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Identifying nitrate sources and migratory pathways is crucial for controlling groundwater nitrate pollution in agricultural watersheds. This study collected 35 shallow groundwater samples in the Nansi Lake Basin (NLB) to identify groundwater nitrate sources and potential health risks. Results showed that NO3− concentration in 62.9% of groundwater samples exceeded the drinking water standard (50 mg/L). Hierarchical cluster analysis (HCA) was used to classify the sampling points into three groups based on hydrochemical and isotopic data. Groups A and C were situated in the eastern recharge and discharge regions of Nansi Lake, while Group B was located in the Yellow River floodplain west of the lake. Hydrochemical data and nitrate stable isotopes (δ15N–NO3− and δ18O–NO3−) indicated that elevated NO3− primarily originated from soil organic nitrogen (SON) in Group A, while manure and sewage (M&S) were the primary sources in Groups B and C samples. Microbial nitrification was identified as the primary nitrogen transformation process across all groups. The source apportionment results indicated that SON contributed approximately 40.1% in Group A, while M&S contributed about 53.9% and 81.2% in Groups B and C, respectively. The Human Health Risk Assessment (HHRA) model indicated significant non-carcinogenic risks for residents east of Nansi Lake, primarily through the oral pathway, with NO3− concentration identified as the most influential factor by sensitivity analysis. These findings provide new perspectives on identifying and handling groundwater nitrogen pollution in agriculture-dominated NLB and similar basins that require enhanced nitrogen contamination management. [ABSTRACT FROM AUTHOR]

The increasing global nitrogen input poses a significant threat to aquatic environments, particularly in agricultural watersheds, where intensive human activities and insufficient water protection infrastructure exacerbate the risk of nitrogen pollution. Accurate identification of nitrogen pollution sources and the associated transformation processes is essential for protecting watershed ecosystems. In this study, a combination of hydrochemical analysis, correlation and principal component analysis, and stable nitrate isotopes (δ15N-NO3− and δ18O-NO3−) were employed to trace nitrogen transport pathways and source contributions in both surface water and groundwater within a typical agricultural watershed. The results revealed the presence of nitrogen pollution, including total nitrogen (TN), ammonia nitrogen (NH3-N), and nitrate nitrogen (NO3−-N), with significant spatial and seasonal variations in both surface water and groundwater. The spatiotemporal evolution of hydrochemical indicators and nitrate isotope compositions highlighted multiple potential sources of nitrogen, including soil input, agricultural input, and manure and sewage input. The results from stable isotope analysis in an R (SIAR) model indicated that ammonium fertilizers (7.1~78.4%) and manure and sewage (2.6~69.7%) were the primary sources of nitrates in surface water, while manure and sewage were the main sources in groundwater (67.9~73.7%). This research demonstrated that nitrification, seasonal variations, and human activities significantly impact nitrogen migration and transformation in agricultural watersheds. However, the issue of groundwater severely polluted by manure and sewage has received insufficient attention. To effectively control nitrogen pollution in agricultural watersheds, it is necessary to improve septic tanks and sewage networks, as well as implement scientific fertilization practices. [ABSTRACT FROM AUTHOR]

Comprehending the impacts of land-use type on soil nutrition and stoichiometry in watersheds is crucial for effective regional ecosystem management. However, a deeper understanding of the influence of land-use type on soil stoichiometry in karst agricultural watersheds is still lacking. Here, we analyzed the contents, stoichiometries, and drivers of topsoil C, N, and P in a karst agricultural watershed in China, focusing on six land-use types: paddy fields, dry farmland, tussock land, shrubland, shrubby tussock land, and woodland. We found that woodland exhibited significantly higher soil organic carbon (SOC) content than other land-use types except shrubland. Moreover, woodland exhibited the highest total nitrogen (TN) and total phosphorus (TP) contents compared with other land-use types. C/N and N/P ratios did not vary significantly with land-use type, whereas dry farmland (18.68) showed a significantly lower C/P ratio than woodland (39), shrubland (39.92), and paddy fields (34.87). In addition, our results revealed that soil pH, catalase and invertase activity, and bacterial and actinomycetes abundance significantly influenced C, N, and P content and stoichiometry. These findings reveal that interactions between multiple biotic and abiotic factors drive variability in soil stoichiometry, offering valuable insight for land improvement and ecological management in karst agricultural watersheds. [ABSTRACT FROM AUTHOR]

This research applies artificial intelligence algorithms for optimizing the water quality monitoring network in a representative basin with intensive agricultural and livestock activities. This study used the water quality database provided by the National Water Commission (CONAGUA). Bi-monthly monitoring was registered from 2013 to 2020 for 23 water quality parameters in 23 sampling locations in tributaries and the mainstream river. Therefore, it was necessary to apply principal component analysis to reduce the dimensionality of the data and thus identify the parameters that contribute most to the variation in the water quality. This artificial intelligence algorithm promoted the ease of clustering sampling sites with similar water quality characteristics by reducing the number of variables involved in the database. The reduction highlighted nutrients (TN and TP), parameters related to dissolved organic matter (NH3-N and TOC), and pathogens such as fecal coliforms. The similarity of sampling sites was determined through hierarchical clustering using the Euclidean distance as a measure of dissimilarity and the Ward method as a grouping method. As a result, nine clusters were obtained for the rainy and dry seasons, reducing approximately 50% of the sampling sites and generating an optimized network of 11 sampling sites. HIGHLIGHTS The monitoring network of a watershed with intensive agriculture was reduced by 50% using artificial intelligence algorithms.; By applying principal component analysis, the variables that contribute the most significant variation to the water quality of the basin, highlighting nutrients, and pathogens were identified.; It was possible to agglomerate sampling sites according to their similarity in terms of water quality.;

Changes of land use, population and climate cause spatial and temporal changes in renewable water resources. For better understanding of the changes and effective management of water resources, hydrological investigations in river catchments are carried out around the world. A special investigation involves a study of hydrological processes in small site-specific catchments. The aim of the study is to analyse three characteristic river flows of a small lowland river on the basis of field surveys over two multiannual periods and to evaluate the applicability of indirect methods for determining characteristic flows in the catchment. Hydrological studies in the small agricultural catchment of the Mławka River, located in the Mławka Hills mesoregion, a part of the North Mazovian Lowland macro-region, have continued since 1966. The recorded data were used to determine daily flows and selected characteristic flows for multiannual periods of 1966–1990 and 1991–2020. To determine characteristic flows with indirect methods, three regional formulae and isorea methods were used. The study showed a decrease in renewable water resources over the period. In the multiannual periods, the average flow at the gauge station of Mławka River decreased by 15.6%. The outflow coefficient decreased from 0.303 to 0.265. The minimum annual flows also decreased by 29.1% and annual maximum flows showed an average increase by 19.7%. The use of indirect methods to determine the mean flow yielded results that converged with those from the second multiannual period.

Despite numerous published literature on the impacts of agriculture on water quality, knowledge gaps persist regarding which farming systems are of most concern for their impact on water quality, which would allow water resource planners to better target water management efforts. Seeking to understand how these relationships vary across different farming systems, we used data on water quality status in watersheds of an agricultural region in southern Portugal and overlaid it with a map of farming systems for the same region provided by a previous study. By intersecting both data layers, we characterized the areal shares of the farming systems in each watershed and inspected how these shares relate to water quality status using logistic regression. The results show that the impact of agriculture on water quality is primarily related to specific farming systems. We believe this type of information can be of significant interest to agricultural planners and policymakers interested in meeting water quality standards, and we conclude this study by suggesting innovative policy options based on payments to farmers operating selected farming systems as a cost-effective way to reconcile agricultural and environmental policy objectives. [ABSTRACT FROM AUTHOR]

This study focuses on the economic value and carbon benefits of riparian buffers in urban drinking water production. The impact of riparian buffers on the waterworks operation in the Raccoon River watershed was quantified using the following metrics: nitrate concentration, days of nitrate removal operation, material and energy cost (based on 17 years of historical records with a watershed model), regression, and cost analysis. The findings indicate that the presence of riparian buffers in agricultural land can substantially decrease nitrate concentration in the water intake of the waterworks during the crop‐growing season: 19% in April, 9% in May, and 11% in June. These reductions mean less nitrate treatment of the plant intake flow: 23% in April, 12% in May, and 3% in June. These changes lead to significant resource savings: 425 metric tons of sodium chloride (NaCl), 147 810 kWh of electricity, 253 metric tons of powdered activated carbon, and 20.8 million liters of fresh water. The buffers would also reduce greenhouse gas emissions by 86.9 metric tons (CO2 equivalent) in 17 years. The total cost saving was estimated at $327 326, with the highest potential savings in May ($215 100), followed by April ($65 465), and June ($46 761). When factoring in buffer installation, cropland loss, nitrate removal, and cost associated with buffer harvest for biofuel in an established biomass market, the benefit to the entire watershed community would be $2.63 million annually. The results underscore the significant cost benefits and environmental benefits associated with cropland riparian buffers in a watershed community. The approach employed in this study holds promise for assessing riparian buffer benefits in other watersheds, contributes to an understanding of sustainable water management practices, and provides a basis for decision making in a wide range of agricultural regions. [ABSTRACT FROM AUTHOR]

Scientific experts from different disciplines often struggle to mesh their specialized perspectives into the shared mindset that is needed to address difficult and persistent environmental, ecological, and societal problems. Many traditional graduate programs provide excellent research and technical skill training. However, these programs often do not teach a systematic way to learn team skills, nor do they offer a protocol for identifying and tackling increasingly integrated interdisciplinary (among disciplines) and transdisciplinary (among researchers and stakeholders) questions. As a result, professionals trained in traditional graduate programs (e.g. current graduate students and employed practitioners) may not have all of the collaborative skills needed to advance solutions to difficult scientific problems. In the present article, we illustrate a tractable, widely implementable structured process called RISE that accelerates the development of these missing skills. The RISE process (Route to Identifying, learning, and practicing interdisciplinary and transdisciplinary team Skills to address difficult Environmental problems) can be used by diverse teams as a tool for research, professional interactions, or training. RISE helps professionals with different expertise learn from each other by repeatedly asking team-developed questions that are tested using an interactive quantitative tool (e.g. agent-based models, machine learning, case studies) applied to a shared problem framework and data set. Outputs from the quantitative tool are then discussed and interpreted as a team, considering all team members' perspectives, disciplines, and expertise. After this synthesis, RISE is repeated with new questions that the team jointly identified in earlier data interpretation discussions. As a result, individual perspectives, originally informed by disciplinary training, are complemented by a shared understanding of team function and elevated interdisciplinary knowledge. [ABSTRACT FROM AUTHOR]

Identifying the nitrogen (N) fate is complicated and a great challenge in karst watersheds because of the co-existence of natural pools and anthropogenic sources. The objective of the study was to use stable isotopic composition of dual-isotope (δ15NNitrate and δ18ONitrate) and LOADEST model approaches to trace N sources, pathways in karst watershed. The study was conducted in the Houzhai watershed, which is a typical agricultural karst watershed from July 2016 to August 2018, to reveal the N fate and the coupled carbon(C)–N processes occurring in the riverine-watershed with agricultural activities. We found that the wet deposition of total nitrogen (TN) flux was 33.50 kg hm−2·a−1 and dissolved nitrogen (DN) flux was 21.66 kg hm−2·a−1. The DN runoff loss was 2.10 × 105 kg·a−1 and the loss of DN during the wet season accounted for 95.4% over a year. In the wet season, NO3−-N daily efflux was 977.62 ± 516.66 kg ha−1·day−1and 248.77 ± 57.83 kg ha−1·day−1 in the dry season. The NH4+-N efflux was 29.17 ± 10.50 kg ha−1·day−1 and 4.42 ± 3.07 kg ha−1·day−1 in the wet and dry seasons, respectively. The main form output load of N was NO3−-N which was more than 30 times as much as NH4+-N output loss. The NO3−-N caused by rainfall contributed 11.82%–53.61% to the export load. Nitrate from soil contributed over 94% of the N to Houzhai river caused by N leaching. In addition, manure and farmland soil were the main sources of groundwater in the Houzhai watersheds, the contribution rates were 25.9% and 22.5%. The chemical N fertilizers affected carbonate weathering strongly, and the HCO3− flux caused by nitrification due to N fertilizers application in soil accounted for 23.5% of the entire watershed. This study suggested that carbonate weathering may be influenced by nitrogen nitrification in the karst watershed.

Comprehending the impacts of land-use type on soil nutrition and stoichiometry in watersheds is crucial for effective regional ecosystem management. However, a deeper understanding of the influence of land-use type on soil stoichiometry in karst agricultural watersheds is still lacking. Here, we analyzed the contents, stoichiometries, and drivers of topsoil C, N, and P in a karst agricultural watershed in China, focusing on six land-use types: paddy fields, dry farmland, tussock land, shrubland, shrubby tussock land, and woodland. We found that woodland exhibited significantly higher soil organic carbon (SOC) content than other land-use types except shrubland. Moreover, woodland exhibited the highest total nitrogen (TN) and total phosphorus (TP) contents compared with other land-use types. C/N and N/P ratios did not vary significantly with land-use type, whereas dry farmland (18.68) showed a significantly lower C/P ratio than woodland (39), shrubland (39.92), and paddy fields (34.87). In addition, our results revealed that soil pH, catalase and invertase activity, and bacterial and actinomycetes abundance significantly influenced C, N, and P content and stoichiometry. These findings reveal that interactions between multiple biotic and abiotic factors drive variability in soil stoichiometry, offering valuable insight for land improvement and ecological management in karst agricultural watersheds.

Classification of remotely sensed imagery for reliable land use and land cover (LULC) remains a challenge in areas where spectrally similar LULC features occur. For example, bare soils of harvested crop fields in agricultural watersheds exhibit spectral characteristics similar to high-intensity developed regions and impede an accurate classification. The goal of this study is to improve the accuracy of LULC classification of satellite imagery for the Big Sunflower River Watershed, Mississippi using ancillary data, multiple classification methods, and a post-classification correction (PCC). To determine the best approach, the methodology was applied to Landsat 8 Operational Land Imager (OLI) imagery during the growing season and post-harvest. Imagery for the growing season was acquired on 25 August 2015, and post-harvest was acquired on 7 January 2018. Three classification methods were applied: maximum likelihood (ML), support vector machine (SVM), and random forest (RF). LULC imagery was classified as open water, woody wetlands, harvested crop, rangeland, cultivated crop, high-intensity developed, and mid-low intensity developed areas. Ancillary data such as normalized difference vegetation index (NDVI), thematic maps of urban areas, river networks, transportation networks, high-resolution National Agriculture Imagery Program (NAIP) imagery, Google Earth time-series data, and phenology were used to determine the training dataset. Initially none of the three classification methods performed adequately. Hence, a post-classification correction (PCC) was implemented by masking and applying a majority filter using thematic maps of urban areas. Once PCC was implemented, the accuracies from each of the classification methods increased significantly with the SVM classification method performing best in both the growing season and post-harvest with an overall classification accuracy of 93.5% with a Kappa statistic of 0.88 in the post-harvest imagery and an overall classification accuracy of 84% with a Kappa statistic of 0.789 in the imagery from the growing season. It was found that SVM was the best classification method while PCC is an effective strategy to implement when dealing with spectrally similar LULC features. The use of SVM together with PCC increased the reliability of the information extracted. Strategies from this study can help to evaluate the LULC in agricultural and other watersheds. [ABSTRACT FROM AUTHOR]

Accurate identification of nitrate (NO3−) sources is the premise of non-point source pollution control in watersheds. The multiple isotope techniques (δ15N-NO3−, δ18O-NO3−, δ2H-H2O, δ18O-H2O), combined with hydrochemistry characteristics, land use information, and Bayesian stable isotope mixing model (MixSIAR), were used to identify the sources and contributions of NO3− in the agricultural watershed of the upper Zihe River, China. A total of 43 groundwater (GW) and 7 surface water (SFW) samples were collected. The results showed that NO3− concentrations of 30.23% GW samples exceeded the WHO maximum permissible limit level, whereas SFW samples did not exceed the standard. The NO3− content of GW varied significantly among different land uses. The averaged GW NO3− content in livestock farms (LF) was the highest, followed by vegetable plots (VP), kiwifruit orchards (KF), croplands (CL), and woodlands (WL). Nitrification was the main transformation process of nitrogen, while denitrification was not significant. Hydrochemical analysis results combined with NO isotopes biplot showed that manure and sewage (M&S), NH4+ fertilizers (NHF), and soil organic nitrogen (SON) were the mixed sources of NO3−. The MixSIAR model summarized that M&S was the main NO3− contributor for the entire watershed, SFW, and GW. For contribution rates of sources in GW of different land use patterns, the main contributor in KF was M&S (contributing 59.00% on average), while M&S (46.70%) and SON (33.50%) contributed significantly to NO3− in CL. Combined with the traceability results and the situation that land use patterns are changing from CL to KF in this area, improving fertilization patterns and increasing manure use efficiency are necessary to reduce NO3− input. These research results will serve as a theoretical foundation for controlling NO3− pollution in the watershed and adjusting agricultural planting structures. [ABSTRACT FROM AUTHOR]

Changes of land use, population and climate cause spatial and temporal changes in renewable water resources. For better understanding of the changes and effective management of water resources, hydrological investigations in river catchments are carried out around the world. A special investigation involves a study of hydrological processes in small site-specific catchments. The aim of the study is to analyse three characteristic river flows of a small lowland river on the basis of field surveys over two multiannual periods and to evaluate the applicability of indirect methods for determining characteristic flows in the catchment. Hydrological studies in the small agricultural catchment of the Mławka River, located in the Mławka Hills mesoregion, a part of the North Mazovian Lowland macro-region, have continued since 1966. The recorded data were used to determine daily flows and selected characteristic flows for multiannual periods of 1966-1990 and 1991-2020. To determine characteristic flows with indirect methods, three regional formulae and isorea methods were used. The study showed a decrease in renewable water resources over the period. In the multiannual periods, the average flow at the gauge station of Mławka River decreased by 15.6%. The outflow coefficient decreased from 0.303 to 0.265. The minimum annual flows also decreased by 29.1% and annual maximum flows showed an average increase by 19.7%. The use of indirect methods to determine the mean flow yielded results that converged with those from the second multiannual period. [ABSTRACT FROM AUTHOR]

Alluvial plain landscapes are some of the most agriculturally productive lands in the world but often have modified stream ecosystems due to cultivation history. This context requires consideration when establishing water quality management goals. We analyzed state water quality databases to demonstrate that Mississippi Alluvial Plain (MAP) ecoregion streams have elevated specific conductivity (SC) and nutrients and lower macroinvertebrate local and regional taxa pools compared to streams in other ecoregions, potentially reducing the efficacy of traditional biomonitoring approaches within the region. To overcome these challenges, we used threshold indicator taxa analysis (TITAN) to compare macroinvertebrate assemblage responses to water quality gradients among ecoregions in Mississippi. We identified individual taxa and assemblage-level responses to increasing water quality degradation in MAP streams. Observed responses occurred at higher concentrations for SC, total organic carbon (TOC) and total phosphorus (TP), but not total nitrogen (TN) relative to other ecoregions. These responses appeared to be driven by a large proportion of indicator taxa considered tolerant or unresponsive in other ecoregions, responding negatively to increasing water quality stressors in MAP streams. Our observed assemblage-level stressor responses to WQ gradients in MAP streams demonstrate shifting tolerance in highly altered ecosystems may require adjustments to recovery expectations but also provide useful measures for monitoring improvements in regional water quality. For example, our observed macroinvertebrate assemblage response to increasing TP identified a management goal similar to guidance based on distributional analysis of water quality data within the MAP ecoregion (0.11 vs 0.128 mg L−1) and thus provide some biological basis for previously identified nutrient goals for the region. Our approach can guide and monitor success of nutrient reduction efforts in MAP watersheds and other alluvial plain agroecosystems where reference conditions do not exist, and local and regional taxa pools are less diverse and may not support full recovery of ecological assemblages. While our results are promising, they should also be compared with more sensitive and less habitat-limited biological assemblages (e.g., algae or bacteria) to better understand complex ecological responses to best management practices designed to increase sustainability of high production agricultural regions.

Conservation practices (CPs) are used in agricultural watersheds to reduce soil erosion and improve water quality, leading to a sustainable management of natural resources. This is especially important as more pressure is applied on agricultural systems by a growing population and a changing climate. A challenge persists, however, in optimizing the implementation of these practices given their complex, non-linear, and location-dependent response. This study integrates watershed modeling using the Annualized Agricultural Non-Point-Source model and a GIS-based field scale localization and characterization of CPs. The investigated practices are associated with the implementation of riparian buffers, sediment basins, crop rotations, and the conservation reserve program. A total of 33 conservation scenarios were developed to quantify their impact on sediment erosion reduction. This approach was applied in an ungauged watershed as part of the Mississippi River Basin initiative aiming at reducing one of the largest aquatic dead zones in the globe. Simulation results indicate that the targeted approach has a significant impact on the overall watershed-scale sediment load reduction. Among the different evaluated practices, riparian buffers were the most efficient in sediment reduction. Moreover, the study provides a blueprint for similar investigations aiming at building decision-support systems and optimizing the placement of CPs in agricultural watersheds. [ABSTRACT FROM AUTHOR]

Dissolved organic carbon (DOC) in inland waters (rivers, reservoirs, lakes, and small ponds) plays a significant role in the global carbon cycle and affects global climate change. In addition, DOC is also a vital indicator of the water environment due to its multiple physical, chemical, and ecological roles. Lakes and ponds of small sizes are abundant on a global and regional scale, and a large increase in ponds is expected with global agricultural land expansion. However, the DOC characteristics of ponds in agricultural watersheds are still unclear, posing a challenge to better understanding the carbon cycle of inland waters. In this study, we explored the DOC variability and their influencing factors in ponds draining different landscapes in a typical agricultural watershed to address the issue. The field measurements over a year showed the DOC concentration varied among ponds draining different landscapes. Specifically, the mean DOC concentrations in the natural pond, sewage pond, aquaculture pond, and irrigation pond were (6.17 ± 1.49) mg/L, (12.08 ± 2.92) mg/L, (9.36 ± 2.92) mg/L, and (8.91 ± 2.71) mg/L, respectively. Meanwhile, monthly measurements found the DOC varied across sampling dates. The DOC variability was positively correlated with nutrients, primary production, and precipitation, suggesting anthropogenic loadings, an internal production rate, and hydrological regime that regulated the substantial variability of DOC in these ponds at the watershed scale. Further, large pollutant discharge and high primary production led to peak DOC occurring in the sewage pond. Our results implied that more attention should be paid to ponds in agricultural watersheds to better understand the roles of inland waters in the global carbon cycle. [ABSTRACT FROM AUTHOR]

The impact of climate change and irrigation management on groundwater resources is of special concern in arid and semi-arid watersheds with intensive irrigation. Additionally, an integrated assessment of groundwater resources is essential to protect aquifers from over-exploitation. This study uses the integrated surface/subsurface hydrologic model SWAT-MODFLOW to quantify the impact of climate change and irrigation pumping schemes on groundwater drawdown for the Neishaboor watershed, Iran. Land use in the Neishaboor watershed is predominantly agricultural, therefore, irrigation plays a crucial role in the water resources balance in the study area. Within the integrated SWAT-MODFLOW model, the pumped groundwater, simulated by MODFLOW, is applied as irrigation water to the cultivated fields within the SWAT plant growth routines, with deep percolation from the soil profile bottom given to the MODFLOW cells as recharge. The developed model was calibrated and tested for the 2000–2010 and 2010–2012 periods, respectively, against measured groundwater level and streamflow data. The tested model is used to investigate the impact of climate change and groundwater pumping on groundwater drawdown under two scenarios: (1) the RCP8.5 pathway (the most pessimistic greenhouse gas emission scenario) and the continuation of the current irrigation trend, and (2) the RCP8.5 pathway with a 40% reduction in irrigation by 2035. Between 2020 and 2035, scenarios 1 and 2 produce a spatially averaged decline in groundwater levels of 20 m and 9.5 m, respectively. The model provides a framework to determine the best management practices for groundwater resources management in the region while minimizing drawdown. [ABSTRACT FROM AUTHOR]

A 3‐year study on erosion and streamflow was conducted in two adjacent paired watersheds that flow into the Passo Real reservoir, one of the largest and most important reservoirs for human water supply and power generation in southern Brazil. The watersheds have similar land use and soil management, but different size and riparian vegetation. The first objective of the study was to monitor and evaluate hydrosedimentological dynamics and effects of riparian vegetation, over a range of rain events, in the two watersheds; the second was to assess the ability of the Limburg Soil Erosion Model (LISEM) to represent these small watersheds in hydrosedimentological terms (runoff and erosion) under individual rain events, in the context of better understanding the role of riparian vegetation and land cover. LISEM is a hydrological model structured on physically based equations that can be used for planning and conservation purposes. Studied rainfall events between 2016 and 2018 had a wide range in total rainfall (10–170 mm), rainfall intensity in 1 h (3–66 mm h−1), stream peak flows (4–5741 L s−1), runoff volume (0.02–40 mm), runoff coefficient (0.1–32%), maximum suspended sediment concentration (20–19 611 mg L−1), and sediment yield (0.002–33.790 Mg km−2). Both watersheds showed a rapid response to rain events with significant runoff generation. Abundance of unpaved roads (often parallel to the slope) promoted high runoff due to channelization effects. South Watershed has 59% more riparian vegetation than North Watershed, but this greater riparian vegetation was not effective in reducing surface runoff and erosion. Furthermore, local adoption of no‐tillage was insufficient to control runoff and sediment yield. [ABSTRACT FROM AUTHOR]

Nitrate (NO3-N) load characteristics in consecutive dry years in the Huai River Basin (HRB), China, were examined using streamflow and NO3-N concentration data. The data set spanned 12 years including three consecutive dry years. Baseflow separation, load estimation, and nonparametric linear regression were applied to separate point source (PS), baseflow, and surface runoff NO3-N loads from the total load. The mean annual nonpoint source (NPS) load was 2.84 kg·ha−1·yr−1, accounting for 90.8% of the total load. Baseflow contributed approximately one-fourth of the natural runoff and half of the NPS load. The baseflow nitrate index (i.e., the ratio of baseflow NO3-N load to total NPS NO3-N load) was 25.4% higher in consecutive dry years than in individual dry years. This study demonstrated that baseflow is the preferential hydrological pathway for NO3-N transport in the HRB and that baseflow delivers a higher NO3-N percentage to streams under long-term drought than under short-term drought. This study highlights the alarming evidence that continuous drought caused by climate change may lead to a higher rate of nitrogen loss in agricultural watersheds. HIGHLIGHTS Baseflow is the preferential hydrological pathway for nitrate transport in the Huai River Basin.; Baseflow delivers a higher percentage of nitrate to streams in consecutive dry years than in individual dry years.; The combination of baseflow separation, load estimation, and nonparametric linear regression provides a convenient method to differentiate the nitrate load from different sources.;

Benthic habitats in shallow oxbow lakes may serve as permanent nitrogen (N) sinks by facilitating denitrification. Oxbow sediments may also accumulate nutrients through uptake, deposition and heterotrophic N2 fixation, and ultimately provide a significant internal source of N and phosphorus (P) through sediment release to the water column. To better understand nutrient source-sink dynamics in oxbow lakes, we explored seasonal and habitat specific patterns in sediment dissolved dinitrogen gas (N2-N) and nutrient flux within an oxbow in the Mississippi Alluvial Plain. Time series models indicate a higher probability of positive N2-N fluxes in fall through spring, significant negative summer fluxes, and clear differences among habitats with net annual N2-N fluxes, ranging from − 2.34 g m−2 Y−1 in open water habitat to 0.26 g m−2 Y−1 in shoreline areas. Integrated lake-wide N2-N sediment flux estimates were negative indicating the significant role of net N2 fixation. More complex models explained similar amounts of variation (Adj. R2 = 0.57 vs. 0.45) and indicated that benthic N2-N fluxes were associated with changes in temperature, dissolved inorganic N, sediment oxygen demand, and sediment carbon:N ratios. Ammonium and P flux from sediments were substantial across all habitats and internal N regeneration far outpaced removal from the system by sediment N2-N flux. Results indicate that nutrient release from sediments generate internal nutrient loads proportional to external loading from the watershed. Our results highlight the significant potential for internal nutrient loading and benthic N2 fixation within sediments to regulate biogeochemical processes within understudied oxbow lake ecosystems. [ABSTRACT FROM AUTHOR]

Small waters, like ponds, are the most abundant freshwater environments, and are increasingly recognized for their function in ecosystem service delivery. In agricultural watershed, artificial ponds play an essential role in reducing nitrogen pollution. However, until now artificial ponds remain the least investigated part of water environments. The importance of microbial activities has seldom been discussed, which makes the microbial pathways and processes rates in nitrogen removal poorly understood. To illustrate the role of artificial ponds in microbial nitrogen removal in agricultural watersheds, 21 pond sediments and 11 soils are collected in an agricultural watershed of China. Results show that surface sediments in ponds carry significantly higher dissolved inorganic nitrogen (9.1–21.9 mg/kg) and total organic matter (64.8–113.0 g/kg) compared to the surrounding agricultural soils. High rates of microbial nitrogen removal in ponds (12.4–25.5 nmol N g−1 h−1) are observed, which are 2–9 times higher than those in dryland soils. In pond sediments, denitrification dominates (> 90% N-loss) the microbial nitrogen removal process with only a minor contribution of anaerobic ammonium oxidation. A high potential of N2O production (up to 9.4 nmol N g−1 h−1) occurs in ponds along with the rapid nitrogen removal. For denitrifier genes, nir gene are always more abundant than nosZ gene. Additionally, the nirS gene is more abundant under flooded conditions, while nirK gene prefers higher dissolved oxygen and NO3− in drylands. These findings highlight the ecosystem function of ponds in agricultural watersheds, and provide new ideas on pollution control and global nitrogen cycling. [ABSTRACT FROM AUTHOR]

Excess nitrogen (N) resulting from human activity causes environmental issues, including eutrophication in agricultural watersheds with intensive livestock farming. Among the N sources in Korea, on-site swine wastewater treatment facilities (OSWTFs) tend to be densely distributed in watersheds with intensive livestock farming. Therefore, it is critical to sustainably manage livestock excreta. This study used the Soil and Water Assessment Tool (SWAT) to investigate the effects of various pollution sources, including OSWTFs, on N loads in rivers in the Cheongmi watershed, which is an intensive livestock farming and agricultural area in Korea. The simulated hydrological and water quality outputs were calibrated and validated for 2012–2019 using Sequential Uncertainty Fitting ver. 2 in the SWAT-Calibration and Uncertainty Program. The hydrological simulations agreed with the observations, with a correlation coefficient (R2) of ≥ 0.8 and Nash–Sutcliffe coefficient of 0.67–0.86. The simulated total N (TN) was also strongly correlated with the observed monthly average loading (R2, 0.36–0.73) and annual average concentration (R2 ≥ 0.5), demonstrating the reliability of the model constructed herein. A simulation of management scenarios indicates that, if the permissible N concentration in effluent from OSWTFs was reduced to 60 mg N/L, the TN concentrations in rivers would decrease by up to 50%. The findings of this study indicate that more stringent effluent water quality standards are required for OSWTFs to protect water quality and aquatic ecosystems in intensive swine farming watersheds. [ABSTRACT FROM AUTHOR]

The bioavailable trace metals are closely related to environmental safety and human health, which might have different source characteristics from the total trace metals in soil. To identify such differences, 31 farmland soil samples were collected from a typical agricultural watershed in East China and analyzed for bioavailable trace metal sources by using chemical fractionation, linear regression, and receptor model. Results showed that the total concentrations of Pb, Cu, Zn, Cr, and Ni in the soils were 1.25–1.59 times higher than watershed background values, but they were all dominated by the residual fraction (63.39–86.36%) according to a modified Community Bureau of Reference (BCR) sequential extraction procedure. Both chemical fractionation and enrichment factors (EFs) indicated a major contribution of the natural source to the total trace metal concentrations in the soils. However, linear regressions revealed that 60.07–89.88% of the bioavailable Pb, Cu, Zn, and Ni concentrations were contributed by anthropogenic sources. Atmospheric deposition and livestock manure were identified as the two major anthropogenic sources, and their contributions were further estimated by using a multiple linear regression of absolute principal component scores (MLR-APCS) model. Together with natural contribution, atmospheric deposition could contribute 74.55–89.86% of bioavailable Pb, Cr, and Ni concentrations. Livestock manure contributed 85.54% of bioavailable Cu and 80.05% of bioavailable Zn concentrations, respectively. These results implied that the bioavailable trace metals were influenced by both anthropogenic and natural sources, but more influenced by anthropogenic sources for bioavailable Pb, Cu, Zn, and Ni in the soils. Special attention should be paid to bioavailable Pb when implementing effective pollution control strategies in this watershed. Moreover, the risk caused by bioavailable trace metal losses from soils to aquatic system should not be ignored. [ABSTRACT FROM AUTHOR]

Abstract Background Aliarcobacter faecis and Aliarcobacter lanthieri are recently identified as emerging human and animal pathogens. In this paper, we demonstrate the development and optimization of two direct DNA-based quantitative real-time PCR assays using species-specific oligonucleotide primer pairs derived from rpoB and gyrA genes for A. faecis and A. lanthieri, respectively. Initially, the specificity of primers and amplicon size of each target reference strain was verified and confirmed by melt curve analysis. Standard curves were developed with a minimum quantification limit of 100 cells mL− 1 or g− 1 obtained using known quantities of spiked A. faecis and A. lanthieri reference strains in autoclaved agricultural surface water and dairy cow manure samples. Results Each species-specific qPCR assay was validated and applied to determine the rate of prevalence and quantify the total number of cells of each target species in natural surface waters of an agriculturally-dominant and non-agricultural reference watershed. In addition, the prevalence and densities were determined for human and various animal (e.g., dogs, cats, dairy cow, and poultry) fecal samples. Overall, the prevalence of A. faecis for surface water and feces was 21 and 28%, respectively. The maximum A. faecis concentration for water and feces was 2.3 × 107 cells 100 mL- 1 and 1.2 × 107 cells g− 1, respectively. A. lanthieri was detected at a lower frequency (2%) with a maximum concentration in surface water of 4.2 × 105 cells 100 mL− 1; fecal samples had a prevalence and maximum density of 10% and 2.0 × 106 cells g− 1, respectively. Conclusions The results indicate that the occurrence of these species in agricultural surface water is potentially due to fecal contamination of water from livestock, human, or wildlife as both species were detected in fecal samples. The new real-time qPCR assays can facilitate rapid and accurate detection in

Agriculturally-driven land use change and hydrologic modifications have influenced solute transport in midwestern U.S. streams. A clear understanding of the mechanisms driving nutrient export from agricultural watersheds will be critical in mitigating diffuse nutrient pollution, given anticipated shifts in hydrology associated with a changing climate. Specifically, more frequent, intense precipitation and altered snow patterns are predicted for the upper Midwest. We used four years of high-frequency nitrate (NO3−–N) sensor data from two tile-drained, agricultural watersheds in Indiana to explore NO3−–N export for 200 storms. We used concentration-discharge (C–Q) relationships and two indices, the hysteresis index (HI) and flushing index (FI), to understand physicochemical controls of NO3−–N export across time scales. On both annual and seasonal time scales, we found NO3−–N concentrations were largely chemostatic; however, patterns in FI suggested C–Q relationships for individual storms were highly variable, which may influence estimates of watershed-scale NO3−–N export. We also found storm NO3−–N export was strongly driven by mobilization of distal sources, given the predominance of counterclockwise hysteresis. In both watersheds, HI and FI values varied seasonally and with storm size, and patterns were linked to changes in hydrologic connectivity related to variation in seasonal tile drain flow. Variation in storm-specific NO3−–N yields was driven by event runoff, storm duration, and antecedent basin moisture, rather than antecedent precipitation. Overall, we found that high-frequency NO3−–N data accurately documented the magnitude of the ecological challenge presented by storm-driven nutrient export in agricultural watersheds. [ABSTRACT FROM AUTHOR]

Phosphorus is the primary eutrophication cause of river, lake, reservoir and estuary and it may be one of the principal pollutants for the agricultural watershed with middle and small cities. The sediment and phosphorus loads, related migration paths and contribution of source regions to receiving waters at different sections of a river basin are not clear. The modified Soil and Water Assessment Tool (SWAT) model was utilized to investigate the phosphorus loads and the relationships among water resources, sediment, and phosphorus loads in one of the important tributaries of the Three Gorge Reservoir (TGR) of China, and to investigate the retention dynamics of phosphorus in the river continuum and the influencing factors. It showed that under the scenario of rice terraces and ponds, the annual sediment loss and total phosphorus load were 125t and 2.5t, being reduced by 40%–80% compared to the natural slope scenario; the daily peak value of suspended sediment load was reduced by 30%–75%, and the relationship between the rainfall and runoff was weakened slightly; the retention rate of phosphorus sources reached 40%–78%. The results confirm that the rice terraces and ponds have altered local hydrological conditions, enhanced a substantial water, sediment, and phosphorus retention capacity that is highly consistent over time and space scales, thereby altering the predominant forms of phosphorus and improving the environmental resilience in soil and nutrition loss for the hilly watershed of the TGR. • Phosphorus and sediment loads are quantitative analyzed in a typical hilly watershed of TGR. • Rice terraces and ponds reduce the particle phosphorus concentration and flux up to 80%. • Response relationship among the flow, sediment and TP in different land use are altered at different degree. • Rice terraces and ponds improved the local environment residence at moderate and relative heavy rainfall. [ABSTRACT FROM AUTHOR]

This landscape investigation is focused on finding the most suitable WetlacultureTM (wetland + agriculture) restoration sites within the former 6700 km2 Great Black Swamp in the western basin of Lake Erie, the shallowest of the Laurentian Great Lakes in North America. The western basin of Lake Erie is now plagued by harmful algal blooms annually due to nutrient discharges primarily from this basin, and water quality was impacted so significantly with toxic cyanobacteria in 2014 that the city of Toledo's water supply was shut off, affecting hundreds of thousands of residents. This study is aimed to estimate the area of suitable WetlacultureTM zones using multi-criteria decision-making GIS model with Analytical Hierarchy Process analysis, especially in agricultural and historic wetland area, with high suitability for flipping farmland to wetlands. A potential indicator GIS model was developed, with various layers of hydrology, soils, and prime farmlands combined, to identify and classify suitable WetlacultureTM areas in the now-drained Great Black Swamp region that could mitigate nutrient inflows to Lake Erie. Overall, the estimated area of highly suitable potential WetlacultureTM restoration areas in the Western Lake Erie Basin and in the Great Black Swamp area is approximately 1000 km2 (4 %) and 800 km2 (13 %), respectively, much larger than the 400 km2 of wetlands that have been suggested as necessary to control the algal blooms in Lake Erie. [ABSTRACT FROM AUTHOR]

Large-scale land cultivation practices for agriculture which disregard conservation principles are resulting in land degradation problems in tropical regions. The differences of environmental condition become the main concern for determining proper strategies to overcome this problem. The present study aimed to evaluate the application of land and water conservation (LWC) practices in tropical agricultural watersheds. The conservation practices (in the form of regreening bare areas and construction of LWC structures i.e. small-scale dam, terrace and stone weir) were performed in a partnership scheme involving government, higher education institution, local inhabitant and private party. The result showed that the partnership approach made conservation activities possible in a shorter time and a lower risk of failure. Economically, it reduced the unit cost of the conservation structures construction up to 70%. We also assessed the dam performance for LWC purpose. The assessment indicated the dam can effectively increase soil water storage and control the river sedimentation. The use of local resources (community and materials for conservation structures) enabled the sustainable of LWC practices on a watershed scale.

A digital elevation model (DEM) is an essential element of input data in the model research of watersheds. Recently, progress in measurement techniques has led to the availability of such data with high spatial resolution. Therefore, simplification of DEMs to shorten the time of their processing is a significant, but insufficiently investigated issue. This study, gradually and with various methods, carried out a great simplification of a detailed LiDAR-derived DEM. Then, the impact of that treatment on the precision of the selected elements for modeling a watershed was assessed. The simplification comprised a reduction in resolution, with the use of statistical resampling methods, namely giving an average, modal, median, minimum, maximum, or the closest value to the pixels. This process was carried out in a wide range of pixel sizes, increasing by 50% each time (from 1 m to 1.5, 2.3, 3.4, 5.1, 7.6, 11, 17, 26, 38, 58, and 86 m, respectively). The precision of the obtained DEMs and the precision of the delineation of boundaries of the watershed and watercourses were assessed. With the systematic reduction in the resolution of a DEM, its precision systematically decreased. The changes in the precision of determining the watercourses and boundaries of a watershed were irregular, ranging from being very small, to mild, to significant. A method of giving the minimum value, that was simple with regard to computing, was singled out. In the determination of both the watercourses and the boundaries of a watershed, this method produced one of the best results for the higher resolution and for the lower resolution—considerably better than the other methods tested. The research was conducted on a flat agricultural catchment, and it can be assumed that the obtained conclusions can be considered for similar cases. For catchments with different characteristics, further research is advisable.

This study investigates the combined effects of land management and hydrology on the temporal dynamics of dissolved organic matter (DOM) quantity and composition in stream water and groundwaters in an agricultural watershed. We assessed dissolved organic carbon (DOC) concentrations, DOM UV–Vis absorbance, and DOM fluorescence in groundwater under cultivated upland, riparian grassland, and riparian woodland land covers, as well as in the stream water at the watershed outlet and livestock-impacted runoff. During one year, stream water and groundwater were monitored weekly to biweekly, complemented by sub-hourly stream sampling during seven storm events. Results showed that: (1) groundwater DOC concentration was lower in cultivated upland (6.4 ± 5.6 mg l−1) than in riparian grassland and woodland (22.4 ± 13.7 mg l−1 and 17.2 ± 9.9 mg l−1, respectively). (2) The proportion of microbially processed compounds decreased in the order upland cropland > riparian grassland > riparian woodland. (3) Principal component analysis (PCA) of groundwater DOM revealed a change in composition indicating that low-aromaticity microbially processed compounds were preferentially exported to the stream. (4) PCA of stream DOM indicated that seasonal increases in groundwater elevation expanded the contributing source areas, thereby increasing the connectivity between upland croplands and the stream, which amplified the effects of cultivation on fluvial DOM during the winter. (5) Storm events occurring after manure application in spring produced hot moments of manure-derived protein-like DOM transport to streams. Together, these results suggest that cultivated uplands in agricultural lands using animal manure as fertilizer may leach more DOM than vegetative buffers. [ABSTRACT FROM AUTHOR]

Copyright of Acta Agriculturae Zhejiangensis is the property of Acta Agriculturae Zhejiangensis Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The irrigated agricultural activity is associated with the massive use of fertilizers and other agrochemicals, which should have a responsible implication for the moderate and efficient consumption of water, as well as the conservation of its quality after being used and released again in the water environment. The objective of this study is to evaluate how the concentration of salts, nitric and ammonium nitrogen evolve in two irrigation seasons, as well as their contaminant load related to the volume of return flows. The study watershed is located in the Idanha-a-Nova County, included in the Idanha Irrigation Project. It has an area of 189 ha, the most representative slopes are between 0 and 4%, the soils are included in Cambisols and Luvisols, and the irrigated crops are mainly tobacco, maize and sorghum. At the watershed outlet a hydrometric and water quality station is installed, that guarantees the evaluation of the runoff and the concentration of pollutants salts and nitrogen. The quality of return flows relative to the pollutants under study, although slightly reduced, is far from compromising their downstream use, showing that if the water derived for agricultural activity is of good quality, it is not significantly degraded when used and released back into the water environment The solubility and mobility characteristics of the contaminants, their availability in the soil, as well as the volume of return flows, determine the dynamics of these contaminants at the level of a small irrigated hydrographic basin. [ABSTRACT FROM AUTHOR]

Streamflow hydrographs summarize the behavior of watersheds. Their separation into quick and slow components requires hydrological knowledge of the specific drainage area. To better understand the hydrological response of 14 small agricultural watersheds in Québec, Canada, covering different physiographic attributes ranging from lowlands to hilly and steep landscapes, streamflow electrical conductivity was used as a geochemical tracer. These agricultural watersheds have undergone significant management practices, including artificial drainage. The objective of this research was to evaluate the performance of existing automated filter methods for hydrograph separation (BFLOW, UKIH, PART, FIXED, SLIDE, LOCMIN, and Eckhardt). The geochemical method was used as a reference for comparison with the filter methods. Comparison of the slow flow estimates from non-calibrated filters, using a MANOVA model, showed that the filter performance increased under conditions with high contributions of quick runoff to the stream, such as during snowmelt (spring season), during heavy precipitation, and in subwatersheds with landscape conditions more prone to quick runoff. However, filter performance decreased as hydrological processes predisposed more flow to slower pathways, typically in summer and fall, as well as in lowland landscapes generally associated with high rates of tile drainage rather than in hilly and steep relief. Underlying the filter assumptions is the classic concept of a rainfall event with quick runoff as the main source of the drainage area response. Thus, slow flow is associated with a low threshold response. Eckhardt filter simulations were in good agreement with the geochemical method after calibration, based on model statistical measures (R, NSE, and PBIAS). However, larger errors were associated with higher flow values. The slow flow overestimations were more pronounced during periods of extreme events, i.e., spring runoff and heavy precipitation. The linear concept of the Eckhardt filter yields no information on slow flow response behavior that could be useful in capturing its temporal variability. Because the routing of water has been managed to improve agricultural productivity, these hydrological modifications resulted in a more complex slow flow response. The performance of filtering methods is thus affected. Therefore, simplifications of filter assumptions are less likely to provide more effective estimates of slow flow. Furthermore, given the heterogeneity of hydrological processes due to seasonal climatic characteristics, the routine application of basic filter concepts is not sufficient to address the variable nature of the hydrological response. The variability scale of geochemical separation, from regional (agro-climatic) to local (adjacent watersheds), proved that it is always relevant to have adequate separation. However, the validation of filters without a tracer is limited and almost unsuitable for these agricultural watersheds. [ABSTRACT FROM AUTHOR]

Background: Aliarcobacter faecis and Aliarcobacter lanthieri are recently identified as emerging human and animal pathogens. In this paper, we demonstrate the development and optimization of two direct DNA-based quantitative real-time PCR assays using species-specific oligonucleotide primer pairs derived from rpoB and gyrA genes for A. faecis and A. lanthieri, respectively. Initially, the specificity of primers and amplicon size of each target reference strain was verified and confirmed by melt curve analysis. Standard curves were developed with a minimum quantification limit of 100 cells mL− 1 or g− 1 obtained using known quantities of spiked A. faecis and A. lanthieri reference strains in autoclaved agricultural surface water and dairy cow manure samples. Results: Each species-specific qPCR assay was validated and applied to determine the rate of prevalence and quantify the total number of cells of each target species in natural surface waters of an agriculturally-dominant and non-agricultural reference watershed. In addition, the prevalence and densities were determined for human and various animal (e.g., dogs, cats, dairy cow, and poultry) fecal samples. Overall, the prevalence of A. faecis for surface water and feces was 21 and 28%, respectively. The maximum A. faecis concentration for water and feces was 2.3 × 107 cells 100 mL- 1 and 1.2 × 107 cells g− 1, respectively. A. lanthieri was detected at a lower frequency (2%) with a maximum concentration in surface water of 4.2 × 105 cells 100 mL− 1; fecal samples had a prevalence and maximum density of 10% and 2.0 × 106 cells g− 1, respectively. Conclusions: The results indicate that the occurrence of these species in agricultural surface water is potentially due to fecal contamination of water from livestock, human, or wildlife as both species were detected in fecal samples. The new real-time qPCR assays can facilitate rapid and accurate detection in < 3 h to quantify total numbers of A. faecis and A. lanthieri cells present in various complex environmental samples. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Agro-Environment Science is the property of Journal of Agro-Environment Science Editorial Board and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

• Optimised configurations of hedgerows reduce discharge volume by up to 97%. • Discharge volume reduction was maximal when hedgerows covered 2% of the watershed. • Optimised configurations performed up to 79% better than random configurations. • Priority locations for vegetated objects were associated with a high upslope area. Ecosystem services provided by vegetated landscape elements (vLEs) are increasingly recognised. One of the services provided is the mitigation of downstream flood risk. Obviously, the type and spatial configuration of vLEs impact the magnitude and timing of the runoff retention. Hence policy programs focused on the conservation and restoration of vLEs would benefit from a capability to determine the optimal spatial configuration of vLEs leading to maximum impact for minimal cost. We integrated the Landlab rainfall-runoff model in an iterative spatial optimisation framework to deal with rasterised linear parcel boundaries whereby the cumulative capability to reduce discharge through the installation of vLEs is the ranking criterion. We applied the procedure to a 191 ha agricultural watershed situated in the Belgian Loess belt encompassing 34 km parcel boundaries. Our results demonstrated that discharge volume can be more effectively reduced when vLEs are implemented based on the priority ranking obtained through our approach compared to both a random positioning of vLEs of the same length and type and the existing vLE configuration. The priority parcel boundaries are mainly located along preferential flow paths, highlighting the importance of the upslope area associated with vLEs and the infiltration enhancement they provoke. The application potential of the optimisation approach is not limited to the topic of finding priority locations for vLEs to reduce discharge but can be applied in a variety of disciplines that require answering questions about the optimal spatial configuration of interventions. [ABSTRACT FROM AUTHOR]

Estimation of soil erosion is of paramount importance due to its serious environmental and societal concern. Soil erosion would have impact on fertility of agricultural land and quality of water. The major objective of this study was to investigate the spatial heterogeneity of annual soil erosion on the grid-cell basis in a small agricultural watershed of eastern India. The study watershed has a drainage area of 973 ha and is subdivided into three sub-watersheds namely: KGSW1, KGSW2 and KGSW3, based on the land topography and drainage network. Average annual soil erosion was estimated on 100 m×100 m grid-cells by integrating universal soil loss equation (USLE) model with GIS for subsequent identification of critical erosion prone areas. It was found that 82.63% area of the total watershed falls under slight-erosion-class (0–5 t-ha−1-yr−1), 6.87% area lies under the moderate-erosion-class (5–10 t-ha−1-yr−1), 5.96% area is under high-erosion-class (10–20 t-ha−1-yr−1), 3.3% area of watershed lies under the very-high-erosion-class (20–40 t-ha−1-yr−1) and 1.24% area falls under “severe-erosion-class” (40–80 t-ha−1-yr−1). The study revealed that the sub-watershed KGSW3 is critical due to the presence of the highest number of critical erosion prone grid-cells. The sediment delivery ratio (SDR) was also estimated to analyze the contribution of sediment yield at the sub-watershed level. Lowest SDR for the whole watershed as compared to sub-watersheds indicates that most of the eroded soil got deposited in rice crop check-basins before reaching the outlet. The reported results can be used for prioritizing critical erosion prone areas and for determining appropriate soil erosion prevention and control measures.

Organic matter (OM) transfers between solid and water phases are critical components of OM cycling in surface waters as they contribute to compositional differences between dissolved OM (DOM) and particulate OM (POM). However, fractionation effects during such phase changes are not well-characterized, especially during the release of soluble OM from sediments and eroded soils. Agricultural practices alter the magnitude and timing of OM export and constitute a major source of sediment through soil erosion. This study assessed the elemental, biomolecular, and optical characteristics of DOM solubilized from sediments and soils in an agricultural watershed of northern California to trace compositional changes during OM flow from mobilized soils in streams. Relative to mineral-bound OM, solubilized DOM was nitrogen-poor (more than doubled C:N ratios) and depleted in amino acids and lignin (three- to six-fold decrease in carbon-normalized yields). Distinct fractionation patterns of individual amino acids and lignin phenols led to a more acidic pool of solubilized DOM that appeared substantially more degraded than its source POM, with decreased degradation index (DI) values and more than doubled molar contributions of non-protein amino acids and processing ratio (PR) values. Lignin composition also greatly differed in solubilized DOM compared to mineral-bound OM, with cinnamyl:vanillyl phenol ratios up to six-fold lower in solubilized lignin than in particulate lignin. Solubilized DOM generally resembled stream DOM more than its source POM and was chemically distinguishable from DOM leached from plants. Absorption coefficients and fluorescence peak intensities were strongly correlated with solubilized DOM concentrations and composition, while optical parameters established to characterize DOM origin and reactivity such as spectral slope, fluorescence index, and carbon-specific fluorescence intensities suggested unique compositional traits for solubilized DOM compared to stream DOM. This study therefore documented strong fractionation patterns during solubilization, linking eroded soil OM and stream DOM and highlighting a pathway that can account for compositional differences between DOM and POM in surface waters. A new amino acid parameter, the Solubilization Index (SI), was defined to capture the effects of solubilization processes on OM composition. SI values in solubilized DOM were up to an order of magnitude higher than in its source POM and were similar to SI values in stream DOM. Because the SI is based on empirical behaviors of individual amino acids, each tied to mechanistic interpretations, the SI is demonstrating a strong potential for mechanistic-driven research on the extent of phase changes in streamwater DOM. [ABSTRACT FROM AUTHOR]

Quantitative identification of anthropogenic trace metal sources in surface river sediments is vital for watershed pollution control and environmental safety. In this study, we developed a reliable approach by integrating enrichment factor (EF), multiple linear regression of absolute principal component scores (MLR-APCS), and Pb stable isotopes, and applied it to a typical hilly agricultural watershed in Eastern China. Results showed that trace metals have accumulated in the river sediments during long-term agricultural development, with special concern of Cu, Ni, Pb, and Cr that may pose adverse biological effects. Among them, Pb was the most anthropogenically impacted trace metal due to its high EF value, but its excessive concentration still did not exceed background concentration. Based on the excessive trace metal concentrations, atmospheric deposition, livestock manure, and chemical fertilizer were identified as the three major anthropogenic pollution sources, and their respective contributions were further estimated by using MLR-APCS model. Together with natural contributions, atmospheric deposition contributed on average 35.3%, 43.1%, and 30.4% of total Ni, Pb, and Cr concentrations in the sediments, respectively. Similarly, livestock manure contributed 41.0% of total Cu and 40.6% of total Zn concentrations, while chemical fertilizer was responsible for 44.3% of total Cd concentration. For Pb, the source contribution of atmospheric deposition to sediment pollution was also quantitatively assessed by isotopic analysis, which was generally close to the value of 43.1% and therefore verified the EF and MLR-APCS results. [ABSTRACT FROM AUTHOR]

The protection of the aquatic environment while managing the risk of water scarcity in the Mediterranean region is challenging. Ensuring future sustainability of water resources needs improved monitoring networks and early warning system of future trends of water quality. A specific concern is given to nonpoint source pollution from agriculture, which is often the main source of water quality degradation in rivers. In this work, we focused on the Joumine river basin, a rural-catchment situated north Tunisia dominated by agricultural activities and exposed to eutrophication problems. Aiming to present an assessment framework of the spatial–temporal water quality variability and quantify "pressure-impact" relationships, we used a physically based modeling approach involving the river/basin integrated model PEGASE (Planification Et Gestion de l'ASsainissement des Eaux). PEGASE simulates watercourses physicochemical quality depending on the morphology of the drainage network, hydrometeorological conditions and natural and anthropogenic influences. Simulation results showed a better description of Joumine river water quality and helped in identifying exposed areas to nutrients export. Results have also emphasized the contribution of different pollution sources. We were able to examine the potential impact of agriculture diffuse pollution and we found that Nitrate is the element mostly threatening water quality. The nutrients patterns suggest that climate and farming practices are important factors controlling their transfer. These findings demonstrate that the adopted assessment approach in investigating the behavior of the studied hydrosystem can be a useful support to develop an appropriate surface water quality management program in a semiarid context. [ABSTRACT FROM AUTHOR]