Modelling the impacts of agricultural management practices on river water quality in Eastern England

SWAT model applications: From hydrological processes to ecosystem services

Ecosystem services in bolstering human well-being and steering environmental management garnered increasing recognition. In this realm, the Soil and Water Assessment Tool (SWAT) rose as an instrumental tool in ecosystem services. The heterogeneous applications of SWAT across diverse studies underscore an imperative for bibliometric analysis to decipher these evolving trends. This study endeavors to execute a comprehensive analysis of SWAT's application for ecosystem services, delineating key thematic development and exploring its utilization in ecosystem services. We conducted a comprehensive literature review by searching the Web of Science database, retrieving a total of 534 articles. The CiteSpace facilitated our co-citation analysis, enabling the identification of seminal publications and burgeoning themes within SWAT. Our analysis delineated thematic development in SWAT pertaining to ecosystem services. Initially concentrated on hydrological processes, the focus progressively broadened to encompass comprehensive ecosystem services evaluations. We examined 81 peer-reviewed publications directly related to ecosystem services, and most of them addressed certain ecosystem services, such as water yield, soil retention, regulation of water flow, food, and carbon storage. SWAT holds a unique advantage in quantifying water-related processes. Future studies should focus more on ecosystem service flows based on SWAT, which contributes to elucidating the relationship between nature and humans, facilitating comprehensive ecosystem management.

Nutrient Removal Potential of Headwater Wetlands in Coastal Plains of Alabama, USA

Headwater streams drain over 70% of the land in the United States with headwater wetlands covering 6.59 million hectares. These ecosystems are important landscape features in the southeast United States, with underlying effects on ecosystem health, water yield, nutrient cycling, biodiversity, and water quality. However, little is known about the relationship between headwater wetlands' nutrient function (i.e., nutrient load removal ( R L ) and removal efficiency ( E R ) ) and their physical characteristics. Here, we investigate this relationship for 44 headwater wetlands located within the Upper Fish River watershed (UFRW) in coastal Alabama. To accomplish this objective, we apply the process-based watershed model SWAT (Soil and Water Assessment Tool) to generate flow and nutrient loadings to each study wetland and subsequently quantify the wetland-level nutrient removal efficiencies using the process-based wetland model WetQual. Results show that the calculated removal efficiencies of the headwater wetlands in the UFRW are 75-84% and 27-35% for nitrate ( NO 3 - ) and phosphate ( PO 4 + ) , respectively. The calculated nutrient load removals are highly correlated with the input loads, and the estimated PO 4 +   E R shows a significant decreasing trend with increased input loadings. The relationship between NO 3 - E R and wetland physical characteristics such as area, volume, and residence time is statistically insignificant (p > 0.05), while for PO 4 + , the correlation is positive and statistically significant (p < 0.05). On the other hand, flashiness (flow pulsing) and baseflow index (fraction of inflow that is coming from baseflow) have a strong effect on NO 3 - removal but not on PO 4 + removal. Modeling results and statistical analysis point toward denitrification and plant uptake as major NO 3 - removal mechanisms, whereas plant uptake, diffusion, and settling of sediment-bound P were the main mechanisms for PO 4 + removal. Additionally, the computed nutrient E R is higher during the driest year of the simulated period compared to during the wettest year. Our findings are in line with global-level studies and offer new insights into wetland physical characteristics affecting nutrient removal efficiency and the importance of headwater wetlands in mitigating water quality deterioration in coastal areas. The regression relationships for NO 3 - and PO 4 + load removals in the selected 44 wetlands are then used to extrapolate nutrient load removals to 348 unmodeled non-riverine and non-riparian wetlands in the UFRW (41% of UFRW drains to them). Results show that these wetlands remove 51-61% of the NO 3 - and 5-10% of the PO 4 + loading they receive from their respective drainage areas. Due to geographical proximity and physiographic similarity, these results can be scaled up to the coastal plains of Alabama and Northwest Florida.

Urbanization and agriculture intensification jointly enlarge the spatial inequality of river water quality

Rivers are severely polluted by multiple anthropogenic stressors. An unevenly distributed landscape pattern can aggravate the deterioration of water quality in rivers. Identifying the impacts of landscape patterns on the spatial characteristics of water quality is helpful for river management and water sustainability. Herein we quantified the nationwide water quality degradation in China's rivers and analyzed its responses to spatial patterns of anthropogenic landscapes. The results showed that the spatial patterns of river water quality degradation had a strong spatial inequality and worsened severely in eastern and northern China. The spatial aggregation of agricultural/urban landscape and the water quality degradation exhibits high consistency. Our findings suggested that river water quality would further deteriorate from high spatial aggregation of cities and agricultures, which reminded us that the dispersion of anthropogenic landscape patterns might effectively alleviate water quality pressures.

Advances in Catchment Science, Hydrochemistry, and Aquatic Ecology Enabled by High-Frequency Water Quality Measurements

High-frequency water quality measurements in streams and rivers have expanded in scope and sophistication during the last two decades. Existing technology allows in situ automated measurements of water quality constituents, including both solutes and particulates, at unprecedented frequencies from seconds to subdaily sampling intervals. This detailed chemical information can be combined with measurements of hydrological and biogeochemical processes, bringing new insights into the sources, transport pathways, and transformation processes of solutes and particulates in complex catchments and along the aquatic continuum. Here, we summarize established and emerging high-frequency water quality technologies, outline key high-frequency hydrochemical data sets, and review scientific advances in key focus areas enabled by the rapid development of high-frequency water quality measurements in streams and rivers. Finally, we discuss future directions and challenges for using high-frequency water quality measurements to bridge scientific and management gaps by promoting a holistic understanding of freshwater systems and catchment status, health, and function.

Scaling an Artificial Neural Network-Based Water Quality Index Model from Small to Large Catchments

Scaling models is one of the challenges for water resource planning and management, with the aim of bringing the developed models into practice by applying them to predict water quality and quantity for catchments that lack sufficient data. For this study, we evaluated artificial neural network (ANN) training algorithms to predict the water quality index in a source catchment. Then, multiple linear regression (MLR) models were developed, using the predicted water quality index of the ANN training algorithms and water quality variables, as dependent and independent variables, respectively. The most appropriate MLR model has been selected on the basis of the Akaike information criterion, sensitivity and uncertainty analyses. The performance of the MLR model was then evaluated by a variable aggregation and disaggregation approach, for upscaling and downscaling proposes, using the data from four very large- and three large-sized catchments and from eight medium-, three small- and seven very small-sized catchments, where they are located in the southern basin of the Caspian Sea. The performance of seven artificial neural network training algorithms, including Quick Propagation, Conjugate Gradient Descent, Quasi-Newton, Limited Memory Quasi-Newton, Levenberg–Marquardt, Online Back Propagation, and Batch Back Propagation, has been evaluated to predict the water quality index. The results show that the highest mean absolute error was observed in the WQI, as predicted by the ANN LM training algorithm; the lowest error values were for the ANN LMQN and CGD training algorithms. Our findings also indicate that for upscaling, the aggregated MLR model could provide reliable performance to predict the water quality index, since the r2 coefficient of the models varies from 0.73 ± 0.2 for large catchments, to 0.85 ± 0.15 for very large catchments, and for downscaling, the r2 coefficient of the disaggregated MLR model ranges from 0.93 ± 0.05 for very large catchments, to 0.97 ± 0.02 for medium catchments. Therefore, scaled models could be applied to catchments that lack sufficient data to perform a rapid assessment of the water quality index in the study area.

Economic optimization to guide climate water stress adaptation

Allocation of water over its six dimensions of quantity, quality, timing, location, price, and cost remains an ongoing challenge facing water resource planning worldwide. This challenge is magnified with growing evidence of climate change and related water supply stressors. This stress will challenge food, energy, and water systems as climate adaptation policy measures see continued debate. Despite numerous achievements made many by previous works, few attempts have scanned the literature on economic optimization analysis for water resources planning to discover affordable climate adaptation measures. This paper aims to fill that gap by reviewing the literature on water resource optimization analysis at the basin scale to guide discovery of affordable climate adaptation measures. It does so by posing the question "What principles, practices, and recent developments are available to guide discovery of policy measures to improve water resource system adaptions to growing evidence of climate water stress?" It describes past achievements and identifies improvements needed for optimization analysis to inform policy debates for crafting plans to improve climate resilience. It describes an economic conceptual framework as well as identifying data needs for conducting economic optimization exercises to support river basin planning faced by the challenge of managing the six water dimensions described above. It presents an example from an ongoing issue facing water planners in the Middle East. Conclusions find considerable utility in the use of economic optimization exercises to guide climate water stressadaptation. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.

Review: Perspective on high-performing dairy cows and herds

Milk and dairy products provide highly sustainable concentrations of essential amino acids and other required nutrients for humans; however, amount of milk currently produced per dairy cow globally is inadequate to meet future needs. Higher performing dairy cows and herds produce more milk with less environmental impact per kg than lower performing cows and herds. In 2018, 15.4% of the world's dairy cows produced 45.4% of the world's dairy cow milk, reflecting the global contribution of high-performing cows and herds. In high-performing herds, genomic evaluations are utilized for multiple trait selection, welfare is monitored by remote sensing, rations are formulated at micronutrient levels, health care is focused on prevention and reproduction is managed with precision. Higher performing herds require more inputs and generate more waste products per cow, thus innovations in environmental management on such farms are essential for lowering environmental impacts. Our focus is to provide perspectives on technologies and practices that contribute most to sustainable production of milk from high-performing dairy cows and herds.

Comparison between water quality indices in watersheds of the Southern Bahia (Brazil) with different land use

The present study evaluated the influence of land use and occupation on water quality indices (WQI); the WQI developed by the National Sanitation Foundation (NSF), the WQI adapted by the Environmental Company of the São Paulo State (CETESB), WQI proposed by Bascarón and the Canadian Council of Ministers of the Environment (CCME) WQI, obtained for watersheds located in the Eastern Water Planning and Management Region (BA). The study also analyzed the divergences and similarities of these WQI methods. Water quality data were obtained from the Monitoring Program (Monitora) of Environment and Water Resources Institute of Bahia (INEMA), covering the period from 2008 to 2015, at thirteen (13) sampling sites, with quarterly collections, as well as land use and occupation data. The influence of land use and occupation on water quality indices was assessed by principal component analysis (PCA). The PCA showed that urban and agricultural/pasture areas were influencing factors on water quality variables, such as total phosphorus, biochemical oxygen demand, total nitrogen, turbidity total residues and consequently lower WQI values in the Cachoeira watershed. Among the tested methods to evaluate the water quality of watersheds in the study area, the most similar were the NSF WQI, CETESB WQI, and Objective Bascarón WQI.

Water Quality Modelling for River Activities Management: Example from a Low- and Middle-Income Country

BACKGROUND

Rivers are susceptible to pollution and water pollution is a growing problem in low- and middle-income countries (LMIC) with rapid development and minimal environmental protections. There are universal pollutant threshold values, but they are not directly linked to river activities such as sand mining and aquaculture. Water quality modelling can support assessments of river pollution and provide information on this important environmental issue.

OBJECTIVES

The objective of the present study was to demonstrate water quality modelling methodology in reviewing existing policies for Malaysian river catchments based on an example case study.

METHODS

The MIKE 11 software developed by the Danish Hydraulic Institute was used to model the main pollutant point sources within the study area - sand mining and aquaculture. Water quality data were obtained for six river stations from 2000 to 2015. All sand mining and aquaculture locations and approximate production capacities were quantified by ground survey. Modelling of the sand washing effluents was undertaken with the advection-dispersion module due to the nature of the fine sediment. Modelling of the fates of aquaculture deposits required both advection-dispersion and Danish Hydraulic Institute ECO Lab modules to simulate the detailed interactions between water quality determinants.

RESULTS

According to the Malaysian standard, biochemical oxygen command (BOD) and ammonium (NH₄) parameters fell under Class IV at most of the river reaches, while the dissolved oxygen (DO) parameter varied between Classes II to IV. Total suspended solids (TSS) fell within Classes IV to V along the mid river reaches of the catchment.

DISCUSSION

Comparison between corresponding constituents and locations showed that the water quality model reproduced the long-term duration exceedance for the main body of the curves. However, the water quality model underestimated the infrequent high concentration observations. A standard effluent disposal was proposed for the development of legislation and regulations by authorities in the district that could be replicated for other similar catchments.

CONCLUSIONS

Modelling pollutants enables observation of trends over the years and the percentage of time a certain class is exceeded for each individual pollutant. The catchment did not meet Class II requirements and may not be able to reach Class I without extensive improvements in the quality and reducing the quantity of both point and non-point effluent sources within the catchment.

COMPETING INTERESTS

The authors declare no competing financial interests.

Simulation of streamflow and instream loads of total suspended solids and nitrate in a large transboundary river basin using Source model and geospatial analysis

The management of LULC changes in transboundary river basins continues to challenge water resources managers due to the differences in development and conservation priorities of the countries sharing the basin. While various watershed models (WMs) exist to support decision making, basin-wide sustainable application of the instituted WM depends on the management priorities, resources, data availability, and knowledge gaps at national and sub-basin levels. Building on the results of our prior comparative analysis of WMs for a large transboundary river basin, we applied the 'Source' model to the Lower Mekong Basin (LMB). The constructed LMB-Source model was evaluated based on its streamflow and instream total suspended solids (TSS) and nitrate loads simulative performances. A combination of predictive performance metrics (PPMs) and sophisticated hydrologic signatures were used to calibrate model parameters and diagnose the model performance. Calibration results indicated strong similarity between the simulated and observed time series data and were further confirmed by the validation results. The successful model calibration generated parameters that represent hydrologic response characteristics (HRCs) and overland TSS and nitrate generation and removal dynamics (GRDs) previously not available for the LMB. The HRCs and GRDs can be regionalised with physical attributes of the LMB in future studies which can be used to support the management of ungauged sub-basins. This study confirms Source's capability as a decision support tool for the management of transboundary river basins, and provides basin-specific values of HRCs and GRDs that can be used for a better evaluation of the potential effects of LULC changes.

Mapping of Major Land-Use Changes in the Kolleru Lake Freshwater Ecosystem by Using Landsat Satellite Images in Google Earth Engine

India’s largest freshwater ecosystem of the Kolleru Lake has experienced severe threats by land-use changes, including the construction of illegal fishponds around the lake area over the past five decades. Despite efforts to protect and restore the lake and its riparian zones, environmental pressures have increased over time. The present study provides a synthesis of human activities through major land-use changes around Kolleru Lake both before and after restoration measures. For this purpose, archives of all Landsat imageries from the last three decades were used to detect land cover changes. Using the Google Earth Engine cloud platform, three different land-use scenarios were classified for the year before restoration (1999), for 2008 immediately after the restoration, and for 2018, i.e., the current situation of the lake one decade afterward. Additionally, the NDVI (Normalized Difference Vegetation Index) and NDWI (Normalized Difference Water Index) indices were used to identify land cover dynamics. The results show that the restoration was successful; consequently, after a decade, the lake was transformed into the previous state of restoration (i.e., 1999 situation). In 1999, 29.7% of the Kolleru Lake ecosystem was occupied by fishponds, and, after a decade of sustainable restoration, 27.7% of the area was fishponds, almost reaching the extent of the 1999 situation. On the one hand, aquaculture is one of the most promising sources of income, but there is also limited awareness of its negative environmental impacts among local residents. On the other hand, political commitment to protect the lake is weak, and integrated approaches considering all stakeholders are lacking. Nevertheless, alterations of land and water use, increasing nutrient concentrations, and sediment inputs from the lake basin have reached a level at which they threaten the biodiversity and functionality of India’s largest wetland ecosystem to the degree that immediate action is necessary to prevent irreversible degradation.

Quantifying effects of conservation practices on non-point source pollution in the Miyun Reservoir Watershed, China

Non-point source (NPS) pollution, including fertilizer and manure application, sediment erosion, and haphazard discharge of wastewater, has led to a wide range of water pollution problems in the Miyun Reservoir, the most important drinking water source in Beijing. In this study, the Soil and Water Assessment Tool (SWAT) model was used to evaluate NPS pollution loads and the effectiveness of best management practices (BMPs) in the two subwatersheds within the Miyun Reservoir Watershed (MRW). Spatial distributions of soil types and land uses, and changes in precipitation and fertilizer application, were analysed to elucidate the distribution of pollution in this watershed from 1990 to 2010. The results demonstrated that the nutrient losses were significantly affected by soil properties and higher in both agricultural land and barren land. The temporal distribution of pollutant loads was consistent with that of precipitation. Soil erosion and nutrient losses would increase risks of water eutrophication and ecosystem degradation in the Miyun Reservoir. The well-calibrated SWAT model was used to assess the effects of several Best Management Practices (BMPs), including filter strips, grassed waterways, constructed wetlands, detention basins, converting farmland to forest, soil nutrient management, conservation tillage, contour farming, and strip cropping. The removal rates of those BMPs ranged from 1.03 to 38.40% and from 1.36 to 39.34% for total nitrogen (TN) and total phosphorus (TP) loads, respectively. The efficiency of BMPs was dependent on design parameters and local factors and varied in different sub-basins. This study revealed that no single BMP could achieve the water quality improvement targets and highlighted the importance of optimal configuration of BMP combinations at sub-basin scale. The findings presented here provide valuable information for developing the sustainable watershed management strategies.

Accident Trend Prediction of Heavy Metal Pollution in the Heshangshan Drinking Water Source Area Based on Integrating a Two-Dimensional Water Quality Model and GIS

In recent years, water pollution accidents have frequently occurred, which have caused enormous economic loss and an adverse social impact. In this study, an accident trend prediction system was developed based on integrating a two-dimensional water quality model and GIS, and Arsenic (As) was adopted as a typical pollutant to study the temporal-spatial changes of heavy metal pollutions under different hydrological and meteorological conditions in the Heshangshan drinking water source area. The simulation for a recent accident indicated that pollutant changes were influenced by lateral diffusion, longitudinal diffusion, flow velocity, water flow, and the self-purification of the water body. It took 79.5 min for the As concentration to meet the water quality standard during the dry period, while it spent 61.3 min, 71 min, and 52 min in the impound period, falling period, and flood period, respectively. The emergency response times were 32 min (in the flood period), 38 min (in the impound period), 48 min (in the falling period), and 52 min (in the dry period). Furthermore, wind speed and wind direction also had impacts on pollutant spread. The times in which the maximum values met the water quality standard were 71 min (southeast wind), 77 min (southwest wind), and 87 min (no wind). The emergency response times were 38 min (southeast wind), 49 min (southwest wind), and 59 min (no wind). This study not only provides a reference for relevant departments and managers to carry out a risk assessment, disaster prevention, and emergency management after actual pollution accidents, but also makes up for the lack of research on the spatial-temporal change of heavy metal pollutants.

Water Framework Directive programmes of measures: Lessons from the 1st planning cycle of a catchment in England

The European Union's Water Framework Directive (WFD) required Member States to establish programmes of measures to achieve good water status formally by 2015, but on postponing the deadline by two six-year periods, by 2027 at the latest. With many Member States facing problems with developing such measures in the first planning cycle, and limited change in ecological status since the first river basin management plans were reported, we look at the implementation of the Directive in England, where only 17% of the surface water bodies were found at good status in 2015, a reduction of 4% since 2009. Using as a case study the Broadland Rivers catchment, we examine the measures taken for Cycle 1 and changes in the classifications of water body status, to investigate whether the way the measures were developed could have limited their potential to deliver WFD objectives. While the WFD was adopted to succeed and replace management practices targeting individually non-compliant element, findings indicate that little had changed in the way measures were developed. Although considerable progress has been made on the implementation of these measures, the limited progress in improving classifications demonstrates the limits of this approach and further makes the case for what the WFD was introduced for: the harmonised transposition of the Integrated River Basin Management paradigm, as the key for delivering good ecological status.

Automatic calibration and selection of optimal performance criterion of a water quality model for a river controlled by total maximum daily load (TMDL)

When manually calibrating water quality models, considerable time and attention are required. Hence, developing an automated model that allows for efficient and objective automatic calibration is highly desirable. The QUAL2Kw model calibrates the QUAL2K automatically using a genetic algorithm (GA). This study analyzes auto-calibration results and selects the optimal criterion for each objective function from six performance criteria. Additionally, a multi-objective auto-calibration was conducted using two kinds of performance statistics as the objective function of the GA. The auto-calibration model was applied to the Yeongsan River and the total maximum daily load (TMDL) was established to achieve water quality goals at specific target points of this river. Among the six auto-calibration results based on a single performance criterion, Nash-Sutcliffe model efficiency (NSE) was the best criterion for calculating fitness through auto-calibration. To consider the calibration accuracies of the TMDL target points and the entire river simultaneously, an objective function using multiple performance criteria, specifically the weighted average of the normalized root mean squares error (CV(RMSE)) and the ratio of the RMSE to the standard deviation of the observed data (the RSR), was selected as the final auto-calibration of the model. The model calibration performance was good across the whole region as well as at the target points.

Landscape characteristics driving spatial variation in total phosphorus and sediment loading from sub-watersheds of the Nottawasaga River, Ontario

Eutrophication from agricultural runoff is a global problem, often resulting in formation of anoxic zones in receiving water bodies. The Nottawasaga River Watershed (NRW) is dominated by agricultural land-use, and drains into Nottawasaga Bay, Georgian Bay (Lake Huron). A fundamental feature of the NRW is the Minesing Wetlands, a Ramsar site and the largest inland wetland in southern Ontario. We used total phosphorus (TP) concentration-discharge relationships to estimate annual loading from six sub-watersheds and compared these against published models, which did not offer a way to account for the unique properties of the Minesing Wetlands. We developed predictive loading models specifically for the NRW to account for these characteristics, which accurately predict daily summer base-flow TP (r² = 0.76, p = <0.0001) and total suspended solids (TSS; r² = 0.65, p = <0.0001) loads for 11 subwatersheds using geomorphic and land-cover variables. Drainage area and % pasture land were the most significant predictive variables driving spatial variability in TP and TSS loading rates among subwatersheds. The positive relationship between TP and % wetland (r² = 0.22, p = 0.0063) also suggested that the Minesing Wetlands are a source of nutrients to the Nottawasaga River. Watershed geomorphology (e.g. slope) was a good predictor of land cover, and produced accurate loading estimates. This study is the first to offer a new approach to predict TP and TSS loading rates during the growing season using readily available geospatial data.

Holistic water quality dynamics in rural artificial shallow water bodies

The water environment in diversely used rural artificial water bodies is generally varied with seasonal and diurnal changes, stability of which is significant in water resources management. Understanding of interaction among different water quality parameters that depend on their diurnal variations is the concern of this study. A rural homestead pond used for aquaculture in Bangladesh and a micro-dam used as an irrigation tank for paddy farming in Japan are chosen for contrasting the analysis of data. The observed data series of four typical water quality parameters exhibits the diurnal variations, which are primarily inferred to be driven by solar radiation and complex bio-chemical interactions. The study proposes a stochastic differential equation model to represent holistic water quality dynamics based on continuous measurements. The water quality parameters are considered as temporally continuous Markov process, where their individual effects on each parameter are evaluated in a specific time step and immediately reflected to the next observation. The model parameters are calibrated and the stability is discussed based on the eigenvalues of model parameters. The result mostly shows the mean reverting properties for dissolved oxygen and water temperature, while pH and oxidation reduction potential are rather depend on other parameters or external disturbance.

Integrating the economic and environmental performance of agricultural systems: A demonstration using Farm Business Survey data and Farmscoper

There is a continued need to monitor the environmental impacts of agricultural systems while also ensuring sufficient agricultural production. However, it can be difficult to collect relevant environmental data on a large enough number of farms and studies that do so often neglect to consider the financial drivers that ultimately determine many aspects of farm management and performance. This paper outlines a methodology for generating environmental indicators from the Farm Business Survey (FBS), an extensive annual economic survey of representative farms in England and Wales. Data were extracted from the FBS for a sample of East Anglian cereal farms and south western dairy farms and converted where necessary to use as inputs in 'Farmscoper'; farm-level estimates of nitrate, phosphorus and sediment loadings and ammonia and greenhouse gas emissions were generated using the Farmscoper model. Nitrate losses to water, ammonia and greenhouse gas emissions were positively correlated with food energy production per unit area for both farm types; phosphorus loading was also correlated with food energy on the dairy farms. Environmental efficiency indicators, as measured by either total food energy or financial output per unit of negative environmental effect, were calculated; greenhouse gas emission efficiency (using either measure of agricultural output) and nitrate loading efficiency (using financial output) were positively correlated with profitability on cereal farms. No other environmental efficiency measures were significantly associated with farm profitability and none were significant on the dairy farms. These findings suggest that an improvement in economic performance can also improve environmental efficiency, but that this depends on the farm type and negative environmental externality in question. In a wider context, the augmentation of FBS-type data to generate additional environmental indicators can provide useful insights into ongoing research and policy issues around sustainable agricultural production.

Assessing strategies to mitigate phosphorus leaching from drained clay soils

Assessing mitigation of phosphorus (P) leaching from subsurface drainage systems is challenging due to high spatial and temporal variation in leaching. Mean measured total P leaching from a clayey soil in an eight-year study period (four replicates per treatment) was (kg ha^-1 year^-1): 1.21 from shallow autumn tillage (ShT), 0.84 from unfertilised fallow (UF), 0.81 from conventional autumn ploughing (CT) and 0.57 from structure liming (SL-CT). Treatment was not significant using Richards-Baker flow index or a distance factor as covariate (p = 0.084 and 0.057). A tendency for lower leaching was obtained comparing SL-CT with ShT (p _adjusted = 0.060 and 0.009 respectively). A combination of measures adapted to drainage conditions and clay content in different parts of the field is proposed since P leaching was approximately halved from an adjacent field (4.3 ha) in a three-year post-period compared with a three-year pre-period for structure liming the entire field and drainage system renovation plus structure lime drain backfilling.

Major agricultural changes required to mitigate phosphorus losses under climate change

Phosphorus losses from land to water will be impacted by climate change and land management for food production, with detrimental impacts on aquatic ecosystems. Here we use a unique combination of methods to evaluate the impact of projected climate change on future phosphorus transfers, and to assess what scale of agricultural change would be needed to mitigate these transfers. We combine novel high-frequency phosphorus flux data from three representative catchments across the UK, a new high-spatial resolution climate model, uncertainty estimates from an ensemble of future climate simulations, two phosphorus transfer models of contrasting complexity and a simplified representation of the potential intensification of agriculture based on expert elicitation from land managers. We show that the effect of climate change on average winter phosphorus loads (predicted increase up to 30% by 2050s) will be limited only by large-scale agricultural changes (e.g., 20-80% reduction in phosphorus inputs).The impact of climate change on phosphorus (P) loss from land to water is unclear. Here, the authors use P flux data, climate simulations and P transfer models to show that only large scale agricultural change will limit the effect of climate change on average winter P loads in three catchments across the UK.

Assessing anthropogenic impacts on riverine ecosystems using nested partial least squares regression

The results of three Partial Least Squares (PLS) regression models were used to gain a holistic view on the consequences of natural processes and anthropogenic pressures for water quality degradation and biodiversity decline in a multi-use watershed. The processes were soil erosion and wildfire risk; the pressures comprised land use conflicts, leachates from domestic and industrial waste, arable farming intensity and livestock density. Water quality was characterized for concentrations of nutrients (nitrate, phosphate), oxygen demands (Biochemical Oxygen Demand - BOD₅, Chemical Oxygen Demand - COD) and various metals (e.g., As, Cr). Ecological integrity was assessed by the recently developed MELI (Multiple Ecological Level Index). In total, 18 variables were processed in the regression models. Two models were called "nested models" because they dealt with initial (pressures), intermediate (water quality) and final (MELI) environmental descriptors, used as dependent (MELI, quality) or independent (quality, pressures) variables. The third was called "bypass model" because it dealt solely with initial and final descriptors. Overall, the results of PLS regression linked the ineffective treatment of domestic sewage to water quality and ecological integrity declines in the studied watershed. Put another way, all models recurrently affirmed the major role of local factors, meaning of point source pollution, in determining the quality of stream water and the integrity of freshwater ecosystems. Sources of diffuse pollution were accounted for as contributing factors in the PLS regressions, but their influence was scarcely perceptible in the results. The poor treatment of domestic effluents is a public concern. In their strategic plans for mitigating this problem in the forthcoming years, administrative authorities are concentrated on management initiatives to improve the quality of provided services, instead of considering the construction of new wastewater treatment plants.