Agricultural Catchments Research Articles

The role of nitrogen and iron biogeochemical cycles in the production and export of dissolved organic matter in agricultural headwater catchments

Abstract. To better understand the seasonal variations in environmental conditions regulating dissolved organic matter (DOM) export in agricultural headwater catchments, we combined the monitoring of nitrate, iron, soluble phosphorus, and DOM concentration (as dissolved organic carbon; DOC) and composition (3D fluorescence) in soil and stream waters at regular intervals during 1 hydrological year. We installed 17 zero-tension lysimeters in organic-rich top soil horizons (15 cm below the surface) in the riparian area of a well-monitored agricultural catchment in French Brittany and collected them at a fortnightly frequency from October 2022 to June 2023. We observed a large increase in DOC concentrations in soil waters during the high-flow period linked to the establishment of Fe-reducing conditions and the subsequent release of DOM. We also noted that the timing and the spatial variability in Fe(II) biodissolution in soils was regulated by nitrate from agricultural origin and the heterogeneity of water flow paths at the hillslope scale. Contrary to our current understanding of DOM export in headwater catchments, these results lead us to consider the winter high-flow period as an active phase of both DOM production and export.

Soil quality index: a tool to detect the sensitivity to soil erosion in an agricultural catchment from the Middle Atlas of Morocco.

Abstract The present paper focuses on the application of the Soil Quality Index (SQI) within the Tiguert catchment, situated in the Middle Atlas of Morocco. The studied catchment, covering approximately 10.2 km², experiences a semi-arid climate with irregular rainfall and is designated as an agricultural area, making it an ideal site for studying the intricate interactions between natural processes and human activities. The SQI developed as part of the Mediterranean Desertification and Land Use (MEDALUS) project is tailored to the unique conditions of the Mediterranean region. In the case of the Tiguert catchment, SQI is calculated using a formula that considers topographical slope, horizontal depth of soil, parental material, and soil brightness. Consequently, the results depict a promising scenario, with 61% of the soil classified as “High Quality,” indicating robust soil health and resilience despite the challenges posed by a semi-arid climate. The 31% categorized as “Moderate Quality” underscores areas requiring specific management attention, while the 8% identified as “Low Quality” signals localized challenges potentially influenced by irregular rainfall patterns. Furthermore, the SQI results are closely linked to soil erosion dynamics, with higher SQI values associated with improved resistance to erosion. The dynamic connection between precipitation patterns and SQI over a 40-year analysis indicates the impact of varying rainfall on soil health. Extreme rainfall events correspond to higher SQI percentages in the “High Quality” category, while drier periods align with lower SQI percentages, emphasizing the dynamic relationship between climate and soil quality. A comprehensive analysis of SQI across diverse ecosystems in Tiguert reveals variations in soil health, emphasizing the importance of tailored land management approaches for different land use types to optimize overall soil sustainability.

Transport Pathways of Nitrate in Stormwater Runoff Inferred from High-Frequency Sampling and Stable Water Isotopes.

Storm events can mobilize nitrogen species from landscapes into streams, exacerbating eutrophication and threatening aquatic ecosystems as well as human health. However, the transport pathways and storm responses of different nitrogen forms remain elusive. We used high-frequency chemical and isotopic sampling to partition sources of stormwater runoff and determine transport pathways of multiple nitrogen forms in an agricultural catchment. Bayesian mixing modeling reveals shallow subsurface water as the dominant source of stormwater runoff, contributing 74% of the water flux and 72, 71, and 79% of total nitrogen (TN), total dissolved nitrogen (TDN), and nitrate (NO3-N), respectively. Groundwater, by contrast, contributed 11% of stormwater runoff and 21, 22, and 17% of TN, TDN, and NO3-N, respectively. The remaining 14% of stormwater runoff can be attributed to rainwater, which contains much less TN, TDN, and NO3-N. Surprisingly, during storm events, the dominant nitrogen form was NO3-N rather than dissolved organic nitrogen. Antecedent conditions and runoff characteristics have an important influence on nitrogen loads during storm events. Our results provide insight into hydrological mechanisms driving nitrogen transport during storm events and may help in developing catchment management practices for reducing nitrogen pollution in aquatic ecosystems.

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.

Tracing sulfate sources in a tropical agricultural catchment with a stable isotope Bayesian mixing model

Sulfate (SO42−) is an essential anion in drinking water and a vital macronutrient for plant growth. However, elevated sulfate levels can impact ecosystem or human health and could be an important indicator of acid rock drainage or pollution. Therefore, monitoring SO42− sources and transport is important for water quality assessments. This study focused on exploring the sources and transformations of SO42− as well as estimating the proportional contribution of the potential SO42− pollutant sources to groundwater and surface water in a tropical river basin, the Densu River Basin. The study used major ions combined with stable sulfur and oxygen isotope compositions and a Bayesian isotope mixing model, MixSIAR. The major ion characteristics indicate that SO42− concentrations remain stable throughout the rainy and dry seasons but originate from diverse sources. The multi-isotope model (δ34SSO4, δ18OSO4) identified four potential SO42− sources: detergent, precipitation, sewage, and sulfate fertilizer. However, the δ34SSO4 and δ18OSO4 values of the fertilizer source signatures overlapped with those of precipitation and sewage. Nevertheless, the contributions from each source were disentangled using the MixSIAR model, which revealed sewage as the most dominant SO42− pollutant in the Densu Basin, accounting for ~47 % of sulfate in groundwater and ~ 56 % of sulfate in surface water. Sulfate fertilizer (~33 %) was the second most important source after sewage for groundwater, while detergent (~23 %) was the second most important source for surface water. The redox processes of bacterial sulfate reduction and sulfide oxidation were determined to have a minimal impact on the sulfur isotope fractionation within the basin. This study highlights the benefits of combining major ions, sulfur isotopes and the MixSIAR model for identifying sources of sulfate. This approach accounts for uncertainties in source contributions which allows for more robust and reliable apportionment of sulfate sources. The study emphasizes the need for effective waste management and pollution control measures to protect water quality and provides vital guidelines on how to partition sulfate sources on a large catchment scale and evidence for making pollution management decisions on water resources.

Agricultural intensification in Lake Naivasha Catchment in Kenya and associated nutrients and pesticides pollution

Investments in agricultural intensification in sub-Saharan Africa aim to fulfill food and economic demands. However, the increased use of fertilizers and pesticides poses ecological risks to water bodies in agricultural catchments. This study focused on assessing the impact of agricultural intensification on nutrient and pesticide pollution in the L. Naivasha catchment in Kenya. The research revealed significant changes in the catchment’s agricultural landscape between 1989 and 2019, driven by intensified agricultural expansion. As a result, nutrient and pesticide emissions have worsened the lake’s trophic status, shifting it towards hypereutrophic conditions. The study found a weak relationship between total nitrogen (TN) and sum dichlorodiphenyltrichloroethane (∑DDT), indicating that an increase in TN slightly predicted a reduction in ∑DDT. Analysis also showed potential phosphorus (P) limitation in the lake. Additionally, the observed ratio between dichlorodiphenyldichloroethane and dichlorodiphenyldichloroethylene (DDD:DDE) and (DDE + DDD):DDT ratios suggest recent use of banned DDT in the catchment. The study concludes that the transformation of L. Naivasha landscape shows unsustainable agricultural expansion with reduced forest cover, increased croplands, and increased pesticide contamination. This reflects a common issue in sub-Saharan Africa, that sustainable catchment management must address, specifically for combined pollutants, to support water quality and achieve the SDGs in agriculture.

Modelling the impacts of climate change on agrochemical fate and transport by water on a catchment scale

The export of agrochemicals and their transformation products (TPs) following their application in the agricultural fields poses a threat to water quality. Future changes in climatic conditions (e.g. extreme weather events such as heavy rainfall or extended dry periods) could alter the degradation and mobility of agrochemicals. In this research, we use an integrated modelling framework to understand the impact of extreme climate events on the fate and transport of the agrochemical S-Metolachlor and two of its TPs (M-OXA, Metolachlor Oxanilic Acid and M-ESA, Metolachlor Ethyl Sulfonic Acid). This is done by coupling climate model outputs to the Zin-AgriTra agrochemical reactive transport model in four simulation scenarios. 1) Reference (2015–2018), 2) Very dry (2038–2041), 3) Very wet (2054–2057) and 4) High temperature (2096–2099) conditions of a selected RCP8.5 based regional climate scenario. The modelling framework is tested on an agricultural catchment, Wulka, in Burgenland, Austria. The model results indicate that 13–14 % of applied S-Metolachlor is retained in the soil, and around 85 % is degraded into TPs in the different scenarios. In very dry and high-temperature scenarios, degradation is higher, and hence, there is less S-Metolachlor in the soil. However, a large share of formed M-OXA and M-ESA are retained in the soil, which is transported via overland and groundwater flow, leading to a build-up effect in M-OXA and M-ESA river concentrations over the years. Though a small share of S-Metolachlor and TPs are transported to rivers, their river export is affected by the intensity and amount of rainfall. The very wet and high-temperature scenarios show higher S-Metolachlor and TP concentrations at the catchment outlet due to higher river discharge. The reference scenario shows higher river peak concentrations associated with higher overland flow caused by measured hourly rainfall compared to disaggregated daily precipitation data in the other scenarios.

Transferability of a Bayesian Belief Network across diverse agricultural catchments using high-frequency hydrochemistry and land management data

Biogeochemical catchment models are often developed for a single catchment and, as a result, often generalize poorly beyond this. Evaluating their transferability is an important step in improving their predictive power and application range. We assess the transferability of a recently developed Bayesian Belief Network (BBN) that simulated monthly stream phosphorus (P) concentrations in a poorly-drained grassland catchment through application to three further catchments with different hydrological regimes and agricultural land uses. In all catchments, flow and turbidity were measured sub-hourly from 2009 to 2016 and supplemented with 400–500 soil P test measurements. In addition to a previously parameterized BBN, five further model structures were implemented to incorporate in a stepwise way: in-stream P removal using expert elicitation, additional groundwater P stores and delivery, and the presence or absence of septic tank treatment, and, in one case, Sewage Treatment Works. Model performance was tested through comparison of predicted and observed total reactive P (TRP) concentrations and percentage bias (PBIAS). The original BBN accurately simulated the absolute values of observed flow and TRP concentrations in the poorly and moderately drained catchments (albeit with poor apparent percentage bias scores; 76 % ≤ PBIAS≤94 %) irrespective of the dominant land use, but performed less well in the groundwater-dominated catchments. However, including groundwater total dissolved P (TDP) and Sewage Treatment Works (STWs) inputs, and in-stream P uptake improved model performance (−5 % ≤ PBIAS≤18 %). A sensitivity analysis identified redundant variables further helping to streamline the model applications. An enhanced BBN model capable for wider application and generalisation resulted.

Surface Flux Patterns of Nutrient Concentrations and Total Suspended Solids in Western Carpathian Stream within Agricultural, Forest, and Grassland Landscapes

The intricate processes of surface water erosion are vital for ecological systems and river-scale management; yet, understanding them comprehensively remains a challenge. Forested agricultural catchments, especially in the Carpathian region, face significant degradation, potentially leading to inorganic nutrient leaching and total suspended solid (TSS) flux. Continuous rainwater inundation of soils in river valleys exacerbates this issue. Utilizing innovative tools like SWAT+, studies have revealed higher concentrations of inorganic nutrients in main watercourses from flysch catchments, with agricultural use linked to N-NO3− concentrations and pasture use linked to anion P-PO43−. Maintaining detailed records is crucial for researchers comparing data. SWAT+ proves valuable for studying TSS washing out and inorganic nutrient leaching, informing collaborative watershed management policies involving stakeholders from agriculture, conservation, and water management sectors. The insights on nutrient leaching, particularly phosphorus (P) and nitrogen (N), are instrumental for shaping policies targeting nutrient pollution within pasture land use for EU agriculture. These findings can guide policy frameworks focused on sustainable practices, especially for eco-schemes, and encourage collaborative watershed management efforts.

Podnebne projekcije temperature zraka in padavin za porečja Ledave, Pesnice in Vipave do konca 21. stoletja

As part of the project ‚CeVoTak‘, Integrated Management of Small Water Retention and Soil Erosion Prevention Measures in Agricultural Catchments, we studied changing temperature and precipitation conditions up to the year 2100. The study was conducted on agricultural lands in the catchments of the Ledava and Pesnica rivers in the sub-Pannonian region and the Vipava river in the sub-Mediterranean region. A common climate database was used to create the climate projections - RCM (Regional Climate Model) simulations from the project EURO-CORDEX and scenarios RCP (Representative Concentration Pathway), RCP2.6, 4.5 and 8.5. The projections were prepared for three time periods 2011-2040; 2041-2070 and 2071-2100 for 6 different regional climate models for average, minimum and maximum air temperatures and precipitation. Analysis of the ensemble of model simulations for all scenarios shows similar results for the basin of all rivers, an increase in temperature (maximum in winter, minimum in spring), with high confidence for all scenarios and periods. Projections of precipitation are less reliable, but show an increase in annual precipitation due to the winter increase. The use of climate change projections with expert interpretation is essential for determining the vulnerability of individual areas and building resilience through the implementation of climate change adaptation.

Comparison of two isotopic hydrograph separation methods in the Hydrological Open Air Laboratory, Austria

AbstractExploring the contributions of new and old water to runoff during precipitation events in agricultural catchments is essential for understanding runoff generation, solute transport, and soil erosion. The aim of this study was to investigate the variability in the isotopic composition of precipitation and runoff in the 66 ha agricultural catchment in Austria, in the Hydrological Open Air Laboratory (HOAL), in order to compare two isotope hydrograph separation methods. The classical two‐component (IHS) and the ensemble hydrograph separation (EHS) were applied to multiple large events in May–October of 2013–2018 using δ18O and δ2H. The peak flow new water contributions obtained by IHS were compared with the average new water fraction from EHS. The average new water fraction calculated with EHS based on regular weekly sampling was close to zero, which can be explained by the large diffuse groundwater discharge into the stream between the events. When only investigating events with high temporal resolution sampling, the results suggest that EHS provided average new water fractions during peak flows (0.46 ± 0.04 for δ18O, 0.47 ± 0.03 for δ2H) that were close to the averages obtained by IHS (0.47 for δ18O, 0.50 for δ2H). New water fractions tended to be higher for larger rainfall intensities. High peak flow new water fractions could be explained by the agricultural land use and soils with low permeability promoting overland flow generation and by some of the tile drainage systems contributing to the delivery of water. In conclusion, a weekly sampling frequency was not sufficient in the HOAL but instead high‐resolution sampling during events was necessary to estimate the average new water contributions during events. While EHS may be a more robust approach compared to IHS, as it relaxes some of the assumptions of IHS, IHS can provide information on the variability of new water contributions of individual events.

How to Achieve a 50% Reduction in Nutrient Losses From Agricultural Catchments Under Different Climate Trajectories?

AbstractUnder persistent eutrophication of European water bodies and a changing climate, there is an increasing need to evaluate best‐management practices for reducing nutrient losses from agricultural catchments. In this study, we set up a daily discharge and water quality model in Hydrological Predictions of the Environment for two agricultural catchments representative for common cropping systems in Europe's humid continental regions to forecast the impacts of future climate trajectories on nutrient loads. The model predicted a slight increase in inorganic nitrogen (IN) and total phosphorus (TP) loads under RCP2.6, likely due to precipitation‐driven mobilization. Under RCP4.5 and RCP8.5, the IN loads were forecasted to decrease from 16% to 26% and 21%–50% respectively, most likely due to temperature‐driven increases in crop uptake and evapotranspiration. No distinct trends in TP loads were observed. A 50% decrease in nutrient loads, as targeted by the European Green Deal, was backcasted using a combination of management scenarios, including (a) a 20% reduction in mineral fertilizer application, (b) introducing cover crops (CC), and (c) stream mitigation (SM) by introducing floodplains. Target TP load reductions could only be achieved by SM, which likely results from secondary mobilization of sources within agricultural streams during high discharge events. Target IN load reductions were backcasted with a combination of SM, fertilizer reduction, and CC, wherein the required measures depended strongly on the climatic trajectory. Overall, this study successfully demonstrated a modeling approach for evaluating best‐management practices under diverging climate change trajectories, tailored to the catchment characteristics and specific nutrient reduction targets.

Assessment of the Applicability of Compact Aerating Reactors for the Improvement of Water Quality in a Small Water Body Functioning in an Agricultural Catchment

The study investigates water quality in a small water body in an agricultural catchment in a zone of temperate climate (East Poland). The pond is affected by annual mass cyanobacterial blooms, limiting its use. The improvement of the state of water quality involved the application of underwater aerating reactors. The economic analysis of their application was also an important issue. The analysis of the effectiveness of the proposed solution was conducted from February to October 2021. The results from the analysis of water from the pond showed that the nutrient content and phytoplankton structure conformed to the trophic status of eutrophy–hypertrophy. The primary factors causing excessive eutrophication of the pond included nutrient supply from the river, sediments, and fallen tree leaves. No development of cyanobacterial scum was observed in the water body, a phenomenon which was interpreted as the effect of the operation of the aerators ensuring additional water circulation in the pond and promoting its aeration. It was found that permanent improvement of the water quality in the studied water body is largely dependent on limiting the nitrogen and phosphorus supply to the pond. This should involve the application of systems combining traditional hydrotechnical infrastructure with Nature-Based Solutions (NBS). The economic analysis of the use of underwater aeration reactors confirmed the validity of searching for alternative solutions to power them, e.g., a photovoltaic installation. When designing a reactor system with a photovoltaic installation, it is necessary to choose the correct dimensions to reduce construction costs and, thus, increase the profitability of the potential investment.

Using MODFLOW to Model Riparian Wetland Shallow Groundwater and Nutrient Dynamics in an Appalachian Watershed

Simulating shallow groundwater (SGW) flow dynamics and stream–SGW interactions using numerical modeling tools is necessary to develop a mechanistic understanding of water flow systems and improve confidence in water resource management practices. A three-dimensional (3D) SGW flow model was developed for a riparian wetland in a mixed forest and agricultural catchment in West Virginia (WV), Appalachia, USA, using a Modular 3D Groundwater Model (MODFLOW). The MODFLOW simulation was calibrated in steady (R2 = 0.98, ME = −0.21, and RMSE = 0.77), transient state (R2 = 0.97, ME = −0.41, and RMSE = 1.28) and validated (R2 = 0.97, ME = −0.28, and RMSE = 1.05) using observed SGW levels from thirteen nested piezometers under steady and transient states. An experimental MT3D transport scenario was developed to show the lateral transport of NO₃-N from the aquifer to stream cells. Relatively stable SGW head distribution was observed. In the downstream reach, SGW discharge varied from 948 m3/day to 907 m3/day in 2020, with creek seepage ranging from 802 m3/day to 790 m3/day. Similarly, SGW input to the stream ranged from 891 m3/day to 978 m3/day, while creek seepage ranged from 796 m3/day to 800 m3/day in 2021. In upstream reaches, losing stream conditions were observed in January, June, and September 2020 and January to April 2021, while gaining stream conditions prevailed during other months. Thus, an approximately monthly alternating gaining–losing stream condition was observed in the upstream area. An experimental MT3D transport scenario resulted in an advection–dispersion scenario, showing a cumulative loss of 947 g of NO3-N from SGW to the stream. Denitrification accounted for the cumulative loss of 1406 g of NO3-N from SGW, surpassing 639 g of nitrate from the SGW to the stream during the study period. Additionally, particle tracking using MODPATH indicated a long residence time for SGW nutrients, affirming the efficiency of nitrogen transformation through denitrification. This study is among the first to simulate hydrologic and nutrient interactions in riparian wetlands of a mixed land use catchment in the Appalachian region of the northeastern United States. The results better inform water resource management decisions and modeling efforts in the Appalachian region and similar physiographic regions globally.

Quali-quantitative water behaviour in an intensive swine production catchment in the Atlantic Forest biome, Southern Brazil.

Agriculture is an essential economic activity in Brazil. However, it is also the main source of water quality degradation. Monitoring catchments with agricultural land use is a way to generate information on a scale to identify causes and sources of water quality degradation. This work used monitoring data derived from hydrology and the quality of surface and underground water in an intensive agricultural catchment in the Atlantic Forest biome. The Fortaleza River catchment is located in the western part of Santa Catarina state in southern Brazil and has 62 km2 of drainage area. Hydrological and water quality monitoring was conducted for 7years at two fluviometric stations, three lysimeters, one meteorological station, and one piezometer. Data on precipitation, temperature, water flow, surface runoff, drainage, and water quality were used. Statistical analyses were also developed. Precipitation between 2013 and 2019 presented a homogeneous distribution in monthly and annual data, with January and July the months with the highest and lowest values, respectively. Statistical difference in the average and Q95 flows was found in upstream and downstream fluviometric sections. In terms of quality, statistical differences were identified for ammonium, nitrate, and potassium concentrations, which had higher concentrations in lysimeter runoff, indicating direct influence of agricultural activity on water quality. Principal component analysis (PCA) indicated that (i) surface water presented a positive relationship in Component 1 for the magnesium-calcium, sulphate-chloride, and acetate-bromide groups and a negative relationship for phosphate-nitrate; (ii) in lysimeters, the positive relationship occurred for Component 2 for the phosphate-chloride and sulphate-nitrate groups and was negative for ammonium-lithium and calcium-potassium-magnesium; and (iii) in piezometer, positive relationships were found for chloride-sodium and phosphate-nitrite pairs, while negative relationships were found for calcium-magnesium.

Divergence Between Long‐Term and Event‐Scale Nitrate Export Patterns

AbstractThe mechanisms driving catchment nitrogen storage and release operate at multiple spatiotemporal scales. Consequently, analyses grounded in different observational timescales can yield discrepant interpretations of underlying mechanisms. To assess the consistency of nitrate export patterns between event‐ and inter‐annual scales, we evaluated multiple years of high‐frequency observations of nitrate concentrations (C) and discharge (Q) including 3,480 discrete discharge events from 28 dominantly agricultural catchments. We observed consistent and often drastic divergence between long‐term and median event‐specific C‐Q patterns. Most catchments showed long‐term enrichment patterns (positive C‐Q slope), but events were, on average, more chemostatic (close‐to‐zero C‐Q slopes). C‐Q slope variability was high for small events but decreased with event magnitude, approaching chemostatic patterns during the largest storms, yielding compelling evidence against nitrate source limitation. We conclude that nitrate export patterns observed at different temporal scales and event magnitudes are controlled by different processes, therefore embedding complementary information.

Impact of Land Use on Peat Soil Elemental Content and Carabidae and Plant Species Composition and Abundance

This study, conducted in 2020–2022, was designed to determine the impact of livestock grazing on habitat biodiversity and Carabidae beetles. Two research plots (a meadow and a pasture) were established on a farm in the village of Otapy, located in the agricultural catchment area of the Nurzec River in Eastern Poland. They were located next to each other so that they would possess the same set of atmospheric phenomena and processes shaped by the physical and geographical characteristics of the area. The study showed that the pasture was the richest in terms of the magnesium and calcium contents, while the meadow had significantly higher levels of phosphorus and zinc. The study also showed some differences in the abundance and species composition of plants and animals. The meadow had higher biodiversity, while the pasture was dominated by grasses. A disparity in the abundance of individual species was also presented. The study indicated the preference of individual species for particular forms of land use. Anisodactylus binotatus, Harpalus rufipes and Poecilus cupreus were most abundant in the meadow, while Carabus granulatus and Pterostichus melanarius were mostly represented in the pasture. The number of species, on the other hand, was the same. Our research concluded that proper landscape management through different uses affects plant and beetle diversity and soil element content.

Variation in soil erosion rate under typical land uses and vertical zones in an agricultural catchment of the Daliangshan region, Southwest China

AbstractThe Daliangshan region (DLS) is characterized by significant vertical differentiation in human activity and land use owing to the high elevation gradient, which may affect the soil erosion pattern in the vertical direction. However, the spatial variability of soil erosion rates along a hillslope at the catchment scale remains poorly understood. In this study, we used the cesium‐137 tracer technique to estimate soil erosion rates under different land uses and vertical zones from a small agricultural catchment, the Luowugou catchment in the DLS. Ten plots comprising four typical vertical zones (valley, low mountain, middle mountain and sub‐alpine) and five land‐use types (sloping farmland, grassland, abandoned farmland, forest land and horizontal terrace) were selected. In addition, two parallel downslope transects were built in each plot, and soil samples were collected at 3–7 m intervals along these transects. The results indicated that the soil erosion rates on sloping farmland (4.82 kg·m−2·y−1) and grassland (4.09 kg·m−2·y−1) were significantly higher than those on abandoned farmland (0.91 kg·m−2·y−1) and forest land (0.80 kg·m−2·y−1). In contrast, the horizontal terrace showed net deposition, with a deposition rate of 0.62 kg·m−2·y−1. The erosion rates varied across different zones, with the low mountain zone having the highest erosion rate (5.65 kg·m−2·y−1), followed by the middle mountain (2.96 kg·m−2·y−1) and subalpine (1.46 kg·m−2·y−1) zones, and the valley zone having the lowest erosion rate (1.28 kg·m−2·y−1). Furthermore, there were significant correlations (P < 0.05) between the soil erosion rates from different vertical zones and the proportion of sloping farmland, implying that sloping farmland plays a dominant role in shaping soil erosion along a vertical gradient. These comparisons suggest that the highest soil erosion rate occurred in the low mountain zone, indicating that the steeply sloping farmlands, resulting from migration from high‐altitude areas, have intensified soil erosion in the vertical zone. These findings highlight the role of agricultural activities originating from sloping farmlands in influencing soil erosion across different vertical zones, which has important implications for mitigating soil erosion and optimizing agricultural layout in the region.

Exploring the hydrologic regulation and pollutant release of complex paddy systems in a large-scale agricultural catchment

Complex paddy systems (CPSs) are prevalent in humid agricultural regions, presenting a dilemma between restoring them to wetlands or maintaining them for food production. Thus, a comprehensive assessment of CPSs is necessary. However, the current model’s description of CPS is insufficient, leading to incomplete representation of the water and pollutant transfer processes of CPS in the model. Therefore, a new version of the soil and water assessment tool (SWAT-CPS) was proposed, which utilizes physically based rules to measure the horizontal seepage-overflow process within CPSs. Overall, the SWAT-CPS outperforms SWAT in streamflow, water cycle simulation, hydrological event reproduction and pollutant release simulation. Water balance analysis and scenario simulations showed that CPSs increase baseflow and pollutant release throughout the year (about 7.69% and 3.05%, respectively) while affecting quickflow in different ways depending on the streamflow conditions. Changing the area of the CPS may have significant impacts on the hydrological composition. This study highlights the differences between CPSs and wetlands in hydrological regulation and pollutant release. In fact, not all areas are suitable for “returning farmland to wetlands”. Our work providing insights for decision-makers in planning the allocation of CPS and wetland shares.

Bayesian network modelling of phosphorus pollution in agricultural catchments with high-resolution data

A Bayesian Belief Network was developed to simulate phosphorus (P) loss in an Irish agricultural catchment. Septic tanks and farmyards were included to represent all P sources and assess their effect on model performance. Bayesian priors were defined using daily discharge and turbidity, high-resolution soil P data, expert opinion, and literature. Calibration was done against seven years of daily Total Reactive P concentrations. Model performance was assessed using percentage bias, summary statistics, and visually comparing distributions. Bias was within acceptable ranges, the model predicted mean and median P concentrations within the data error, with simulated distributions more variable than the observations. Considering the risk of exceeding regulatory standards, predictions showed lower P losses than observations, likely due to simulated distributions being left-skewed. We discuss model advantages and limitations, the benefits of explicitly representing uncertainty, and priorities for data collection to fill knowledge gaps present even in a highly monitored catchment.