Ecological risk assessment under the PSR framework and its application to shallow urban lakes

Shallow urban lakes are naturally vulnerable to ecosystem degradation. Rapid urbanization in recent decades has led to a variety of aquatic problems such as eutrophication, algal blooms, and biodiversity loss, increasing the risk to lake-wide ecological sustainability. Instead of a simple binary assessment of ecological risk, holistic evaluation frameworks that consider multiple stressors and receptors can provide a more comprehensive assessment of overall ecological risk. In this study, we analyzed a combined dataset of government statistics, remote sensing images, and 1 year of field measurements to develop an index system for urban lake ecological risk assessment based on the pressure-state-response (PSR) framework. We used the developed ecological safety index (ESI) system to evaluate the ecological risk for three urban lakes in Jiangsu Province, China: Lake Yangcheng-LYC, Lake Changdang-LCD, and Lake Tashan-LTS. LYC and LTS were classified as "mostly safe" and "generally recognized as safe," respectively, while LCD was assessed as having "potential ecological risk." Our data suggest that socioeconomic pressure and aquatic health are the two main factors affecting the ecological risk in both LYC and LCD. The ecological risk of LTS could be improved more effectively if regional management plans are well implemented. Our study highlights the pressure of external wastewater loading, low forest-grassland coverage, and lake shoreline damage on the three selected urban lakes. The findings of this study can inform watershed management for lake ecosystem restoration and environmental sustainability.

Sediment source fingerprints of natural processes and anthropogenic pressures: A contribution to manage the Paraopeba River basin impacted by the B1 tailings dam collapse

Understanding the origins of sediment transport in river systems is crucial for effective watershed management, especially after catastrophic events. This information is essential for the development of integrated strategies that guarantee water security in river basins. The present study aimed to investigate the rupture of the B1 tailings dam of the Córrego do Feijão mine, which drastically affected the Brumadinho region (Minas Gerais, Brazil). To address this issue, a confluence-based sediment fingerprinting approach was developed through the SedSAT model. Uncertainty was assessed through Monte Carlo simulations and Mean Absolute Error (MAE). Estimates of the overall average contributions of each tributary were quantified for each station and annually during the period 2019-2021. It was observed that the sampling point PT-09, closest to the dam breach, contributed to almost 80% of the Paraopeba River in 2019. Despite the dredging efforts, this percentage increased to 90% in 2020 due to the need to restore the highly degraded area. Additionally, the main tributaries contributing to sediment increase in the river are Manso River "TT-03" (almost 36%), associated with an area with a high percentage of urban land use, and Cedro stream "TT-07" (almost 71%), whose geology promotes erosion, leading to higher sediment concentration. Uncertainties arise from the limited number of available tracers, variations caused by dredging activities, and reduced data in 2020 due to the pandemic. Parameters such as land use, riparian vegetation degradation, downstream basin geology, and increased precipitation are key factors for successfully assessing tributary contributions to the Paraopeba River. The obtained results are promising for a preliminary analysis, allowing the quantification of key areas due to higher erosion and studying how this disaster affected the watershed. This information is crucial for improving decision-making, environmental governance, and the development of mitigating measures to ensure water security. This study is pioneering in evaluating this methodology in watersheds affected by environmental disasters, where restoration efforts are ongoing.

Identifying critical source areas of non-point source pollution to enhance water quality: Integrated SWAT modeling and multi-variable statistical analysis to reveal key variables and thresholds

By integrating soil and water assessment tool (SWAT) modeling and land use and land cover (LULC) based multi-variable statistical analysis, this study aimed to identify driving factors, potential thresholds, and critical source areas (CSAs) to enhance water quality in southern Alabama and northwest Florida's Choctawhatchee Watershed. The results revealed the significance of forest cover and of the lumped developed areas and cultivated crops ("Source Areas") in influencing water quality. The stepwise linear regression analysis based on self-organizing maps (SOMs) showed that a negative correlation between forest percent cover and total nitrogen (TN), organic nitrogen (ORGN), and organic phosphorus (ORGP), highlighting the importance of forests in reducing nutrient loads. Conversely, Source Area percentage was positively correlated with total phosphorus (TP) loads, indicating the influence of human activities on TP levels. The receiver operating characteristic (ROC) curve analysis determined thresholds for forest percentage and Source Area percentage as 37.47 % and 20.26 %, respectively. These thresholds serve as important reference points for identifying CSAs. The CSAs identified based on these thresholds covered a relatively small portion (28 %) but contributed 47 % of TN and 50 % of TP of the whole watershed. The study underscores the importance of considering both physical process-based modeling and multi-variable statistical analysis for a comprehensive understanding of watershed management, i.e., the identification of CSAs and the associated variables and their tipping points to maintain water quality.

Coincidence of sustainable development indicators for the nekarood watershed with the United Nation's sustainable development goals

The present study evaluated sustainable development indicators of the Nekarood Watershed in Iran using global Sustainable Development Goals (SDGs) indicators. Identifying values and thresholds, justification of optimum values, ranking, and performance assessment of the associated SDGs' indicators were accordingly addressed. Moreover, due to a lack of complete information and ecological conditions, 77 indicators were selected based on compliance with the indicators of global SDGs. These indicators were used to evaluate the development situation of the study area. The indicators were then normalized, weighed, aggregated, and ranked into four categories from achieving to highly challenging. The results showed that among the SDGs, five goals performed above the mean of the global sustainable development goals. So, goals 3 and 1 had the highest performance of 69.82 and 57.97 %, respectively. Likewise, goals 7 and 16 showed the lowest performance beyond the global average of 51.08 and 54.62 %, respectively. SDG3-1-1, SDG3-1-2, SDG3-2-1, and SDG3-2-2 indicators with 100 % performance positively affected SDG3. SDG1-5-1 indicator with 100 % performance also had the most positive effect on SDG1. The performances of nine goals were also lower than the global mean. In this case, the lowest performance was assigned to goal 2, followed by goals 9, 17, 10, and 6, respectively, with 15.24, 19.71, 22.19, 24.98, and 45.78 %. SDG2-4-2, SDG2-4-1, and SDG2-3-1 indicators had the most negative effect on the performance of SDG2. SDG9-2-2 and SDG10-4-1 indicators also had the most negative effect on goals 9 and 10, respectively. The highest performance of the indicators was associated with the Ministry of Health and Medical Education, and the lowest was related to the Ministries of Agriculture Jihad and the Ministry of Industry, Mine, and Trade. The results of the present study verified an overall performance of 36.42 % for the Nekarood Watershed concerning the global SDGs, representing significantly challenging conditions.

A spatiotemporal optimization method for nutrient control in lake watersheds

Developing an efficient strategy for managing nutrients in less-developed lake watersheds that can balance the need for socioeconomic progress with the protection of aquatic ecosystems has become an urgent research subject for achieving sustainable development. This paper improves the optimization method for environmental and economic management of lake watersheds proposed in our previous research. A spatiotemporal optimization method based on a coupling model consisting of the Soil and Water Assessment Tool, system dynamics model, and objective programming model was applied to an agricultural non-point source (ANPS) pollution control program and a rural sewage treatment program at the Yilong Lake watershed as a case study. A simulation evaluation showed that the efficiency of the previous scheme was significantly improved after conducting spatiotemporal optimization. This scheme was dynamic and distributed, demonstrating an annual and high-resolution control program that can provide a basis for the precise management of ANPS. Although it still requires improvement, a framework for coupling simulation and two-step optimization was achieved in this study.

Assessment of the Wanyu River (China) based on a water, sediment and hydrobiont framework

Due to the striving for the development of economy and agriculture, anthropogenic activities in many countries dramatically alter natural hydrology. These activities are primarily responsible for river deterioration. Thus, we need to assess the river environment and take measures for remediation. According to the survey data, the study identified the critical factors causing water quality deterioration and evaluated the aquatic biodiversity in the Wanyu River. First, based on the monitoring data of water (dissolved oxygen (DO), chemical oxygen demand (COD), total phosphorus (TP), and ammonia nitrogen (NH3-N)), sediment (copper (Cu), zinc (Zn), lead (Pb), arsenic (As), nickel (Ni), mercury (Hg), cadmium (Cd), and chromium (Cr)), and aquatic biodiversity (fish and hydrophyte), the study identified the critical factors causing river quality deterioration. Second, the study provided some recommendations that would consolidate the restoration efforts. Consequently, because of the government's efforts in building the municipal sewage treatment plant, dredging, and other measures, the river environment improved during the 2020-2021 period. The maximum concentrations of COD, NH3-N, and TP in water were reduced by 17.76%, 26.17%, and 20.93%, respectively. The sediment had no risk of heavy metal pollution in the past 2 years. And we could utilize sludge as garden soil or compost resource. However, reducing agricultural pollution, internal nutrient loading, and cost-effective restoration and evaluation represent significant challenges in the efforts to recover the river ecosystem.

Assessing and improving the outcomes of nonpoint source water quality trading policies in urban areas: A case study in Virginia

Nonpoint source (NPS) water quality trading (WQT) is a market-based approach to improving water quality. Past work has shown that these programs could increase localized pollutant loadings, in part by exporting water quality controls from urban to rural areas. Virginia's NPS WQT program has enabled thousands of transactions and may provide a model for other programs, but its impacts on urban water quality have not been thoroughly assessed. We quantify the impact of NPS WQT purchases in Virginia on water quality and hydrology in an urban catchment. We go on to assess outcomes of a policy alternative where buyers and sellers are collocated in the urban catchment. Simulation results show that NPS WQT increased total phosphorus (TP) loading by an average of 0.8 lbs TP/year for each 1.0 offsite credits purchased in the analyzed catchment. The TP loading increased in years with greater rainfall, such that TP loads were increased by up to 1.2 lbs TP/year for each offsite credit purchased. These loading increases may or may not be acceptable, depending on the cumulative number of purchases within an urban catchment and existing local water quality issues. In our policy alternative with buyers and sellers collocated in the catchment, we found that the TP increase from development was completely offset at the catchment scale, with a decrease of 4.3 lbs TP/year for each 1.0 credits purchased. This suggests that credits awarded for urban mitigation practices are undervalued compared with water quality requirements for credit purchasers. This undervaluation is a result of the Virginia trading program using one approach to compute the credit value for buyers and a different approach to compute the credit value for sellers. We demonstrate how using a single model to determine both buyer and seller credit values in urban areas could provide greater transparency and mitigate the risk of urban pollution hot spots. This work demonstrates the importance of consistency in the scale of pollutant load calculations between buyers and sellers for NPS WQT, and contributes novel insight into the implications of WQT for urban NPS pollution.

Using watershed characteristics to enhance fecal source identification

Fecal pollution is one of the most prevalent forms of pollution affecting waterbodies worldwide, threatening public health and negatively impacting aquatic environments. Microbial source tracking (MST) applies polymerase chain reaction (PCR) technology to help identify the source of fecal pollution. In this study, we combine spatial data for two watersheds with general and host-associated MST markers to target human (HF183/BacR287), bovine (CowM2), and general ruminant (Rum2Bac) sources. Concentrations of MST markers in samples were determined with droplet digital PCR (ddPCR). The three MST markers were detected at all sites (n = 25), but bovine and general ruminant markers were significantly associated with watershed characteristics. MST results, combined with watershed characteristics, suggest that streams draining areas with low-infiltration soil groups and high agricultural land use are at an increased risk for fecal contamination. Microbial source tracking has been applied in numerous studies to aid in identifying the sources of fecal contamination, but these studies usually lack information on the involvement of watershed characteristics. Our study combined watershed characteristics with MST results to provide more comprehensive insight into the factors that influence fecal contamination in order to implement the most effective best management practices.

Analyzing the impact of agricultural BMPs on stream nutrient load and biotic health in the Susquehanna-Chemung basin of New York

Despite the widespread use of agricultural best management practices (BMPs) to reduce watershed scale nutrient loads, there remain few studies that use directly observed data - instead of models - to evaluate BMP effectiveness at the watershed scale. In this study, we make use of extensive ambient water quality data, stream biotic health data, and BMP implementation data within the New York State portion of the Chesapeake Bay watershed to assess the role of BMPs on reducing nutrient loads and modifying biotic health in major rivers. The specific BMPs considered were riparian buffers and nutrient management planning. A simple mass balance approach was used to evaluate the role of wastewater treatment plant nutrient reductions, agricultural land use changes, and these two agricultural BMPs in matching observed downward trends in nutrient load. In the Eastern nontidal network (NTN) catchment - where BMPs have been more widely reported - the mass balance model suggested a small but discernible contribution of BMPs in matching the observed downward trend in total phosphorus. Contrastingly, BMP implementations did not show clear contributions towards total nitrogen reductions in the Eastern NTN catchment nor for the total nitrogen and phosphorus in the Western NTN catchment, where BMP implementation data are more limited. Assessment of the relationship between stream biotic health and BMP implementation using regression models found limited connection between extent of BMP implementation and biotic health. In this case, however, spatiotemporal mismatches between the datasets and the relatively stable biotic health, typically of moderate to good quality even before BMP implementation, may reflect the need for better monitoring design to assess BMP effects at the subwatershed scale. Additional studies, perhaps using citizen scientists, may be able to provide more suitable data within the existing frameworks of the long-term surveys. Given the preponderance of studies that rely only on modeling to understand nutrient loading reductions achieved by implementation of BMPs, it is essential to continue to collect empirical data to meaningfully evaluate whether there are actual measurable changes due to BMPs.

Static and dynamic source identification of trace elements in river and soil environments under anthropogenic activities in the Haraz plain, Northern Iran

Unsustainable human activities have disrupted the natural cycle of trace elements, causing the accumulation of chemical pollutants and making it challenging to determine their sources due to interwoven natural and human-induced processes. A novel approach was introduced for identifying the sources and for quantifying the contribution of trace elements discharge from rivers to soils. We integrated fingerprinting techniques, soil and sediment geochemical data, geographically weighted regression model (GWR) and soil quality indices. The FingerPro package and the state-of-the-art tracer selection techniques including the conservative index (CI) and consensus ranking (CR) were used to quantify the relative contribution of different upland sub-watersheds in trace element discharge soil. Our analysis revealed that off-site sources (upland watersheds) and in-site sources (land use) both play an important role in transferring trace elements to the Haraz plain (northern Iran). The unmixing model's results suggest that the Haraz sub-watersheds exhibit a higher contribution to trace elements transfer in the Haraz plain, and therefore, require greater attention in terms of implementing soil and water conservation strategies. However, it is noteworthy that the Babolroud (adjacent to Haraz) exhibited a better performance of the model. A spatial correlation between certain heavy metals, such as As and Cu, and rice cultivation existed. Additionally, we found a significant spatial correlation between Pb and residential areas, particularly in the Amol region. Our result highlights the importance of using advanced spatial statistical techniques, such as GWR, to identify subtle but critical associations between environmental variables and sources of pollution. The methodology used comprehensively identifies dynamic trace element sourcing at the watershed scale, allowing for pollutant source identification and practical strategies for soil and water quality control. Tracer selection techniques (CI and CR) based on conservatives and consensus improve unmixing model accuracy and flexibility for precise fingerprinting.

Integrated assessment of land-to-river Cd fluxes and riverine Cd loads using SWAT-HM to guide management strategies

In 2011, China invested US$9.8 billion to combat the severe heavy metal pollution in the Xiang River basin (XRB), aiming to reduce 50% of the 2008 industrial metal emissions by 2015. However, river pollution mitigation requires a holistic accounting of both point and diffuse sources, yet the detailed land-to-river metal fluxes in the XRB remain unclear. Here, by combining emissions inventories with the SWAT-HM model, we quantified the land-to-river cadmium (Cd) fluxes and riverine Cd loads across the XRB from 2000 to 2015. The model was validated against long-term historical observations of monthly streamflow and sediment load and Cd concentrations at 42, 11, and 10 gauges, respectively. The analysis of the simulation results showed that the soil erosion flux dominated the Cd exports (23.56-80.14 Mg yr^-1). The industrial point flux decreased by 85.5% from 20.84 Mg in 2000 to 3.02 Mg in 2015. Of all the Cd inputs, approximately 54.9% (37.40 Mg yr^-1) was finally drained into Dongting Lake; the remaining 45.1% (30.79 Mg yr^-1) was deposited within the XRB, increasing the Cd concentration in riverbed sediment. Furthermore, in XRB's 5-order river network, the Cd concentrations in small streams (1st order and 2nd order) showed larger variability due to their low dilution capacity and intense Cd inputs. Our findings highlight the need for multi-path transport modeling to guide future management strategies and better monitoring schemes to restore the small polluted streams.

Microbial source tracking to elucidate the impact of land-use and physiochemical water quality on fecal contamination in a mixed land-use watershed

Escherichia coli has been widely used as a fecal indicator bacterium (FIB) for monitoring water quality in drinking water sources and recreational water. However, fecal contamination sources remain difficult to identify and mitigate, as millions of cases of infectious diseases are reported yearly due to swimming and bathing in recreational water. The objective of this study was to apply molecular techniques for microbial source tracking (MST) to identify sources of fecal contamination in a representative mixed land-use watershed located in the Appalachian Mountains of the United States of America (USA). Monthly samples were collected over one year at 11 sites, including the confluence of key first-order streams in the study watershed representing distinct land-use types and anticipated fecal sources. Results indicated that coupled monitoring of host-specific MST markers with the FIB E. coli effectively identified sources and quantified fecal contamination in the study watershed. Human-associated MST markers were abundant primarily at developed sites, suggesting septic or sewer failure is a key source of fecal input to the watershed. Across the dataset, samples positive for E. coli and human MST markers were associated with a higher pH than those samples from which each target was not detected, thereby suggesting that acid mine drainage in the watershed likely contributed to inactivation or loss of culturability in E. coli. In addition, this research provides the first evidence that the BacCan-UCD marker is present in fox feces and can influence MST results in areas where substantial wildlife activity is present. Identifying the sources of fecal contamination and better understanding the impact of in-stream physiochemistry throughout this study will help to develop sustainable and effective watershed management plans to control fecal contamination to protect drinking water sources and recreational water.

Impacts of watershed management on land use/cover changes and landscape greenness in Yezat Watershed, North West, Ethiopia

In Ethiopia, watershed management interventions have been implemented since the 1980s to curve land degradation and improve the agricultural productivity of smallholder farmers. However, little effort has been made to investigate the impacts of watershed management on land use/cover changes and landscape greenness. Thus, this study was conducted to assess the long-term impacts of watershed management on land use/cover changes and landscape greenness in the Yezat watershed. Landsat images for 1990, 2000, 2010, and 2021 were employed and analyzed to produce maps of the respective years using GIS and remote sensing techniques. Data from satellite images, coupled with field observation and the socio-economic survey, revealed an effective approach for analyzing the extent, rate, and spatial patterns of land use/cover changes. Normalized difference vegetation index (NDVI) was also employed to detect vegetation greenness. The results of the study show that between 1990 and 2021, the built-up area, plantation, natural forest, shrubland, and grasslands were increased by + 254 ha, + 712.3 ha, 196.3 ha, + 1070.8, and + 425.3 ha respectively due to watershed management interventions. Conversely, cultivated land was decreased with a rate of - 2658.7 ha_, in the study area. However, the reverse is true between 1990 and 2000 due to large-scale land degradation. Besides, the result of the study also shows that a low landscape greenness value (- 0.11) was observed between 1990 and 2000, and a high landscape greenness value (+ 0.2) was observed between 1990 and 2021. The observed change in landscape greenness in the watershed was due to the change in shrubland (+ 1070.8 ha), grassland (+ 425.3 ha), plantation (+ 712.3 ha), and forestland (+ 196.3 ha) covers between 1990 and 2021 years. Such observed changes in land use land covers, landscape greenness, and cultivated land in the study watershed have important implications for the improvement of soil moisture, soil fertility, biodiversity, groundwater recharge, carbon sequestration, soil erosion land, crop yield, and ecosystem services.

Using morphometric analysis for assessment of flash flood susceptibility in the Mediterranean region of Turkey

Flash floods are one of the most severe natural disasters around the world because of their rapid and unpredictable nature. It is expected that the frequency and intensity of flood events will increase because of extreme rainfall events induced by climate change. In this context, the generation of a flood susceptibility map contributes to effective flood management in a basin. The present study aims to generate a flash flood susceptibility map for the Imali Stream Basin (ISB) situated within the Mediterranean region of Turkey. For this purpose, morphometric analysis, geographic information system (GIS), remote sensing (RS), and principal component analysis (PCA) were used in this study. ASTER GDEM (v.3) was used to delineate 9 sub-watersheds and to obtain the required morphometric parameters. To generate a flash flood susceptibility map, the original compound values ​​calculated for each sub-watershed were transformed into values ​​between 0 and 1 by using the min-max normalization method. Then, these values were divided into 3 classes called low, moderate, and high by using the equal interval classification method in ArcGIS. According to both flash flood susceptibility maps produced by using morphometric analysis and PCA, sub-watershed 5 has the highest flash flood susceptibility in the basin. The flash flood that occurred in sub-watershed 5 in 2016 contributes to these results. Therefore, flood management based on morphometric analysis can be a highly effective method for decision-makers and planners in the Mediterranean region, one of the hotspots to be affected by climate change.

Determination of soil quality index in areas with high erosion risk and usability in watershed rehabilitation applications

Erosion is an important environmental issue threatening natural resources and ecosystems, especially soil and water. Soil losses occur in many parts of the world due to erosion at different degrees, and various rehabilitation plans have been carried out to reduce these losses. However, soil protection applications are generally carried out by considering only the essential characteristics of the soil. This may decrease the chance of success of rehabilitation applications. The present study aimed to determine the soil quality index (SQI) by weighting the soil quality parameters according to the analytical hierarchy process (AHP) in the Çapakçur microcatchment (Bingöl, Türkiye) where soil loss is high. Accordingly, 428 soil samples were taken from the study area and analyzed. The soil losses in the Çapakçur watershed were calculated employing the revised universal soil loss equation (RUSLE). To determine the soil quality index, a total of 20 indicators were used, including (i) physical soil properties, (ii) chemical soil properties, and (iii) soil nutrient content. Soil quality index results are divided into classes between 1 and 5. As a result of the study, the annual total amount of soil lost from the microcatchment was calculated as 96,915.20 tons, and the yearly average amount of soil lost from the unit area was calculated as 10.14 tons ha^-1. According to SQI, the largest area in the microcatchment was Class-2 (weak), with 39.49%, whereas the smallest area was 1.4% (the most suitable). However, it was determined that there was a significant negative relationship between SQI and soil erodibility. Considering the SQI distribution of the area in the planning of soil protection and erosion prevention practices in watershed rehabilitation studies may increase success.

Life Cycle Dynamics and Developmental Processes in Collaborative Partnerships: Examples From Four Watersheds in the U.S

Collaborative governance ebbs and flows. Partnerships become dormant or extinct, only to resurface with new members, and names, forms, or boundaries. This paper uses a systematic qualitative analysis of data from 4 watershed governance efforts in the United States--Delaware Inland Bays, Narragansett Bay, Tampa Bay, and Tillamook Bay. The study's objective is to develop theory grounded in these data by examining the developmental trajectories associated with collaborative partnerships. The paper begins by summarizing a four-stage life-cycle model. Each stage identifies a cluster of developmental challenges related to sustaining the health and useful life of a collaborative partnership. The paper identifies 31 partnerships across the four watersheds that were self- or externally-initiated. They experienced many different developmental trajectories. Some remained relatively healthy for a considerable period while others declined quite rapidly. Some partnerships had reorientations involving minor and rapid changes to the partnership structure. Some involved recreations with more profound shifts in core values and purposes. Some partnerships lasted for a considerable period while others ended when their work was done. Healthy partnerships also ended prematurely while unhealthy partnerships endured for a considerable period after their useful life ended. The paper concludes with a discussion of the implications for theory and practice.

Drought and water availability analysis for irrigation and household water needs in the Krueng Jrue sub-watershed

This study aimed to analyze drought conditions and evaluate irrigation water availability and household water needs in the Krueng Jrue sub-watershed, Aceh Province, Indonesia. The Z-score statistics method was developed to analyze the drought, and the Mock model was used to generate discharges. We performed model validation using linear regression, which produced a coefficient of determination (R ² = 0.90^**) and coefficient of regression (r = 0.95^**). In general, this area had a normal Z-score for precipitation (ZSP) class with 90 events (75%) and a normal Z-score for a discharge (ZSD) class with 89 events (74.2%). There were 0-11 (0-9.2%) moderate wet, very wet, extreme wet, moderate drought, and severe drought events. The consistency between the ZSP and ZSD indices reached 85.8%, indicating consensus between the meteorological droughts that were analyzed based on rainfall (ZSP) and hydrological droughts analyzed based on water discharge (ZSD). ZSP and ZSD indices showed negative values during the dry season (April to September) and positive values during the rainy season (October to March). There was a surplus of water availability for irrigation and household water needs during the rainy season and a deficit during the dry season. However, water deficits also occurred in certain months during the rainy rendeng planting season, for example, in October 2009, 2013, 2016, and 2017 as well as in February between 2008 to 2011 and from 2014 to 2017. This observation was probably due to the influence of global climate variables that need to be substantiated. This study offers necessary information for farmers, the community, and the local government when anticipating drought phenomenon, organizing the rice planting season, and evaluating water availability in other watersheds.

Improvement in water pollution control alters nutrient stoichiometry of Guanting Reservoir near Beijing, North China

Significant improvement in wastewater treatment is the most effective way for eutrophication control, especially in semiarid regions. However, its effect on the nutrient status and stoichiometry of the receiving water body has remained poorly considered and understood at broad temporal scales. Taking Guanting Reservoir (GR) in Hebei-Beijing (P. R. China) as an example, we present a study that links a continuous monitoring dataset for GR with corresponding estimates of human-induced nutrient discharges in its watershed from the year 2006 to 2019. We find that current GR belongs to strict P limitation and the faster decrease of TP than TN concentrations and continuous increase of TN/TP mass ratios in GR are attributed to the water restoration investment-induced declining of nutrient loadings. The improved municipal wastewater treatment capacity is mainly responsible for these significant changes, due to the higher removal efficiency of TP than TN in municipal wastewater. Given the potential ecological impact on aquatic biodiversity as well as ecosystem function of changes in TN/TP ratios and higher retention rate of TP (97.4%) compared with TN (93.1%) in GR, our findings highlight that future strategy for water pollution control should not only concentrate on more nutrient reduction efficiencies but attach importance to their stoichiometric balance to reduce the potential risk of phytoplankton blooms and toxin production during the water quality recovery of lakes or reservoirs.

Water and wastewater quality prediction: current trends and challenges in the implementation of artificial neural network

Traditional freshwater supplies have been over-abstracted in the current global problem of water scarcity. Through the analysis of complex experimental and real-time data, to improve the activity of water and wastewater treatment (WWT) systems, an artificial neural network (ANN), a computational model inspired by the human brain, and its variants were created. This review paper focuses on recent trends and advances in modeling and simulating different water and wastewater systems using ANN. This study uses ANN in watershed management, impurity removal from wastewater, and wastewater treatment plants. According to the literature review, ANN can predict nonlinear, linear, and complex systems with high accuracy and well control. Finally, the limitations and future scope of ANNs were discussed. ANN proved itself in the prediction of various water and WWT processes. Still, implementation has practical challenges, which include a lack of data availability, poorly built models, timely updates in developed models, and low repeatability. The use of a proper toolbox, faster computing power, and proper domain knowledge makes the practical implementation of ANN successful. As a result, ANN can build a solid foundation for attracting and motivating investigators to work in this region in the forthcoming.

Relations between physical and ecosystem service flows of freshwater are critical for water resource security in large dryland river basin

Freshwater ecosystem services are the link between ecological systems and social systems, which is an important guarantee of the freshwater safety particularly in dryland regions. However, more quantitative research has been based on the freshwater ecosystem services of static situations, and less on the flow conditions. We established a comprehensive modeling framework for the analysis of water security pattern based on the physical flow (PF) and ecosystem service flow (ESF) of freshwater. The results for Yellow River Basin showed that the water-scarce area have reduced in the past two decades. The PF of freshwater relieves water stress on an average of 52.1 % of the static water in scarce areas per year. The problem in water-deficient areas meanly lies on the water supply side. These results highlight the importance of PF from the upstream to downstream, which is critical for formulating sustainable management strategies in safeguarding long-term regional freshwater resource security.

Hydrological connectivity affects nitrogen migration and retention in the land‒river continuum

Land use change and excessive nitrogen (N) loading threaten the health of receiving water bodies worldwide. However, the role of hydrological connectivity in linking watershed land use, N biogeochemistry and river water quality remain unclear. In this study, we investigated 15 subwatersheds in the Jiulong River watershed (southeastern China) during a dry baseflow period in 2018, combined with 3‒year (2017-2019) nutrient monitoring in 5 subwatersheds to explore river N dynamics (dissolved nutrients, dissolved gases and functional genes) and their controlling factors at three hydrological connectivity scales, i.e., watershed, hydrologically sensitive areas (HSAs) and riparian zone. The results show that land use at HSAs (less than 20% of watershed area) and watershed scales contributed similarly to river N variation, indicating that HSAs are hotspots for transporting land N into river channels. In particular, the agricultural land was the main factor affecting river nitrate and nitrous oxide (N₂O) concentrations, while the built-up land significantly affected river ammonium and nitrite. At the riparian zone scale, soils and sediments substantially influenced river N retention processes (i.e., nitrification and denitrification). Management and protection measures targeting HSAs and riparian zones are expected to efficiently reduce river N loading and improve water quality.

Sediment source fingerprinting as an aid to large-scale landscape conservation and restoration: A review for the Mississippi River Basin

Reliable quantitative information on sediment sources to rivers is critical to mitigate contamination and target conservation and restoration actions. However, for large-scale river basins, determination of the relative importance of sediment sources is complicated by spatiotemporal variability in erosional processes and sediment sources, heterogeneity in sediment transport and deposition, and a paucity of sediment monitoring data. Sediment source fingerprinting is an increasingly adopted field-based technique that identifies the nature and relative source contribution of sediment transported in waterways. Notably, sediment source fingerprinting provides information that is independent of other field, modeling, or remotely sensed techniques. However, the diversity in sampling, analytical, and interpretive methods for sediment fingerprinting has been recognized as a problem in terms of developing standardized procedures for its application at the scale of large river basins. Accordingly, this review focuses on sediment source fingerprinting studies conducted within the Mississippi River Basin (MRB), summarizes unique information provided by sediment source fingerprinting that is distinct from traditional monitoring techniques, evaluates consistency and reliability of methodological approaches among MRB studies, and provides prospects for the use of sediment source fingerprinting as an aid to large-scale landscape conservation and restoration under current management frameworks. Most MRB studies reported credible fingerprinting results and found near-channel sources to be the dominant sediment sources in most cases, and yet a lack of standardization in procedural steps makes results difficult to compare. Findings from MRB studies demonstrated that sediment source fingerprinting is a highly valuable and reliable sediment source assessment approach to assist land and water resource management under current management frameworks, but efforts are needed to make this technique applicable in large-scale landscape conservation and restoration efforts. We summarize research needs and discuss sediment fingerprinting use for basin-scale management efforts with the aim of encouraging that this technique is robust and reliable as it moves forward.

Comparison of multi-objective evolutionary algorithms applied to watershed management problem

Simulation-based optimization (S-O) frameworks are effective in developing cost-effective watershed management strategies, where optimization algorithms have substantial effect on the quality of strategies. Despite the development and improvement of multi-objective evolutionary algorithms (MOEAs) provide more robust alternatives for optimization, they typically have limited applications in real-world decision contexts. In this study, three advanced MOEAs, including NSGA-II, MOEA/D and NSGA-III, were introduced into the S-O framework and applied to a real-world watershed management problem, and their performance and characteristics were quantified through performance metrics. Results show that a higher crossover or mutation probability do not necessarily promote convergence and diversity of solutions, while a larger generation and population size is helpful for MOEAs to find high-quality solutions. Compared to the other two MOEAs, NSGA-II consistently exhibits robust performance in finding solutions with good convergence and high diversity, and provides more options at the same computational cost, while the degenerate Pareto front of the proposed watershed management problem may account for the poor performance of MOEA/D and NSGA-III in terms of diversity. For a 10% TN or TP reduction target, the average cost of the NSGA-II optimized strategies is 32.22% or 47.83% of the commonly used strategies. In addition, this study also discussed the development of resilient watershed management to buffer the impacts of climate change on aquatic system, the incorporation of fuzzy programming into the S-O framework to develop robust watershed management strategies under uncertainty, and the application of machine learning-based surrogate models to reduce computational cost of the S-O framework. These results can contribute to the understanding of MOEAs and provide useful guidance to decision makers.

On the use of contingent valuation method to assess factors affecting the contribution of local people for the management of water hyacinth in Lake Tana, northwestern Ethiopia

The colonization of freshwater lakes by invasive alien species is increasingly alarming primarily owing to nutrient loads from the watersheds. For the sustainable management of invasive weeds, preventive methods, such as watershed management and sustainable agricultural practices, are recommended. Watershed protection activities by the upstream local community are believed to be effective measures to reduce nutrient loading to the receiving water bodies and hence help prevent the spread of water hyacinth. However, their willingness and potential contributions determine the effectiveness of watershed management activities. The objective of this study is, therefore, to evaluate the preferences and contributions (willingness to pay and willingness to contribute labor) of the local community for the management of water hyacinth in Lake Tana (Ethiopia). A contingent valuation method for a hypothetical market "prevention of water hyacinth infestation of Lake Tana through watershed management program" was used to collect data from 560 randomly selected households. A multivariable interval regression model was used to identify factors affecting the contribution of local people. The mean yearly willingness to pay and to contribute labor of the respondents was 435.4 Ethiopian Birr (US$ 10) and 22.4 man-days, respectively. The place of residence (rural/urban), educational level, private farm plot area, annual income, and water hyacinth-related conference participation significantly influenced the willingness to pay. Similarly, the willingness to contribute labor was strongly associated with place of residence, location, educational level, and household family size. The economic value derived from this study reflects community preferences, which could be an input for informed and evidence-based decision-making regarding the prevention of weed expansion and sustainable use of ecosystem services. Therefore, local, regional, and national authorities are advised to mobilize the local community to contribute labor and/or money so as to halt the expansion of the weed.

A coupling simulation and optimization method developed for environmental-economic management of Lake watershed

Many lake basins are facing the challenge of mitigating water shortage and water pollution while maintaining economic growth. Existing planning method for water pollution control often focus on how to alleviate water pollution effectively at the lowest cost, but rarely pay attention to the dynamic feedback and synergy effects between water pollution abatement, water conservation and social economy. This article proposes a method which consists of system dynamics model (SDM), Soil and Water Assessment Tool (SWAT) and objective programming model (OPM). It could be used to create insights on basin-wide water problems from a systematic perspective. The case study on Yilong Lake Watershed evaluates the proposed measures in existing local planning, calculates the optimal scheme, and discusses issues including the uncertainty of effectiveness, choice between recycling sewage and transferring outside, and the necessity of restricting food processing industry. This method could be improved on the simulation of social and industrial economy, the simulation of water cycle, and the spatial planning.

Watershed-scale optimum livestock distribution and crop pattern planning constrained to the minimum nitrogen and phosphorus load in the runoff

Sustainable crop and livestock planning encounter serious challenges when tasked with reducing the associated nutrient pollution entering the watershed environment. To overcome these challenges, approaches for specifying optimal crop pattern and livestock distribution to limit the pollution in the catchment are advised. In this research, a simulation-optimization approach is used in which the Soil and Water Assessment Tool (SWAT) is employed for simulating the complex soil-water-plant quantity and quality relations, and the Harmony Search (HS) algorithm linked with SWAT is used to discover the optimal crop pattern and distribution of livestock in the Ilam Dam basin, Iran. In the developed HS-SWAT model, the cultivation area and the number of livestock in SWAT's hydrologic response units (HRU) are the decision variables for maximizing the net benefit obtained from the crop's and livestock's productions, while the nitrate and phosphate calculated in the outflow of the basin are restrained to meet the allowable rates. Results show that the scattered livestock in the basin have a great impact on the generated pollution where about 90% of the nitrate entering the downstream reservoir is the consequence of animal waste. In the optimum state, by reduction of the cultivation area and the number of livestock across the watershed, the concentration of N and P in the surface runoff is reduced significantly to meet the allowable level. According to the results, the HS-SWAT model performance indicates its capability for solving watershed crop pattern and livestock planning problems.

Regional patterns and drivers of total nitrogen trends in the Chesapeake Bay watershed: Insights from machine learning approaches and management implications

Anthropogenic nutrient inputs have led to nutrient enrichment in many waterbodies worldwide, including Chesapeake Bay (USA). River water quality integrates the spatial and temporal changes of watersheds and forms the foundation for disentangling the effects of anthropogenic inputs. We demonstrate with the Chesapeake Bay Non-Tidal Monitoring Network that machine learning approaches - i.e., hierarchical clustering and random forest (RF) classification - can be combined to better understand the regional patterns and drivers of total nitrogen (TN) trends in large monitoring networks, resulting in information useful for watershed management. Cluster analysis revealed regional patterns of short-term TN trends (2007-2018) and categorized the stations into three distinct trend clusters, namely, V-shape (n = 23), monotonic decline (n = 35), and monotonic increase (n = 26). RF models identified regional drivers of TN trend clusters by quantifying the effects of watershed characteristics (land use, geology, physiography) and major N sources on the trend clusters. Results provide encouraging evidence that improved agricultural nutrient management has resulted in declines in agricultural nonpoint sources, which in turn contributed to water-quality improvement in our period of analysis. Moreover, water-quality improvements are more likely in watersheds underlain by carbonate rocks, reflecting the relatively quick groundwater transport of this terrain. By contrast, water-quality improvements are less likely in Coastal Plain watersheds, reflecting the effect of legacy N in groundwater. Notably, results show degrading trends in forested watersheds, suggesting new and/or remobilized sources that may compromise management efforts. Finally, the developed RF models were used to predict TN trend clusters for the entire Chesapeake Bay watershed at the fine scale of river segments (n = 979), providing fine spatial information that can facilitate targeted watershed management, including unmonitored areas. More broadly, this combined use of clustering and classification approaches can be applied to other regional monitoring networks to address similar water-quality questions.

Developing a watershed screening tool to estimate relative contribution of phosphorus to guide management planning

To support the development of clean water plans, as required by the federal Clean Water Act 303(d) program, the New York State Department of Environmental Conservation (DEC) developed the Loading Estimator of Nutrient Sources (LENS) tool. DEC has prioritized clean water planning for fresh waterbodies experiencing negative impacts due to excessive phosphorus levels. LENS, an Excel based tool, combines several simple steady state models into a single screening tool that may be used to estimate the relative contribution of phosphorus sources within a watershed, waterbody response, and recovery potential of a waterbody. To validate that LENS results are reasonable approximations, LENS loading estimates were statistically compared with loading estimates from more complex watershed models that were used to develop existing clean water plans using simple linear regressions. For this comparison, DEC selected a variety of completed models that have modeled watershed phosphorus loads with different land use compositions and loading from both point and nonpoint sources. This analysis shows that LENS performs reasonably well at estimating the relative loading from a range of source sectors, though cannot replace more robust watershed models. DEC has used LENS to prioritize waterbodies for clean water plans and to guide management actions in watersheds where data is lacking to support more complex modeling efforts. Future expansions of LENS may include modifying the tool to estimate other pollutants (i.e. nitrogen), add the ability to account for internal loading of nutrients within waterbodies; and estimate the contribution of nutrients from groundwater.

Linking Water Quality to Drinking Water Treatment Costs Using Time Series Analysis: Examining the Effect of a Treatment Plant Upgrade in Ohio

We estimate a cost function for a water treatment plant in Ohio to assess the avoided-treatment costs resulting from improved source water quality. Regulations and source water concerns motivated the treatment plant to upgrade its treatment process by adding a granular activated carbon building in 2012. The cost function uses daily observations from 2013 to 2016; this allows us to compare the results to a cost function estimated for 2007-2011 for the same plant. Both models focus on understanding the relationship between treatment costs per 1,000 gallons (per 3.79 m3) of produced drinking water and predictor variables such as turbidity, pH, total organic carbon, deviations from target pool elevation, final production, and seasonal variables. Different from the 2007-2011 model, the 2013-2016 model includes a harmful algal bloom toxin variable. We find that the new treatment process leads to a different cost model than the one that covers 2007-2011. Both total organic carbon and algal toxin are important drivers for the 2013-2016 treatment costs. This reflects a significant increase in cyanobacteria cell densities capable of producing toxins in the source water between time periods. The 2013-2016 model also reveals that positive and negative shocks to treatment costs affect volatility, the changes in the variance of costs through time, differently. Positive shocks, or increased costs, lead to higher volatility compared to negative shocks, or decreased costs, of similar magnitude. After quantifying the changes in treatment costs due to changes in source water quality, we discuss how the study results inform policy-relevant decisions.

Particulate PhozzyLogic Index for policy makers-an index for a more accurate and transparent identification of critical source areas

The identification of critical source areas (CSAs) is a key element in a cost-effective mitigation of diffuse emissions of phosphorus from agricultural soils into surface waters. One of the challenges related to CSAs is how to couple complex, data-intensive fate and transport models with easy-to-use information on field level for management purposes at the scale of large watersheds. To fill such a gap and create a bridge between the two tasks, this study puts forward the new Particulate PhozzyLogic Index (PPLI) based on the innovative combination of the results of a complex watershed model (in this case the PhosFate model) with fuzzy logic. Its main feature is the ability to transform the results of diverse scenarios or even models into a final map showing a catchment-wide ranking of the possibility of high PP emissions reaching surface waters for all agricultural fields. Further, this study enhances the PhosFate model with a new algorithm for the allocation of particulate phosphorus (PP) loads entering surface waters to their sources of origin. This is a basic requirement for the identification of critical PP source areas and in consequence for a cost-effective implementation of mitigation measures. By means of a sensitivity analysis, this study investigates the impacts of storm drains, discharge frequencies and flow directions on the designation of CSAs with the help of present-day scenarios for a case study catchment with an area of several hundred square kilometres. The upfront model calibration exhibits a Nash-Sutcliffe efficiency (NSE) of about 0.95 and a modified Nash-Sutcliffe efficiency (mNSE) of around 0.83. A core result of the sensitivity analysis is that the scenarios at least partially disagree on the identified CSAs and suggest that especially open furrows at field borders have the potential to lead to deviating outcomes. All scenario results nevertheless support the 80:20 rule, which states that about 80% of the phosphorus inputs into the surface waters of a catchment originate from only about 20% of its area.

Effects of forest cover pattern on water quality of low-order streams in an agricultural landscape in the Pirapora river basin, Brazil

Low-order streams are important places for river formation and are highly vulnerable to changes in terrestrial ecosystems. Thus, the land-use/land-cover plays an important role in the maintenance of water quality. However, only land-use/land-cover composition may not explain the spatial variation in water quality, because it does not consider land-use/land-cover configuration and forest cover pattern. In this context, the study aimed to evaluate the forest cover pattern effects on water quality on low-order streams located in an agricultural landscape. Applying a paired watershed method, we selected two watersheds classified according to their morphometry and average slope to discard other physical factors that could influence the water quality. Land-use/land-cover pattern was analyzed for composition and forest cover configuration using landscape metrics, including the riparian zone composition. Water quality variables were obtained every two weeks during the hydrological year. This way, watersheds had similar morphometry, slope, and land-use/land-cover composition but differed in forest cover pattern. Watershed with more aggregated forest cover had a better water quality than the other one. The results show that forest cover contributes to water quality maintenance, while forest fragmentation influences the water quality negatively, especially in sediment retention. Agricultural practices are sources of sediment and nutrients to the river, especially in steep relief. Thus, in addition to land-use/land-cover composition, forest cover pattern must be considered in management of low-order streams in tropical agricultural watersheds.

Application of phosphorus loading models to understand drivers of eutrophication in a complex rural lake-watershed system

Several lakes in southwestern Nova Scotia, Canada have experienced reoccurring algal blooms and possess concentrations of phosphorus (P) that are in the eutrophic to hypereutrophic range (>35 μg/L). In this study a mass balance modeling approach was used to evaluate the relative contribution of P sources within these watersheds and lakes. Primary sources of P included land runoff, septic systems, agricultural activities including mink fur farming, aquaculture, as well as internal loading. These sources were assessed for three different study years (1983, 2008, and 2017), based on availability of water quality data, and to quantify the relative impact of the mink farming industry as it rapidly expanded during this time period. A novel method to estimate P loads from intensive fur farming operations was developed, using agricultural census, remote sensing, and publicly available spatial data. A suite of simulations were generated, using a steady state mass balance model, to examine lake P concentrations and sources for baseline conditions (no anthropogenic sources), no mink farming, and varying levels of P retention on mink farms (25%, 50%, 75%) scenarios. An additional scenario was also constructed which involved calibrating mink farm P retention coefficients using available water quality data. In the baseline scenario it was predicted that all study lakes would be oligotrophic, indicating that cultural eutrophication of these lakes has occurred. In the no mink farming scenario, it was predicted that all study lakes would be oligotrophic except for Hourglass Lake, which was predicted to be mesotrophic due to inputs from an aquaculture facility. Internal loading of P from lake sediments was also identified as an important potential P loading mechanism, which will likely be exacerbated by climate change. These findings indicate that the P from mink farms is the primary driver of cultural eutrophication in the study lakes, and highlights the need to consider these nutrient sources within watershed management plans. It is recommended that lake remediation efforts continue to focus on reducing P inputs from mink farms, and on controlling P loading from any new anthropogenic development in these watersheds.

Optimizing invasive species management using mathematical programming to support stewardship of water and carbon-based ecosystem services

Invasive species alter hydrologic processes at watershed scales, with impacts to biodiversity and the supporting ecosystem services. This effect is aggravated by climate change. Here, we integrated modelled hydrologic data, remote sensing products, climate data, and linear mixed integer optimization (MIP) to identify stewardship actions across space and time that can reduce the impact of invasive species. The study area is the windward coast of Hawai'i Island (USA) across which non-native strawberry guava occurrence varies from extremely dense stands in lower watershed reaches, to low densities in upper watershed forests. We focused on the removal of strawberry guava, an invader that exerts significant impacts on watershed condition. MIP analyses spatially optimized the assignment of effective management actions to increase water yield, generate revenue from enhanced freshwater services, and income from removed biomass. The hydrological benefit of removing guava, often marginal when considered in isolation, was financially quantified, and single- and multiobjective MIP formulations were then developed over a 10-year planning horizon. Optimization resulted in $2.27 million USD benefit over the planning horizon using a payment-for-ecosystem-services scheme. That value jumped to $4.67 million when allowing work schedules with overnight camping to reduce costs. Pareto frontiers of weighted pairs of management goals showed the benefit of clustering treatments over space and time to improve financial efficiency. Values of improved land-water natural capital using payment-for-ecosystem-services schemes are provided for several combinations of spatial, temporal, economical, and ecosystem services flows.

Tracking nitrate sources in agricultural-urban watershed using dual stable isotope and Bayesian mixing model approach: Considering N transformation by Lagrangian sampling

A dual isotopes approach and the Bayesian isotope mixing model were applied to trace nitrogen pollution sources and to quantify their relative contribution to river water quality. We focused on two points to enhance the applicability of the method: 1) Direct measurement on the end-members to distinguish "sewage" and "manure" which used to be grouped in one pollution source as their isotope ranges overlap; 2) The Lagrangian sampling method was applied to consider the transport of nitrogen pollutants in a long river so that any fractionation process can be dealt with in the given Bayesian modeling framework. The results of the analysis confirmed the NO₃^- isotope composition in the river of interest to be within the range of NO₃^- with origins in "NH₄⁺ in fertilizer", "Soil N", and "Manure and sewage" pollution. This suggests that nitrogen pollution is mostly attributed to anthropogenic sources. The δ¹⁸O _NO3 value follows the range +2.5∼+15.0‰, implying that NO₃^- in the river is mainly derived from nitrification, and possible nitrification in groundwater or waterfront other than surface water. The ratio of the concentration of δ¹⁵N _NO3 to that of δ¹⁸O _NO3, and the corresponding regression equation indicates that the denitrification effect in surface water was insignificant during the study period. From the results of the contribution ratio of each source, improving the water quality of the discharge from the sewage treatment plants was proved to be the key factor to reduce nitrogen pollution in the river.

Performance of AnnAGNPS model in predicting runoff and sediment yields in Nan Province, Thailand

Land use changes such as deforestation and urban development influences the river discharge, soil erosion and sediment yield. It is important to evaluate tools which can be used to assess such impacts on water and sediment yield. Therefore, this study evaluated the Annualized Agricultural Non-Point Source Pollutant (AnnAGNPS) model's performance in simulating runoff and sediment loads in Nan Province, Thailand using seven years of continuous monitoring data. The river discharge and sediment yield data from 2011–2013 were used for calibration, and data from 2014–2017 were used for validation. Several input parameters were computed using methods suggested by other researchers and previous studies. In this study, the runoff curve number, soil erodibility factor (K), and RUSLE-C value were used to accurately simulate runoff and sediment loads. The results indicate that the model satisfactorily simulated runoff and sediment loads (R² = 0.65 and NSE = 0.53 for runoff volume, and R² = 0.62 and NSE = 0.60 for sediment yields). Moreover, the model estimated the total sediment yield, which contributed 12,932 hundred tons of material to the Nan River in 2017. The maximum sediment yield was obtained below the catchment (Na Noi sub-district, Na Noi district), which corresponds to areas with high crop densities. Cropland generated the highest soil erosion of all investigated land use (87.52% of total soil erosion). Thus, the AnnAGNPS model has the potential to use for investigating management practices to reduce soil erosion and controlling floods and droughts in Nan Province of Thailand.

Nonpoint Source Water Quality Trading outcomes: Landscape-scale patterns and integration with watershed management priorities

Nonpoint source (NPS) water quality trading (WQT) has been lauded as a way to reduce water pollution while mitigating costs, but NPS WQT programs often do not account for cumulative landscape-scale impacts to hydrological and ecological processes. In this work, we parameterize the landscape-scale patterns of an emerging NPS WQT market in Virginia (n = 606 transactions) and describe potential tradeoffs and synergies. We also examine program outcomes in the context of Virginia's spatially-explicit conservation and restoration priorities, and discuss ways in which NPS WQT integrates or fails to integrate with these state-level watershed management goals. These spatial and policy analyses demonstrate novel ways to evaluate NPS WQT programs. Our results reveal how NPS WQT has influenced Virginia land management patterns in practice. Specifically, we show that this program has encouraged the transfer of water quality Best Management Practices (BMPs) from urban to rural areas. Impact sites are often far from mitigation sites, at an average of 164.6 km apart measured along the stream network and most often migrated outside the 8-digit Hydrologic Unit Code watershed boundaries. We also find opportunity for improved integration with the state-level management priorities, including that an estimated 22% of the NPS WQT mitigation site area works against state priorities (for example by converting prime farmland to forest), 9% supports state priorities, and 69% neither negates nor supports state priorities. We suggest policy and management actions that can increase the integration of NPS WQT with statewide watershed management goals, and could ultimately improve environmental returns from this fast-growing program.

Characterizing the river water quality in China: Recent progress and on-going challenges

Food production systems, urbanization, and other anthropogenic activities dramatically alter natural hydrological and nutrient cycles, and are primarily responsible for water quality impairments in China's rivers. This study compiled a 16-year (2003-2018) dataset of river water quality (161,337 records from 2424 sites), watershed/landscape features, and meteorological conditions to investigate the spatial water quality patterns and underlying drivers of river impairment (defined as water quality worse than Class V according to China's Environmental Quality Standards for Surface Waters, GB3838-2002) at a national scale. Our analysis provided evidence of a distinct water quality improvement with a gradual decrease in the frequency of prevalence of anoxic conditions, an alleviation of the severity of heavy metal pollution, whereas the cultural eutrophication has only been moderately mitigated between 2003 and 2018. We also identified significant spatial variation with relatively poorer water quality in eastern China, where 17.2% of the sampling sites registered poor water quality conditions, compared with only 4.6% in western China. Total phosphorus (TP) and ammonia-nitrogen (NH₃-N) are collectively responsible for >85% of the identified incidences of impaired conditions. Bayesian modelling was used to delineate the most significant covariates of TP/NH₃-N riverine levels in six large river basins (Liao, Hai, Yellow, Yangtze, Huai, and Pearl). Water quality impairments are predominantly shaped by anthropogenic drivers (82.5% for TP, 79.5% for NH₃-N), whereas natural factors appear to play a secondary role (20.5% for TP, 17.5% for NH₃-N). Two indicator variables of urbanization (urban areal extent and nighttime light intensity) and farmland areal extent were the strongest predictors of riverine TP/NH₃-N levels and collectively accounted for most of the ambient nutrient variability. We concluded that there is still a long way to go in order to eradicate eutrophication and realize acceptable ecological conditions. The design of the remedial measures must be tailored to the site-specific landscape characteristics, meteorological conditions, and should also consider the increasing importance of non-point source pollution and internal nutrient loading.

Geospatial technology for prioritization of Koyna River basin of India based on soil erosion rates using different approaches

The information about different morphometric parameters of any watershed is necessary for better watershed management and planning. This study aimed to investigate morphometric characteristics, to assess the soil erosion risk, and to prioritize different sub-watersheds of the Koyna River basin, India, with two different approaches using geospatial technology. Different linear, shape, and relief parameters of the basin were estimated and analyzed. The linear and shape parameters indicated that the basin has less flood hazard. The relief parameters indicated that the basin has moderate roughness and unevenness. The parallel drainage pattern is dominant inside the basin due to the highly elongated nature of the basin. The bifurcation ratio (R_b) indicated lithological and geological variations inside the basin. Two different approaches namely morphometric analysis and empirical Revised Universal Soil Loss Equation (RUSLE) method were applied for prioritization of different sub-watersheds. Rainfall, soil, digital elevation model (DEM), and normalized difference vegetation index (NDVI) data were used for identifying erosion-prone zones with RUSLE analysis. Based on RUSLE analysis, the entire study area was divided into five soil erosion risk classes namely very slight (80.43 %), slight (14.94 %), moderate (3.21 %), severe (0.79 %), and very severe (0.63%), respectively. Most of the study area was found to be under a very slight soil erosion vulnerability class based on the RUSLE approach. The conservation practices should be carried out as per the priority ranking of different sub-watershed based on soil erosion rates. The results found in this study can surely assist in the implementation of soil conservation planning and management practices to reduce soil loss in the Koyna River basin of India.

Verifying the applicability of SWAT to simulate fecal contamination for watershed management of Selangor River, Malaysia

The Soil and Water Assessment Tool (SWAT) ecohydrological model was utilized to simulate fecal contamination in the 1937 km² Selangor River Watershed in Malaysia. The watershed conditions posed considerable challenges owing to data scarcity and tropical climate conditions, which are very different from the original conditions that SWAT was developed and tested for. Insufficient data were compensated by publicly available data (e.g., land cover, soil, and weather) to run SWAT. In addition, field monitoring and interviews clarified representative situations of pollution sources and loads, which were used as input for the model. Model parameters determined by empirical analyses in the USA (e.g., surface runoff, evapotranspiration, and temperature adjustment for bacteria die-off) are thoroughly discussed. In particular, due consideration was given to tropical climate characteristics such as intense rainfall, high potential evapotranspiration, and high temperatures throughout the year. As a result, the developed SWAT successfully simulated fecal contamination ranging several orders of magnitude along with its spatial distribution (i.e., Nash-Sutcliffe Efficiency (NSE) = 0.64, Root Mean Square Error-Observations Standard Deviation Ratio (RSR) = 0.64 at six mainstem sites, and NSE = 0.67 and RSR = 0.57 at 12 major tributaries). Moreover, mitigation countermeasures for future worsening of fecal contamination (i.e., E.coli concentration > 20,000 CFU/100 mL for 690 days during nine years at a raw water intake point for Kuala Lumpur [KL] residents) were analyzed through scenario simulations, thereby contributing to discussing effective watershed management. The results propose improving decentralized sewage treatment systems and treating chicken manure with effective microorganisms in order to guarantee water safety for KL residents (i.e., E.coli concentrations <20,000 CFU/100 mL throughout the period, considering Malaysian standards). Accordingly, this study verified the applicability of SWAT to simulate fecal contamination in areas that are difficult to model and suggests solutions for watershed management based on quantitative evidence.

Land use management recommendations for reducing the risk of downstream flooding based on a land use change analysis and the concept of ecosystem-based disaster risk reduction

Sustainable management of ecosystems can provide various socio-ecological benefits, including disaster risk reduction. Through their regulating services and by providing natural protection, ecosystems can reduce physical exposure to common natural hazards. Ecosystems can also minimize disaster risk by reducing social and economic vulnerability and enhancing livelihood resilience. To showcase the importance and usefulness of ecosystem-based disaster risk reduction (Eco-DRR), this study (1) analyzed the land use change in a watershed in central Japan, (2) applied the concept of Eco-DRR, and made land use management recommendations regarding the watershed scale for reducing the risk of downstream flooding. The recommendations that emerged from the application, based on the land use change analysis, are: the use of hard infrastructure and vegetation to store and retain/detain stormwater and promote evapotranspiration is recommended for downstream, urban areas; the sustainable management of upland forest ecosystems and secondary forest-paddy land-human systems, and proactive land use planning in the lowland delta, where built land is concentrated, are key to the watershed-scale landscape planning and management to reduce downstream flooding risks.

Natural and anthropogenic forcings lead to contrasting vegetation response in long-term vs. short-term timeframes

Understanding vegetation response to natural and anthropogenic forcings is vital for managing watersheds as natural ecosystems. We used a novel integrated framework to separate the impacts of natural factors (e.g. drought, precipitation and temperature) from those of anthropogenic factors (e.g. human activity) on vegetation cover change at the watershed scale. We also integrated several datasets including satellite remote sensing and in-situ measurements for a twenty-year time period (2000-2019). Our results show that despite no significant trend being observed in temperature and precipitation, vegetation indices expressed an increasing trend at both the control and treated watersheds. The vegetation cover was not significantly affected by the natural factors whereas the watershed management practice (as a human activity) had significant impacts on vegetation change in the long-term. Further, the vegetation cover long-term response to watershed management practice was mainly linear. We also found that the vegetation indices values in the 2011-2019 period (as the treated period in treated watershed) were significantly higher than those in the 2000-2010 period. In the short-term, however, the drought condition and decreased precipitation (as natural factors) explained the majority of the change in vegetation cover. For example, the majority of the breakpoints occurred in 2008, and it was related to a widespread extreme drought in the area. The watershed management practice as a human activity along with extreme climatic events could explain a large part of the vegetation changes observed in the treated and control watersheds.

Riparian buffer length is more influential than width on river water quality: A case study in southern Costa Rica

Riparian zones are one of the most productive ecosystems in the world, but are at risk due to agricultural expansion and climate change. To maximize return on conservation investment in mixed-use landscapes, it is important to identify the minimum intact riparian forest buffer sizes to conserve riparian ecosystem services. The minimum riparian forest buffer width necessary to maintain tropical river water quality remains unclear, and there is little analysis of effective riparian buffer lengths. Also, in studies on the effect of land use on river water quality globally, there is little standardization in the area where land use is analyzed. Here, these challenges were addressed in the Osa Peninsula in southwestern Costa Rica. Water quality parameters and social variables were sampled at 194 locations across the region. For each sample, land use was calculated in nine different riparian buffer sizes and at the sampling location. Riparian forest cover had a positive effect on water quality parameters, while agricultural cover had a negative effect. The longer the length of the buffer considered, the greater the relative support for influencing water quality (1000 m > 500 m > 100 m). All buffer widths yielded similar support within each length class. These results indicate that length of riparian forest buffers, not width, drives their ability to conserve water quality. While wide and long riparian forests are ideal to maximize the protection of river water quality and other ecosystem services, in landscapes where that is impractical, the 15-m-wide riparian forest buffers that are supported by Costa Rican legislation could improve water quality, providing that they are at least 500 m long. The results also indicate the importance of methodological standardization in studies that monitor land use effects on water quality. The authors propose that studies in similar regions analyze land use in riparian zones 15-m-wide by 1000 m upstream. Conserving and restoring narrow, long riparian forest buffers could provide a rapid, economical management approach to balance agricultural production and water quality protection.

A multicriteria evaluation approach to set forest restoration priorities based on water ecosystem services

Forest plays an important role in keeping water ecosystem services, such as drinking water provision. Thus, payment for ecosystem services is an essential instrument to promote forest restoration in agricultural watersheds. However, funds are limited and must be well planned to ensure water resources conservation and water ecosystem services improvement. In this context, our study aimed to identify priority areas for forest restoration, based on water ecosystem services in agricultural landscapes. For this, we have developed a decision-making support model for agricultural watersheds (in the Atlantic Forest region), based on mixed approaches, that were multicriteria evaluation (MCE) and Participatory Technique. The model will help decision-makers and stakeholders to set priorities for payment for ecosystem services programs implementation. So, we evaluate its application in watersheds with different forest cover patterns to check if it can be applied to different landscape patterns. The base of the model was the following criteria, that were produced with high-resolution data and ranking in the Participatory Technique context, considering their importance for the study: proximity to spring, slope, soil erodibility, topographic index, and land-use/land-cover (LULC). The criteria were aggregated by the Weighted Linear Combination (WLC) method (an MCE method). The priorities maps showed areas classified as high priority near the rivers (at most 200 m far from rivers), on the greatest slopes (>40%), on soils associated with high potential of erosion, and predominantly in agriculture lands. However, this class presented more percentage of the area associated with native forest in the forested watershed (native forest covers 55% of its area) than in the watershed non-forested (native forest covers 25%). Another important point of the final maps was a high percentage of areas associated with the medium class, which is a characteristic of the WLC method. Thus, areas classified as high and medium priority was defined as targets for forest restoration in the watersheds. We can conclude that for small watersheds, the MCE method, with high-resolution data, supports an appropriate prioritization of areas for forest restoration, aiming at the improvement of water ecosystem services. This way, our model can be applied to various payments for ecosystem services schemes in agricultural landscapes worldwide.

Integrating hydrological, landscape ecological, and economic assessment during hydropower exploitation in the upper Yangtze River

Comprehensive investigation of hydrological processes associated with landscape ecology and economic development plays a key role in watershed management, and is less developed in watersheds with large-scale cascade dams. With the abundant hydropower resources and its unprecedented advantages, hydropower exploitation in the upper Yangtze River (Jinsha River) is critical to energy structure adjustment in China. Therefore, we integrated hydrological modeling, landscape ecology analysis, and economic analysis in the dammed Jinsha River. With climate variations in the Jinsha River Basin, the average flow near the uppermost dams in the mainstream grew from 796 m³ s^-1 (1990s), to 918 m³ s^-1 (2000s), and further to 1025 m³ s^-1 (2010s). During 1991 to 2017, the source power in the headwater region grew slightly, but varied little in the downstream area. In the lower dammed Jinsha River, analysis of landscape indicators showed that the landscape was enriched, while the landscape type distribution was more uniform. Moreover, hydropower exploitation brought benefits to regional economic development. Principal component analysis further highlighted the landscape ecological and economic variations with high loadings in the first principal component. With the non-significant temporal variations and normal spatial fluctuations in flow discharge, the landscape pattern was basically stable, and the utilization of hydropower can be sustainable in the Jinsha River. In addition, hydropower development drove local economic development. Based on the integrated analysis of hydrological, landscape ecological, and economic assessment at the watershed scale, our results stressed the significance of hydropower exploitation in the Jinsha River. However, more attention should be paid to the warming climate during hydropower exploitation. These findings are valuable for the scientific planning of hydropower bases in watersheds with large-scale cascade dams, and have substantial implications for sustainable hydropower development.

Stochastic reliability-based risk evaluation and mapping for watershed systems and sustainability (STREAMS)

Mitigating water contamination, improving water security, and increasing sustainability involve environmental awareness and conscientious decision-making by denizens and stakeholders. Achieving such awareness requires visually compelling geospatial decision-making tools that take into account the probabilistic and spatially distributed nature of water contamination. Inspired by the success of weather maps, this paper presents a novel STochastic Reliability-based Risk Evaluation And Mapping for watershed Systems and Sustainability (STREAMS) tool that produces and effectively communicates the risk of water contamination as maps. STREAMS is integrated with ArcGIS geoprocessing tools and uses physics-based reliability theory to compute the spatial distribution of risk, which is defined as the probability of exceeding a safety threshold of water contamination within a watershed. A quantitative analysis of the efficacy of mitigation strategies is conducted by estimating risk reduction from best management practices throughout the entire watershed. Two case studies at different spatial scales are presented, demonstrating STREAMS application to watersheds with varied properties.

Response of non-point source pollution to landscape pattern: case study in mountain-rural region, China

Landscape patterns have a substantial effect on non-point source (NPS) pollution in watersheds. Facilitating sustainable development of mountain-rural areas is a major priority for China. Knowledge of the impacts of various landscapes on water quality in these areas is critical to meeting environmental goals. This study applied the Soil and Water Assessment Tool (SWAT) to create a hydrologic and water quality model of the study watershed; then, the relationship between water quality and landscape patterns was investigated using multiple linear regression and redundancy analysis. The results show that the western sub-basins had higher nitrogen pollution loads, and the total nitrogen concentration reached a maximum value of 3.91 mg/L; the eastern sub-basins had a higher pollution load of phosphorous featured by maximum total phosphorous concentration of 2.15 mg/L. The water quality of the entire watershed in all scenarios tended to deteriorate over time. Landscape metrics accounted for 81.7% of the total variation in pollutant indicators. The percentage of forest landscape was negatively correlated with NPS pollution, while other types of landscape showed a positive correlation. The patch density, landscape shape index, and largest patch index of urban and agricultural lands were negatively correlated with pollutant concentrations. Upland landscapes contributed more pollutants than paddy fields. Some measures, e.g., returning grassland and farmland to forest in steep regions and replacing upland crops with paddy fields, were recommended for mitigating NPS pollution in the study watershed.

Integrating ecosystem services and landscape ecological risk into adaptive management: Insights from a western mountain-basin area, China

There is an increasing interest in introducing ecosystem services (ESs) and landscape ecological risk (LER) into environmental policies and governance. Yet, we know little about how to integrate LER into real decision-making and ESs management. Using the ESs valuation method and the models of InVEST and LER, this study analyzed the spatiotemporal changes of cropland food production, carbon storage, water yield, biodiversity index and LER of Bailongjiang watershed (BLJW), China in 1990, 2002 and 2014, and the relationship between them. We found clear spatial differences in both ESs and LER levels in BLJW during the study period. The cropland food production service kept rising, and the areas of high yield mainly distributed in the loessal regions of BLJW with intensive human population. The carbon storage, water yield and biodiversity index first decreased and then increased. The LER was higher in the areas along the valleys with low elevation and intensive human activities. The regional ecological zoning based on overlay analysis of ESs with LER is effective for providing interactive spatial knowledge for adaptive landscape management. Our results illustrate the integrative approach on linking landscape ecological risk with ecosystem services is a comprehensive and helpful methodology for both regional risk reduction and ecosystem services enhancement at landscape scale.

Emergency response to stormwater contamination: A framework for containment and treatment

This paper presents a Stormwater Emergency Response Framework (SERF) for use in the containment and treatment of stormwater runoff following a hazardous material release. The framework consists of four high level process steps and a decision tree. These resources are intended to assist stormwater managers in fulfilling their emergency response responsibilities within the United States' National Incident Management System. Robust hydraulic and watershed modeling may take weeks to months to develop for a contaminated site, whereas decisions made in the initial hours can have a significant impact on limiting contamination spread. Many web resources are publicly available to assist responders in visualizing stormwater runoff flow paths. A case study provided in this paper also demonstrates how simple calculations may be utilized to estimate peak flows and storage volumes necessary to respond to precipitation events immediately. These calculations are useful for decision makers' allocation of containment and treatment resources within the impacted area. This includes where to deploy available resources to minimize contamination risks to downstream communities and where supplemental resources from outside partners are urgently needed.

Agent-based modelling of water balance in a social-ecological system: A multidisciplinary approach for mountain catchments

The European Alps are known as the 'water towers of Europe'. However, climatic and socioeconomic changes influence both water supply and demand, increasing the need to manage this limited and valuable resource properly to avoid user conflicts and water scarcity. Two major challenges emerge when assessing water scarcity in the Alps: Firstly, mountainous regions are very heterogeneous regarding water availability and demand over space and time, and therefore water scarcity assessments need to be done at low temporal and spatial scales. Secondly, the tight coupling of the natural and the social sphere necessitate an integrative approach considering dynamics and interactions of the social-ecological system. Hence, we applied the agent-based water supply and demand model Aqua.MORE, which is designed for catchment scale and sub-daily temporal resolution, to a case study site in the Italian Alps. In the model, the water supply, the local water managers and water users are represented by interacting model agents. We estimated the water supply by refining the annual runoff data provided by the InVEST water yield model for within-year variations. Local stakeholders contributed to the development of quantitative and spatially-explicit scenarios for land use and tourism evolution. To evaluate water supply and demand dynamics, we assessed six scenarios for the period of 2015 to 2050: three different socio-economic policy pathways, both alone and in combination with a climate change scenario. In all six scenarios, the water demand:supply (D:S) ratio continuously rises from 2015 to 2050.The highest D:S ratio values are prognosed at the beginning of the irrigation period in May. In all scenarios considering climatic changes, the D:S ratio exceeds 20% for several days, indicating potential water scarcity. The simulation results reinforce the importance of analysing water balances at a high temporal resolution and can support management processes and stakeholder dialogues for sustainable watershed management.

Assessment of comprehensiveness of soil conservation measures using the DPSIR framework

The assessment of comprehensiveness of soil conservation measures (SCMs), along with economic, social, and environmental assessments of these projects, is a prerequisite for good governance in a watershed. This study was conducted using the cause-and-effect framework of DPSIR (Driver-Pressure-State-Impact-Response) to assess the comprehensiveness of SCMs in reducing the soil erosion potential of the Kond watershed area and its adverse impacts. Horticultural, mining, and ranching activities; population growth; and road network development were identified as the most important driving forces of the watershed. After determining the indicators, the integrated index was calculated based on weight calculation and standardization of values to detect changes before and after the implementation of SCMs. The results showed a decrease in soil erosion and the corresponding adverse impacts in 2019 compared with the base year, 1997, so that according to the integrated index, the soil erosion status and related impacts have decreased by 16 and 35%, respectively. Despite this decline, the watershed still has a high rate of soil erosion (26.27 t ha^-1 year^-1). This is because SCMs are more focused on improving the state and impacts, and there are no necessary managerial responses to the components of the driving forces and pressures. Given that the proactive approach has less contribution than the reactive approach in SCMs, in addition to the reactive approach, it is necessary to pay more attention to the proactive approach to reduce the soil erosion rate of the watershed and decrease the relevant negative impacts.