Mitigating nitrogen losses with almost no crop yield penalty during extremely wet years.

Climate change-induced precipitation anomalies during extremely wet years (EWYs) result in substantial nitrogen losses to aquatic ecosystems (Nw). Still, the extent and drivers of these losses, and effective mitigation strategies have remained unclear. By integrating global datasets with well-established crop modeling and machine learning techniques, we reveal notable increases in Nw, ranging from 22 to 56%, during historical EWYs. These pulses are projected to amplify under the SSP126 (SSP370) scenario to 29 to 80% (61 to 120%) due to the projected increases in EWYs and higher nitrogen input. We identify the relative precipitation difference between two consecutive years (diffPr) as the primary driver of extreme Nw. This finding forms the basis of the CLimate Extreme Adaptive Nitrogen Strategy (CLEANS), which scales down nitrogen input adaptively to diffPr, leading to a substantial reduction in extreme Nw with nearly zero yield penalty. Our results have important implications for global environmental sustainability and while safeguarding food security.

Modeling transport and fate of heavy metals at the watershed scale: State-of-the-art and future directions.

A predictive understanding of the source-specific (e.g., point and diffuse sources) land-to-river heavy metal (HM) loads and HM dynamics in rivers is essential for mitigating river pollution and developing effective river basin management strategies. Developing such strategies requires adequate monitoring and comprehensive models based on a solid scientific understanding of the watershed system. However, a comprehensive review of existing studies on the watershed-scale HM fate and transport modeling is lacking. In this review, we synthesize the recent developments in the current generation of watershed-scale HM models, which cover a wide range of functionalities, capabilities, and spatial and temporal scales (resolutions). Existing models, constructed at various levels of complexity, have their strengths and weaknesses in supporting diverse intended uses. Additionally, current challenges in the application of watershed HM modeling are covered, including the representation of in-stream processes, organic matter/carbon dynamics and mitigation practices, the issues of model calibration and uncertainty analysis, and the balance between model complexity and available data. Finally, we outline future research requirements regarding modeling, strategic monitoring, and their combined use to enhance model capabilities. In particular, we envisage a flexible framework for future watershed-scale HM models with varying degrees of complexity to accommodate the available data and specific applications.

Integrated assessment of land-to-river Cd fluxes and riverine Cd loads using SWAT-HM to guide management strategies.

In 2011, China invested US$9.8 billion to combat the severe heavy metal pollution in the Xiang River basin (XRB), aiming to reduce 50% of the 2008 industrial metal emissions by 2015. However, river pollution mitigation requires a holistic accounting of both point and diffuse sources, yet the detailed land-to-river metal fluxes in the XRB remain unclear. Here, by combining emissions inventories with the SWAT-HM model, we quantified the land-to-river cadmium (Cd) fluxes and riverine Cd loads across the XRB from 2000 to 2015. The model was validated against long-term historical observations of monthly streamflow and sediment load and Cd concentrations at 42, 11, and 10 gauges, respectively. The analysis of the simulation results showed that the soil erosion flux dominated the Cd exports (23.56-80.14 Mg yr-1). The industrial point flux decreased by 85.5% from 20.84 Mg in 2000 to 3.02 Mg in 2015. Of all the Cd inputs, approximately 54.9% (37.40 Mg yr-1) was finally drained into Dongting Lake; the remaining 45.1% (30.79 Mg yr-1) was deposited within the XRB, increasing the Cd concentration in riverbed sediment. Furthermore, in XRB's 5-order river network, the Cd concentrations in small streams (1st order and 2nd order) showed larger variability due to their low dilution capacity and intense Cd inputs. Our findings highlight the need for multi-path transport modeling to guide future management strategies and better monitoring schemes to restore the small polluted streams.

Identification of priority management areas for non-point source pollution based on critical source areas in an agricultural watershed of Northeast China.

Identification of critical source areas (CSAs) for non-point source (NPS) pollution is of great significance for environment governance and prevention. However, the CSAs are generally characterized as great spatial dispersion, and spatially heterogeneous precipitation has a great influence on the spatial distribution of nutrient yields. Therefore, we identify the CSAs for nutrient yields in an agricultural watershed of Northeast China at hydrological response units (HRUs) scale based on the Soil and Water Assessment Tool (SWAT), assess the impacts of spatially heterogeneity of precipitation on the identification of the CSAs, analyze the sensitivity of nutrient yields to precipitation by scenarios analysis method, and further identify priority management areas (PMAs) that have poor ability to retain nutrients. The results showed that the CSAs for nutrient yields identified by uniform precipitation showed greater fluctuation range and coverage area than actual precipitation; the major prevention areas of total nitrogen (TN) yield were mainly distributed in regions nearby main stem of lower reaches, while that of total phosphorus (TP) yield were mostly located in urban area nearby outlet of the watershed; the identification of the PMAs significantly decreased the CSAs for TN yield, whereas that for TP yield was no significant difference with the CSAs. This study could provide scientific guidance for the NPS pollution governance and prevention.

Integrated assessment of climate change impacts on multiple ecosystem services in Western Switzerland.

Climate change can affect the provision of ecosystem services in various ways. In this study, we provide an integrated assessment of climate change impacts on ecosystem services, considering uncertainties in both climate projection and model parameterization. The SWAT model was used to evaluate the impacts on water regulation, freshwater, food, and erosion regulation services for the Broye catchment in Western Switzerland. Downscaled EURO-CORDEX projections were used for three periods of thirty years: base climate (1986-2015), near future (2028-2057), and far future (2070-2099). Results reveal that in the far future, low flow is likely to decrease in summer by 77% and increase in winter by 65%, while peak flow may decrease in summer by 19% and increase in winter by 26%. Reduction in summer precipitation reduces nitrate leaching by 25%; however, nitrate concentrations are projected to increase by 14% due to reduced dilution. An increase in winter precipitation increases nitrate leaching by 44%, leading to an increase of nitrate concentration by 11% despite increasing discharge and dilution. Yields of maize and winter wheat are projected to increase in the near future but decrease in the far future because of increasing water and nutrient stress. Average grassland productivity is projected to benefit from climate change in both future periods due to the extended growing season. This increase in productivity benefits erosion regulation as better soil cover helps to decrease soil loss in winter by 5% in the far future. We conclude that water regulation, freshwater and food services will be negatively affected by climate change. Hence, agricultural management needs to be adapted to reduce negative impacts of climate change on ecosystem services and to utilize emerging production potentials. Our findings highlight the need for further studies of potentials to improve nutrient and water management under future climate conditions.

Author Correction: The future of extreme climate in Iran.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

The future of extreme climate in Iran.

Iran is experiencing unprecedented climate-related problems such as drying of lakes and rivers, dust storms, record-breaking temperatures, droughts, and floods. Here, we use the ensemble of five high-resolution climate models to project maximum and minimum temperatures and rainfall distribution, calculate occurrences of extreme temperatures (temperatures above and below the historical 95th and 5th percentiles, respectively), analyze compound of precipitation and temperature extremes, and determine flooding frequencies across the country. We found that compared to the period of 1980-2004, in the period of 2025-2049, Iran is likely to experience more extended periods of extreme maximum temperatures in the southern part of the country, more extended periods of dry (for ≥120 days: precipitation <2 mm, Tmax ≥30 °C) as well as wet (for ≤3 days: total precipitation ≥110 mm) conditions, and higher frequency of floods. Overall, the combination of these results projects a climate of extended dry periods interrupted by intermittent heavy rainfalls, which is a recipe for increasing the chances of floods. Without thoughtful adaptability measures, some parts of the country may face limited habitability in the future.

Achieving High Crop Yields with Low Nitrogen Emissions in Global Agricultural Input Intensification.

Increasing demand for food is driving a worldwide trend of agricultural input intensification. However, there is no comprehensive knowledge about the interrelations between potential yield gains and environmental trade-offs that would enable the identification of regions where input-driven intensification could achieve higher yields, yet with minimal environmental impacts. We explore ways of enhancing global yields, while avoiding significant nitrogen (N) emissions (Ne) by exploring a range of N and irrigation management scenarios. The simulated responses of yields and Ne to increased N inputs (Nin) and irrigation show high spatial variations due to differences in current agricultural inputs and agro-climatic conditions. Nitrogen use efficiency (NUE) of yield gains is negatively correlated with incremental Ne due to Nin additions. Avoiding further intensification in regions where high fractions of climatic yield potentials, ≥ 80%, are already achieved is key to maintain good NUE. Depending on the intensification scenarios, relative increases in Ne could be reduced by 0.3-29.6% of the baseline Ne with this intensification strategy as compared to indiscriminate further intensification, at the cost of a loss of yield increases by 0.2-16.7% of the baseline yields. In addition, irrigation water requirements and Nin would dramatically decrease by considering this intensification strategy.

A web platform for landuse, climate, demography, hydrology and beach erosion in the Black Sea catchment.

The Black Sea catchment (BSC) is facing important demographic, climatic and landuse changes that may increase pollution, vulnerability and scarcity of water resources, as well as beach erosion through sea level rise. Limited access to reliable time-series monitoring data from environmental, statistical, and socio-economical sources is a major barrier to policy development and decision-making. To address these issues, a web-based platform was developed to enable discovery and access to key environmental information for the region. This platform covers: landuse, climate, and demographic scenarios; hydrology and related water vulnerability and scarcity; as well as beach erosion. Each data set has been obtained with state-of-the-art modelling tools from available monitoring data using appropriate validation methods. These analyses were conducted using global and regional data sets. The data sets are intended for national to regional assessments, for instance for prioritizing environmental protection projects and investments. Together they form a unique set of information, which lay out future plausible change scenarios for the BSC, both for scientific and policy purposes.

Discharge permit market and farm management nexus: an approach for eutrophication control in small basins with low-income farmers.

The economic concerns of low-income farmers are barriers to nutrient abatement policies for eutrophication control in surface waters. This study brings up a perspective that focuses on integrating multiple-pollutant discharge permit markets with farm management practices. This aims to identify a more economically motivated waste load allocation (WLA) for non-point sources (NPS). For this purpose, we chose the small basin of Zrebar Lake in western Iran and used the soil and water assessment tool (SWAT) for modeling. The export coefficients (ECs), effectiveness of best management practices (BMPs), and crop yields were calculated by using this software. These variables show that low-income farmers can hardly afford to invest in BMPs in a typical WLA. Conversely, a discharge permit market presents a more cost-effective solution. This method saves 64% in total abatement costs and motivates farmers by offering economic benefits. A market analysis revealed that nitrogen permits mostly cover the trades with the optimal price ranging from $6 to $30 per kilogram. However, phosphorous permits are limited for trading, and their price exceeds $60 per kilogram. This approach also emphasizes the establishment of a regional institution for market monitoring, dynamic pricing, fair fund reallocation, giving information to participants, and ensuring their income. By these sets of strategies, a WLA on the brink of failure can turn into a cost-effective and sustainable policy for eutrophication control in small basins.

Global assessment of nitrogen losses and trade-offs with yields from major crop cultivations.

Agricultural application of reactive nitrogen (N) for fertilization is a cause of massive negative environmental problems on a global scale. However, spatially explicit and crop-specific information on global N losses into the environment and knowledge of trade-offs between N losses and crop yields are largely lacking. We use a crop growth model, Python-based Environmental Policy Integrated Climate (PEPIC), to determine global N losses from three major food crops: maize, rice, and wheat. Simulated total N losses into the environment (including water and atmosphere) are 44TgNyr-1. Two thirds of these, or 29TgNyr-1, are losses to water alone. Rice accounts for the highest N losses, followed by wheat and maize. The N loss intensity (NLI), defined as N losses per unit of yield, is used to address trade-offs between N losses and crop yields. The NLI presents high variation among different countries, indicating diverse N losses to produce the same amount of yields. Simulations of mitigation scenarios indicate that redistributing global N inputs and improving N management could significantly abate N losses and at the same time even increase yields without any additional total N inputs.

Improving crop yield and water productivity by ecological sanitation and water harvesting in South Africa.

This study quantifies the potential effects of a set of technologies to address water and fertility constraints in rain-fed smallholder agriculture in South Africa, namely in situ water harvesting (WH), external WH, and ecological sanitation (Ecosan, fertilization with human urine). We used the Soil and Water Assessment Tool to model spatiotemporally differentiated effects on maize yield, river flow, evaporation, and transpiration. Ecosan met some of the plant nitrogen demands, which significantly increased maize yields by 12% and transpiration by 2% on average across South Africa. In situ and external WH did not significantly affect the yield, transpiration or river flow on the South Africa scale. However, external WH more than doubled the yields for specific seasons and locations. WH particularly increased the lowest yields. Significant water and nutrient demands remained even with WH and Ecosan management. Additional fertility enhancements raised the yield levels but also the yield variability, whereas soil moisture enhancements improved the yield stability. Hence, coupled policies addressing both constraints will likely be most effective for improving food security.

Simulation of pharmaceutical and personal care product transport to tile drains after biosolids application.

Pharmaceuticals and personal care products (PPCPs) carried in biosolids may reach surface waters or ground water when these materials are applied as fertilizer to agricultural land. During preferential flow conditions created by land application of liquid municipal biosolids (LMB), the residence time of solutes in the macropores may be too short for sorption equilibration. The physically based dual-permeability model MACRO is used in environmental risk assessments for pesticides and may have potential as an environmental risk assessment tool for PPCPs. The objective of this study was to evaluate MACRO and an updated version of MACRO that included non-equilibrium sorption in macropores using data from experiments conducted in eastern Ontario, Canada on the transport of three PPCPs (atenolol, carbamazepine, and triclosan), the nicotine metabolite cotinine, and the strongly sorbing dye rhodamine WT applied in LMB. Results showed that the MACRO model could not reproduce the measured rhodamine WT concentrations (Nash-Sutcliffe coefficient [NS] for the best simulation = -0.057) in drain discharge. The updated version resulted in better fits to measured data for PPCP (average NS = 0.97) and rhodamine WT (NS = 0.84) concentrations. However, it was not possible to simulate all compounds using the same set of hydraulic parameters, which indicates that the model does not fully account for all relevant processes. The results presented herein show that non-equilibrium sorption in macropores has a large impact on simulated solute transport for reactive compounds contained in LMB. This process should be considered in solute transport models that are used for environmental risk assessments for such compounds.

Statistical modeling of global geogenic fluoride contamination in groundwaters.

The use of groundwater with high fluoride concentrations poses a health threat to millions of people around the world. This study aims at providing a global overview of potentially fluoride-rich groundwaters by modeling fluoride concentration. A large database of worldwide fluoride concentrations as well as available information on related environmental factors such as soil properties, geological settings, and climatic and topographical information on a global scale have all been used in the model. The modeling approach combines geochemical knowledge with statistical methods to devise a rule-based statistical procedure, which divides the world into 8 different "process regions". For each region a separate predictive model was constructed. The end result is a global probability map of fluoride concentration in the groundwater. Comparisons of the modeled and measured data indicate that 60-70% of the fluoride variation could be explained by the models in six process regions, while in two process regions only 30% of the variation in the measured data was explained. Furthermore, the global probability map corresponded well with fluorotic areas described in the international literature. Although the probability map should not replace fluoride testing, it can give a first indication of possible contamination and thus may support the planning process of new drinking water projects.

Statistical modeling of global geogenic arsenic contamination in groundwater.

Contamination of groundwaters with geogenic arsenic poses a major health risk to millions of people. Although the main geochemical mechanisms of arsenic mobilization are well understood, the worldwide scale of affected regions is still unknown. In this study we used a large database of measured arsenic concentration in groundwaters (around 20,000 data points) from around the world as well as digital maps of physical characteristics such as soil, geology, climate, and elevation to model probability maps of global arsenic contamination. A novel rule-based statistical procedure was used to combine the physical data and expert knowledge to delineate two process regions for arsenic mobilization: "reducing" and "high-pH/ oxidizing". Arsenic concentrations were modeled in each region using regression analysis and adaptive neuro-fuzzy inferencing followed by Latin hypercube sampling for uncertainty propagation to produce probability maps. The derived global arsenic models could benefit from more accurate geologic information and aquifer chemical/physical information. Using some proxy surface information, however, the models explained 77% of arsenic variation in reducing regions and 68% of arsenic variation in high-pH/oxidizing regions. The probability maps based on the above models correspond well with the known contaminated regions around the world and delineate new untested areas that have a high probability of arsenic contamination. Notable among these regions are South East and North West of China in Asia, Central Australia, New Zealand, Northern Afghanistan, and Northern Mali and Zambia in Africa.

A water resources threshold and its implications for food security.

Cereal import has played a crucial role in compensating local water deficit. A quantitative account of water deficit and cereal import relations therefore is of significance for predicting future food import demand and formulating corresponding national and international policies. On the basis of data for countries in Asia and Africa, we estimated a water resources threshold with respect to cereal import. Below the threshold, the demand for cereal import increases exponentially with decreasing water resources. There appeared to be a declining trend in the threshold, from 2000 m3/(capita year) in the early 1980s to 1500 m3/(capita year) by the end of the 1990s. Until recently, most countries below the threshold were oil-rich and thus were able to afford cereal import. However, the next 30 yr may see many poor and populous countries dropping below the threshold in association with their rapid population growth and the depletion of fossil groundwater. Water deficit-induced food insecurity and starvation could intensify because cereal import may not be affordable for these countries.