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.