Evaluating the impact of interbasin water transfer on water quality in the recipient river basin with SWAT

Pathways and risk analysis of arsenic and heavy metal pollution in riverine water: Application of multivariate statistics and USEPA-recommended risk assessment models

This study analyzed surface water from the River Swat, Pakistan, using inductively coupled plasma mass spectrometry, multivariate statistical techniques, and US-EPA risk assessment models to evaluate the concentrations, distribution, pathways, and potential risks of arsenic (As) and heavy metals, including chromium (Cr), manganese (Mn), cobalt (Co), nickel (Ni), copper (Cu), zinc (Zn), cadmium (Cd), mercury (Hg), and lead (Pb). The results revealed significant correlations (p ≤ 0.01) among metals that indicated common pollution sources, likely influenced by anthropogenic point and non-point activities. Along the monitored sites (S1-S10), the mass flow of ∑metals showed a dynamic pattern: progressively increasing downstream, decreasing at S6-S7, rising again at S7-S8, and then steadily declining toward S10, with Ni being the most abundant metal, followed by Cr > As> Cu > Mn > Co > Zn > Hg > Cd > Pb. The As and Heavy Metal Pollution Index (HPI), As and Heavy Metal Evaluation Index (HEI), and Pollution Index (PI) revealed variations in pollution levels, ranking the metals in the orders of Co > As> Cr > Cd > Mn > Hg > Ni > Pb > Cu > Zn, As> Cr > Ni > Hg > Cd > Co > Mn > Cu > Zn > Pb, and Hg > Ni > As> Co > Cu > Cd > Mn > Zn > Pb, respectively. However, according to the risk assessment, overall individual metal contamination in the River Swat water was below the ecological risk threshold (ERI 〈110). Where, the Chronic Daily Intakes (CDIs), Hazard Quotients (HQs), Hazard Indices (HIs), Cancer Risks (CRs), and Total Cancer Risks (TCRs) of Cr, Mn, Co, Ni, Cu, Zn, As, Cd, Hg, and Pb associated with daily river water intake and dermal contact indicate that long-term exposure to untreated river water may pose both carcinogenic and non-carcinogenic health risks to residents.

Long-term study of phytoplankton dynamics in a supply reservoir reveals signs of trophic state shift linked to changes in hydrodynamics associated with flow management and extreme events

This study analyses over a decade (2009-2022) of monitoring data to understand the impact of hydrological characteristics on water quality and phytoplankton dynamics in Prospect Reservoir, a critical water supply for Greater Sydney, Australia, known for its excellent water quality. Water quality and phytoplankton dynamics were related to hydrodynamics, linked to flow management and the water quality of inflows. Phytoplankton biovolume increased after a prolonged drawdown and subsequent refill event, mainly driven by dinoflagellates, and corresponded to increases in total phosphorus and water temperature. The hydrological period following the 2019/2020 summer bushfires (post-bushfire) that impacted connected reservoirs, was marked by increased flow activity and nutrient loading, leading to significant shifts in the phytoplankton community. Functional group classification and ordination analysis indicated a transition from taxa typically dominant in oligotrophic conditions to meso‑eutrophic. This transition correlated with elevated nutrient levels and chlorophyll-a (Chl-a), and reduced Secchi depth and dissolved oxygen, providing evidence of eutrophication. Q index indicated good water quality post-bushfire, contrasting with a eutrophic status assessment using Chl-a. Our findings highlight the importance of analysing long-term datasets encompassing varied hydroclimatological conditions for a deeper understanding of reservoir behaviour. A comprehensive approach to water quality assessment is recommended, combining functional group classification, Q index and Chl-a measurements for effective reservoir health assessment. This research provides novel insights into the effects of disturbances such as bushfires, on water quality and phytoplankton dynamics in an underrepresented geographic region, offering valuable knowledge for managing water resources amidst growing climate variability.

A water quality prediction model based on signal decomposition and ensemble deep learning techniques

Accurate water quality predictions are critical for water resource protection, and dissolved oxygen (DO) reflects overall river water quality and ecosystem health. This study proposes a hybrid model based on the fusion of signal decomposition and deep learning for predicting river water quality. Initially, complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) is employed to split the internal series of DO into numerous internal mode functions (IMFs). Subsequently, we employed multi-scale fuzzy entropy (MFE) to compute the entropy values for each IMF component. Time-varying filtered empirical mode decomposition (TVFEMD) is used to further extract features in high-frequency subsequences after linearly aggregating the high-frequency sequences. Finally, support vector machine (SVM) and long short-term memory (LSTM) neural networks are used to predict low- and high-frequency subsequences. Moreover, by comparing it with single models, models based on 'single layer decomposition-prediction-ensemble' and combination models using different methods, the feasibility of the proposed model in predicting water quality data for the Xinlian section of Fuhe River and the Chucha section of Ganjiang River was verified. As a result, the combined prediction approach developed in this work has improved generalizability and prediction accuracy, and it may be used to forecast water quality in complicated waters.

Evaluating the impacts of inter-basin water transfer projects on ecosystem services in the Fenhe River Basin using the SWAT model

Inter-basin water transfer (IBWT) projects have been widely constructed to alleviate the pressure on water resources in water shortage basins. However, the ecological effects of IBWT projects have often been ignored. Based on the Soil and Water Assessment Tool (SWAT) model and a constructed total ecosystem services (TES) index, the impacts of IBWT projects on recipient basin ecosystem services were analyzed in this study. The results showed that the TES index was relatively stable from 2010 to 2020, but in the wet season it was 1.36 times that of the other months with high water yield and nutrient loads. Spatially, areas with high index values were mainly distributed in the sub-basins around the reservoirs. The IBWT projects had positive impacts on ecosystem services, and the TES index with IBWT projects was 5.98% higher than that without projects. Water yield and total nitrogen were the two most affected indexes, with increased of 5.65% and 5.41%, respectively, under the impacts of IBWT projects. Seasonally, the change rates of the TES index were less than 3% while the change rates of water yield and nitrogen load peaked at 8.23% and 53.42%, respectively, in March, owing to the large amount of water released from the reservoirs. Areas affected by the three evaluated IBWT projects accounted for 61%, 18%, and 11% of the watershed, respectively. Under the impact of each project, the TES index generally increased, whereas the impact decreased as the distance from the inflow location increased. Intense changes in ecosystem services occurred in sub-basin 23, the sub-basin closest to an IBWT project, with water yield, water flow, and local climate regulation increasing the largest.

Prediction of the migration and accumulation of pollution based on the use of a deicing agent

In this study, we simulated and predicted the accumulation of deicing agents in the soil and water system of the study area (a ski resort in Beijing, China) and discussed the environmental impact of deicing agents on the surrounding water system and soil under a standardized dosage. The widely used sodium chloride deicing agent was selected, and the standardized dosage of the deicing agent was estimated. Analysing the prediction results of the changes in chloride ion content in water systems and soils after the use of deicing agents from 2021 to 2029 leads to the conclusion that the use of deicing agents will increase the chloride ion content of the study area. It is predicted that chloride ion content in the water system and soil will increase year-by-year from 2021 to 2026, achieving a stable trend after 2027. It is concluded that the deicing agent has no obvious effect on the surrounding water body and soil under the standardized dosage. This research is intended to fill the gap in quantitative research on the environmental impact of deicing agents, to provide a reference and guidance for the engineering application of deicing agents, and to offer support for the improvement of deicing agent management measures.

Identifying trends and driving factors of spatio-temporal water quality variation in Guanting Reservoir Basin, North China

Assessment of river quality has been attracting a great deal of attention because of its important implications for the living environment of human beings and aquatic organisms. This study investigated the spatial and temporal variation of water quality and its possible driving factors of Guanting Reservoir Basin. For this purpose, water quality was assessed with the Canadian Council of Ministers of the Environment Water Quality Index, together with nutrient inputs and social-economic data which were collected and analyzed during the period 2009-2019. The results showed that the overall water quality in Guanting Reservoir increased over time and was rated as "good" during the studied decade. Spatially, water quality in tributary upstream of Yanghe River and Sanggan River was better than that in Guishui River, resulting in better quality in West Reservoir than in East Reservoir. Among water quality indices, total nitrogen was the main pollutant affecting the water quality of the studied area. In addition, principal component analysis and correlation analysis were applied to evaluate the relationships between the socio-economic factors and water quality variation. Urbanization and industry structure were significantly correlated with the water quality variation in upstream tributaries. The findings provide insightful understanding into the spatio-temporal variations of water quality and the associated driving factors of Guanting Reservoir basin, which would help managers in executing theoretical reference for water quality protection.

Study of water quality response to water transfer patterns in the receiving basin and surrogate model

The spatio-temporal response of water quality in the receiving basins to water transfer remains unclear when considering more practical factors. Moreover, a much fast surrogate model is highly required to realize the purpose of rapid prediction of water quality. In this study, a two-dimensional hydrodynamic and water quality model was primarily established by considering the most comprehensive important pollution sources so far to investigate the water quality variation in Baiyangdian Lake, China. The pollution sources include atmospheric deposition, sediment release, village and tourism domestic sewage, livestock breeding, rainfall runoff, aquatic plants, and animals. The water quality at different sample sites was assessed using the water quality index (WQI). Subsequently, a surrogate model was proposed using the nonlinear autoregressive network with exogenous inputs (NARX), and the NARX model can realize fast prediction of the annual time series of water quality in a few seconds. The results showed that there are significant differences in water quality at different sample sites in each season. The highest WQI value occurred in autumn (65.46), and the average values at different sample sites were between 47.54 and 58.22 in this season. The water quality at Nanliuzhuang site and Caiputai site was significantly affected by water transfer patterns. In addition, the correlation coefficient R² between the predicted results and the simulated ones except that of parameter TP was larger than 0.90. The prediction performance of surrogate model was shown to be very high efficiency and accurate. The proposed models and the results of this approach are guiding significance for lake management.

Improvement of simulating sub-daily hydrological impacts of rainwater harvesting for landscape irrigation with rain barrels/cisterns in the SWAT model

Rain barrels/cisterns, a popular type of low impact development (LID) practice, can restore urban hydrological processes and decrease municipal water use by harvesting roof runoff for later use, such as landscape irrigation. However, tools to assist decision makers in creating efficient rainwater harvesting and reuse strategies are limited. This study improved the Soil and Water Assessment Tool (SWAT) in simulating the subdaily hydrological impacts of rainwater harvesting for landscape irrigation with rain barrels/cisterns, including the simulation of rainwater harvesting with rain barrels/cisterns, rainwater reuse for auto landscape irrigation, evapotranspiration, initial abstraction, impervious area, soil profile, and lawn management operation. The improved SWAT was applied in the urbanized Brentwood watershed (Austin, TX) to evaluate its applicability and investigate the impacts of rainwater harvesting and reuse strategies on the reductions and reduction efficiencies (reductions per volume of rain barrels/cisterns implemented) of field scale runoff (peak and depth) and watershed scale streamflow (peak and volume) for two storm events. Scenarios explored included different sizes of rain barrels/cisterns, percentages of rooftop areas with rain barrels/cisterns implemented, auto landscape irrigation rates, and landscape irrigation starting times. The performance of rainwater harvesting and reuse strategies, which is determined by features of fields, watersheds, and storm events, varied for different reduction goals (streamflow or runoff, and peak or depth/volume). For instance, the scenario with rain barrel/cistern sizes of 7.5 mm (design runoff depth from treated roof area) and the scenario with 10% of suitable area implemented with rain barrels/cisterns provided the highest peak streamflow reduction efficiency and total streamflow volume reduction efficiency at the watershed scale, respectively for the smaller storm event. To achieve sustainable urban stormwater management, the improved SWAT model has enhanced capability to help stakeholders create efficient rainwater harvesting and reuse strategies to reduce field scale runoff and watershed scale streamflow.

Biomass Production Potential in a River under Climate Change Scenarios

Excessive production of biomass, in times of intensification of agriculture and climate change, is again becoming one of the biggest environmental issues. Identification of sources and effects of this phenomenon in a river catchment in the space-time continuum has been supported by advanced environmental modules combined on a digital platform (Macromodel DNS/SWAT). This tool enabled the simulation of nutrient loads and chlorophyll "a" for the Nielba River catchment (central-western Poland) for the biomass production potential (defined here as a TN:TP ratio) analysis. Major differences have been observed between sections of the Nielba River with low biomass production in the upper part, controlled by TN:TP ratios over 65, and high chlorophyll "a" concentrations in the lower part, affected by biomass transport for the flow-through lakes. Under the long and short-term RCP4.5 and RCP8.5 climate change scenarios, this pattern will be emphasized. The obtained results showed that unfavorable biomass production potential will be maintained in the upper riverine sections due to a further increase in phosphorus loads induced by precipitation growth. Precipitation alone will increase biomass production, while precipitation combined with temperature can even enhance this production in the existing hot spots.