Environmental Water Management Research Articles

A socio-hydrological model for assessing water resource allocation and water environmental regulations in the Maipo River basin

Overuse of water resources has led to serious ecological degradation in most river basins. However, there is little processed-based understanding of the dynamic feedback between management decisions from different sectors in river basins and their resultant socio-economic and ecological outcomes. This study developed a socio-hydrological model to track the evolution of water used for socio-economic and ecological uses and to simulate the response of water resource allocation and water environmental regulations to the resulting economic and ecological outcomes. It was applied in the Maipo River basin, Chile, from 1990 to 2019. The results show that this model successfully simulated water resources allocation and water environmental regulations over time. Water environmental regulations showed a strongly linear responsive behaviour to observed accumulated ecological degradation. Results also show that the observed decrease in water resource allocation for economic uses was influenced by increasing agricultural economic benefits and accumulated ecological degradation. It is suggested that environmental regulations should be stronger, synchronized and coordinated with water resources allocation decisions to revert the increasing ecological degradation. This socio-hydrological model, with revision into different contexts, could be used to assess integrated water resources and water environmental management in other river basins.

Current Status and Issues of Water Environment Management Policy

Current Status and Issues of Water Environment Management Policy

Comprehensive evaluation of water resources and environmental carrying capacity based on dualistic water cycle analysis and its application in the Tuo River Basin, China

Maintaining water quantity and quality are two problems that occur during water resource development. Considering the reciprocal relationship, the threshold of water resource development urgently needs to be evaluated to guarantee environmental water function. In this study, the water resources and environmental carrying capacity (WRECC) evaluation method was proposed based on dualistic water cycle analysis. Nine indicators from 4 aspects, including the water resource utilization proportion, water use efficiency, pollutant treatment efficiency, river flow, and mutual coupling in the dualistic water cycle processes, were selected to represent the comprehensive WRECC. The first-order tributary of the Yangtze River, the Tuo River Basin, was chosen to validate the method. During the year 2009 to 2018, the water environment quality was improving in the study area, and WRECC evaluation results were in accordance with the change in the water system, which showed a decreasing trend during the study periods. WRECC revealed that the upstream area had severer water pressure than the middle area, mainly coming from insufficient freshwater to support social development and provide dilution capacity. The study proposed a human water cycle intervention scenario by increasing the recycled water use rate and wastewater treatment rate to improve the WRECC, and the improvement effects can reach 30%. The WRECC method provides a useful tool for water environment management and water resource planning.

Analysis of flood control in Lambidaro sub-watershed using EPA SWMM

In the Lambidaro sub-watershed, precisely on Jalan Colonel Sulaiman Amin, the problem of flooding continues, especially when it rains. The occurrence of flooding around the canal along the Colonel Sulaiman Amin road drainage is caused by several factors, one of which is the capacity of the reservoir which is not able to control the flood discharge optimally so that water cannot overflow into the canal. and eventually caused flooding in the surrounding area. This study aims to determine whether the drainage capacity is still able to drain surface runoff water or not and determine alternative flood control solutions for Colonel Sulaiman Amin Street. The method used is the EPA Model SWMM (Environmental Protection Agency Storm Water Management Model). From this study, the simulation results obtained from EPA SWMM showed alternative solutions offered such as the use of flood pumps, retention ponds, and optimization of drainage, the most effective solution of the six flood mitigation experiments was channel optimization in the form of changing the shape and size of the channel 7 to a square channel with a width of 1 .5 meters. This alternative is 5.26% more effective with an effective percentage of 85.538% and can drain 36.36% more water flow than drainage with a widening of 1.1 meters.

Spatial-temporal characteristics of corrected total phosphorus pollution loads from agricultural non-point sources in Tuojiang River watershed, Sichuan Province of southwestern China.

Traditional method of estimating pollution loads may neglect the internal spatial heterogeneity of socio-economic driving factors, which can result in overestimate and underestimate of pollution loads. In this study, the corrected approach to estimating total phosphorus (TP) pollution load was proposed to explore its future variation to develop effective phosphorus pollution control strategies for water environment management. As the first-class tributary of the Yangtze River, the TP out of limits in the Tuojiang River is serious. Thus, based on the presently related basic datasets related to TP pollution load estimation, we firstly adopted the GM (1,1) model to predict their varied trends from 2021 to 2025. We then used the pollution emission coefficient method to calculate the TP pollution load. Moreover, considering the temporal and spatial heterogeneity of the pollutant generation coefficient, we further introduced population and GDP factors to further modify the pollutant generation coefficient to correct TP pollution load. Finally, we employed the exploratory spatial data analysis (ESDA) method to explore spatial distribution characteristics and spatial autocorrelation of TP pollution load from diverse pollution sources in 2025. The results showed that the total TP pollution load from diverse pollution sources will increase from 12,194.92 t in 2021 to 12,461.26 t in 2025, an increase of 2.18%. More concretely, the TP pollution load from rural domestic sewage, rural domestic waste and livestock, and poultry pollution sources will separately decrease by 94.24 t, 77.9 t, and 86.52 t. However, the TP pollution load from agricultural runoff and agricultural solid wastes pollution sources will increase by 74.52 t and 451.49 t, respectively. The contribution of TP pollution load from diverse pollution sources to total TP pollution load will be as follows: livestock and poultry (63.49%) > agricultural solid wastes (16.72%) > agricultural runoff (12.26%) > rural domestic sewage (4.12%) > rural domestic waste (3.41%). The difference in the spatial distribution of TP pollution load from diverse pollution sources in 2025 will be prominent. TP pollution from rural domestic sewage and rural domestic waste pollution sources is more serious in the Xindu and Longquanyi districts, and that from agricultural runoff and agricultural solid wastes pollution sources is more prominent in the midstream and downstream. TP pollution load from livestock and poultry pollution source is higher in the Renshou, Anyue, Rongxian, Luxian counties, and Jiangyang district. Additionally, TP pollution load from rural domestic sewage, rural domestic waste, agricultural runoff, and agricultural solid wastes pollution sources in 2025 will show a clear spatial correlation, but the spatial correlation of TP pollution load from livestock and poultry pollution source will be weak. The study is effective to eliminate the influence of temporal and spatial variation of pollutants generates coefficients on TP pollution load estimation. The method can reflect the actual condition of pollution loads in watersheds more objectively, which can be applied to estimate other pollution loads of similar watersheds with intensive socio-economic activities. The findings in this study can provide a critical reference for the stakeholders to balance water environment conservation and socio-economic development.

Microplastics contamination in the fishes of selected sites in Pasig River and Marikina River in the Philippines

Microplastics (MPs), <5 mm in size, are a concerning pollutant in bodies of water because they can be ingested by biological organisms, posing risks to humans and the environment. This study assessed the extent of MPs contamination in various fish species (Oreochromis niloticus, Arius manillensis, and Pterygoplichthys spp.) in selected sites along two major river systems in the Philippines – Pasig and Marikina Rivers. An optimized Raman microspectroscopy technique was used for imaging and identification of MPs using a mean laser spot size of about 1 μm, which is advantageous in the identification of fibers which have small diameters (<50 μm). It also allowed the simultaneous identification of MPs and their pigment additives, which in turn enabled the tracing of possible sources of these MPs. This is important because the fate and accumulation of MPs in rivers systems, as well as its toxicity is dependent on various factors including polymer type and surface chemistry. Majority of the MPs identified from all the fish species were composed of polypropylene and polyethylene in the form of fragments, which reflects both the widespread use of these polymers for packaging and their environmental fate as riverine plastic debris. Moreover, the detection of MPs in the fish species may affect the food chain and eventually pose health risks for humans. The study could provide guidance on waste and environmental water management in the surrounding region.

An integrated simulation–optimization framework for assessing environmental flows in rivers

The present study proposes an integrated simulation–optimization framework to assess environmental flow by mitigating environmental impacts on the surface and ground water resources. The model satisfies water demand using surface water resources (rivers) and ground water resources (wells). The outputs of the ecological simulation blocks of river ecosystem and the ground water level simulation were utilized in a multiobjective optimization model in which six objectives were considered in the optimization model including (1) minimizing losses of water supply (2) minimizing physical fish habitat losses simulated by fuzzy approach (3) minimizing spawning habitat losses (4) minimizing ground water level deterioration simulated by adaptive neuro fuzzy inference system(ANFIS) (5) maximizing macroinvertebrates population simulated by ANFIS (6) minimizing physical macrophytes habitat losses. Based on the results in the case study, ANFIS-based model is robust for simulating key factors such as water quality and macroinvertebrate’s population. The results demonstrate the reliability and robustness of the proposed method to balance environmental requirements and water supply. The optimization model increased the percentage of environmental flow in the drought years considerably. It supplies 69% of water demand in normal years, while the environmental impacts on the river ecosystem are minimized. The proposed model balances the portion of using surface water and ground water in water supply considering environmental impacts on both sources. Using the proposed method is recommendable for optimal environmental management of surface water and ground water in river basin scale.

A Multi-Objective Decision Model for Water Pollution Load Allocation under Uncertainty

In order to control the discharge of regional total pollutants in the region and improve the ability of water environment management and decision making, a multi-objective decision-making optimization model of water pollution load allocation was constructed, which took into account economy and fairness. The model takes the maximum environmental benefit and the minimum weighted comprehensive Gini coefficient as the objective function and takes into account the uncertainty and multi-objectives of the model, which is conducive to promoting economic development and ensuring the fairness of regional water pollutant discharge. A method based on Monte Carlo simulation coupled with a genetic algorithm was designed to obtain the optimal solution set through multiple simulation optimization. This model is applied to Anhui Province to solve the allocation optimization problem of total pollutant reduction in the 13th Five-Year Energy Conservation and Emission Reduction Plan. After the optimization of water pollution load distribution, the comprehensive Gini coefficients of COD and NH3-N are reduced by different ranges. The comprehensive Gini coefficient after COD optimization decreased by 2.4–4.6%, and the comprehensive Gini coefficient after NH3-N optimization decreased by 25.1–32.5%, which verified the feasibility and rationality of the model in the optimal allocation of the total discharge of regional water pollutants. The model takes into account uncertain subjective and objective factors that have an important impact on water pollutant discharge targets and decision variables, thus optimizing the total emissions of the entire regional control unit in both space and time.

Analysis on Residents’ Satisfaction and Its Influencing Factors with Water Environment Management: Based on the Data from Xiaoqing River

Xiaoqing River is one of the key rivers in the Yellow River Basin, and its management satisfaction is the content that the government should consider when formulating policies. This paper concentrates on residents’ satisfaction of water environment management in Jinan section of Xiaoqing River, using questionnaires to find out the problems and effects of Xiaoqing River management. Based on the correlation analysis of the questionnaire data, the results show that five factors including the impact of water pollution, understanding of Xiaoqing River governance, willingness to participate in Xiaoqing River governance, policy publicity, and government regulation have a positive impact on the satisfaction of Xiaoqing River water environment governance. Finally, the paper puts forward some countermeasures and suggestions to increase residents’ satisfaction from five aspects, such as increasing publicity efforts, paying attention to the cultivation of public participation consciousness, etc.

Application of Riverbank Integrated Super-Magnetic Separation in River Water Environment Management

Riverbank integrated super-magnetic separation (ISMS) played an important role in river water (RW) environment management when the diminishing of suspension is a major task. This paper provides a comprehensive analysis of its operation performance from the perspective of pollutant controlling and carbon mitigation potential using the method proposed by intergovernmental panel on climate change. The results showed that turbidity of discharge from ISMS is maintained below 3 NTU and total phosphate removal above 85%. From ISMS to sludge dewater and final incineration, the net carbon emission can is negative at -0.07 kgCO2/m3RW thanks to incineration with combined heat and power generation and cement substitute by slag. The indirect carbon emission associated with the use of PAC and PAM contributed 79% of the total emissions which amounted to 0.087 kgCO2/m3RW. Future work is suggested on accurate dosing adjustment for cost reduction and carbon mitigation.

Perceptions of climate change adaptation barriers in environmental water management

Climate change is irreversibly changing the water cycle, yet existing environmental flow assessment methods often fail to recognize the non-stationarity of hydro-climatic systems. Failure to do so will lead to the inability of environmental water management to achieve its ecological targets. Australia has undergone major reform over the past 12 years to recover water from consumptive use for environmental benefit and this paper examines how government agencies responsible for planning and delivery of environmental water establish ecological objectives, and whether there are any barriers to including climate adaptations. We used semi-structured interviews and an online survey of environmental water staff throughout Australia, focusing on southeast Australia, to gather information on methods and perceptions regarding these key issues. The results show water managers perceive current ecological objectives as unachievable and are frustrated by using outdated, government-recommended flow assessment methods. There are many general and industry-specific barriers to climate adaptation that are not insurmountable, yet the current lack of legislative and policy guidance provides little assistance on the best way to respond. We conclude that environmental water planning needs to more formally incorporate climate change considerations along with modelling approaches that can evaluate outcomes under a range of possible future hydro-climatic scenarios to ensure proactive decision making can occur. As the industry currently exists in Australia, it is ill prepared for the challenge of meeting legislated ecological targets under future climates.

Performance Evaluation of Urban Water Environment Management Projects for the Protection of the Yangtze River Based on AHP-Fuzzy Comprehensive Evaluation Method

In order to promote the urban water environment management work for the protection of the Yangtze River, it is necessary to use a scientific evaluation index system to evaluate the governance effectiveness of completed management projects in pilot cities. Based on the characteristics of urban water environment management projects, this paper uses a constructed evaluation index system for the effectiveness of urban water environment management projects in the protection of the Yangtze River to evaluate the effectiveness of Phase I urban water environment management projects in Jiujiang City. The weights of each criterion layer and indicator layer were determined using the Analytic Hierarchy Process, and the fuzzy comprehensive evaluation method was used for comprehensive evaluation. The conclusions are as follows: (1) the engineering efficiency evaluation result is poor, mainly affected by the urban rain and sewage pipe network engineering criterion layer, in which the weight of the BOD5 concentration of domestic sewage in the influent of the sewage treatment plant is relatively large, and the membership degree result is poor, so attention should be paid to the BOD5 concentration of the sewage treatment plant within the scope of the project. (2) the engineering benefit evaluation result is generally good, and this evaluation result can reflect the overall benefits of the Phase I urban water environment comprehensive management project to the "plant-network-river-lake-shore" within the scope of Jiujiang City, but it is only reflected significantly by the surface water improvement contribution criterion. The reflection of social and economic aspects is not obvious, and follow-up research needs to increase the participation of residents through questionnaires or field surveys to make the results more reflective of the economic and social benefits.

Research on Surface Water Quality Prediction based on a CNN-BiLSTM-Attention Combined Deep Learning Approach

The ability to predict the environmental conditions of surface water is crucial for prompting the refined management of surface water pollution in China. This paper carried out research on the prediction method of surface water quality based on deep learning algorithms and combined with the real-time data of national automatic monitoring of surface water quality. Under the encoder-decoder framework, the research proposed a CNN-BiLSTM-Attention water quality prediction model which contains CNN, bidirectional LSTM, and attention mechanism. To evaluate the performance of the proposed hybrid model, the research also compared the model with LSTM and CNN-LSTM models, carrying out a comparative analysis of the prediction results of each model through three performance metrics. The research results showed that compared with other models, the CNN-BiLSTM-Attention water quality prediction model can effectively take advantages of each neural network layer and has better prediction ability and higher stability for forecasting future water quality, which can provide strong technical support for water environment management and early warning.

The normative construction of the River Chief system model of river basin water environment management under legal perspective

The normative construction of the River Chief system model of river basin water environment management under legal perspective

Spatiotemporal Variation of Riverine Dissolved Organic Matter Degradation Based on EEMs-PARAFAC: A Case Study of Shili River in Jiujiang, Jiangxi Province, China, as a Typical Demonstration City of the Yangtze River protection Strategy

This study investigated the spatio-temporal distribution of dissolved organic matter (DOM) composition and its sources before and after degradation in the Shili River watershed in Jiujiang (China). Spatio-temporal variation of riverine DOM water samples before and after five days of degradation in a simulated channel was characterized by spectral feature analysis using three-dimensional excitation-emission matrix fluorescence spectroscopy coupled with parallel factor analysis. Across all water samples (#1,#2 and #3) before and after degradation, a total of four fluorescent components in DOM were identified: C1, C2, C3, and C4. The aromaticity index (SUVA254) was negatively correlated with the C2 and C3 components and biological index (BIX) and freshness index (β:α), but it had little correlation with the humification index (HIX). The greater the aromaticity of DOM in water, the lower the proportion of recently produced DOM and its biological activity. The C3 component had a strong positive correlation with BIX, β:α, and C2. The results suggested that C2 and C3 were derived from the same substances. According to the fluorescence parameters, DOM was dominated by autochthonous contributions. The fluorescence intensity of DOM increased gradually along the direction of water flow. The increase of water temperature in spring and autumn enhanced the endogenous level of DOM. The levels and fluctuations of BIX and β:α in different seasons and different sampling points were basically consistent. DOC concentration does not fully represent the localized nature of the DOM. The analysis of some fluorescence parameters and light absorption parameters showed that the DOM source was more internal than terrestrial. This study reveals the composition, source and temporal and spatial characteristics of DOM in the Shili River Basin, which has theoretical guiding significance for water environment management.

Remote Sensing for Water Resources and Environmental Management

In line with the United Nations Sustainable Development Goal (SDG) 6, the main goal of the Special Issue on “Remote sensing for water resources and environmental management” was to solicit papers from a diverse range of scientists around the world on the use of cutting-edge remote sensing technologies to assess and monitor freshwater quality, quantity, availability, and management to ensure water security. Special consideration was given to scientific manuscripts that covered, but were not limited to, the development of geospatial techniques and remote sensing applications for detecting, quantifying, and monitoring freshwater water resources, identifying potential threats to water resources and agriculture, as well as other themes related to water resources and environmental management at various spatial scales. The Special Issue attracted over thirteen peer-reviewed scientific articles, with the majority of manuscripts originating from China. Most of the studies made use of satellite datasets, ranging from coarse spatial resolution data, such as the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO), to medium spatial resolution data, such as the Landsat series, ERA5, Modern-Era Retrospective Analysis for Research and Application Land version 2 reanalysis product (MERRA2), CLSM and NOAH ET, and MODIS (Moderate Resolution Imaging Spectroradiometer). Google Earth Engine (GEE) data, together with big data processing techniques, such as the remote sensing-based energy balance model (ALEXI/DisALEXI approach) and the STARFM data fusion technique, were used for analyzing geospatial datasets. Overall, this Special Issue demonstrated significant knowledge gaps in various big data image processing techniques and improved computing processes in assessing and monitoring water resources and the environment at various spatial and temporal scales.

Estimation of the Key Water Quality Parameters in the Surface Water, Middle of Northeast China, Based on Gaussian Process Regression

To estimate the key water quality parameters on a large scale, based on Pearson’s correlation analysis and band ratio, this study first obtains multiple sensitive band combinations (R ≥ 0.30, p &lt; 0.01) for three key water quality parameters: dissolved oxygen (DO), total nitrogen (TN), and total phosphorus (TP). Then, principal component analysis is used to reduce the dimensions and analyze multiple optimal combinations, and the first three principal components (PCs) of the optimal combinations are selected to analyze the water quality parameters. Finally, the water quality parameter models of DO, TN, and TP are proposed and compared based on spectral analysis and field measured water quality data respectively using Gaussian process regression and PCs for each parameter. Through model verification and by comparing the performance of the three models, it is found that the TP model performed well (R = 0.9824, p &lt; 0.01), and TP grade accuracy rate is up to 94.97%. Through the error analysis of TN and DO, it is found that 93.0% of error samples occurs when TP &lt; 0.1 mg/L in the water quality. These results would provide a scientific basis for water quality monitoring and water environment management in the study area and could also be used as a reference for water quality monitoring in other basins.

Surface water quality assessment by Random Forest

Abstract The energetic nature of these important water resources makes them the most vulnerable to contamination from additional waste from multiple sources. Water quality monitoring is critical to water environmental management, and successful monitoring provides direction and confirms the effectiveness of water management. Models based on artificial intelligence are fundamental for anticipating appropriate moderation measures for surface water quality. In any case, it remains a challenge and requires a requirement to improve display accuracy. Faster and cheaper control is required due to the real-world impact of low water quality. With this inspiration, this research examines an array of machine-learning calculations to estimate water quality. The proposed approach uses Random Forest for modeling and is also useful for predicting surface water quality in the Kulik geographic region of West Bengal, India. It is a good tool for assessing the quality and ensuring the safe use of drinking water. Various water quality parameters (iron, fluoride, total coliform, fecal coliform, pH, total dissolved solids, magnesium, alkalinity, chloride, total hardness, nitrate, calcium, and Escherichia coli) were measured seasonally (winter, summer, rain) over 10 years (2010–2019). The estimated water quality parameters in this study were total dissolved solids (TDS), pH, and iron.

Performance Study and Assessment of Electrocatalytic Treatment of Substation Domestic Sewage

In China, the power grid construction process is accelerating. At the same time, the requirements for power grid water environment management are also constantly improving. There are a large number of substations and most of them are located in the countryside and surrounded by farmland. Therefore, it is important to treat the domestic sewage of the substation to meet the relevant standards. Recently, electrocatalysis technology has attracted much attention because of its high efficiency and no secondary pollution such as sludge. However, there are few reports on the application and performance evaluation of electrocatalytic treatment of domestic sewage in substations. Therefore, the experimental research aims to treat domestic sewage in substations reaching the corresponding standard. The optimal operating parameters and comprehensive performance assessment of the electrocatalysis technology are investigated, applying iridium-tantalum, ruthenium-iridium, boron-doped diamond anodes, titanium cathodes, and carbon fiber cathodes. The results show that the application of the three anodes can efficiently treat the sewage reaching the corresponding standard, indicating that electrocatalysis is suitable for the treatment of domestic sewage in substations. Moreover, comprehensively considering cost, treatment effect, energy consumption, and reaction temperature, the composite performance of iridium tantalum anode and Ti cathode is the best. In summary, this paper provides a comprehensive study and assessment of the performance of electrocatalytic treatment of domestic sewage in substations, providing theoretical support for the water environment management of power grids.

Zoning method of aquatic ecosystem functional management fourth-level region in the Daqing River Basin, China

Watershed management needs more information on ecological function and services in large regions. Spatial units are particularly important for the watershed management. Zoning of aquatic ecosystem functional management region refers to the zoning of terrestrial ecosystems as per the characteristics of aquatic ecosystems, providing an ecological background and basic spatial units for water environment management in basins. Although basin water environment management based on aquatic ecosystem functional management region and control unit is highly effective in practice, the current need for refined management of water environments cannot be met by existing zoning schemes of aquatic ecosystem functional management regions and control units. In response to the need to protect basin water environments, which is raised in the 14th Five-Year plan, a zoning method of aquatic ecosystem functional management fourth-level region for basins is proposed in this study. It features an effective integration of aquatic ecosystem functional management regions and control units and township-level administrative divisions, thus contributing to the implementation of a basin water environment management system that fulfils the zoning, grading, classification and period goals of aquatic ecosystem functional management. In this way, it can satisfy the business application of administrative management and refined management of water environments, which features coupling terrestrial and aquatic ecosystems and unification of water resources, water environments and aquatic ecology. The feasibility and effectiveness of the proposed zoning method were verified by using the Daqing River Basin, Beijing–Tianjin–Hebei region, China, as a case study. The results were accepted by the Ministry of Ecology and Environment and the Haihe River Water Conservancy Commission of the Ministry of Water Resources, which can provide scientific rationale and technical support for the accurate and differentiated watershed water environments management and ecological restoration of coastal wetlands in the Haihe River Basin based on aquatic ecosystem functional management fourth-level region with clear responsibility for the local government during the period of the 14th Five-Year plan.