Agricultural Watersheds Research Articles

Trends in extreme rainfall over the past 55 years suggest springtime subhourly rainfall extremes have intensified in Mahantango Creek, Pennsylvania.

Extreme short-duration rainfall is intensifying with climate warming, and growing evidence suggests that subhourly rainfall extremes are increasing faster than more widely studied durations at hourly and daily timescales. In this case study, we used 55 years (1968-2022) of 5-min precipitation data from Mahantango Creek, a long-term experimental agricultural watershed in east-central Pennsylvania, United States, to examine annual and seasonal changes in subhourly (15-min), hourly, and daily rainfall extremes. Specifically, we evaluated temporal trends in the magnitude and frequency of subhourly, hourly, and daily rainfall extremes. We then estimated apparent scaling rates between rainfall extremes and dew point temperature (Td) and compared these rates to the Clausius-Clapeyron (CC) rate (∼ 7% per °C). We also determined the coincidence of extreme rainfall trends with indicators of atmospheric instability and convective-type precipitation. Overall, we found the most significant changes in rainfall extremes at 15-min durations during the spring, with magnitudes of these subhourly extremes increasing by 0.6 to 0.9% per year, and frequencies rising by 3.4% per year. Apparent scaling rates in the spring showed that 15-min rainfall extremes transitioned from sub-CC scaling to greater than 2CC scaling when Td reached 11° C, implying a possible shift from stratiform rains to more intense convective rains above this Td threshold. Notably, trends in maximum hourly convective available potential energy (CAPE) increased during spring, as did the ratio of 15-min rainfall extremes to their corresponding daily rainfall totals. Findings indicate that convective-type precipitation may be playing an increasing role in the intensification of springtime 15-min rainfall extremes in Mahantango Creek.

Identification of groundwater nitrate sources and its human health risks in a typical agriculture-dominated watershed, North China.

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.

How Do Satellite Precipitation Products Affect Water Quality Simulations? A Comparative Analysis of Rainfall Datasets for River Flow and Riverine Nitrate Load in an Agricultural Watershed

Excessive nitrate loading from agricultural runoff leads to substantial environmental and economic harm, and although hydrological models are used to mitigate these effects, the influence of various satellite precipitation products (SPPs) on nitrate load simulations is often overlooked. This study addresses this research gap by evaluating the impacts of using different satellite precipitation products—ERA5, IMERG, and gridMET—on flow and nitrate load simulations with the Soil and Water Assessment Tool Plus (SWAT+), using the Tar-Pamlico watershed as a case study. Although agricultural activities are higher in the summer, this study found the lowest nitrate load during this season due to reduced runoff. In contrast, the nitrate load was higher in the winter because of increased runoff, highlighting the dominance of water flow in driving riverine nitrate load. This study found that although IMERG predicts the highest annual average flow (120 m3/s in Pamlico Sound), it unexpectedly results in the lowest annual average nitrate load (1750 metric tons/year). In contrast, gridMET estimates significantly higher annual average nitrate loads (3850 metric tons/year). This discrepancy underscores the crucial impact of rainfall datasets on nitrate transport predictions and highlights how the choice of dataset can significantly influence nitrate load simulations.

Identifying and assessing pond best management practice under future climate scenarios

Climate change can play important roles in the hydrological processes within watershed with ponds as the Best Management Practice (BMP). Unlike several other studies, this study integrated remote sensing technique with hydrological model to identify and simulate pond BMP. Limited studies have been carried out to evaluate pond BMP in relation to the climate change impacts on hydrology and water quality particularly in Mississippi watersheds. The objective of this study was to classify ponds on satellite imagery within the Big Sunflower River Watershed (BSRW) using Google Earth Engine (GEE) and incorporate this data with Soil and Water Assessment Tool (SWAT) model to evaluate future hydrological and water quality outputs. The SWAT model was calibrated and validated against streamflow (R2 and NSE values from 0.81 to 0.56) and sediment (R2 and NSE values from 0.91 to 0.40). Future climate data for the mid (2040–2060) and late (2079–2099) centuries were utilized to create climate change scenarios (e.g., RCP 4.5 and 8.5). Results of this study projected that the average annual flow and sediment load will increase by 26–46%, and 107-150% respectively by the late century compared to the baseline period (2002–2021). However, the projected sediment load with modified pond BMP data used in the SWAT model could decrease average annual sediment load by 44–46% under both RCP scenarios. Seasonal data analysis determined that spring, summer, and fall sediment loads were projected to decrease up to 42%, 52%, and 46% respectively under both RCP scenarios due to pond BMP. This study can be useful for the development of climate-smart management strategies in agricultural watersheds.

Combined impacts of climate and land use scenarios on sediment loads in small agricultural watershed in Tunisia

This study investigates the impact of conservation practices, specifically mulching and terracing, on soil erosion in the Kamech watershed (2.6 km²) situated in the Cap Bon region of northeastern Tunisia, under both current and future climate scenarios. Utilizing the Soil and Water Assessment Tool (SWAT) model, the research evaluates the effectiveness of these Best Management Practices (BMPs) in reducing soil loss, revealing significant reductions of 1.5 t ha⁻¹ yr⁻¹ for mulching and 2 t ha⁻¹ yr⁻¹ for terracing. The findings indicate that these practices play a crucial role in enhancing soil conservation amidst climate change challenges, including altered precipitation patterns and increased temperatures. Additionally, the study highlights a notable decline in average monthly rainfall projected for the period 2051 to 2100 under the RCP8.5 scenario, further emphasizing the importance of implementing effective soil management strategies. This paper indicates that both methods, mulching and terracing, significantly contribute to reducing soil erosion under future scenarios (2051-2100). Their implementation proves essential for effective soil conservation, helping to mitigate the impacts of climate change and maintain soil health in the Kamech watershed. The results contribute to a better understanding of BMP performance in addressing soil erosion, water quality, and hydrological responses in the face of evolving environmental conditions. By enhancing our understanding of these interactions, this research aims to provide valuable insights for sustainable watershed management, particularly in regions prone to water scarcity and land degradation.

Quantifying the impact of a constructed wetland on downstream nitrate concentrations and loads in the U.S. Midwest

Constructed wetlands are standard conservation practices used to reduce nitrate loads in agricultural watersheds. Many studies have examined the efficiency of denitrification in wetlands under various scenarios, but quantifying the watershed-scale impact of wetlands on downstream nitrate levels is rarely done using field observations. In this study, we estimated nitrate removal in a constructed wetland in the headwaters of Mud Creek, a HUC12 watershed in eastern Iowa, from May–September 2022 and May–September 2023 (a ten-month period). We also measured nitrate loads at four successive downstream sites, three along Mud Creek and one below its confluence with the larger Cedar River. The wetland removed 6,200 kg of nitrate (74% of total inputs). At the three downstream locations in Mud Creek, the percentage of each site’s total nitrate load removed by the wetland decreased to 19, 8.6, and 4.1%—this latter value represents the wetland’s influence on nitrate removal in the entire Mud Creek basin. The wetland’s impact of nitrate loads in the Cedar River was negligible (reduction of 0.02%). The percentage of a site’s drainage area treated by the wetland approximately followed a 1:1 relationship to that site’s percent reduction in nitrate. Profiles of nitrate concentrations in Mud Creek notably varied pre- and post-wetland. Concentrations before the installation steadily decreased along the waterway, while post-wetland concentrations rapidly decreased directly downstream of the wetland and steadily increased at each succeeding site. Our results demonstrate that while the wetland successfully lowered local nitrate levels, its effect on the basin’s overall nitrate loads was minimal. Achieving nutrient reduction goals at the watershed scale solely using constructed wetlands appears infeasible given that the required number of practices greatly exceeds current efforts.

An Integrated Spatial Fuzzy‐Based Site Suitability Assessment Framework for Agricultural BMP Placement

ABSTRACTAssigning crisp class boundaries to landscape features can result in the loss of vital information for land evaluation objectives, especially when these boundaries lack clear definitions. This challenge becomes particularly pronounced when land suitability is assessed for implementing agricultural best management practices (BMPs)—conservation measures aimed at reducing the environmental risks of farming activities to aquatic ecosystems while simultaneously achieving water quality and economic objectives. To address the limitations associated with Boolean suitability assessment frameworks, we have introduced an integrated spatial, fuzzy‐based land evaluation framework that considers a range of hydrological and economic determinants for BMP placement. By employing data‐driven fuzzy membership functions and overlay operators, this framework generates a joint suitability index for BMP placement across agricultural watersheds. The application of the proposed framework to the Thames River Watershed in southwestern Ontario, Canada, produced the first joint suitability index of the watershed. Further analysis of the average farm‐level joint suitability scores identified statistically significant clusters of highly suitable and unsuitable lands for BMP placement, with 85% of highly suitable lands being situated in the upper basin areas. The proposed framework is adaptable to various agricultural production geographies, especially in data‐limited environments, allowing for strategic BMP placement to mitigate the global impacts of anthropogenic nutrient loadings on aquatic ecosystems. For optimal results, context‐specific applications should prioritize research on locally relevant fuzzy membership functions and BMP implementation drivers.

Assessing Organochlorine Pesticide Behavior in Agricultural Watershed Soil, Water and Sediment: A Dynamic Modeling Approach

ABSTRACT The utilization of pesticides has experienced a substantial rise in order to enhance both the quantity and caliber of the produced goods. Agricultural runoff, a major source of nonpoint pollution, adversely impacts surface water, groundwater, soil and sediment quality in the watershed. Especially, organochlorine pesticides have adverse effects on the environment because of their toxicity, persistence and bioaccumulation. In this study, the presence of organochlorine pesticides (DDTs- dichlorodiphenyltrichloroethane and HCHs- hexachlorocyclohexane) in the environment of the dryland agricultural watershed, was determined. For this purpose, soil, sediment and water samples from the landscape of pond were collected. The concentrations of organochlorine pesticides in water, sediment, and soil ranged from 0.0005 to 0.0138 μg/L, 0.03 to 1.02 μg/kg, and 0.54 to 52 μg/kg, respectively. The persistence of these pesticides in soil and sediment poses long-term risks to both terrestrial and aquatic ecosystems. Sediment, as a significant reservoir for these contaminants, can act as a secondary source of pollution, releasing pesticides back into the water column under certain environmental conditions. Similarly, soil contamination not only affects plant health and productivity but also leads to further leaching and runoff into water bodies. The behavior of a toxic substance in water, soil and sediment environment, which is organochlorine pesticide, in a well-mixed lake watershed, was modeled using mass balances in the lake. Statistical analysis, including a paired t-test and calculation of the Nash-Sutcliffe index, confirms the consistency and reliability of the model’s predictions compared to observed data. Simulated concentrations closely matched observed values, and the distribution patterns and trends remained consistent across different months. Moreover, the Risk Quotient (RQ) for DDTs and HCHs is less than 0.1, indicating low ecological risk.

High resolution concentration-discharge relationships in managed watersheds: A 30+ year analysis

Concentration-discharge (C-Q) relationships provide insight into solute transport and biogeochemical processes for watersheds. A 30+ year, high-resolution dataset from the North Appalachian Experimental Watershed (NAEW) offers an unparalleled opportunity to explore land use and land management impacts on C-Q relationships for small watersheds of varying land management histories (agricultural to forested). The NAEW was among the few hydrologic research sites where storm event runoff was sampled using proportional sampling. This method captures the concentration-discharge behavior associated with land use more effectively than instantaneous sampling, which favors rising limb or falling limb dynamics. In this study, we explore C-Q relationships by investigating baseflow and storm event flow across their total behavior. We also build a systems-understanding by comparing chemostatic behavior to soil geochemistry and land use history. Highly managed agricultural watersheds with no associated stream baseflow demonstrate near-chemostatic behavior for most solutes, while mixed use and forested watersheds with associated streams are more mutable depending on whether primary sources of water were groundwater or surface water. Using this unique high-resolution dataset, we show that concentration-discharge relationships are influenced by soil and baseflow geochemistry, pore fluid concentration, and land type/land use legacy effects.

Nitrogen Transport Pathways and Source Contributions in a Typical Agricultural Watershed Using Stable Isotopes and Hydrochemistry

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.

Subsurface influences on watershed nutrient concentrations and loading in a clay dominated agricultural system

Water quality issues in the Great Lakes Basin persist despite management and monitoring efforts. With changing land use and climatic conditions, the need for improved understanding of nutrient loss from agricultural field to surface water is imperative to reduce consequences on human and aquatic life, such as perpetual algal blooms and contaminated drinking water. There remains a gap in holistic rural water management studies that investigate the understanding of the water cycle in rural settings and the interconnections between different components of the water cycle, including artificial drainage. In the current study, a year-round paired investigation of subsurface and nutrient dynamics was conducted in a small, intensively managed agricultural watershed within southwestern Ontario, Canada. Nutrients (Nitrate and Phosphorus) and stable isotopes of water (δ2H and δ18O) were sampled at varying scales (i.e., field and watershed), from multiple hydrologic components (e.g., groundwater, surface water, tile flow, and soil water), from 2020 to 2022. Results indicate that nutrient concentrations in surface water were elevated during the growing season, while nutrient loading was greater during the non-growing season in surface water. Monthly nitrate loads were found to be significantly (p < 0.01) related to groundwater elevation, soil moisture and tile flow, whereas total phosphorus loading was found to be significantly (p < 0.01) related to soil moisture and tile flow. δ2H and δ18O signatures revealed that during the growing season nutrient movement was predominantly through interflow pathways (including tile drainage) comprised of event-water. In the non-growing season, there was an increased subsurface influence on nutrient transport. This study highlights the importance of including subsurface characterization in nutrient management studies. A comprehensive understanding of varying seasonal hydrologic mechanisms that control nutrient movement within an agricultural watershed is essential to sustain growing rural communities.

Mutual impact of salinity and climate change on crop production water footprint in a semi-arid agricultural watershed: Application of SWAT-MODFLOW-Salt

Sustainable agriculture in intensively irrigated watersheds, particularly those in arid and semi-arid regions, requires enhanced management practices to maintain crop production, which depends on climate, available water resources, soil conditions, irrigation practices, and crop type. Among these factors, soil salinity and climate change are significant challenges to agricultural productivity. To investigate the long-term influence of salinity and climate change on crop production from 1999 to 2100 in irrigated semi-arid regions, we apply the water footprint (WF) concept using the hydro-chemical watershed model SWAT-MODFLOW-Salt, driven by five General Circulation Models (GCMs) and two climate scenarios (RCP4.5 and RCP8.5), to a 732 km2 irrigated stream-aquifer system within the Lower Arkansas River Valley (LARV), Colorado, USA. The study focused on calculating the green (WFgreen), blue (WFblue), and total (WFtotal) crop production WFs for 29 crops in the region, with and without including salinity effect on crop yield. Results reveal that during the baseline period (1999–2009), the total annual average WFgreen, WFblue, and WFtotal increased by 7.6 %, 4.4 %, and 6.5 %, respectively, under salinity stress, as crops experienced reductions of up to 4.6 %, 1.6 %, and 2.3 % in green, blue, and total crop yield. The mutual impact of salinity and the worst-case climate model (IPSL_CM5A_MR) under the higher emission scenario (RCP8.5) led to a 3.3 %, 1.9 %, and 3 % increase in green, blue, and total crop production WFs. Furthermore, the study highlighted that the proportion of green, blue, and total crop production WFs in the LARV exceeded the world average. This discrepancy was attributed to various factors, including different spatial and temporal crop distribution, irrigation practices, soil types, and climate conditions. Notably, salinity stress affected green crop yield and green WF more significantly than blue crop yield and blue WF across all GCM models. This finding underscores the importance of prioritizing management practices to control salinity-associated challenges within the region.

Development of an inclusive, scalable, and flexible hydrologic modeling system: Establishing integrated flood simulation system at agricultural watersheds

In this study, we developed a comprehensive hydrological modeling system to address the diverse needs of hydrologists and researchers. The system comprised nine modules, each serving a specific purpose. These modules include a multiplicative random cascade model, frequency analysis, inflow simulation, Hydrologic Engineering Center – 5, Hydrologic Engineering Center – River Analysis System, and farmland drainage simulations. The system follows a structured sequence within a large framework, beginning with user inputs for the initial condition information and period specifications for frequency analysis. It then calculates the time-disaggregated precipitation data utilizing the Dask distributed server for efficient computation. Subsequent module computations were conducted on dedicated mask workers. The Integrated Database serves as a comprehensive repository for simulation studies, encompassing historical precipitation data, shared socioeconomic pathways, climate change scenario data, and reservoir and farmland survey data. This system has been used in several studies and has provided cohesive and reliable results for flood simulations.

Mainstream Planting Systems Influence Spatiotemporal Variations in the Soil Quality of Watershed Sloping Farmland

Mainstream planting systems of watershed sloping farmland span the globe and are closely related to the variations in the soil quality of watershed sloping farmland. However, little information is available about how mainstream planting systems influence spatiotemporal variations in the soil quality of watershed sloping farmland. The soil of 0–20 cm was collected at fixed points in three mainstream planting systems (a low-altitude citrus orchard system, a mid-altitude double-cropping system, and a high-altitude single-cropping system) at a fixed time each year for 15 years in a typical agricultural watershed of the Three Gorges Reservoir area of China. Fourteen physicochemical properties of the sampled soil were measured. We found that (1) the soil quality indexes of the citrus orchard system, double-cropping system, and single-cropping system decreased from 0.75, 0.71, and 0.67 in 2004 to 0.68, 0.57, and 0.55 in 2019, respectively; (2) the order of the six master control factors influencing soil quality was sand content &gt; bulk density &gt; total nitrogen &gt; clay content &gt; pH &gt; total phosphorus in the citrus orchard system, sand content &gt; bulk density &gt; clay content &gt; pH &gt; total phosphorus &gt; total nitrogen in the double-cropping system, and sand content &gt; clay content &gt; total phosphorus &gt; pH &gt; bulk density &gt; total nitrogen in the single-cropping system; and (3) the total effects of soil erosion and fertilization on soil quality were −0.496 and −0.308 in the citrus orchard system, −1.254 and 0.371 in the double-cropping system, and −0.844 and 0.013 in the single-cropping system, respectively. We suggest that the three mainstream planting systems influence soil quality through variations in their master control factors caused primarily by soil erosion and secondarily by fertilization. These findings are important for controlling soil degradation through controlling soil erosion and rational fertilization in watersheds.

Large variations of dissolved carbon occurred in small ponds within an agricultural watershed

Dissolved organic carbon (DOC) and dissolved inorganic carbon (DIC) significantly affect the aquatic carbon budget and ecosystem functions. Small ponds are abundant globally and widely distributed especially in agricultural watersheds, however, the variability of DOC and DIC, along with their driving factors, remains poorly understood, which likely hampers the understanding of carbon cycle of inland waters. The presented study was designed to fill the knowledge gap based on a detailed year-long field investigation via examining DOC and DIC concentrations across ponds with differing functionalities (e.g. sewage ponds, irrigation ponds, and natural ponds) of a typical agricultural watershed in eastern China. Our results found a pronounced impact of human activities on pond DOC and DIC, with higher DOC occurring in sewage ponds (10.84 ± 2.83 mg L−1) and irrigation ponds (9.09 ± 2.57 mg L−1) and peak DIC in irrigation ponds (20.36 ± 2.49 mg L−1) compared to that at natural ponds (DOC: 7.54 ± 2.55 mg L−1; DIC: 11.16 ± 3.85 mg L−1) with less human activity. The positive correlations between DOC/DIC and key environmental variables (e.g. nutrients and chlorophyll-a) further demonstrated that human activity can either directly increase the carbon concentrations via pollutant discharge, or indirectly increase DOC concentration via stimulating primary production. Meanwhile, field measurements found precipitation and temperature play roles in determining the carbon variability. Specifically, precipitation increased the DOC of these ponds via enhancing land-based carbon inputs, and decrease the DIC of irrigation ponds via diluting. Temperature can influence the carbon dynamics through increasing primary productivity and metabolism. Our study underscores the roles of human and natural influences in determining the large variations of DOC and DIC in small ponds, which should be considered to better understand the carbon dynamic variability of human-impacted small aquatic systems.

Impacts of climate change and best management practices on nitrate loading to a eutrophic coastal lagoon

Anthropogenic climate change and associated increasing nutrient loading to coasts will worsen coastal eutrophication on a global scale. Basin Head is a coastal lagoon located in northeastern Prince Edward Island, Canada, with a federally protected ecosystem. Nitrate-nitrogen (NO3-N) is conveyed from agricultural fields in the watershed to the eutrophic lagoon via intertidal groundwater springs and groundwater-dominated tributaries. A field program focused on four main tributaries that discharge into the lagoon was conducted to measure year-round NO3-N loading. These measurements were used to calibrate a SWAT+ hydrologic model capable of simulating hydrologic and NO3-N loads to the lagoon. Several climate change scenarios incorporating different agricultural best management practices (BMPs) were simulated to better understand potential future NO3-N loading dynamics. Results indicate that all climate change scenarios produced increased annual NO3-N loading to the lagoon when comparing historical (1990–2020) to end of century time periods (2070–2100); however, only one climate scenario (MRI-ESM2-0 SSP5-8.5) resulted in a statistically significant (p-value &amp;lt;0.05) increase. Enlarged buffer strips and delayed tillage BMP simulations produced small (0%–8%) effects on loading, while changing the crop rotation from potato-barley-clover to potato-soybean-barley yielded a small reduction in NO3-N loading between the historical period and the end of the century (26%–33%). Modeling revealed changes in seasonal loading dynamics under climate change where NO3-N loads remained more consistent throughout the year as opposed to current conditions where the dominant load is in the spring. An increase in baseflow contributions to streamflow was also noted under climate change, with the largest change occurring in the winter (e.g., up to a five-fold increase in February). These findings have direct implications for coastal management in groundwater-dominated agricultural watersheds in a changing climate.

Antibiotic resistome dynamics in agricultural river systems: Elucidating transmission mechanisms and associated risk to water security

Usage of antibiotics in agriculture has increased dramatically recently, significantly raising the influx of antibiotic resistance genes (ARGs) into river systems through organic manure runoff, seriously threatening water security. However, the dynamics, transmission mechanisms, and potential water security risk of ARGs, as well as their response to land use spatial scale and seasonal variations in agricultural river systems remain unclear. To address these challenges, this work employed metagenomic technique to systematically evaluate the pollution and dissemination of ARGs in overlying water and sediment within a typical agricultural catchment in China. The results demonstrated significant differences between overlying water and sediment ARGs. Overlying water dominated by multidrug ARGs exhibited higher diversity, whereas sediment predominantly containing sulfonamide ARGs had higher abundance. The dynamics of ARGs in overlying water were more responsive to seasonal variations compared to sediment due to greater changes in hydrodynamics and nutrient conditions. The profiles of ARGs in overlying water were largely regulated by microbiota, whereas mobile genetic elements (MGEs) were the main forces driving the dissemination of ARGs in sediment. The variation in dissemination mechanisms led to different resistance risks, with sediment presenting a higher resistance risk than overlying water. Furthermore, Mantel test was applied to discover the impact of land use spatial scale and composition on the transmission of ARGs in river systems. The findings showed that cultivated land within 5 km of the riverbank was the key influencing factor. Cultivated land exacerbated ARGs spread by increasing MGEs abundance and nutrient concentrations, resulting in the abundance of ARGs in high-cultivated sites being twice that in low-cultivated sites, and raising the regional water security risk, with a more pronounced effect in sediment. These findings contribute to a better understanding of ARGs dissemination in agricultural watersheds, providing a basis for implementing effective resistance control measures and ensuring water security.

A methodological framework for assessing sea level rise impacts on nitrate loading in coastal agricultural watersheds using SWAT+: A case study of the Tar-Pamlico River basin, North Carolina, USA

This study addresses the urgent need to understand the impacts of climate change on coastal ecosystems by demonstrating how to use the SWAT+ model to assess the effects of sea level rise (SLR) on agricultural nitrate export in a coastal watershed. Our framework for incorporating SLR in the SWAT+ model includes: (1) reclassifying current land uses to water for areas with elevations below 0.3 m based on SLR projections for mid-century; (2) creating new SLR-influenced land uses, SLR-influenced crop database, and hydrological response units for areas with elevations below 2.4 m; and (3) adjusting SWAT+ parameters for the SLR-influenced areas to simulate the effects of saltwater intrusion on processes such as plant yield and denitrification. We demonstrate this approach in the Tar-Pamlico River basin, a coastal watershed in eastern North Carolina, USA. We calibrated the model for monthly nitrate load at Washington, NC, achieving a Nash-Sutcliffe Efficiency (NSE) of 0.61. Our findings show that SLR substantially alters nitrate delivery to the estuary, with increased nitrate loads observed in all seasons. Higher load increases were noted in winter and spring due to elevated flows, while higher percentage increases occurred in summer and fall, attributed to reduced plant uptake and disrupted nitrogen cycle transformations. Overall, we observed an increase in mean annual nitrate loads from 155,000 kg NO3-N under baseline conditions to 157,000 kg NO3-N under SLR scenarios, confirmed by a statistically significant paired t-test (p = 2.16 × 10−10). This pioneering framework sets the stage for more sophisticated and accurate modeling of SLR impacts in diverse hydrological scenarios, offering a vital tool for hydrological modelers.

Size-dependent of phosphorus loss and migration driven by rainfall: Evidences from observation and stochastic simulation

A deep understanding of the loss and migration of various sizes of phosphorus (P) is crucial for the effective management of nutrients in agricultural watersheds. In this study, three P species including large-particle phosphorus (LPP, >1 μm), colloidal phosphorus (CP, 1 nm–1 μm), and dissolved phosphorus (DP, <1 nm), were observed and simulated. Then the size-dependent of nonpoint source P (NPS-P) process was discussed at both field and watershed scales. Finally, a stochastic rainfall algorithm was developed to investigate different P species driven by rainfall. The results indicated the losses of LPP, CP, and DP under different land use patterns differ markedly, whereas paddy fields are hotspots of CP loss. Sloping farmlands typically exhibit greater losses of DP and LPP, while CP account for 13 %–38 % of total P losses. At the watershed scale, the contribution of CP riverine inputs ranged from 13 % to 40 % due to its mobility and special feature. Compared with LPP, CP has an extended half-decay distance and is more capable of being transported to water bodies. Heavy rainfall significantly increases the contribution of CP to NPS-P. At rainfall levels of 300 mm, the contribution of CP riverine inputs from paddy fields can be up to 47.4 %. The findings provide novel insights into future agricultural nutrient management and NPS-P control from the perspective of the size effect.

Evaluating the spatiotemporal variation of Ba River water quality in the agricultural and urban watershed in the highland of Vietnam.

The Ba River in Vietnam has been facing pollution due to waste generation from agricultural and urban areas. This study focuses on evaluating the spatiotemporal variations in river water quality based on physicochemical characteristics and pesticide parameters for different seasons in 2022-2023. The results indicate that the concentrations of most parameters in the rainy season were higher than those in the early-dry and dry seasons due to the non-point sources in agricultural areas. Notably, the analysis of pesticide residue in both the rainy and dry seasons revealed low levels of chlorpyrifos (ethyl), and deltamethrin was detected in the only rainy season. The results from the hierarchical cluster analysis and water quality index show that the water quality at Ben Mong, An Khe, and Ba River Bridges was classified as moderately to highly polluted. These areas should focus on regular water quality monitoring and appropriate pollution source management. PRACTITIONER POINTS: Agriculture activities strongly affected the water quality of the Highland Ba River of Vietnam. Chlorpyrifos and deltamethrin pesticides (0.0074-0.0218 μg/L) were detected in Ba River. Non-point pollution sources significantly influenced water quality in the Ba River. Variations in river water quality mainly depend on seasons and locations. Water quality index values in rainy seasons (26-88) are lower than that in dry season (37-92).