Modelling mitigation options to reduce diffuse nitrogen water pollution from agriculture

GIS-based multi-criteria decision analysis model for utility water demand: The case of Lodwar Municipality, Turkana County, Kenya

Water scarcity is a global issue resulting from rapid urbanization, increasing population growth, industrial development and expansion of human activities over time and space. Water shortage affects every continent and is listed as one of the largest global risks hence the need for proper management of water resources. Municipalities and cities worldwide are struggling to maintain a steady supply of water to meet the increasing water demand. The study used Geographic Information System (GIS) techniques and Multi-Criteria Decision Analysis (MCDA) to develop a decision support model that can be applied to improve the utility water demand management for the Lodwar Municipality in Turkana Kenya. The data comprised remotely sensed data, population density, spatial plans, utility infrastructure maps and metered water connections data. The AHP pairwise comparison matrix was applied to assign weights for the 8 criteria influencing water demand in the area. The population density, proximity to water network facilities and land use criteria were equivalent to 30 %, 25 %, and 23 % respectively whereas 22 % of other criteria were dependent on each other. The analysis of satellite images showed the expansion of built-up areas and emerging human activities in regions towards the South and Western of Lodwar Town. The resulting model outcome identified the potential demand priority sites within the region of which some are underserved. The model efficiency was assessed through the application of statistical indicators as well as graphical and map presentations. Consequently, the addition of more input variables affecting demand is likely to improve the results over changing aspects within the zones. Municipality water utility managers and decision-makers can therefore employ the model information to highlight suitable areas for network expansion as well as infrastructure management planning within the municipality. This method offers an alternative hybrid technique for mapping potential utility water demand in rural municipalities with inadequate data.

Characteristics of water quality mitigation measures that lead to greater adoption on farms

Globally, agriculture is a significant pressure on water quality. While nutrient and sediment loss from agricultural land to water can be scientifically complex, mitigation measures primarily focus on reducing farm nutrient stocks or blocking loss pathways. The appropriateness of mitigation measures is dependent on the identification of specific context-related risks on individual farms. However, advisers also need to consider the likelihood of uptake of measures by farmers. Past research has looked at uptake of particular mitigation measures or a small range of measures. This research expands the literature with an analysis of uptake of a broad and diverse range of measures. Farm characteristics, farmer norms, knowledge required and costs (direct and indirect) associated with individual mitigation measures are investigated to identify factors that could influence greater adoption. Results show that alignment to farmer norms and lower specific costs were associated with high adoption rates. These results have implications for advisers in relation to the selection of measures most likely to be adopted by farmers, and also for policy-makers in relation to the need to incentivise the adoption of high-cost measures.

Long short-term memory models of water quality in inland water environments

Water quality is substantially influenced by a multitude of dynamic and interrelated variables, including climate conditions, landuse and seasonal changes. Deep learning models have demonstrated predictive power of water quality due to the superior ability to automatically learn complex patterns and relationships from variables. Long short-term memory (LSTM), one of deep learning models for water quality prediction, is a type of recurrent neural network that can account for longer-term traits of time-dependent data. It is the most widely applied network used to predict the time series of water quality variables. First, we reviewed applications of a standalone LSTM and discussed its calculation time, prediction accuracy, and good robustness with process-driven numerical models and the other machine learning. This review was expanded into the LSTM model with data pre-processing techniques, including the Complete Ensemble Empirical Mode Decomposition with Adaptive Noise method and Synchrosqueezed Wavelet Transform. The review then focused on the coupling of LSTM with a convolutional neural network, attention network, and transfer learning. The coupled networks demonstrated their performance over the standalone LSTM model. We also emphasized the influence of the static variables in the model and used the transformation method on the dataset. Outlook and further challenges were addressed. The outlook for research and application of LSTM in hydrology concludes the review.

Water quality management at a critical checkpoint by coordinated multi-catchment urban-rural load allocation

Improving river water quality at critical checkpoints, defined as locations with significant impacts on water use, to satisfy regulation standards is an important goal of sustainable catchment management. Challenges remain in investigating pollution hotspots, designing efficient target reduction, and evaluating management performance. To address these challenges, we develop a systems approach for water quality management that integrates natural physical processes with human activities and their environmental impacts. In this approach, we firstly expand the concepts of headroom (amount under a permitted value) and excess (amount exceeding a permit) onto the source, spatial, and temporal domains for water quality management. We evaluate system-wide pollution contributions by simulating physical processes in a semi-distributed integrated representation using the CatchWat-SD model. We apply the model to the Upper Thames River basin and validate it using available monitoring data. We then incorporate the evaluated headroom-excess into a coordinated load allocation to enhance the efficiency and feasibility of interventions. Load allocation scenarios where headroom-excess is coordinated at different domains are generated and simulated. Finally, we evaluate the performance of these scenarios using multi-criteria metrics to demonstrate the advantages of headroom-excess coordination. Results show that urban sources, downstream sub-catchments, and dry season flows are associated with excess, thus, enabling managers to identify which cases (pollution sources, locations, and times) to focus load reductions towards. The more a load allocation strategy coordinates headroom-excess across domains, the more target reduction is allocated to the cases with excess, and the better performance it obtains in all the criteria. The study emphasises the need to incorporate headroom-excess in load allocation, which helps to improve systems-level water quality performance more efficiently. The approach can be further expanded to water quality management at multiple checkpoints for sustainable management of regional water systems.

Assessing the effectiveness of MARPOL Annex V at reducing marine debris on Australian beaches

To mitigate marine debris and promote sustainable marine industries, legislation and regulations surrounding the management of marine debris have been adopted worldwide. One of the most well-known and important agreements is the International Convention for the Prevention of Pollution from Ships (MARPOL), which focuses on reducing all types of ship-sourced marine pollution. MARPOL Annex V, which deals with the disposal of solid waste, came into force on 31 December 1988. However, was only amended to include a complete ban on waste disposal as of 1 January 2013. Assessing the effectiveness of key regulations is fundamental for supporting evidence-based decisions regarding the management of our oceans. Here, we evaluated whether MARPOL Annex V translated into a decrease in the incidence of shipping- and commercial fishing-sourced debris on remote beaches in Australia using 14 years of standardised, community-driven data. From 2006 to 2020 there was a significant change over time in the density of fishing and shipping debris on Australian beaches; debris density increased up to 2013 followed by a decrease until mid-2017. Although the new regulation started in January 2013, the decrease in density was not recorded until one year later. The decline was only observed for 4 years, reinforcing the existence of lags between the implementation of international agreements and the corresponding potential reduction in debris in the environment. This provides compelling evidence that international agreements and policies by themselves are not enough to solve the debris problem, with improved implementation and enforcement also required. We discuss future perspectives and solutions to reduce ocean-sourced litter inputs into the ocean and highlight the urgent need for action.

Food and agricultural wastes-derived biochars in combination with mineral fertilizer as sustainable soil amendments to enhance soil microbiological activity, nutrient cycling and crop production

The ever-increasing human population associated with high rate of waste generation may pose serious threats to soil ecosystem. Nevertheless, conversion of agricultural and food wastes to biochar has been shown as a beneficial approach in sustainable soil management. However, our understanding on how integration of biochar obtained from different wastes and mineral fertilizers impact soil microbiological indicators is limited. Therefore, in the present study the effects of agricultural (AB) and food waste derived (FWB) biochars with and without mineral fertilizer (MF) on crop growth and soil health indicators were compared in a pot experiment. In particular, the impacts of applied amendments on soil microbiological health indicators those related to microbial extracellular (C, N and P acquiring) enzymes, soil basal as well as different substrate induced respirations along with crop's agronomic performance were explored. The results showed that compared to the control, the amendment with AB combined with MF enhanced the crop growth as revealed by higher above and below ground biomass accumulation. Moreover, both the biochars (FWB and AB) modified soil chemical properties (pH and electric conductivity) in the presence or absence of MF as compared to control. However, with the sole application of MF was most influential strategy to improve soil basal and arginin-induced respiration as well as most of the soil extracellular enzymes, those related to C, N and P cycling. Use of FWB resulted in enhanced urease activity. This suggested the role of MF and FWB in nutrient cycling and plant nutrition. Thus, integration of biochar and mineral fertilizers is recommended as an efficient and climate smart package for sustainable soil management and crop production.

The Combined Inoculation of Curvularia lunata AR11 and Biochar Stimulates Synthetic Silicon and Potassium Phosphate Use Efficiency, and Mitigates Salt and Drought Stresses in Rice

Synthetic chemical fertilizers are a fundamental source of nutrition for agricultural crops; however, their limited availability, low plant uptake, and excessive application have caused severe ecological imbalances. In addition, the gravity of environmental stresses, such as salinity and water stress, has already exceeded the threshold limit. Therefore, the optimization of nutrient efficiency in terms of plant uptake is crucial for sustainable agricultural production. To address these challenges, we isolated the rhizospheric fungus Curvularia lunata ARJ2020 (AR11) and screened the optimum doses of biochar, silicon, and potassium phosphate (K2HPO4), and used them-individually or jointly-to treat rice plants subjected to salt (150 mM) and drought stress (20-40% soil moisture). Bioassay analysis revealed that AR11 is a highly halotolerant and drought-resistant strain with an innate ability to produce gibberellin (GA1, GA3, GA4, and GA7) and organic acids (i.e., acetic, succinic, tartaric, and malic acids). In the plant experiment, the co-application of AR11 + Biochar + Si + K2HPO4 significantly improved rice growth under both salt and drought stresses. The plant growth regulator known as abscisic acid, was significantly reduced in co-application-treated rice plants exposed to both drought and salt stress conditions. These plants showed higher Si (80%), P (69%), and K (85%) contents and a markedly low Na+ ion (208%) concentration. The results were further validated by the higher expression of the Si-carrying gene OsLSi1, the salt-tolerant gene OsHKT2, and the OsGRAS23's drought-tolerant transcriptome. Interestingly, the beneficial effect of AR11 was significantly higher than that of the co-application of Biochar + Si + K2HPO4 under drought. Moreover, the proline content of AR11-treated plants decreased significantly, and an enhancement of plant growth-promoting characteristics was observed. These results suggest that the integrated co-application of biochar, chemical fertilizers, and microbiome could mitigate abiotic stresses, stimulate the bioavailability of essential nutrients, relieve phytotoxicity, and ultimately enhance plant growth.

Quantifying influences of administrative division adjustment on PM2.5 pollution in China's mega-urban agglomerations

China's mega-urban agglomerations have experienced severe particulate matter pollution that is accompanied by rapid economic growth and extensive administrative division adjustment (ADA). However, the precise roles of ADA on the environmental quality are unknown. Using the geographical detector and evolution tree model, this study quantifies the effects and mechanisms of ADA on the changes in PM_2.5 concentration in three mega-urban agglomerations: Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD), and Pearl River Delta (PRD) during 2000-2017. Our results showed that: (1) ADA had strong positive effects on PM_2.5 concentrations in the 0-6 years lag and negative effects in the 7-10 years lag; (2) During 2000-2009, ADA elevated PM_2.5 concentration by 5.93% via stimulating the development and transfer of heavy industry and urban sprawl in the BTH; (3) YRD and PRD respectively reduced the ADA's exacerbating effect to 5.26% and 4.98% via reasonable industrial structures and comprehensive cooperation mechanisms; (4) During 2009-2017, BTH and YRD integrated industrial transformation and environmental protection services through ADA, which alleviated 9.51% and 8.49% of PM_2.5 pollution. PRD, meanwhile, accomplished orderly population dispersal and urban expansion by combining ADA with urban planning, thus reducing the PM_2.5 concentration by 8.01%. We located three agglomerations in the evolution tree, which provide a basis for formulating relevant policies and region-oriented air pollution joint prevention control strategies.

Ammonium Nitrogen Streamflow Transport Modelling and Spatial Analysis in Two Chinese Basins

Ammonium nitrogen (NH4+-N), which naturally arises from the decomposition of organic substances through ammonification, has a tremendous influence on local water quality. Therefore, it is vital for water quality protection to assess the amount, sources, and streamflow transport of NH4+-N. SPAtially Referenced Regressions on Watershed attributes (SPARROW), which is a hybrid empirical and mechanistic modeling technique based on a regression approach, can be used to conduct studies of different spatial scales on nutrient streamflow transport. In this paper, the load and delivery of NH4+-N in Poyang Lake Basin (PLB) and Haihe River Basin (HRB) were estimated using SPARROW. In PLB, NH4+-N load streamflow transport originating from point sources and farmland accounted for 41.83% and 32.84%, respectively. In HRB, NH4+-N load streamflow transport originating from residential land and farmland accounted for 40.16% and 36.75%, respectively. Hence, the following measures should be taken: In PLB, it is important to enhance the management of the point sources, such as municipal and industrial wastewater. In HRB, feasible measures include controlling the domestic pollution and reducing the usage of chemical fertilizers. In addition, increasing the vegetation coverage of both basins may be beneficial to their nutrient management. The SPARROW models built for PLB and HRB can serve as references for future uses for different basins with various conditions, extending this model’s scope and adaptability.

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.

Managing food-ecosystem synergies to sustain water resource systems

Measures implemented to restore ecosystem services are widely believed to conflict with food production in the world's irrigated regions because of their competition for scarce water. However, little integrated analysis has been conducted to test this hypothesis. This work tests that hypothesis by presenting results of a basin-scale hydroeconomic analysis linking biophysical, hydrologic, agronomic, ecological, economic, policy, and institutional dimensions of the partially-restored Mesopotamian Marshes of Western Asia. Results serve to partly reject the hypothesis: Here we find that an economically-optimized ecosystem restoration trajectory can be achieved with a minimal loss in food production or farm income where restored wetlands complement important dimensions of food production. Moreover, we find that where water shortage sharing rules can be made more flexible, ecosystem restoration more nearly complements improved food security. Our results point to previously unexplored synergies among food production, ecosystem restoration, and water laws in arid and semi-arid regions internationally.

Bioaccumulation of trace metals and speciation of copper and zinc in Pacific oysters (Crassostrea gigas) using XANES/EXAFS spectroscopies

Copper (Cu) and zinc (Zn) concentrations in oyster soft tissues can be particularly high due to contamination, leading to extremely green/blue colors. This raises key questions regarding the behavior and speciation of trace metals in oyster soft tissues. This study investigated trace metal concentration profiles of contaminated Pacific oyster (Crassostrea gigas) soft tissues collected from trace metal-contaminated coastal area of Xiangshan District using inductively coupled plasma optical emission spectrometry (ICP-OES), energy dispersive X-ray (EDX), Fourier-transform infrared spectroscopy (FTIR), and X-ray photoelectron spectroscopy (XPS). Moreover, Cu and Zn speciation in contaminated and non-contaminated oyster soft tissues were investigated by X-ray absorption near edge structure spectroscopy/extended X-ray absorption fine structure (XANES/EXAFS) spectroscopic methods. The contents of Cu (1,100-1,400 mg/kg) and Zn (500-700 mg/kg) dry weight were high in oyster soft tissue samples. The XANES/EXAFS results revealed that Cu and Zn existed primarily as copper (II) oxide (CuO) and zinc oxide (ZnO) in contaminated oysters. Furthermore, Cu and Zn formed clusters with Cu-O and Zn-O interatomic distances of 1.97 and 2.21 Å, (coordination numbers 1.0 and 5.6), respectively. In non-contaminated oysters, the less abundant Cu and Zn existed mainly as copper(I) sulfide (Cu₂S) and zinc sulfide (ZnS) forming clusters with Cu-S and Zn-S (thiolates) bond distances of 2.09 and 1.23 Å (coordination numbers of 4.6 and 2.4). These results provide further understanding on the chemical speciation of Cu and Zn in contaminated and non-contaminated oyster soft tissues as well as the bioaccumulation of trace metals in the oyster soft tissues.

Rationalization of water quality monitoring locations under spatiotemporal heterogeneity of diffuse pollution using seasonal export coefficient

Water quality is continuously changing because of anthropogenic origin of point and diffuses (non-point) pollution sources. Most of the time diffuse sources are not considered for rationalization of sampling sites as their accurate estimation is tedious and data intensive. The estimation of diffuse pollution is conventionally carried out using observed water quality data. These conventional approaches are data intensive and demands detailed information for a considerably long-time horizon and hence becomes challenging to implement in data-scarce regions. Also, diffuse pollution sources are characterized by spatio-temporal heterogeneity as they depend upon seasonal behavior of precipitation. The present study proposes an innovative semi-empirical approach of Seasonal Export Coefficients (SECs) for estimation of diffuse pollution loads, especially for tropical countries like India. This approach takes into account the effect of seasonality on the estimation of diffuse pollution loads, by considering seasonal heterogeneity of terrain and precipitation impact factors and land use applications. This seasonal heterogeneity is then tested for its possible impact on rationalization of water quality monitoring locations for Kali River basin in India. The SECs are estimated for available water quality dataset of 1999-2000 and are further used for simulation of nutrient loading for experimental years 2004-2005, 2009-2010, and 2014-2015. The resulting SECs for Kali river basin are: 2.03 (agricultural), 1.44 (fallow), and 0.92 (settlement) for monsoonal nitrate; while for non-monsoonal nitrate, SECs are 0.51 (agricultural), 0.23 (fallow), and 0.10 (settlement). The monsoonal phosphate SECs for land use classes - agricultural, fallow and settlement are 1.01, 0.68, and 0.25, while non-monsoonal phosphate SECs are 0.27, 0.14 and, 0.03 respectively. The seasonal variation of diffuse pollution sources is effectively captured by SECs. The proposed approach, by considering both point and diffuse pollution, is found efficient in determining optimum locations and number of monitoring sites where seasonal variations are found evident during experimental years.

Identification of nitrate sources and transformations in basin using dual isotopes and hydrochemistry combined with a Bayesian mixing model: Application in a typical mining city

The external nitrogen load input caused by human activities exacerbates the eutrophication process of aquatic ecosystems in mining areas, causing water quality problems. However, knowledge of the sources and environmental behavior of nitrate in the surface water of mining areas is still very limited. This study investigated the nitrate content and spatiotemporal variation characteristics of surface water in the Linhuan mining area, identified the sources and transformation processes of nitrate using isotopes and hydrochemistry, and evaluated the contribution rates of different potential nitrate sources based on a Bayesian mixing model. The nitrogen pollution in the surface water in the mining area seriously exceeded class Ⅴ of the Environmental Quality Standard of Surface Water of China (GB3838-2002). The NO₃^- content ranged from 0.87 to 3.41 mg/L, showing obvious seasonal and spatial differences. Isotope and NO₃^-/Cl^- analysis indicated that nitrate in the subsidence area water (SAW) was mainly derived from chemical fertilizer (NF) and soil organic nitrogen (NS), while nitrate in the mainstream of the Huihe River water (HRW) was mainly derived from manure/sewage (MS). The nitrate in the tributary of the Baohe River water (BRW) was mainly derived from soil NS, and nitrification was a nitrogen conversion pathway in the soil. The results of the Bayesian mixing model showed that the main sources of nitrate in the BRW, HRW and SAW were NF (34.5%), MS (68.8%) and NF (40.8%) in the wet season, and NS (33.4%), MS (70.9%) and NF (58.1%) in the dry season, respectively. The results of this study provide a new integrated method for the identification of nitrate pollution sources in mining areas, and this method can be used to improve the biogeochemical information of nitrogen in the aquatic ecosystems of mining areas and help formulate relevant measures to reduce water nitrogen pollution.

Drivers and barriers for taking account of geological uncertainty in decision making for groundwater protection

The geological conceptual model is considered a major source of uncertainty in groundwater modelling and well capture zone delineation. However, how to account for it in groundwater policy and management remains largely unresolved. We explore the drivers and barriers to account for geological conceptual uncertainty in groundwater protection amongst decision makers and stakeholders in an agricultural groundwater catchment in Denmark. Using a groundwater model, we analyze the impact of alternative geological conceptual models on capture zone delineation. A focus area, which covers multiple modelled capture zones, is defined and considered for groundwater protection. Model uncertainty and focus area are discussed at two workshops, one with local and national stakeholders and another with local farmers. The drivers to account for model uncertainty include: i) safer drinking water protection by considering a larger area for protection than identified from a single geological model; and ii) stability over time of management plans. The main barrier is the additional cost to the stakeholders for the protection of a larger area. We conclude that integration of geological uncertainty in groundwater protection plans may be improved through: i) better communication between the research community and the national water authority; ii) more constraining guidelines regarding the estimation of geological uncertainty; and iii) the development of a framework ensuring knowledge transfer to the local water authorities and detailing how to integrate uncertainty in management plans.

A comparative analysis of the application of water quality exemptions in the European Union: The case of nitrogen

Freshwater ecosystems and water uses may be jeopardized by the degradation of water quality. The Water Framework Directive of the European Union (EU) sets environmental objectives for water bodies but foresees the establishment of exemptions under some circumstances. The criteria used to justify these exemptions, however, are not fully developed, leaving their application open to some arbitrariness. Our study explores the relations between the magnitude of pressures affecting continental surface water bodies and the declared exemptions on the permitted concentration of nitrogen. It identifies different approaches to declare exemptions to nitrogen environmental objectives across six EU Member States and discusses the underlying criteria. A better understanding of the pressures-impact-measures/exemptions relation helps compare water policy decisions across different regions subject to the same legal obligations and set priorities for mitigation measures.

Modeling the Contribution of Crops to Nitrogen Pollution in the Yangtze River

Agriculture contributes considerably to nitrogen (N) inputs to the world's rivers. In this study, we aim to improve our understanding of the contribution of different crops to N inputs to rivers. To this end, we developed a new model system by linking the MARINA 2.0 (Model to Assess River Input of Nutrient to seAs) and WOFOST (WOrld FOod STudy) models. We applied this linked model system to the Yangtze as an illustrative example. The N inputs to crops in the Yangtze River basin showed large spatial variability. Our results indicate that approximately 6,000 Gg of N entered all rivers of the Yangtze basin from crop production as dissolved inorganic N (DIN) in 2012. Half of this amount is from the production of single rice, wheat, and vegetables, where synthetic fertilizers were largely applied. In general, animal manure contributes 12% to total DIN inputs to rivers. Three-quarters of manure-related DIN in rivers are from vegetable, fruit, and potato production. The contributions of crops to river pollution differ among sub-basins. For example, potato is an important source of DIN in rivers of some upstream sub-basins. Our results may help to prioritize the dominant crop sources for management to mitigate N pollution in the future.

Demonstrating efficacy of rural land management actions to improve water quality - How can we quantify what actions have been done?

Despite several decades of encouraging land management actions to improve water quality on rural land, we are still struggling to accurately quantify what management actions have been implemented, where these actions have been used and the intensity of implementation. This is largely because standardised approaches to recording and reporting of land management actions have not been established, resulting in a lack of robust information that can be used to determine the effectiveness and longevity of these actions at a catchment or larger scale. Better information on the effectiveness of different land management actions will provide land managers with more certainty that their investments in land management actions will make a difference. We reviewed a total of 91 global publications and proceedings between 1989 and 2019 which assessed the complexities related to recording and reporting sustainable land use actions with a focus on freshwater ecosystems in rural areas in the developed world. We then summarised these complexities (i.e., temporal and spatial lag-effects, confidentiality issues, lack of data robustness) and mined the literature about methodologies on how actions can be measured, how to address the challenges with doing this and recommended a suite of indicators of land management actions that could be standardised and widely used to improve water quality. Our review of literature identified numerous sources describing land management actions, but little information on standardised indicators of location, scale and intensity of the most common actions. Some common actions are measured using a wide variety of incompatible approaches (e.g., riparian management is often indicated by length of fencing, width of vegetated buffer strips, proportion of the catchment with stock exclusion), whereas other indicators of land management action are at such a high level (e.g., costs) that they do not provide information on the actions used. The scale/intensity of land management efforts is often not reported spatially with information typically restricted to small scales such as single point location information, making it difficult, if not impossible to determine the scale of actions within a catchment relative to a given water quality monitoring site.

Lag Time as an Indicator of the Link between Agricultural Pressure and Drinking Water Quality State

Diffuse nitrogen (N) pollution from agriculture in groundwater and surface water is a major challenge in terms of meeting drinking water targets in many parts of Europe. A bottom-up approach involving local stakeholders may be more effective than national- or European-level approaches for addressing local drinking water issues. Common understanding of the causal relationship between agricultural pressure and water quality state, e.g., nitrate pollution among the stakeholders, is necessary to define realistic goals of drinking water protection plans and to motivate the stakeholders; however, it is often challenging to obtain. Therefore, to link agricultural pressure and water quality state, we analyzed lag times between soil surface N surplus and groundwater chemistry using a cross correlation analysis method of three case study sites with groundwater-based drinking water abstraction: Tunø and Aalborg-Drastrup in Denmark and La Voulzie in France. At these sites, various mitigation measures have been implemented since the 1980s at local to national scales, resulting in a decrease of soil surface N surplus, with long-term monitoring data also being available to reveal the water quality responses. The lag times continuously increased with an increasing distance from the N source in Tunø (from 0 to 20 years between 1.2 and 24 m below the land surface; mbls) and La Voulzie (from 8 to 24 years along downstream), while in Aalborg-Drastrup, the lag times showed a greater variability with depth—for instance, 23-year lag time at 9–17 mbls and 4-year lag time at 21–23 mbls. These spatial patterns were interpreted, finding that in Tunø and La Voulzie, matrix flow is the dominant pathway of nitrate, whereas in Aalborg-Drastrup, both matrix and fracture flows are important pathways. The lag times estimated in this study were comparable to groundwater ages measured by chlorofluorocarbons (CFCs); however, they may provide different information to the stakeholders. The lag time may indicate a wait time for detecting the effects of an implemented protection plan while groundwater age, which is the mean residence time of a water body that is a mixture of significantly different ages, may be useful for planning the time scale of water protection programs. We conclude that the lag time may be a useful indicator to reveal the hydrogeological links between the agricultural pressure and water quality state, which is fundamental for a successful implementation of drinking water protection plans.

Characterizing the impacts of land use on nitrate load and water yield in an agricultural watershed in Atlantic Canada

Excessive nitrate loading from agricultural non-point source is threatening the health of receiving water bodies at the global scale. Quantifying the drivers/sources of water and nitrate flux in watersheds and relating them to spatial and temporal land uses is essential for developing effective mitigation strategies. This study investigated the impact of land use on water yield and nitrate loading to surface water in a typical agricultural watershed in Prince Edward Island (PEI), Canada. We used historical streamflow and water quality records to calibrate the comprehensive hydrological model Soil and Water Assessment Tool (SWAT), which was setup with detailed annual land use records. The SWAT model performed well in predicting both daily streamflow and nitrate load. Land use demonstrated little impact on water yield but affected nitrate load significantly. Annual nitrate load ranged from 5.6 to 44.4 kg N ha^-1 yr^-1 for forest and soybean, respectively. Potato rotated land contributed 84.5% of annual nitrate load to the watershed. Source of water yield demonstrated high variability between the growing season and non-growing season. About 90% of water yield was contributed by groundwater during growing season, while runoff contributed over 60% of water yield during the non-growing season. Groundwater was the dominant source of nitrate loading for both seasons. The watershed estuary faced the highest threats from subbasins in the south western area due to the high nitrate load and proximity to the watershed outlet. Results by the machine learning algorithm random Forest analysis indicated that the climatic variables of temperature and precipitation were the top two factors affecting water yield, with a combined relative importance of 61%. Land use was the dominant factor affecting nitrate load, the relative importance of land use alone was ~50%. The results of this study provided critical insights for watershed management in Atlantic Canada.

Trustable Environmental Monitoring by Means of Sensors Networks on Swarming Autonomous Marine Vessels and Distributed Ledger Technology

The article describes a highly trustable environmental monitoring system employing a small scalable swarm of small-sized marine vessels equipped with compact sensors and intended for the monitoring of water resources and infrastructures. The technological foundation of the process which guarantees that any third party can not alter the samples taken by the robot swarm is based on the Robonomics platform. This platform provides encrypted decentralized technologies based on distributed ledger tools, and market mechanisms for organizing the work of heterogeneous multi-vendor cyber-physical systems when automated economical transactions are needed. A small swarm of robots follows the autonomous ship, which is in charge of maintaining the secure transactions. The swarm implements a version of Reynolds' Boids model based on the Belief Space Planning approach. The main contributions of our work consist of: (1) the deployment of a secure sample certification and logging platform based on the blockchain with a small-sized swarm of autonomous vessels performing maneuvers to measure chemical parameters of water in automatic mode; (2) the coordination of a leader-follower framework for the small platoon of robots by means of a Reynolds' Boids model based on a Belief Space Planning approach. In addition, the article describes the process of measuring the chemical parameters of water by using sensors located on the vessels. Both technology testing on experimental vessel and environmental measurements are detailed. The results have been obtained through real world experiments of an autonomous vessel, which was integrated as the “leader” into a mixed reality simulation of a swarm of simulated smaller vessels.The design of the experimental vessel physically deployed in the Volga river to demonstrate the practical viability of the proposed methods is shortly described.

Nitrogen and Phosphorus Loads in Greek Rivers: Implications for Management in Compliance with the Water Framework Directive

Reduction of nutrient loadings is often prioritized among other management measures for improving the water quality of freshwaters within the catchment. However, urban point sources and agriculture still thrive as the main drivers of nitrogen and phosphorus pollution in European rivers. With this article we present a nationwide assessment of nitrogen and phosphorus loads that 18 large rivers in Greece receive with the purpose to assess variability among seasons, catchments, and river types and distinguish relationships between loads and land uses of the catchment. We employed an extensive dataset of 636 field measurements of nutrient concentrations and river discharges to calculate nitrogen and phosphorus loads. Descriptive statistics and a cluster analysis were conducted to identify commonalties and differences among catchments and seasons. In addition a network analysis was conducted and its modularity feature was used to detect commonalities among rivers and sampling sites with regard to their nutrient loads. A correlation analysis was used to identify major possible connections between types of land uses and nutrient loads. The results indicated that the rivers Alfeios, Strymonas, and Aliakmonas receive the highest inorganic nitrogen loads while the highest inorganic phosphorus loads were calculated for the rivers Strymonas, Aliakmonas, and Axios. Concerning the temporal variation of loads, inorganic nitrogen presented a peak on March and gradually declined until October when the dry period typically ends for most regions of Greece. Inorganic phosphorus loads had the highest average value in August and the lowest in October. Thus, our findings confirmed the presence of a typical seasonal variation in nitrogen loads that follows the seasonality in hydrology where high surface runoff during the wet months contribute to higher river discharges and higher nitrogen loads from the catchment. On the contrary, high phosphorus loads persisted during dry months that could be attributed to a dilution effect. Furthermore, the results imply a clear connection between agriculture and both nitrogen and phosphorus. Overall, this work presents extensive information on the nitrogen and phosphorus loads that major rivers in Greece receive that can largely aid water managers to adapt and revise basin management plans in accordance with agricultural management (e.g., which months farmers should reduce the use of fertilizers) with the purpose of meeting the environmental targets defined by the Water Framework Directive (WFD).

Assessment of denitrification potential for coastal and inland sites using groundwater and soil analysis: the multivariate approach

In an effort to determine the reason behind excellent nitrate remediation capacity at Kelantan region, a multivariate approach is employed to evaluate extent to which the influence of sea on soil geochemical composition affect variation pattern of groundwater quality. The results obtained from geochemical analysis of paleo-beach soil in coastal site at Bachok revealed multiple redox activity at different soil strata, involving both heterotrophic and autotrophic denitrification. In soil and water analysis, eight of the fourteen hydro-geochemical parameters (conductivity, temperature, soil texture, oxidation reduction potential, pH, total organic carbon, Fe, Cu, Mn, Cl^-, SO₄^2-, NO₂^-, NO₃^- and PO₄^3-) measured using standard procedures were subjected to multivariate analysis. Evaluation of general variation pattern across the area reveals that the principal component analysis (PCA), hierarchical cluster analysis (HCA) and linear discriminant analysis (LDA) are in consonance with one another on apportioning three parameters (SO₄^2-, Cl^- and conductivity) to the coastal sites and two parameters (Fe and NH₄⁺ or NO₃^-) to inland sites. The step forward analysis of LDA reveals four parameters in order of decreasing significance as Cl^-, Fe and SO₄^2-, while the two-way HCA identifies three clusters on location basis, respectively. In addition to the significant data reduction obtained, the results indicate that proximity to sea and location/geological-based influence are more significant than temporal-based influence in denitrification. By extension, the research reveals that influence of labile portion of natural resources is explorable for broader application in other remediation strategies.

Source, contribution and microbial N-cycle of N-compounds in China fresh snow

The importance and contribution of nitrogen compounds and the related microbial nitrogen cycling processes in fresh snow are not well understood under the current research background. We collected fresh snow samples from 21 cities that 80% are from China during 2016 and 2017. Principal component analysis showed that SO₄^2- were in the first principal component, and N-compounds were the second. Furthermore, the main pollutant ions SO₄^2- and NO₃^- were from anthropogenic sources, and SO₄^2- contributed (61%) more to the pollution load than NO₃^- (29%), which were confirmed through a series of precipitation mechanism analysis. We selected five N-cycle processes (consist of oxidation and reduction processes) for molecular biology experiments, including Ammonia-oxidation process, Nitrite-oxidation process, Denitrification process, Anaerobic-ammoxidation process (Anammox) and Dissimilatory nitrate reduction to ammonium process (DNRA). Except ammonia-oxidizing archaeal (AOA) and bacterial (AOB) amoA genes (above 10⁷ copies g^-1), molecular assays of key functional genes in various nitrogen conversion processes showed a belowed detection limit number, and AOB abundance was always higher than AOA. The determination of the microbial transformation rate using the ¹⁵N-isotope tracer technique showed that the potential rate of five N-conversion processes was very low, which is basically consistent with the results from molecular biology studies. Taken together, our results illustrated that microbial nitrogen cycle processes are not the primary biological processes causing the pollution in China fresh snow.

Optimization and Application of Snow Melting Modules in SWAT Model for the Alpine Regions of Northern China

Snowmelt is the main source of runoff in the alpine regions of northern China. When using the soil and water assessment tool (SWAT) to simulate snowmelt runoff, the snowmelt date and snowmelt factor parameters are set according to the North American values. To improve the accuracy of the runoff simulation in northern China, we innovatively used a baseflow segmentation method to determine the snowmelt time, taking temperature as a reference. The snowmelt period was extracted from statistical data, and the corresponding parameters in the source code of SWAT were optimized for the study area. After the calibration was completed, the modified simulation value was compared with the original code simulation value. The simulation accuracy of the daily runoff was improved, and we found that the greater the difference between the source code simulation value and the observed value was, the better the simulation accuracy. Therefore, modifying the source code in SWAT is an effective way to improve the accuracy of simulations of Alpine regions in Northern China. The results show that adjustments to the snowmelt modules of SWAT to reflect local conditions can be an effective way to improve the predictions.

Modelling Impacts of a Municipal Spatial Plan of Land-Use Changes on Surface Water Quality—Example from Goriška Brda in Slovenia

Intensive agriculture causes nutrient leaching and accelerates erosion processes, which threatens the good quality status of surface waters, as proposed by the European Union (EU) Water Framework Directive. The purpose of this study was to define the impact of two alternative agricultural land-use change scenarios defined in a Municipal Spatial Plan on surface water quality by using the Agricultural Policy/Environmental eXtender (APEX) model. As experimental area, we chose a small Kožbanjšček stream catchment (1464 ha) situated in the Goriška Brda region in Slovenia. The area, due to favorable conditions for vineyards, is facing increasing deforestation. The change of 66.3 ha of forests to vineyards would increase the sediment, nitrate, and phosphorus loads in the stream by 24.8%, 17.1%, and 10.7%, respectively. With the implementation of vegetative buffer strips as a mitigation measure of the current situation, we could reduce the sediment, nitrate, and phosphorus loads by 17.9%, 11.1%, and 3.1%, respectively, while a combination of the two land-use change scenarios would result in a slight increase of the above-mentioned loads, corresponding to 0.61%, 2.1%, and 6.6%, respectively, compared to the baseline situation. The results confirm that, as we can increase pollution levels with deforestation, we can also reduce water pollution by choosing proper types of land management measures.

Increasing nitrogen export to sea: A scenario analysis for the Indus River

The Indus River Basin faces severe water quality degradation because of nutrient enrichment from human activities. Excessive nutrients in tributaries are transported to the river mouth, causing coastal eutrophication. This situation may worsen in the future because of population growth, economic development, and climate change. This study aims at a better understanding of the magnitude and sources of current (2010) and future (2050) river export of total dissolved nitrogen (TDN) by the Indus River at the sub-basin scale. To do this, we implemented the MARINA 1.0 model (Model to Assess River Inputs of Nutrients to seAs). The model inputs for human activities (e.g., agriculture, land use) were mainly from the GLOBIOM (Global Biosphere Management Model) and EPIC (Environmental Policy Integrated Model) models. Model inputs for hydrology were from the Community WATer Model (CWATM). For 2050, three scenarios combining Shared Socio-economic Pathways (SSPs 1, 2 and 3) and Representative Concentration Pathways (RCPs 2.6 and 6.0) were selected. A novelty of this study is the sub-basin analysis of future N export by the Indus River for SSPs and RCPs. Result shows that river export of TDN by the Indus River will increase by a factor of 1.6-2 between 2010 and 2050 under the three scenarios. >90% of the dissolved N exported by the Indus River is from midstream sub-basins. Human waste is expected to be the major source, and contributes by 66-70% to river export of TDN in 2050 depending on the scenarios. Another important source is agriculture, which contributes by 21-29% to dissolved inorganic N export in 2050. Thus a combined reduction in both diffuse and point sources in the midstream sub-basins can be effective to reduce coastal water pollution by nutrients at the river mouth of Indus.

Application of Export Coefficient Model and QUAL2K for Water Environmental Management in a Rural Watershed

Water quality deterioration caused by excessive nutrient discharge from various point and non-point sources are a global challenge. Understanding the pollution sources and their respective contribution is the prerequisite for environmental planning, management and restoration. In this study, the influence of complex pollution sources on the water quality of the Dengsha River watershed in Dalian, China, was investigated. The export coefficient method was coupled with the QUAL2K water quality model to estimate the loads of ammonia nitrogen (NH4-N) and total phosphorus (TP) from different sources, and to explore their respective contributions. Results indicated that animal feedlot and crop production were major sources for NH4-N load, and crop production, soil erosion and animal feedlot are the largest three sources of TP load with an annual total contribution of 98.4%. The pollutant load exhibited an intra-annual variation mainly due to the seasonality of rainfall and anthropogenic agricultural activities. The overall waste assimilation capacity (WAC) is overloaded and suggestions for water pollution control and treatment regarding each pollution source were proposed. This study addressed a new application of QUAL2K model coupled with the export coefficient model for watershed managers towards a sustainable water environmental management, and can therefore be a reference example for other small and medium-sized rural watersheds.

Assessment of Agriculture Pressures Impact on the Joumine River Water Quality Using the PEGASE Model

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

Pursuing implementation solutions for targeted nitrogen management in agriculture- a novel approach to synthesize knowledge and facilitate sustainable decision making based on collaborative landscape modelling

Regulation of nitrate emission from agriculture to aquatic environments in Denmark currently depend on general rules for nutrient application and associated farm-level reporting schemes. Similar or comparable centralized regulation instruments dedicated to controlling and limiting rather than focusing and improving N application practices exist in large parts of the OECD. Recent policy debates have exposed an array of problems relating to this type of regulation. Problems include issues of appropriate scale, transparency and failures to adapt intervention and regulation to relevant geo-ecological variations in contexts where general rules are being imposed on varied agro-ecosystems. Therefore it has been proposed to rescale regulation to better fit relevant socio-political and agro-environmental processes including the scale of farmers' decision making, the scale of relevant hydrological systems and the scale of key agro-ecological conditions such as soil characteristics and drainage. However, the challenge of shifting the regulation to a more local scale raises a number of questions. These include (1) How information produced locally can be integrated with national scale data? (2) In what way integrated datasets can used to model environmental effects of current and possible land use patterns? (3) In what way data and estimates of consequences of land use changes are best made available in decision making processes? To address these questions this article reports on ongoing work in Denmark to develop a decision support tool for N-management at the scale of agricultural landscapes, which are areas where a similar pattern of land use is repeated across the land surface, reflecting a specific mode of adapting agriculture to natural conditions. The aim of the article is to evaluate the design of a decision support tool aiming at enabling strategic N-management at landscape scales by linking decision support at the scale of individual farms with decision support targeted at groups of farms where a coordinated effort to solve common problems may be more efficient. Design targets for the tool were established empirically based on evidence from exploratory workshops with farmers and other stakeholders in 6 case areas across Denmark. On this basis a prototype GIS-tool for capturing, storing, editing, displaying and modelling landscape scale farming practices and associated emission consequences was developed. The tool was designed to integrate locally held knowledge with national scale datasets in live scenario situations through the implementation of a flexible, uniform and editable data model for land use data - the dNmark landscape model. Based on input data that is corrected and co-authored by workshop participants, the tool estimates the effect of potential land use scenarios on nutrient emissions. The tool was tested in 5 scenario workshops in case areas in Denmark in 2016, on the basis of which its design is evaluated and discussed in this article.

Concurrent transport and removal of nitrate, phosphate and pesticides in low-cost metal- and carbon-based materials

Low-cost magnesium- and/or carbon-based materials have a great potential to remove soluble contaminants from surface and ground water. This study examined mechanisms that control the removal of nitrate, phosphate and pesticides (tricyclazole, malathion and isoprothiolane) during their transport through calcined magnesia (MgO) and corn stalk biochar. Various miscible column breakthrough experiments were carried out and morphology and crystallographic structures of reactive materials were examined. Approximately 96% (78,950 mg-NO₃^-/kg) and 48% (27,455 mg-NO₃^-/kg) of nitrate were removed from biochar and MgO columns, respectively. Chemical adsorption dominated nitrate removal during early phase (i.e., <11 PVs for biochar and <100 PVs for MgO, respectively), and microbial denitrification dominated during the following phase. 92% of the applied phosphate (6168 mg-PO₄^3-/kg) was removed in MgO column, while much less in biochar column (4%, 347 mg-PO₄^3-/kg). Mineral surface analyses confirmed that electrostatic attraction, ligand exchange, and chemical precipitation were responsible for phosphate removal. For the three pesticides, biochar exhibited larger removal capacity (1260-2778 mg/kg) than MgO (28-2193 mg/kg) due to the functional groups on biochar. The removal of pesticides based on their physico-chemical properties. Malathion had highest removal rate (98-100%), attributing to chemical sorption and bio-degradation, followed by isoprothiolane (47-79%) and tricyclazole (6-64%).

Water Quality and Hydromorphological Variability in Greek Rivers: A Nationwide Assessment with Implications for Management

European rivers are under ecological threat by a variety of stressors. Nutrient pollution, soil erosion, and alteration in hydrology are considered the most common problems that riverine ecosystems are facing today. Not surprisingly, river monitoring activities in Europe have been intensified during the last few years to fulfil the Water Framework Directive (WFD) requirements. With this article, we present a nationwide assessment of the water quality and hydromorphological variability in Greek Rivers based on the results of the national monitoring program under the WFD. Water quality and hydromorphological data from 352 sites belonging to 221 rivers were explored with principal component analysis (PCA) to identify main environmental gradients and the variables that contribute the most to the total variance. Nitrate, phosphate, ammonium and electrical conductivity were identified as the most important water chemistry parameters, and typical vector-based spatial data analysis was applied to map their spatial distribution at sub-basin scale. In addition, we conducted simple linear models between the aforementioned parameters and the share of land uses within the basin of each sampling site in order to identify significant relationships. Agriculture was the most important land use affecting the nitrate and electrical conductivity, while artificial surfaces were the best predictor for phosphate and ammonium. Concerning the hydromorphological variability, fine types of substrate and discharge were the variables with the highest contribution to the total variance. Overall, the results of this article can be used for the preliminary assessment of susceptible areas/rivers to high levels of nutrient pollution that can aid water managers to formulate recommendations for improvement of further monitoring activities. Furthermore, our findings implicate the need for enhancement of agri-environmental measures and reduction of point-source pollution in disturbed areas to avert the risk of further environmental degradation under the anticipated global change.

Reactive Transport and Removal of Nutrients and Pesticides in Engineered Porous Media

Agricultural nonpoint pollution has been recognized as a primary source of nutrients and pesticides that contaminate surface water and groundwater. Reactive materials have great potential to remove nutrients and pesticides from agricultural drainage water. In this study, we investigated the reactive transport and removal of coexisting nitrate, phosphate, and three pesticides (tricyclazole, isoprothiolane, and malathion) by iron filings and natural ore limestone through column experiments under saturated flow conditions. Breakthrough results showed that 45.0% and 35.8% of nitrate were removed by iron filings and limestone during transport, with average removal capacities of 2670 mg/kg and 1400 mg/kg, respectively. The removal of nitrate was mainly due to microbial denitrification especially after 131–154 pore volumes (≈30 d), whereas reduction to ammonia dominated nitrate removal in iron filings during early phase (i.e., <21.7 d). The results showed that 68.2% and 17.6% of phosphate were removed by iron filings and limestone, with average removal capacities of 416.1 mg/kg and 155.2 mg/kg, respectively. Mineral surface analyses using X-ray diffraction (XRD) and scanning electron microscope (SEM) coupled with energy-dispersive X-ray analysis (EDX) suggested that ligand exchange, chemical precipitation, and electrostatic attraction were responsible for phosphate removal. Chemical sorption was the main mechanism that caused removals of 91.6–100% of malathion and ≈27% of isoprothiolane in iron filings and limestone. However, only 22.0% and 1.1% of tricycalzole were removed by iron filings and limestone, respectively, suggesting that the removal might be relevant to the nonpolarity of tricyclazole. This study demonstrates the great potential of industrial wastes for concurrent removal of nutrients and pesticides under flow conditions.

Springs drive downstream nitrate export from artificially-drained agricultural headwater catchments

Excessive nutrient loading from small agricultural headwaters can substantially degrade downstream water quality and ecological conditions. But, our understanding of the scales and locations to implement nutrient attenuation tools within these catchments is poor. To help inform farm- and catchment-scale management, we quantified nitrate export in nine one-kilometre-long lowland agricultural headwaters fed by tile and open tributary drains in a region with high groundwater nitrate (<1 to >15 mg L^-1 NO₃-N) over four years. Across-catchment differences in upstream spring water nitrate concentrations predicted differences in annual nitrate loads at catchment outlets (range <1-72 megagrams NO₃-N 365 d^-1), and nitrate loads were higher in wet seasons and wet years, reflecting strong groundwater influences. Partitioning the sources of variability in catchment nitrate fluxes revealed that ~60% of variation was accounted for by a combination of fluxes from up-stream springs and contributions from tile and open tributary drains (46% and 15%, respectively), with ~40% of unexplained residual variation likely due to groundwater upwellings. Although tile and open tributary drains contributed comparatively less to catchment loads (tile drains: <0.01 and up to 50 kg NO₃-N d^-1; open drains: <5 kg and up to 100 kg NO₃-N d^-1), mitigation targeted at these localised, farm-scale sources will contribute to decreasing downstream nitrate fluxes. However, high nitrate loads from groundwater mean current NO₃-N waterway management and rehabilitation practices targeting waterway stock exclusion by fencing alone will be insufficient to reduce annual NO₃-N export. Moreover, managing catchment nutrient fluxes will need to acknowledge contributions from groundwater as well as farm-scale losses from land. Overall, our results highlight how nutrient fluxes in spring-fed waterways can be highly dynamic, dominated more by groundwater than local run-off, and point to the scales and locations where nitrate attenuation tools should be implemented.

Large scale prediction of groundwater nitrate concentrations from spatial data using machine learning

Reducing nitrogen inputs, in particular nitrate, to groundwater is becoming increasingly important to fulfil requirements of the European Water Framework Directive. When developing management plans for mitigation measures at larger scales, complex hydro-biogeochemical models reach their limits due to data availability and spatial discretization. To circumvent this problem, the spatial distribution of nitrate concentration in groundwater is estimated using a parsimonious GIS-based statistical approach. Point nitrate concentrations and spatial environmental data as predictors are used to train statistical models. In order to compile the spatial predictors with the respective monitoring sites, different designs of contributing areas (buffer zones) and their effects on the performance of different statistical models are investigated. Multiple Linear Regression (MLR), Classification and Regression Trees (CART), Random Forest (RF) and Boosted Regression Trees (BRT) are compared in terms of the predictive performance of each model according to various objective functions. We determine the most influential spatial predictors used in the respective models. After training the models with a subset of the data, we then predict the spatial nitrate distribution in groundwater for the entire federal state of Hesse, Germany on a 1 × 1 km grid by only the spatial environmental data. The Random Forest model outperforms the other models (R² = 0.54), relying on hydrogeological units, the percentage of arable land and the nitrogen balance as the three most influencing predictors based on a 1000 m circular contributing area. The use of exclusively spatial available predictors is a big step forward in the prediction of nitrate in groundwater on regional scale.

Modelling Nitrate Reduction Strategies from Diffuse Sources in the Po River Basin

Water contamination caused by the presence of excessive amounts of nitrate can be catastrophic for aquatic ecosystems and human health. Due to these high risks, a great deal of emphasis has been placed on finding effective measures to reduce nitrate concentrations in rivers and aquifers. In this study, we used the SWAT model based on grid-cells of 5 minutes of resolution for assessing the processes involved in nitrate loads generation and transport into aquifers and rivers and for providing basin management strategies of nitrate reduction. We applied the model in the Po River Basin (Italy), one of the most densely populated and highly agriculturally exploited area in the Mediterranean basin. The model was successfully calibrated and validated in eight monitoring stations along the Po River for the period 2000–2012. Simulated monthly streamflow and nitrate concentrations were in good agreement with observations, obtaining values of bias around ±25% in both calibration and validation. Among the tested scenarios of nitrogen reduction from agricultural sources, red clover cover crop after corn, coupled with a targeted reduction of mineral fertilizers and the limitation of nitrogen manure leads to a reduction of nitrate leaching and nitrogen emissions of around 37%.

Development of effective sequence multi-barrier reactive media for nitrate remediation in groundwater systems

Early depletion of carbon-based electron donors and pollution swapping are among the recalcitrant challenges for in situ remediation technology. There is a pressing need to provide a slow but steady dose of materials for a prolonged period in order to sustain in situ treatments. In an effort to develop effective sequence multi-barrier reactive media that can address these challenges, the present study reports laboratory column experiments using organic (date seed, Moringa oleifera and wood chips) and inorganic (limestone; CaCO3) carbonaceous materials in varying proportions. The substances are supported by paleo sandy beach soil and are sequentially packed in line with the geometric pattern of a hypothetical funnel and gate for nitrate (NO3 -) remediation. The optimized reactive media show remarkable efficiency, remediating 94.4% of NO3 - as a target pollutant within the system. They also remediate 99.20% of the NO3 - down the gradient and 96.4% of its lethal by-product - NO2 -. However, with the generation of an 11-fold biomass build-up, the system is only able to eliminate 53% of the total organic carbon generated. Hence, the advective dispersive features of aquifers are required for the complete remediation of the generated secondary biomass. The results also reveal that the efficiency of the sequential media depends on the composition/ratio of the constituents, flow rate and the initial concentration of NO3 - in the influent. Surface characterization studies (FESEM-EDX and FTIR) show that compared to wood chips, date seed is less prone to degradation, suggesting a longer life span. A degradation study affirms the findings of the surface studies as it reveals that the half-life of date seed is three times longer than that of wood chips. In addition, the study reveals that the double exponential model is more suitable than the single exponential model in determining the rate of decay of both wood chips and date seed.

Controlled Drainage as a Targeted Mitigation Measure for Nitrogen and Phosphorus

Drainage systems provide a more or less direct conduit for excess water and nutrients from fields to surface water. High nutrient loads to streams and lakes are known to adversely affect water quality and may potentially cause algae blooms. Therefore, in-field as well as edge-of-field mitigation measures that can assist in reducing the loss of nutrients are needed. The aim of this study was to investigate the effectiveness and possibility of using controlled drainage during the drainage season to reduce nutrient losses while growing a winter crop in a temperate climate. The 3-yr-long (2012-2015) study was conducted on four experimental field plots on loamy soil. The impacts of controlled drainage on groundwater levels, drain flow, and water quality at regulation levels of 50 and 70 cm above the conventional drain pipe level were determined by using a before-after control-impact study design. A regulation level of 70 cm was required to significantly elevate groundwater levels and reduce the drain outflow and N and P loss, which decreased by 37 to 54%, 38 to 51%, and 43 to 46%, respectively, relative to conventional drainage levels. Denitrification in the root zone, as measured with stable isotopes, was not markedly enhanced at the plots with controlled drainage, except on a few occasions. Resetting the groundwater level to conventional levels in early spring only had a marginal influence on water and nutrient losses. Thus, potential water quality tradeoffs (e.g., increased N loss to groundwater) need to be more thoroughly investigated before implementing controlled drainage as a mitigation measure in Denmark.

Modelling nutrient fluxes into the Mediterranean Sea

STUDY REGION

Mediterranean River Basins.

STUDY FOCUS

Human activities and consequent pollution have put the freshwater and marine ecosystems of the Mediterranean region under pressure, with high risk of eutrophication phenomena. In this study, an extended version of the Geospatial Regression Equation for European Nutrient losses model (GREEN), originally developed for estimating nutrient loads from diffuse and point sources in Europe, was extended to include additional nutrient sources using a grid cell discretization. The spatial resolution is 5 arc minute and the model inputs consist of the latest and best available global data.

NEW HYDROLOGICAL INSIGHTS FOR THE REGION

The results of this study show that during 2003-2007 (baseline), 1.87 Tg/y of total nitrogen (TN), 1.22 Tg/y of nitrates (N-NO₃), 0.11 Tg/y of total phosphorus (TP) and 0.03 Tg/y of orthophosphate (P-PO₄) were discharged in the Mediterranean Sea. The source apportionment analysis showed that the main contributor to total nitrogen and nitrate loads is agriculture followed by natural background, while for orthophosphate dominant sources include wastewater and scattered dwellings. Two scenarios were investigated to assess sustainable water and nutrient management options, showing that the reduction of 50% of nitrogen surplus leads to a significant reduction of nitrogen emission in regions characterized by high intensity agriculture, while the upgrading of wastewater treatment plants to tertiary level was more efficient for TP reduction.

Coupling stable isotopes and water chemistry to assess the role of hydrological and biogeochemical processes on riverine nitrogen sources

Accurate source identification is critical for optimizing water pollution control strategies. Although the dual stable isotope (¹⁵N-NO₃^-/¹⁸O-NO₃^-) approach has been widely applied for differentiating riverine nitrogen (N) sources, the relatively short-term (<1 yr) ¹⁵N-NO₃^-/¹⁸O-NO₃^- records typically used in previous studies often hinders rigorous assessment due to high temporal variability associated with watershed N dynamics. Estimated contributions of legacy N sources in soils and groundwater to riverine N export by modeling approaches in many previous studies also lack validation from complementary information, such as multiple stable isotopes. This study integrated three years of multiple stable isotope (¹⁵N-NO₃^-/¹⁸O-NO₃^- and ²H-H₂O/¹⁸O-H₂O) and hydrochemistry measurements for river water, groundwater and rainfall to elucidate N dynamics and sources in the Yongan watershed (2474 km²) of eastern China. Nonpoint source N pollution dominated and displayed considerable seasonal and spatial variability in N forms and concentrations. Information from δ¹⁵N-NO₃^- and δ¹⁸O-NO₃^- indicated that riverine N dynamics were regulated by contributing sources, nitrification and denitrification, as well as hydrological processes. For the three examined catchments and entire watershed, slow subsurface and groundwater flows accounted for >75% of river discharge and were likely the major hydrological pathways for N delivery to the river. Riverine NO₃^- sources varied with dominant land use (p < 0.001), with the highest contributions of groundwater (60%), wastewater (35%), and soil (50%) occurring in agricultural, residential and forest catchments, respectively. For the entire watershed, groundwater (∼50%) and soil N (>30%) were the dominant riverine NO₃^- sources, implying considerable potential for N pollution legacy effects. Results were consistent with observed nitrous oxide dynamics and N sources identified in previous modeling studies. As the first attempt to apply multiple isotope tracers for exploring and quantifying N transformation and transport pathways, this study provides an integrated approach for verifying and understanding the N pollution legacy effects observed in many watersheds worldwide. This study highlights that river N pollution control in many watersheds requires particular attention to groundwater restoration and soil N management in addition to N input control strategies.

The reduction effects of riparian reforestation on runoff and nutrient export based on AnnAGNPS model in a small typical watershed, China

The continuous deterioration of the aquatic environment in rivers and streams is increasingly causing social and political tensions. To alleviate aquatic environmental problems, especially for the nonpoint source pollution, establishment of riparian forest buffers has been demonstrated as an effective control measure. However, few comprehensive studies of the reduction effects of riparian reforestation on the aquatic environment have been performed, particularly in identifying the suitable widths of reforestation projects. In this paper, the Annualized Agricultural Non-Point Source (AnnAGNPS) model was used to simulate the reduction effects of riparian reforestation on runoff and nutrient loads in Wucun watershed, China. The results showed that 20-m, 40-m, and 60-m widths of riparian buffer reforestation had significant effects on the yearly loads of total nitrogen (TN) and total phosphorus (TP), with reduced rates of 23.21 to 56.2% and 18.16 to 52.14%, respectively. The reduction effect on annual runoff varied from 2.8 to 5.4%. Furthermore, the reduction effect of nutrients performed best during the transition period, while the best runoff reduction was found during the dry period. These distinct reductions indicated that the implementation of riparian forest buffers was capable of reducing the risk and frequency of flooding and eutrophication, especially during the wet and transition periods. Additionally, the 20-m width of riparian buffer reforestation achieved the highest reduction efficiency for runoff, and the 40-m width was the most suitable reforested riparian buffer width for TN and TP. Therefore, 40 m may be the optimum buffer width for the implementation of riparian reforestation in the Wucun watershed. These research results provided scientific information on selecting the optimum buffer width for aquatic environmental regulators and managers as the reduction effects of different widths of riparian buffers on runoff and nutrients were different when considering buffer reforestation.

Delay in catchment nitrogen load to streams following restrictions on fertilizer application

A MIKE SHE hydrological-solute transport model including nitrate reduction is employed to evaluate the delayed response in nitrogen loads in catchment streams following the implementation of nitrogen mitigation measures since the 1980s. The nitrate transport lag times between the root zone and the streams for the period 1950-2011 were simulated for two catchments in Denmark and compared with observational data. Results include nitrogen concentration and mass discharge to streams. By automated baseflow separation, stream discharge was separated into baseflow and drain flow components, and the nitrogen concentration and mass discharge in baseflow and drain flow were determined. This provided insight on the development of stream nitrogen loads, with a short average lag time in drain flow and a long average lag time in baseflow. The long term effect of nitrogen mitigation measures was determined, with results showing that there is a 15 years long delay in the appearance of peak nitrogen loads in streams. This means that real time stream monitoring data cannot be used alone to assess the effect of nitrogen mitigation measures.

Assessing the potential impacts of a revised set of on-farm nutrient and sediment 'basic' control measures for reducing agricultural diffuse pollution across England

The need for improved abatement of agricultural diffuse water pollution represents cause for concern throughout the world. A critical aspect in the design of on-farm intervention programmes concerns the potential technical cost-effectiveness of packages of control measures. The European Union (EU) Water Framework Directive (WFD) calls for Programmes of Measures (PoMs) to protect freshwater environments and these comprise 'basic' (mandatory) and 'supplementary' (incentivised) options. Recent work has used measure review, elicitation of stakeholder attitudes and a process-based modelling framework to identify a new alternative set of 'basic' agricultural sector control measures for nutrient and sediment abatement across England. Following an initial scientific review of 708 measures, 90 were identified for further consideration at an industry workshop and 63 had industry support. Optimisation modelling was undertaken to identify a shortlist of measures using the Demonstration Test Catchments as sentinel agricultural landscapes. Optimisation selected 12 measures relevant to livestock or arable systems. Model simulations of 95% implementation of these 12 candidate 'basic' measures, in addition to business-as-usual, suggested reductions in the national agricultural nitrate load of 2.5%, whilst corresponding reductions in phosphorus and sediment were 11.9% and 5.6%, respectively. The total cost of applying the candidate 'basic' measures across the whole of England was estimated to be £450 million per annum, which is equivalent to £52 per hectare of agricultural land. This work contributed to a public consultation in 2016.

Quantifying the combined effects of land use and climate changes on stream flow and nutrient loads: A modelling approach in the Odense Fjord catchment (Denmark)

Water pollution and water scarcity are among the main environmental challenges faced by the European Union, and multiple stressors compromise the integrity of water resources and ecosystems. Particularly in lowland areas of northern Europe, high population density, flood protection and, especially, intensive agriculture, are important drivers of water quality degradation. In addition, future climate and land use changes may interact, with uncertain consequences for water resources. Modelling approaches have become essential to address water issues and to evaluate ecosystem management. In this work, three multi-stressor future storylines combining climatic and socio-economic changes, defined at European level, have been downscaled for the Odense Fjord catchment (Denmark), giving three scenarios: High-Tech agriculture (HT), Agriculture for Nature (AN) and Market-Driven agriculture (MD). The impacts of these scenarios on water discharge and inorganic and organic nutrient loads to the streams have been simulated using the Soil and Water Assessment Tool (SWAT). The results revealed that the scenario-specific climate inputs were most important when simulating hydrology, increasing river discharge in the HT and MD scenarios (which followed the high emission 8.5 representative concentration pathway, RCP), while remaining stable in the AN scenario (RCP 4.5). Moreover, discharge was the main driver of changes in organic nutrients and inorganic phosphorus loads that consequently increased in a high emission scenario. Nevertheless, both land use (via inputs of fertilizer) and climate changes affected the nitrate transport. Different levels of fertilization yielded a decrease in the nitrate load in AN and an increase in MD. In HT, however, nitrate losses remained stable because the fertilization decrease was counteracted by a flow increase. Thus, our results suggest that N loads will ultimately depend on future land use and management in an interaction with climate changes, and this knowledge is of utmost importance for the achievement of European environmental policy goals.

Partitioning multi-source uncertainties in simulating nitrogen loading in stream water using a coherent, stochastic framework: Application to a rice agricultural watershed in subtropical China

Uncertainty is recognized as a critical consideration for accurately predicting stream water nitrogen (N) loading, but identifying the relative contribution of individual uncertainty sources within the total uncertainty remains unclear. In this study, a powerful method, referred to as the Bayesian inference combined with analysis of variance (BayeANOVA) was adopted to detect the timing and magnitude of multiple uncertainty sources and their relative contributions to total uncertainty in simulating daily loadings of three stream water N species (ammonium-N: NH₄⁺-N, nitrate-N: NO₃^--N and total N: TN) in a rice agricultural watershed (the Tuojia watershed) as influenced by non-point source N pollution. Five sources of uncertainty have been analyzed in this study, which arise from model structure, parameters, inputs, interaction effects between parameters and inputs, and internal variability (induced by random errors of model or environment). The results show that uncertainty in parameters relating to the processes of both N and hydrologic cycles contributed the largest fractions of total uncertainty in N loading simulations (58.83%, 63.48% and 61.64% for NH₄⁺-N, NO₃^--N and TN loading, respectively). Additionally, three of the largest uncertainties (i.e. parameters, inputs and interaction effects) in all three simulated N loadings were on average significantly greater in the rice-growing season relative to the fallow season, primarily due to the excess fertilization application during the rice-growing season. The predicted TN uncertainty was mainly attributed to the inaccuracy of NO₃^--N simulation, which contributed to 75.48% of predicted TN uncertainty. It is concluded that reducing the parameter uncertainty of NO₃^--N loading simulation during the rice-growing season is the key factor to improving stream water N modeling precision in rice agricultural watersheds.

Environmental Indicator Principium with Case References to Agricultural Soil, Water, and Air Quality and Model-Derived Indicators

Environmental indicators are powerful tools for tracking environmental changes, measuring environmental performance, and informing policymakers. Many diverse environmental indicators, including agricultural environmental indicators, are currently in use or being developed. This special collection of technical papers expands on the peer-reviewed literature on environmental indicators and their application to important current issues in the following areas: (i) model-derived indicators to indicate phosphorus losses from arable land to surface runoff and subsurface drainage, (ii) glutathione-ascorbate cycle-related antioxidants as early-warning bioindicators of polybrominated diphenyl ether toxicity in mangroves, and (iii) assessing the effectiveness of using organic matrix biobeds to limit herbicide dissipation from agricultural fields, thereby controlling on-farm point-source pollution. This introductory review also provides an overview of environmental indicators, mainly for agriculture, with examples related to the quality of the agricultural soil-water-air continuum and the application of model-derived indicators. Current knowledge gaps and future lines of investigation are also discussed. It appears that environmental indicators, particularly those for agriculture, work efficiently at the field, catchment, and local scales and serve as valuable metrics of system functioning and response; however, these indicators need to be refined or further developed to comprehensively meet community expectations in terms of providing a consistent picture of relevant issues and/or allowing comparisons to be made nationally or internationally.