Precipitation, landscape properties and land use interactively affect water quality of tropical freshwaters

Rainfall impacts on nonpoint nitrogen and phosphorus dynamics in an agricultural river in subtropical montane reservoir region of southeast China

The increased frequency and intensity of heavy rainfall events due to climate change could potentially influence the movement of nutrients from land-based regions into recipient rivers. However, little information is available on how the rainfall affect nutrient dynamics in subtropical montane rivers with complex land use. This study conducted high-frequency monitoring to study the effects of rainfall on nutrients dynamics in an agricultural river draining to Lake Qiandaohu, a montane reservoir of southeast China. The results showed that riverine total nitrogen (TN) and total phosphorus (TP) concentrations increased continuously with increasing rainfall intensity, while TN:TP decreased. The heavy rainfall and rainstorm drove more than 30% of the annual N and P loading in only 5.20% of the total rainfall period, indicating that increased storm runoff is likely to exacerbate eutrophication in montane reservoirs. NO3--N is the primary nitrogen form lost, while particulate phosphorus (PP) dominated phosphorus loss. The main source of N is cropland, and the main source of P is residential area. Spatially, forested watersheds have better drainage quality, while it is still a potential source of nonpoint pollution during rainfall events. TN and TP concentrations were significantly higher at sites dominated by cropland and residential area, indicating their substantial contributions to deteriorating river water quality. Temporally, TN and TP concentrations reached high values in May-August when rainfall was most intense, while they were lower in autumn and winter than that in spring and summer under the same rainfall intensities. The results emphasize the influence of rainfall-runoff and land use on dynamics of riverine N and P loads, providing guidance for nutrient load reduction planning for Lake Qiandaohu.

Impact of Landscape Patterns on Water Quality in Urbanized Rivers at Characteristic Scale: A Case of Pearl River Delta, China

The impacts of landscape patterns on river water quality are commonly acknowledged, but understanding the complex processes by which landscape patterns affect water quality is still limited, especially in densely populated urban areas. Exploring the mechanisms through which landscape characteristics influence water quality changes in urbanized rivers will benefit regional water resource protection and landscape-scale resource development and utilization. Utilizing daily water quality monitoring data from rivers in the urbanized area of the Pearl River Delta in 2020, our research employed canonical analysis and partial least squares structural equation modeling (PLS-SEM) to explore the processes and mechanisms of the influence of urbanized river landscape patterns on surface water quality. The results indicated that total nitrogen (TN) was the critical indicator limiting the water quality of rivers in the Pearl River Delta. The landscape composition and configuration indexes exhibited non-linear variations with scale, and the landscape fragmentation was higher closer to the river. Landscape patterns had the most significant influence on water quality under the characteristic scale of a 5.50 km circular buffer zone, and landscape composition dominated the change of water quality of urbanized rivers, among which 30.64% of the percentage patch area of construction (C_PLAND) contributed 46.40% to the explanation rate of water quality change, which was the key landscape index affecting water quality. Moreover, landscape patterns had a higher interpretive rate of 39.29% on water quality in the wet season compared to 36.62% in the dry season. Landscape composition had an indirect negative impact on water quality, with a value of 0.47, by affecting the processes of runoff and nutrient migration driven by human activities, while landscape configuration had an indirect negative impact on water quality, with a value of 0.11. Our research quantified the impacts of landscape patterns driven by human activities on surface water quality and proposed management measures to optimize the allocation of landscape resources in riparian zones of urbanized rivers. The results provide a scientific basis for water quality management and protection in urbanized rivers.

Modelling relationships between land use and water quality using statistical methods: A critical and applied review

Land use/land cover (LULC) can have significant impacts on water quality and the health of aquatic ecosystems. Consequently, understanding and quantifying the nature of these impacts is essential for the development of effective catchment management strategies. This article provides a critical review of the literature in which the use of statistical methods to model the impacts of LULC on water quality is demonstrated. A survey of these publications, which included hundreds of original research and review articles, revealed several common themes and findings. However, there are also several persistent knowledge gaps, areas of methodological uncertainty, and questions of application that require further study and clarification. These relate primarily to appropriate analytical scales, the significance of landscape configuration, the estimation and application of thresholds, as well as the potentially confounding influence of extraneous variables. Moreover, geographical bias in the published literature means that there is a need for further research in ecologically and climatically disparate regions, including in less developed countries of the Global South. The focus of this article is not to provide a technical review of statistical techniques themselves, but to examine important practical and methodological considerations in their application in modelling the impacts of LULC on water quality.

Simulating the land use change effects on non-point source pollution in the Duliujian River Basin

The uncertainty in the generation and formation of non-point source pollution makes it challenging to monitor and control this type of pollution. The SWAT model is frequently used to simulate non-point source pollution in watersheds and is mainly applied to natural watersheds that are less affected by human activities. This study focuses on the Duliujian River Basin (Xiqing section), which is characterized by a dense population and rapid urbanization. Based on the calibrated SWAT model, this study analyzed the effects of land use change on non-point source pollution both temporally and spatially. It was found that nitrogen and phosphorus non-point source pollution load losses were closely related to land use type, with agricultural land and high-density urban land (including rural settlements) being the main contributors to riverine nitrogen and phosphorus pollution. This indicates the necessity of analyzing the impact of land use changes on non-point source pollution loads by identifying critical source areas and altering the land use types that contribute heavily to pollution in these areas. The simulation results of land use type changes in these critical source areas showed that the reduction effect on non-point source pollution load is in the order of forest land > grassland > low-density residential area. To effectively curb surface source pollution in the study area, strategies such as modifying urban land use types, increasing vegetation cover and ground infiltration rate, and strictly controlling the discharge of domestic waste and sewage from urban areas can be implemented.

Evolutionary patterns and influencing factors of relationships among ecosystem services in the hilly red soil region of Southern China

As a crucial ecological protection area in China, the Southern hilly red soil region is characterized by uneven spatial and temporal distribution of ecological landscape elements, unpredictable and changeable interrelationships between them, diversified driving factors, and lack of comprehensive consideration of ecosystem services. In order to better understand the interaction between ecosystem services, restore regional ecology, and promote sustainable development, the evolution law and influencing mechanism of ecosystem services and their driving factors are quantitatively analyzed in the study. Based on simulations of different ecosystem services from 2000 to 2020, their spatial and temporal changes and the contributions of main drivers are quantified, their trade-offs and synergies are analyzed, and the changing rules under the influence of natural factors and socioeconomic factors are explored. The results show that (1) the crop production significantly increases in the southwest and north regions, the habitat quality decreases in urban and coastal areas, and the soil retention and water yield show an increasing trend from west to east. (2) Land use/cover is the main driver of carbon storage and habitat quality variation, and precipitation is an important driver of water yield spatial variation. (3) The crop production and the other four ecosystem services show a trade-offs relationship, and the relationship between supporting services and regulating services is the synergetic. (4) The altitude weakens the synergistic relationship between soil retention and habitat quality/carbon storage, while it enhances the synergistic relationship between soil retention and water yield. Driven by precipitation factors, ecosystem services related to water yield have significant differences in the change. The population density enhances the trade-offs of crop production and soil retention, as well as the synergistic relationship between soil retention and habitat quality/carbon storage. In different land use/cover (LULC), the influence of urban land on ecosystem services relationship change is more obvious. Overall, this study can provide scientific bases and policy suggestions for ecosystem protection/restoration in the red soil region of Southern China, which has an important theoretical and practical significance.

Influence of land use on spatial distribution of mobile phosphorus forms in the sediment of a tropical semi-arid reservoir

Changes in land use and land cover influence the transport of nutrients, mainly phosphorus (P), to aquatic ecosystems. P can be available in the water column to primary producers' assimilation or be stored in different forms in limnic sediment. Therefore, this study aims to analyze the impact of land use and land cover on the spatial distribution of phosphorus forms in the sediment of a tropical semi-arid reservoir. We hypothesize that agriculture, exposed soil and the presence of floodable vegetation increase the amount of mobile phosphorus in the sediment and the sediment closer to the dam show a greater amount of mobile phosphorus due to the confluence of the flows. The classification of land use and land cover was carried out through supervised analysis at the level of the reservoir's drainage basin and area of influence. Sediment samples from the reservoir were collected at four different sampling points within the influence of two sub-basins. P forms were obtained through chemical fractionation of these sediment samples along the reservoir. Sparse Caatinga was the predominant land cover in the drainage basin and in the influence area, accounting for >50 % of these areas. This land cover represents a risk for nutrient transport to aquatic environments. The sediment samples from Boqueirão reservoir exhibited a high amount of phosphorus, mainly in the mobile forms. These forms were heterogeneously distributed throughout the reservoir. Agriculture activities, exposed soil, and floodable vegetation, influence the distribution and increase of mobile forms of phosphorus in the reservoir sediment. This suggests the need for specific strategies for manage these activities properly. Additionally, the sediment closest to the dam showed a lower amount of mobile phosphorus compared to samples further upstream.

Effects of environmental factors on the river water quality on the Tibetan Plateau: a case study of the Xoirong River, China

Climate, topography, and landscape patterns affect river water quality through processes that influence non-point source pollution. However, little is known about the response of the water quality of rivers on China's Tibetan Plateau to these environmental factors. Based on the water quality parameters data of the Xoirong River on the Tibetan Plateau in western China, the redundancy analysis and variation partitioning analysis were adopted to determine the main influencing factors affecting river water quality and their spatial scale effects. The major water pollutants were further analyzed using the partial least square-structural equation modeling (PLS-SEM). Another mountainous river with a similar latitude, the same stream order, and low anthropogenic disturbance in central China, the Jinshui River, was also selected for comparative discussion. The results indicated that the overall river water quality on the Tibetan Plateau was superior to that of the Jinshui River. At the catchment scale, the cumulative explanatory powers of the influencing factors of both rivers were greatest. Landscape composition and configuration were the determinant factors for the overall water quality of the two rivers, while the river on the Tibetan Plateau was also significantly affected by climatic and topographical factors. Regarding the main water quality issue, i.e., total nitrogen, agricultural production activities might be the main cause of the river on the Tibetan Plateau. This study unveiled that the river water quality on the Tibetan Plateau is sensitive to climate and topography through comparative studies.

Effects of comprehensive landscape patterns on water quality and identification of key metrics thresholds causing its abrupt changes

Comprehensive landscape patterns influence water quality with multiple factors, complex processes, and scale dependence. However, studies identifying landscape thresholds causing abrupt water quality changes and characterizing the contribution of topography to water quality are still limited. Exploring the impact mechanisms of natural geographical and landscape characteristics on spatial and seasonal water quality variations is conducive to watershed water resource protection and ecosystem restoration. Based on water quality monitoring data of Minjiahe River in the typical headwater area of the upstream Dan River in China from 2019 to 2021, we employed redundancy analysis, partial redundancy analysis, and nonparametric change-point analysis to analyze the relationship between stream water quality and multi-spatial scale comprehensive landscape patterns, to obtain the interactive and independent contributions of different landscape categories at multi-spatial scales on water quality, and to find the key landscape threshold leading to abrupt changes in water quality. Results showed that landscape configuration, landscape composition, and topographic factors collectively explain over 89.1% of water quality variation. Most seasonal variations in water quality were primarily caused by landscape configuration. The landscape composition was mainly responsible for the differences in water quality variations among spatial scales. The topographic factors made the least independent contribution and had a potential impact on overall water quality variation. In order to protect the water quality of streams, it is more reasonable to regulate the landscape at different scales. At the sub-catchment scale, interspersion and juxtaposition index (IJI) and landscape shape index (LSI) should be controlled below 82% and 22. At the 100 m riparian scale, farmland, urban land, IJI, and LSI should be controlled below 29%, 6.5%, 92%, and 26, respectively. Our results provide important guidance for optimizing landscape patterns and water conservation in the watershed.

Output characteristics and driving factors of non-point source nitrogen (N) and phosphorus (P) in the Three Gorges reservoir area (TGRA) based on migration process: 1995-2020

Although physical models at present have made important achievements in the assessment of non-point source pollution (NPSP), the requirement for large volumes of data and their accuracy limit their application. Therefore, constructing a scientific evaluation model of NPS nitrogen (N) and phosphorus (P) output is of great significance for the identification of N and P sources as well as pollution prevention and control in the basin. We considered runoff, leaching and landscape interception conditions, and constructed an input-migration-output (IMO) model based on the classic export coefficient model (ECM), and identified the main driving factors of NPSP using geographical detector (GD) in Three Gorges Reservoir area (TGRA). The results showed that, compared with the traditional export coefficient model, the prediction accuracy of the improved model for total nitrogen (TN) and total phosphorus (TP) increased by 15.46 % and 20.17 % respectively, and the error rates with the measured data were 9.43 % and 10.62 %. It was found that the total input volume of TN in the TGRA had declined from 58.16 × 10⁴ t to 48.37 × 10⁴ t, while the TP input volume increased from 2.76 × 10⁴ t to 4.11 × 10⁴ t, and then decreased to 4.01 × 10⁴ t. In addition Pengxi River, Huangjin River and the northern part of Qi River were high value areas of NPSP input and output, but the range of high value areas of migration factors has narrowed. Pig breeding, rural population and dry land area were the main driving factors of N and P export. The IMO model can effectively improve prediction accuracy, and has significant implications for the prevention and control of NPSP.

Determination of the ecological water quality in the Orienco stream using benthic macroinvertebrates in the Northern Ecuadorian Amazon

In recent years, pollution of watercourses in nearby protected ecosystems has increased due to urbanization. Standard physiochemical methods and probes are one way to monitor watercourses for quality. However, they often do not provide the full ecological status of the body of water. In this work, we set out to assess the ecological water quality of an urban stream by using benthic macroinvertebrates as bioindicators. We conducted the work on the Orienco stream in Lago Agrio in the province of Sucumbíos in the Northern Ecuadorian Amazon (NEA). The stream has become a sink of raw domestic sanitary wastewater from rural and urban areas. A total of 4511 macroinvertebrates from 10 families were identified across 17 sampling points. We compared our results from the biotic indices derived from the macroinvertebrates to standard water-quality parameters (temperature, conductivity, dissolved oxygen, biochemical oxygen demand, chemical oxygen demand, total suspended solids, ammonia-nitrogen, and pH) simultaneously sampled in the stream. The standard parameter results indicated that the water-quality levels of the stream met the Ecuadorian water-quality criteria most of the time. However, the results from the biotic indices classified the stream water as poor or very poor water quality. The results from the Biological Monitoring Working Party, Average Score per Taxon, and Family Biotic Indices had overall scores of heavily polluted waters of 45, 4.5, and 8.74, respectively. Furthermore, these results were consistent with reduced richness and evenness, and overall lower Shannon diversity and relatively higher Simpson Dominance indices of 0.71 and 2.56, respectively. We conclude that the macroinvertebrates were better indicators of the ecological water quality of the Orienco stream than the water-quality parameters from standard methods and probes alone. Our findings highlight the need for more integrated ecological assessments, which can provide critical information to the management and conservation strategies of urban watercourses in the NEA region. Integr Environ Assess Manag 2023;19:615-625. © 2022 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Plant Traits Guide Species Selection in Vegetation Restoration for Soil and Water Conservation

Great efforts have been made to improve the soil and water conservation capacity by restoring plant communities in different climatic and land-use types. However, how to select suitable species from local species pools that not only adapt to different site environments, but also achieve certain soil and water conservation capacities is a great challenge in vegetation restoration for practitioners and scientists. So far, little attention has been paid to plant functional response and effect traits related to environment resource and ecosystem functions. In this study, together with soil properties and ecohydrological functions, we measured the seven plant functional traits for the most common species in different restoration communities in a subtropical mountain ecosystem. Multivariate optimization analyses were performed to identify the functional effect types and functional response types based on specific plant traits. We found that the community-weighted means of traits differed significantly among the four community types, and the plant functional traits were strongly linked with soil physicochemical properties and ecohydrological functions. Based on three optimal effect traits (specific leaf area, leaf size, and specific root length) and two response traits (specific leaf area and leaf nitrogen concentration), seven functional effect types in relation to the soil and water conservation capacity (interception of canopy and stemflow, maximum water-holding capacity of litter, maximum water-holding capacity of soil, soil surface runoff, and soil erosion) and two plant functional response types to soil physicochemical properties were identified. The redundancy analysis showed that the sum of all canonical eigenvalues only accounted for 21.6% of the variation in functional response types, which suggests that community effects on soil and water conservation cannot explain the overall structure of community responses related to soil resources. The eight overlapping species between the plant functional response types and functional effect types were ultimately selected as the key species for vegetation restoration. Based on the above results, we offer an ecological basis for choosing the appropriate species based on functional traits, which may be very helpful for practitioners involved in ecological restoration and management.

Functional threshold responses of benthic macroinvertebrates to environmental stressors in reservoirs

Reservoirs are aquatic ecosystems created by humans to supply water needs. They can impair aquatic diversity due to the lack of connectivity, reduced water volume, and pressures exerted by surrounding human activities. These changes are expected to produce abrupt fluctuations in the reservoirs' environment, thus influencing the structure and functioning of aquatic communities. Therefore, this study aimed to understand the impact of a range of environmental stressors in reservoirs on benthic macroinvertebrates by analyzing their functional threshold response. Biological data were collected in six reservoirs from the semi-arid region of Northeast Brazil, as case study. A total of 37.874 benthic macroinvertebrates belonging to 35 taxa were collected. Nevertheless, almost 90% of this abundance belonged to three species alone, considered generalists, with multivoltine reproduction and from the gatherer-collectors feeding group. Increases in environmental stressors such as salinity, nitrate, ammonia, and dissolved solids led to the selection of macroinvertebrates with specific traits (e.g., protected body, gill respiration, and large body size). These functional traits showed differences in their threshold response depending on the stressors and are indicators of the effects of these stressors on the reservoirs. Some of the potential sensitive traits (with a negative threshold response to the stressor) could also associate with other stressors, demonstrating that tolerance of benthic macroinvertebrates is defined by a set of functional characteristics. Overall, the increase in stressor' gradients selected functionally tolerant organisms with high resistance capacity, but these were represented by dominant species. This resulted in low diversity in the reservoirs, which may compromise ecosystem functioning, and raises concerns about adequate management of the systems.

Predicting water quality from geospatial lake, catchment, and buffer zone characteristics in temperate lowland lakes

Lakes provide essential ecosystem services and strongly influence landscape nutrient and carbon cycling. Therefore, monitoring water quality is essential for the management of element transport, biodiversity, and public goods in lakes. We investigated the ability of machine learning models to predict eight important water quality variables (alkalinity, pH, total phosphorus, total nitrogen, chlorophyll a, Secchi depth, color, and pCO₂) using monitoring data from 924 to 1054 lakes. The geospatial predictor variables comprise a wide range of potential drivers at the lake, buffer zone, and catchment level. We compared the performance of nine predictive models of varying complexity for each of the eight water quality variables. The best models (Random Forest and Support Vector Machine in six and two cases, respectively) generally performed well on the test set (R² = 0.28-0.60). Models were then used to predict water quality for all 180,377 mapped Danish lakes. Additionally, we trained models to predict each water quality variable by using the predictions we had generated for the remaining seven variables. This improved model performance (R² = 0.45-0.78). Overall, the uncovered relationships were in line with the findings of previous studies, e.g., total nitrogen was positively related to catchment agriculture and chlorophyll a, Secchi depth, and alkalinity were influenced by soil type and landscape history. Remarkably, buffer zone geomorphology (curvature, ruggedness, and elevation) had a strong influence on nutrients, chlorophyll a, and Secchi depth, e.g., curvature was positively related to nutrients and chlorophyll a and negatively to Secchi depth. Lake area was a strong predictor of multiple variables, especially its relationship with pH (positive), pCO₂ (negative), and color (negative). Our analysis shows that the combination of machine learning methods and geospatial data can be used to predict lake water quality and improve national upscaling of predictions related to nutrient and carbon cycling.

Understanding the relative roles of local environmental, geo-climatic and spatial factors for taxonomic, functional and phylogenetic β-diversity of stream fishes in a large basin, Northeast China

The primary objective of this study was to determine the relative roles of local environmental (Local), geo-climatic (Geo), and spatial (Spatial) factors to taxonomic, functional, and phylogenetic β-diversity of stream fish in a large basin in Northeast China. We quantified the current biodiversity patterns of fish communities in the Hun-Tai River using β-diversity. We assessed (i) corresponding contributions of turnover and nestedness within the taxonomic, functional, and phylogenetic β-diversity of fishes; (ii) correlations among β-diversity facets (i.e., taxonomic, functional, and phylogenetic facets); (iii) relative contributions of Local, Geo, and Spatial factors to β-diversity. We collected fish communities from 171 sampling sites. Mantel tests were used to examine the correlation of three facets of β-diversity and their components (i.e., total, nestedness, and turnover). Distance-based redundancy analysis and variation partitioning assess the relative contributions of Local, Geo, and Spatial factors to β-diversity. We found that turnover is the main driving mechanism for β-diversity in fish. Among the facets of β-diversity, taxonomic and phylogenetic facets have strong ecological information association. Spatial factors have a general contribution to various facets of β-diversity and its components. From aspects of fish β-diversity conservation, connectivity and habitat heterogeneity need to be maintained in the entire aquatic environment. In addition, protecting taxonomic β-diversity is helpful for maintaining phylogenetic β-diversity.

Estimating the pollutant loss rate based on the concentration process and landscape unit interactions: a case study of the Dianchi Lake Basin, Yunnan Province, China

The landscape analysis model establishes a quantitative relationship between landscape patterns and pollution processes. The spatial heterogeneity within and between landscapes affects the pollutant transmission process and originates from the superposition effect of terrestrial geographical and morphological characteristics. This study aimed to develop a new method to estimate the pollutant loss rate. From the perspective of the flow process of pollutants entering a water body, the interaction between each landscape unit and adjacent unit during pollutant migration was simulated along the pollutant migration flow path. The role of pollutants affected by external forces in the process of migration could be divided into "promoting" and "hindering." Four indices were proposed to simulate the pollutant loads entering the lake. The linear coefficients between the load of the pollutants chemical oxygen demand (COD_Cr), ammoniacal nitrogen (NH₃-N), total nitrogen (TN), and total phosphorus (TP) entering the lake and the pollutant load emission weighted by the upstream and downstream confluence ratio index were 0.930, 0.835, 0.925, and 0.795, respectively, and the non-linear variance explanation coefficients were 87.70%, 87.50%, 87.60%, and 84.70%, respectively. When the surface resistance was integrated into the index as a parameter, the linear and nonlinear correlation coefficients were significantly improved. The linear coefficients were 0.952, 0.897, 0.919, and 0.939, respectively, and the non-linear variance explanations were 99.00%, 97.30%, 95.10%, and 97.30%, respectively. The spatial distribution of landscape surface resistance reflects the spatial movement trend of pollutants from different sources. The indices characterizing the promoting and hindering effects could be integrated to calculate the loss rate of pollutant load entering the lake from landscape units at different locations in the basin space.

Evaluation of management practices on agricultural nonpoint source pollution discharges into the rivers under climate change effects

In recent years, agricultural non-point source pollution (ANPSP) has become the biggest threat to Aras River water quality by completing the Mughan irrigation and drainage network. Nutrient pollutants, including nitrate and phosphate, released into the river through drains have created a range of obstacles for locals living around the river. Agricultural activities are generally considered the largest source of non-point pollution. They have no complex and uniform impact along the river. Thus, the spatial distribution of ANPS and highly polluted areas should be identified to manage watershed management. This study proposes a simple framework for identifying pollutant-sensitive areas along the river and management strategies to improve water quality. To this aim, the main factors affecting ANPSP were identified, and the effectiveness of the scenarios selected to comply with water quality regulations for drinking and environment during 1993-2007 were simulated. Based on the sensitivity analysis, land use and fertilizer are the main factors affecting river ANPSP. Thus, their changes were modeled in different scenarios. Based on the results, the ANPSP load was higher downstream. The agricultural lands in region 3 were considered the main source of pollution. Comparing the management scenarios showed that the amount of nitrate and phosphate leaching into the river decreased to 18.1 and 8.35 %, respectively, by reducing the consumption of urea and phosphate fertilizers by 50 %. The results help watershed managers implement eco-friendly land use and nutrient management programs at specific locations during specific periods to control ANPSP along the rivers.

Anthropogenic eutrophication of shallow lakes: Is it occasional?

Understanding and managing the susceptibility of lakes to anthropogenic eutrophication has been a primary goal of limnological research for decades. To achieve United Nations' Sustainable Development Goals, scientists have attempted to understand why shallow lakes appear to be prone to eutrophication and resistant to restoration. A rich data base of 1151 lakes (each ≥ 0.5 km²) located within the Europe and the United States of America offers a rare opportunity to explore potential answers. Analysis of sites showed that lake depth integrated socio-ecological systems and reflected potential susceptibility to anthropogenic stressors, as well as lake productivity. In this study, lakes distributed in agricultural plain and densely populated lowland areas were generally shallow and subjected to intense human activities with high external nutrient inputs. In contrast, deep lakes frequently occurred in upland regions, dominated by natural landscapes with little anthropogenic nutrient input. Lake depth appeared to not only reflect external nutrient load to the lake, but also acted as an amplifier that increased shallow lake susceptibility to anthropogenic disturbance. Our findings suggest that shallow lakes are more susceptible to human forcing and their eutrophication may be not an occasional occurrence, and that societal expectations, policy goals, and management plans should reflect this observation.

Study on the Water Quality Characteristics of the Baoan Lake Basin in China under Different Land Use and Landscape Pattern Distributions

Land use and landscape pattern highly affect water quality. Their relationship can assist in land-use management and improve land-use efficiency. In this study, a water quality survey of rivers and lakes was performed in 2020 to analyze the effects of land use and the landscape pattern on the water quality of the rivers and lakes in the Baoan Lake basin and is expected to provide a reference for land use planning. The results demonstrated that the effects of land use on water quality were generally higher during the dry season than during the wet season; however, the opposite was demonstrated for the landscape pattern index. Cropland and urban land were closely correlated with deteriorating water quality, with contributions to total nitrogen, total phosphorous, and ammonia nitrogen in the basin. The impact of the landscape pattern of the basin on water quality was controlled by the original land-use type. In addition, the landscape configuration formed different land-use types to produce different effects on water quality. The basin scale better explained the changes in water quality, especially for construction land, followed by the 250 m and 500 m scales in the buffer zone.

The spatial variations of water quality and effects of water landscape in Baiyangdian Lake, North China

Baiyangdian Lake (BYD), a large shallow lake in North China, has complex water landscape patterns that are underlies spatial variations in water quality. In this study, we collected 61 water samples from three water landscapes (reed littoral zones, fish ponds, and open water) and analyzed them for water quality parameters, such as dissolved organic carbon (DOC), total nitrogen (TN), and total phosphorus (TP). Water landscape distribution (determined using remote sensing imagery) was then used to assess correlations between water quality parameters and water landscape proportion in differently scaled buffer zones. There was substantial variation across all subareas, with TN and TP concentrations ranging from 0.90 to 4.10 mg/L and 0.06 to 0.18 mg/L, respectively, in class IV of water quality as a whole. Spatial variations in water quality were mainly caused by water landscape distribution and external nutrient inputs. There were negative correlations between DOC, TN, and TP concentrations and the area proportion of reed littoral zones in the 300 and 500 m buffers. In contrast, DOC, TN, and TP concentrations were significantly positively correlated with the area proportion of fish ponds in the 100 m buffer. Furthermore, compared with reed littoral zones, a lower ratio of nitrogen to phosphorus and a higher proportion of dissolved organic nitrogen and tyrosine-like proteins were found in fish ponds. These effects were mainly attributed to the development of internal sediment loadings due to nutrient exchange across the sediment-water interface. Therefore, dredging-based sediment removal from fish ponds should be considered to suppress internal phosphorus loading and accelerate recovery of the BYD ecosystem.

Influence of the catchment area use on the water quality in the Utrata River

The present paper discusses the impact of land use and seasons on the concentration of nutrients in the waters of the Utrata River (Pruszków Poviat, Mazowieckie Voivodeship) from April 2018 to March 2019. The pollution of rivers by nutrients is a major problem for society. Surface water is a source of drinking water, water used for industrial and agricultural purposes. With the increasing pollution of rivers, the purification process for these purposes becomes more expensive and more challenging. To assist in carrying out activities aimed at reducing the inflow of biogenic substances into large river systems and then down to the Baltic Sea, we analyzed the spatial and temporal dynamics of loads from the entire Utrata River catchment area. We divided the entire catchment area into three impact zones: grasslands and wastelands, urbanized areas, and agricultural land and examined changes in nutrient concentrations (total phosphorus, nitrate nitrogen, ammonium nitrogen) in each of the zones. The results were statistically processed using the 1-factor ANOVA method with the p-value of significance below 0.05. Research indicates an increase in the concentration of total phosphorus and nitrogen forms down the course of the river in urban and agricultural areas with persistently low concentrations of these biogenic substances in grasslands.

Precipitation projection over Daqing River Basin (North China) considering the evolution of dependence structures

Understanding dynamic future changes in precipitation can provide prior information for nonpoint source pollution simulations under global warming. However, the evolution of the dependence structure and the unevenness characteristics of precipitation are rarely considered. This study applied a two-stage bias correction to daily precipitation and max/min temperature data in the Daqing River Basin (DQRB) with the HadGEM3-RA climate model. Validated from 1981 to 2015, future scenarios under two emission paths covering 2031-2065 and 2066-2100 were projected to assess variations in both the amount and unevenness of precipitation. The results suggested that, overall, the two-stage bias correction could reproduce the marginal distributions of variables and the evolution process of the dependence structure. In the future, the amount of precipitation in the plains is expected to increase more than that in the mountains, while precipitation unevenness, as measured by relative entropy, shows a slight increase in the mountains and a decrease in the plains, with enhanced seasonality. Conditioned on rising temperatures, high-/low-intensity precipitation tends to intensify/weaken precipitation unevenness. Additionally, the potential application of the bias correction method used herein and the possible impacts of uneven precipitation on nonpoint source pollution are given for further analyses. This study can provide useful information for future nonpoint source pollution simulations in the DQRB.

Critical source areas' identification for non-point source pollution related to nitrogen and phosphorus in an agricultural watershed based on SWAT model

Water eutrophication caused by the extensive expansion of slope farming has caused the high attention of the Chinese government. We choose Lake Tianmu basin as the study area because it can represent vast majority of basins plagued by water eutrophication derived from slope tillage in southern China. The water ecosystem in the reservoir Daxi and Shahe within the basin has been seriously threatened by multiple pollution sources related to many intricate human activities especially agricultural production. For the first time, we identified the critical source areas (CSAs) within the basin based on nutrient load and nutrient load intensity (NLI), and on this basis, we further excavated the main causes of pollution and proposed pertinent remediation measures. The results based on the calibrated Soil and Water Assessment Tool model indicated that the TN load of each reservoir remarkably exceeded their respective water environmental capacity from 2014 to 2018. Accordingly, six main tributaries with great nutrient contributions and their corresponding sub-basins were then identified. Overall, tea and rice plantations appear to be the major nutrient contributors to reservoir Daxi. And the main nutrient sources for reservoir Shahe are tea plantations, orchards, farmland, forestland, and point sources. Regarding the CSAs identified only by nutrient load, agronomic measures such as reducing fertilizer amount, biochar application, straw incorporation, and plastic mulch coverage can be employed to improve soil water retention and curb soil erosion. Regarding the CSAs identified by nutrient load intensity (NLI), the CSAs with narrow areas should be turned directly into forestland. For the CSAs with large areas, engineering measures such as constructing ecological riparian zone, filtration, and sedimentation tank can be employed to prevent pollutants from entering downstream reaches. Overall, the present results can provide the decision-making support for the safe and efficient management of watershed land use in southern China.

Pilot Demonstration of Reclaiming Municipal Wastewater for Irrigation Using Electrodialysis Reversal: Effect of Operational Parameters on Water Quality

The modification of ion composition is important to meet product water quality requirements, such as adjusting the sodium adsorption ratio of reclaimed water for irrigation. Bench- and pilot-scale experiments were conducted using an electrodialysis reversal (EDR) system with Ionics normal grade ion-exchange membranes (CR67 and AR204) to treat the reclaimed water in the Scottsdale Water Campus, Arizona. The goal is to investigate the impact of operating conditions on improving reclaimed water quality for irrigation and stream flow augmentation. The desalting efficiency, expressed as electrical conductivity (EC) reduction, was highly comparable at the same current density between the bench- and pilot-scale EDR systems, proportional to the ratio of residence time in the electrodialysis stack. The salt flux was primarily affected by the current density independent of flow rate, which is associated with linear velocity, boundary layer condition, and residence time. Monovalent-selectivity in terms of equivalent removal of divalent ions (Ca²⁺, Mg²⁺, and SO₄²⁻) over monovalent ions (Na⁺, Cl⁻) was dominantly affected by both current density and water recovery. The techno-economic modeling indicated that EDR treatment of reclaimed water is more cost-effective than the existing ultrafiltration/reverse osmosis (UF/RO) process in terms of unit operation and maintenance cost and total life cycle cost. The EDR system could achieve 92–93% overall water recovery compared to 88% water recovery of the UF/RO system. In summary, electrodialysis is demonstrated as a technically feasible and cost viable alternative to treat reclaimed water for irrigation and streamflow augmentation.

Spatiotemporal variation of nitrogen and phosphorus and its main influencing factors in Huangshui River basin

The foundation of managing excess nutrients in river is the identification of key physical processes and the control of decisive influencing factors. The existing studies seldom consider the influence of rainfall-runoff relationship and only focus on a few anthropogenic activities and natural attributes factors. To address this issue, a comprehensive set of influencing factors including rainfall-runoff relationship (represented by runoff coefficient), basic physical and chemical parameters of water quality, land use types, landscape patterns, topography, and socioeconomic development was constructed in this study. M-K test and cluster analysis were conducted to identify the temporal mutation and spatial clustering characteristics of NH₃-N and TP in Huangshui River basin, respectively. Partial least squares regression was used to elucidate the linkages between water contaminants and the factors. As shown in the results, the temporal mutations of NH₃-N and TP were obvious in the middle reaches, with 4 out of 7 catchments in the middle reaches have a larger number of mutations of NH₃-N than other catchments. The cluster analysis results of NH₃-N and TP among catchments were similar. This study also indicated that although the Huangshui River basin was located in the upper reaches of the Yellow River, the influences of rainfall-runoff relationship on spatiotemporal changes of NH₃-N and TP in its sub-basins were limited. Only the temporal change of NH₃-N in Jintan catchment in the upstream area was significantly affected by runoff coefficient. The indexes of proportion of water area (PWA), proportion of impervious area (PIA), and proportion of primary industry (PPI) were the top three influencing factors of temporal variation of NH₃-N and TP for most catchments in the middle reaches. The temporal change of NH₃-N in Jintan catchment in the upstream area was obviously affected by runoff coefficient. The spatial variation of NH₃-N and TP were all affected by PWA and proportion of secondary industry significantly. The results of this study can provide theoretical basis and technical support for the control and management of nitrogen and phosphorus pollution in upper reaches of rivers.

Rapid Changes in the Phytoplankton Community of a Subtropical, Shallow, Hypereutrophic Lake During the Rainy Season

Lake Cajititlán is a small, shallow, subtropical lake located in an endorheic basin in western Mexico. It is characterized by a strong seasonality of climate with pronounced wet and dry seasons and has been classified as a hypereutrophic lake. This eutrophication was driven by improperly treated sewage discharges from four municipal wastewater treatment plants (WWTPs) and by excessive agricultural activities, including the overuse of fertilizers that reach the lake through surface runoff during the rainy season. This nutrient rich runoff has caused algal blooms, which have led to anoxic or hypoxic conditions, resulting in large-scale fish deaths that have occurred during or immediately after the rainy season. This study investigated the changes in the phytoplankton community in Lake Cajititlán during the rainy season and the association between these changes and the physicochemical water quality and environmental parameters measured in the lake’s basin. Planktothrix and Cylindrospermopsis were the dominant genera of the cyanobacterial community, while the Chlorophyceae, Chrysophyceae, and Trebouxiophyceae classes dominated the microalgae community. However, the results showed a significant temporal shift in the phytoplankton communities in Lake Cajititlán induced by the rainy season. The findings of this study suggest that significant climatic variations cause high seasonal surface runoff and rapid changes in the water quality (Chlorophyll-a, DO, NH₄⁺, and NO₃^–) and in variations in the composition of the phytoplankton community. Finally, an alternation between phosphorus and nitrogen limitation was observed in Lake Cajititlán during the rainy season, clearly correlating to the presence of Planktothrix when the lake was limited by phosphorus and to the presence of Cylindrospermopsis when the lake was limited by nitrogen. The evidence presented in this study supports the idea that the death of fish in Lake Cajititlán could be mainly caused by anoxia, caused by rapid changes in water quality during the rainy season. Based on our review of the literature, this is the first study on the phytoplankton community in a subtropical lake during the rainy season using high throughput 16S rRNA and 18S rRNA amplicon sequencing.

Identification of the control factors affecting water quality variation at multi-spatial scales in a headwater watershed

Understanding the effect of landscape characteristics on water quality can provide insight into mitigating water quality impairment. However, there is no consensus about the key controlling factors influencing water quality. This paper examined the combined effects of land use and topography on water quality across multi-scale, and identified the key controlling factors determining water quality variation in the headwater watershed of the Hengxi reservoir in Eastern China. Water quality impairment (WQI), expressed as a composite variable, was established to measure the overall water quality. We used the partial least squares (PLSR) method to explore the combination of landscape metrics and identify the key controlling factors. Results showed that the optimal PLSR model at 50-m, 100-m, and 150-m buffer scales and catchment scale explained 77%, 63%, 60%, and 56% of variability in WQI, respectively. At catchment scale, patch density, the percentage of paddy field, and hypsometric integral were the key controlling factors impacting water quality. At buffer scales, the slope gradient, the percentage of forest land, and topographic wetness index were more effectively determined WQI variation. Thus, the key controlling factors depend on spatial scales. Both spatial scales and corresponding key controlling factors should be considered in the adjustment of land use composition and planning of landscape configuration to better protect water quality.

Numerical Simulations of Non-Point Source Pollution in a Small Urban Catchment: Identification of Pollution Risk Areas and Effectiveness of Source-Control Measures

Urban non-point source pollution is becoming a serious issue under the context of rapid urbanization and its impacts on surface hydrologic processes. The identification of non-point source risk areas and the effectiveness of source-control measures provides important first steps to improve the degrading aquatic environment but is challenged by the complex dynamics and variabilities of surface pollutants in urban environments. In this study, we investigate the spatial and temporal variabilities of non-point source pollution in a small urban catchment based on numerical simulations and in-situ samplings. Our results show that residential, industrial, and commercial land contribute to the most pollutant loadings and are the main constituents of the pollution risk area. Rainfall duration and intensity are the main factors in determining the temporal variations of urban non-point source pollution. There is no correlation between early drought days and pollution load. Numerical simulations show that it is more effective to increase urban vegetation coverage than to enhance road cleaning for effective non-surface pollution control. For enhanced road cleaning, it is more effective to improve the frequency of road cleaning than its efficiency. Our results provide important guidance for effective controls of non-point source pollution as well as the establishment of long-term surface pollutant monitoring network in complex urban environments.

Dynamic export coefficient model for evaluating the effects of environmental changes on non-point source pollution

The classic export coefficient model has been questioned due to its fixed coefficient, especially for those large-scale watersheds where great temporal-spatial heterogeneity exists. In this paper, a dynamic export coefficient model (DECM) was proposed for simulating non-point source (NPS) pollution by incorporating the impacts of factors on export coefficients. The relationships between rainfall, slope, soil, land use, other factors and export coefficients were constructed at relatively smaller catchment based on the information of mechanistic-based model, while these dynamic export coefficients were then extended to the large ungauged basins. This new model was tested in the Three Gorges Reservoir Region (TGRR), China. The results indicated the new method improved the accuracy of large-scale NPS prediction as well as reducing the computation burden. The rainfall temporal variability was identified as the major factor influencing the variability of flow and NPS pollution with the coefficient of variation being 0.1678 and 0.2046, respectively. Using the new method, the Long watershed, the Jialing watershed, the Quxi watershed, the Xiangxi watershed and the main stream in the TGRR were identified as those sensitive regions under the changing environment. The DECM could be extended to other large scale to quantify the NPS pollution, especially data-poor watersheds.

Simulation of streamflow and instream loads of total suspended solids and nitrate in a large transboundary river basin using Source model and geospatial analysis

The management of LULC changes in transboundary river basins continues to challenge water resources managers due to the differences in development and conservation priorities of the countries sharing the basin. While various watershed models (WMs) exist to support decision making, basin-wide sustainable application of the instituted WM depends on the management priorities, resources, data availability, and knowledge gaps at national and sub-basin levels. Building on the results of our prior comparative analysis of WMs for a large transboundary river basin, we applied the 'Source' model to the Lower Mekong Basin (LMB). The constructed LMB-Source model was evaluated based on its streamflow and instream total suspended solids (TSS) and nitrate loads simulative performances. A combination of predictive performance metrics (PPMs) and sophisticated hydrologic signatures were used to calibrate model parameters and diagnose the model performance. Calibration results indicated strong similarity between the simulated and observed time series data and were further confirmed by the validation results. The successful model calibration generated parameters that represent hydrologic response characteristics (HRCs) and overland TSS and nitrate generation and removal dynamics (GRDs) previously not available for the LMB. The HRCs and GRDs can be regionalised with physical attributes of the LMB in future studies which can be used to support the management of ungauged sub-basins. This study confirms Source's capability as a decision support tool for the management of transboundary river basins, and provides basin-specific values of HRCs and GRDs that can be used for a better evaluation of the potential effects of LULC changes.

Quantifying climate, streamflow, and watershed control on water quality across Southeastern US watersheds

Identification of the key variables that influence spatial variation in stream water quality is crucial for designing sustainable water management strategies. In this study, we investigated the key variables that influence the spatial variability of stream of water quality, across multiple watersheds. This study uses water quality data collected over 19 years for 59 watersheds located in the Southeast Atlantic region of the United States, which includes the states of North Carolina, South Carolina, and Georgia. A conceptual modeling framework was developed to understand the linkage between the long-term mean water quality constituents (Total nitrogen, Total phosphorus, Turbidity, and pH) and the watershed characteristics (e.g., topography, land use/cover, soil type), streamflow data, and climatic variables (precipitation and temperature). The modeling results suggest that not only anthropogenic variables influence the mean water quality constituents, but other watershed characteristics, such as soil properties, have a significant impact. The natural watershed characteristics explain most of the spatial variability in the mean Turbidity and pH values in streams. The modeling results also suggest that once land use and soil properties are considered, watershed topography has a limited role to explain the variation in the mean water quality. Overall, the developed watershed models can be used to forecast stream water-quality responses to future land use, climate, soil, and land management changes within the study area.

Responses of lake macrophyte species and functional traits to climate and land use changes

Aquatic plants are essential components in the regulation of microhabitat complexity and physico-chemical parameters in lake ecosystems. Increased eutrophication, land use change, modification of hydrological regimes, and expansion of invasive species are expected to impact aquatic plant community composition; however, historical pathways and response patterns are not well understood at the national scale. We analyzed temporal changes in aquatic plant communities in Japan from the early 1900s to the 2000s using field survey records from 248 lakes. Relationships of species associations with climate, land use, and lake characteristics were described using a joint species distribution model. The mean variation attributable to lake characteristics was 25.4%, followed by climate (14.0%), and land use (10.5%). Among the 13 functional traits used in our analysis, sexual and pollination traits showed marked responses to precipitation and land use. Hypohydrophily increased with precipitation, whereas monoecious aquatic plants increased in lakes surrounded by urbanized area. The relative ratio of floating to submerged plants has increased over time. Our results provide insight into long-term changes in aquatic plant communities and identify functional traits sensitive to environmental change.

Small Reservoirs, Landscape Changes and Water Quality in Sub-Saharan West Africa

Small reservoirs (SRs) are essential water storage infrastructures for rural populations of Sub-Saharan West Africa. In recent years, rapid population increase has resulted in unprecedented land use and land cover (LULC) changes. Our study documents the impacts of such changes on the water quality of SRs in Burkina Faso. Multi-temporal Landsat images were analyzed to determine LULC evolutions at various scales between 2002 and 2014. Population densities were calculated from downloaded 2014 population data. In situ water samples collected in 2004/5 and 2014 from selected SRs were analyzed for Suspended Particulate Matter (SPM) loads, an integrative proxy for water quality. The expansion of crop and artificial areas at the expense of natural covers controlled LULC changes over the period. We found a very significant correlation between SPM loads and population densities calculated at a watershed scale. A general increase between the two sampling dates in the inorganic component of SPM loads, concomitant with a clear expansion of cropland areas at a local scale, was evidenced. Results of the study suggest that two complementary but independent indicators (i.e., LULC changes within 5-km buffer areas around SRs and demographic changes at watershed scale), relevantly reflected the nature and intensity of overall pressures exerted by humans on their environment, and locally on aquatic ecosystems. Recommendations related to the re-greening of peripheral areas around SRs in order to protect water bodies are suggested.

A conceptual model to assess the impact of anthropogenic drivers on water-related ecosystem services in the Brazilian Cerrado

Abstract: The development of strategies that conciliate anthropogenic activities with nature conservation is becoming increasingly urgent, particularly in regions facing rapid conversion of native vegetation to agriculture. Conceptual modelling enables assessment of how anthropogenic drivers (e.g. land use/land cover change and climate change) modify natural processes, being a useful tool to support strategic decision-making. The present work describes a conceptual model to evaluate water-related ecosystem service provision under different land use scenarios in the Matopiba region of the Brazilian Cerrado, the world’s most biodiverse savanna and an agricultural frontier. Model variables were determined (direct drivers, indirect drivers, focal components and responses) and the Nature Futures Framework was consulted to incorporate socio-ecological components and feedbacks. Future scenarios were developed considering potential trajectories of drivers and governance responses that may impact land use in the region, including the possibility of full compliance with Forest Code and implementation of the Soy Moratorium in the region. The conceptual model and scenarios developed in the present study may be useful to improve understanding of the complex interactions among anthropogenic drivers, water-related ecosystem services and their potential repercussions for natural and social systems of the region. Governance decisions will be critical to maintaining the ecosystems of the region, the services it provides and the culture and tradition of the people historically embedded in the landscape. In acknowledgment of humanity’s dependence on nature, the importance of inverting the way scenarios are used is highlighted. Rather than using scenarios to measure the impacts of different policy options on nature, scenarios representing the desired outcomes for biodiversity and ecosystem services can be used to inform how policies can guarantee ecosystem integrity into the future.