intensity, and the optimal value was 2.17 (increased 38.22%), and cluster IV (ecological forest areas) was mainly affected by the fragmentation of cropland, and the optimal value was 1.14 (reduction of 1.72%). The research provides a reference for the prediction of water quality response and presents an ecological and economic sustainability way for watershed governance.

Optimal configuration of low impact development practices for the management of urban runoff pollution under uncertainty

The urbanization process has seen an accelerated increase in recent decades, leading to urban runoff pollution becoming more prominent. However, uncertainty of the pollution output and complexity of management systems have made controlling urban runoff pollution challenging. Therefore, it is necessary to propose advanced modeling methods for these challenges. This research presents an integrated urban runoff pollution management (IURPM) model for optimal configuration of low impact development (LID) practices under multiple uncertainties. The IURPM model combines the hybrid land-use prediction and improved pollution estimation models with interval parameter, stochastic parameter, and multi-objective programming. The proposed IURPM model can not only predict the output characteristics, but also provide optimal configuration schemes for the LID practices in the management of urban runoff pollution under multiple scenarios. In addition, uncertainties expressed as discrete intervals and probability density function in the management systems can be effectively addressed. A case study of the IURPM model was conducted in Dongguan City, South China. Results show that considerable amounts of urban runoff pollutants would export from Dongguan City by 2025. The export loads and pollution output flux per unit area would have significant spatial heterogeneity. The results further indicate that population size, gross domestic product, and regional area size are expected to play important roles in the pollution export, while impervious surface coverage and population density would likely have great influences on the output flux of urban runoff pollution. Based on the model findings, multiple LID practices should be adopted in Dongguan City to reduce the urban runoff pollution loads. Using the IURPM model, multiple LID implementation schemes can be obtained under different pollution reduction scenarios and significance levels, that can provide decision-making support for urban water environmental management, considering variations in the policymaker's decision-making preferences. This study demonstrates that the IURPM model can be applied to the optimal configuration of LID practices for the management of urban runoff pollution under uncertainty.

Improving surface water quality of the Yellow River Basin due to anthropogenic changes.

Understanding of how changes in diverse human activities and climate contribute to water quality dynamics is crucial for sustainable water environment management especially in the arid and semi-arid regions. This study conducted a comprehensive estimation of the surface water quality change in the Yellow River basin during 2003-2017 and its responses to varied pollution sources and water volumes under socioeconomic and environmental influences. Basin-wide measurements of chemical oxygen demand (COD), ammonium nitrogen (NH+4-N) and dissolved oxygen (DO) concentrations were used in trend detection. Annual anthropogenic (covering six sectors) and natural (sediment-induced, flow-in from the upstream and stored last year) pollution sources and water components (inflow, natural runoff, water consumption, reservoir storage and evaporation) were compiled for each sub-basin. Bottom-up hierarchical analysis was then performed to differentiate individual contributions. Results showed significant decreasing trends in COD and NH+4-N concentrations and increasing trends in DO concentrations. The middle reaches that traverse the Loess Plateau however remained severely polluted with 11.3-39.0% inferior to level III in 2017. The pollutant load played major positive contributions that gradually increased from upper to lower reaches. Declines in urban, rural and industrial pollution discharges following environmental investments and rural depopulation contributed the most: 78-96% for COD and 55-100% for NH+4-N. The total surface water volume had dilution effects in the upper and middle reaches (3-28%) and condensing effects in the lower reaches (2-37%). Precipitation and vegetation dynamics contributed slightly. The primary unfavorable factors were the growing agricultural pollution discharges and water consumption in the upper and middle reaches that also threatened the lower reaches. This study is expected to provide in-depth insights for the systematic response of regional water quality to combined human interventions and references for water quality management in other arid and semi-arid river basins worldwide.

Impact of local environmental standards on water environmental carrying capacity in large water diversion project: A system dynamics analysis in Shandong, China

Large water diversion projects have extensive impact on the water systems in the receiving areas, where inevitable regional responses are aroused and alert to local environmental carrying capacity. To ensure the water quality of China's eastern South-to-North Water Diversion Project (SNWDP), Shandong Province had issued strict local wastewater discharge standards since 2006. However, some flexibility exists in the enforcement of local standards, which created uncertainty to the outcomes. A system dynamic (SD) model and Water Environmental Carrying Capacity (WECC) method were integrated to dynamically illustrate the interaction between the enforcement of the local standards and the performance of the regional water system. The WECC was calculated based on an indicator system representing the multi-dimensional impact of the local standards on the regional water system. The SD model was constructed to simulate and forecast the variations of those indicators of WECC. The SD-WECC model was trained and validated with yearly data from 2000 to 2020, then four scenarios with different levels of enforcement of local standards were illustrated. The results showed that overall WECC improves during period from 2000 to 2025, and that the SNWDP improves the balance of water supply and demand in Shandong in the long run in the three scenarios that have introduced the local standards. The adoption of the local standard helps the concentration of industrial Chemical Oxygen Demand (COD) discharge to meet the discharging standards earlier by stimulating the investment in pollution control. Therefore, the flexibility in local water environment management enabled the local actors to pursue a balance between environmental protection and economic growth in a dynamic context with multi-objects for local development.