Continuous measurement of nitrate concentration in a highly event-responsive agricultural catchment in south-west of France: is the gain of information useful?

A nitrate sensor has been set up to measure every 10 min the nitrate signal in a stream draining a small agricultural catchment dominated by fertilized crops during a 2-year study period (2006–2008) in the south-west of France. An in situ sampling protocol using automatic sampler to monitor flood events have been used to assume a point-to-point calibration of the sensor values. The nitrate concentration exhibits nonsystematic concentration and dilution effects during flood events. We demonstrate that the calibrated nitrate sensor signal gathered from the outlet is considered to be a continuous signal using the Nyquist–Shannon sampling theorem. The objectives of this study are to quantify the errors generated by a typical infrequent sampling protocol and to design appropriate sampling strategy according to the sampling objectives. Nitrate concentration signal and flow data are numerically sampled to simulate common sampling frequencies. The total fluxes calculated from the simulated samples are compared with the reference value computed on the continuous signal. Uncertainties are increasing as sampling intervals increase; the method that is not using continuous discharge to compute nitrate fluxes bring larger uncertainty. The dispersion and bias computed for each sampling interval are used to evaluate the uncertainty during each hydrological period. High underestimation is made during flood periods when high-concentration period is overlooked. On the contrary, high sampling frequencies (from 3 h to 1 day) lead to a systematic overestimation (bias around 3%): highest concentrations are overweighted by the interpolation of the concentration in such case. The in situ sampling protocol generates less than 1% of load estimation error and sample highest concentration peaks. We consider useful such newly emerging field technologies to assess short-term variations of water quality parameters, to minimize the number of samples to be analysed and to assess the quality state of the stream at any time

Giving credit to reforestation for water quality benefits.

While there is a general belief that reforesting marginal, often unprofitable, croplands can result in water quality benefits, to date there have been very few studies that have attempted to quantify the magnitude of the reductions in nutrient (N and P) and sediment export. In order to determine the magnitude of a credit for water quality trading, there is a need to develop quantitative approaches to estimate the benefits from forest planting in terms of load reductions. Here we first evaluate the availability of marginal croplands (i.e. those with low infiltration capacity and high slopes) within a large section of the Ohio River Basin (ORB) to assess the magnitude of the land that could be reforested. Next, we employ the Nutrient Tracking Tool (NTT) to study the reduction in N, P and sediment losses from converting corn or corn/soy rotations to forested lands, first in a case study and then for a large region within the ORB. We find that after reforestation, N losses can decrease by 40 to 80 kg/ha-yr (95-97% reduction), while P losses decrease by 1 to 4 kg/ha-yr (96-99% reduction). There is a significant influence of local conditions (soils, previous crop management practices, meteorology), which can be considered with NTT and must be taken into consideration for specific projects. There is also considerable interannual and monthly variability, which highlights the need to take the longer view into account in nutrient credit considerations for water quality trading, as well as in monitoring programs. Overall, there is the potential for avoiding 60 million kg N and 2 million kg P from reaching the streams and rivers of the northern ORB as a result of conversion of marginal farmland to tree planting, which is on the order of 12% decrease for TN and 5% for TP, for the entire basin. Accounting for attenuation, this represents a significant fraction of the goal of the USEPA Gulf of Mexico Hypoxia Task Force to reduce TN and TP reaching the dead zone in the Gulf of Mexico, the second largest dead zone in the world. More broadly, the potential for targeted forest planting to reduce nutrient loading demonstrated in this study suggests further consideration of this approach for managing water quality in waterways throughout the world. The study was conducted using computational models and there is a need to evaluate the results with empirical observations

Water Integration for Squamscott Exeter (WISE): Preliminary Integrated Plan, Final Technical Report

This document introduces the goals, background and primary elements of an Integrated Plan for the Lower Exeter and Squamscott River in the Great Bay estuary in southern New Hampshire. This Plan will support management of point (wastewater treatment plant) and nonpoint sources in the communities of Exeter, Stratham and Newfields. The Plan also identifies and quantifies the advantages of the use of green infrastructure as a critical tool for nitrogen management and describes how collaboration between those communities could form the basis for an integrated plan. The Plan will help communities meet new wastewater and proposed stormwater permit requirements. Critical next steps are need before this Plan will fulfill the 2018 Nitrogen Control Plan requirements for Exeter and proposed draft MS4 requirements for both Stratham and Exeter. These next steps include conducting a financial capability assessment, development of an implementation schedule and development of a detailed implementation plan. The collaborative process used to develop this Plan was designed to provide decision makers at the local, state and federal levels with the knowledge they need to trust the Plan’s findings and recommendations, and to enable discussions between stakeholders to continue the collaborative process. This Plan includes the following information to guide local response to new federal permit requirements for treating and discharging stormwater and wastewater: Sources of annual pollutant load quantified by type and community; Assessment and evaluation of different treatment control strategies for each type of pollutant load; Assessment and evaluation of nutrient control strategies designed to reduce specific types of pollutants; Evaluation of a range of point source controls at the wastewater treatment facility based on regulatory requirements; Costs associated with a range of potential control strategies to achieve reduction of nitrogen and other pollutants of concern; and A preliminary implementation schedule with milestones for target load reductions using specific practices for specific land uses at points in time; Recommendations on how to implement a tracking and accounting program to document implementation; Design tools such as BMP performance curves for crediting the use of structural practices to support nitrogen accounting requirements; and Next Steps for how to complete this Plan

Allocating Nutrient Load Reduction across a Watershed: Implications of Different Principles

A watershed based model, the Soil and Water Assessment Tool (SWAT), along with transfer coefficients is used to assess alternative principles of allocating nutrient load reduction in the Raccoon River watershed in central Iowa. Four principles are examined for their cost-effectiveness and impacts on water quality: absolute equity, equity based on ability, critical area targeting, and geographic proximity. Based on SWAT simulation results, transfer coefficients are calculated for the effects of nitrogen application reduction. We find both critical area targeting and downstream focus (an example of geographic proximity) can be more expensive than equal allocation, a manifestation of absolute equity. Unless abatement costs are quite heterogeneous across the subwatersheds, the least-cost allocation (an application of the principle of equity based on ability) have a potential of cost savings of about 10% compared to equal allocation. We also find that the gap between nitrogen loading estimated from transfer coefficients and nitrogen loading predicted by SWAT simulation is small (in general less than 5%). This suggests that transfer coefficients can be a useful tool for watershed nutrient planning. Sensitivity analyses suggest that these results are robust with respect to different degrees of nitrogen reduction and how much other conservation practices are used.Environmental Economics and Policy,

Detection and Predictability of Spatial and Temporal Patterns and Trends of Riverine Nutrient Loads in the Midwest

The deleterious effects of multiple stressors on global water resources have become more significant over the past few decades. Anthropogenic activities such as industrialization, urbanization, deforestation, and increased application of agricultural nutrients have led to a decline in overall quality of our aquatic environment. Additionally, these activities have increased greenhouse gas concentrations globally, warming the earth’s atmosphere and eventually having a detrimental effect on global water and energy balances. The global water cycle has been altered, leading to its overall intensification and an increase in frequency of extreme floods and droughts. Addressing increasing water demands coupled with declining water quality and a depletion of water resources requires new approaches in water management. In determining optimum management actions, it is critical to understand the spatial and temporal variability and trends in water quantity and quality. This research aims to improve our knowledge of anthropogenic and natural impacts on water resources by evaluating and refining the science of predicting pollutant (nutrient and sediment) loadings from medium- to large-scale watersheds. To enable these goals, this research is centered on large watersheds in the Midwestern United States, which have been some of the primary sources of nutrient and sediment loadings to downstream water bodies such as the Gulf of Mexico and Lake Erie. In total, 14 watersheds in Illinois, Indiana, Ohio, and Michigan, with extensive water quality datasets, are analyzed in different stages of this research. Most of these watersheds are predominantly agricultural with intensive row-cropped farmlands and have a network of sub-surface tile drainage systems. Pollutant loadings and associated hydrological processes have been simulated using four major modeling approaches: statistical modeling, empirical modeling, physically based modeling, and data mining methods. This report includes eight chapters. The first three chapters describe the problem and research objectives, study area, and data preparation and processing. Next, the impacts of available water quality data on concentration and load predictions and trend calculations are assessed based on traditional statistical methods and several new, improved, and modified approaches (Chapter 4). This segment emphasizes the difficulties in predicting nutrient load and concentration trends under changing climatic conditions, highlighting the importance of continuous nutrient monitoring. Next, two data mining techniques (the nearest-neighbor method and decision trees), scarcely used in hydrology, were applied to predict the missing Nitrate Nitrogen (NO3-N) concentrations for two extensively monitored watersheds in the Lake Erie basin. These predictions (Chapter 5) are important in load estimations and demonstrate the potential of data mining to produce results comparable with statistical and empirical methods presented in the previous chapter. In Chapter 6, statistical regression techniques are used to assess the role of large load events in predicting Total Suspended Solids (SS), Total Phosphorus (TP), and NO3-N annual loads. A novel constituent-specific baseflow separation technique based on mechanistic differences in nutrient and sediment loadings is proposed and applied. As a result, regression relationships between the largest annual loads and total annual loads were developed for all three constituents. An Analysis of Covariance (ANCOVA) indicated that these relationships are often statistically indistinguishable from each other when applied to watersheds with a similar land use. Then, in Chapter 7, the temporal patterns of pollutant loadings from large Midwestern watersheds are analyzed using circular statistics. Critical periods of high loadings, precipitation, and river flow were identified. While river flows and pollutant loadings are highest in late winter and early spring (e.g., March and April), rainfall totals are highest during late spring and early summer (e.g., May through August). Finally, Chapter 8 shows the results based on the physically based SWAT model. The model is calibrated for river discharge and water quality in the largest watershed in the Lake Erie basin, the Maumee River watershed. The calibrated model is used to gauge the impacts of future projected climate change from the mid-century and late-century time periods on the hydrology and water quality in the watershed. The results indicate that climate change could have a significant impact on sediment and nutrient loads, and that more detailed studies are needed to more accurately assess this impact and its confidence limits.published or submitted for publicationis peer reviewedOpe

Watershed Management for Water Quality Improvement: the role of agricultural research

Research and Development/Tech Change/Emerging Technologies, Resource /Energy Economics and Policy,

ASSESSMENT OF WATERSHED NUTRIENT LOADS AND EFFECTIVENESS OF BEST MANAGEMENT PRACTICES

Several methods have been developed for use in estimating the water quality loads associated with urban and agricultural landuses and practices. These include the use of sophisticated computer models, typically based on using pollutant loading and runoff functions, regression equations, load export coefficients (LECs), and event mean concentrations (EMCs). This research has examined the feasibility of using a simple EMC approach with the Kentucky Nutrient Model (KYNM). The thesis includes an extensive literature review of EMCs and a synthesis of recommended values for a range of typical urban and agricultural landuses. The thesis also includes an extensive literature review of potential BMPs along with a summary of the typical removal efficiencies and costs associated with each type of BMP. The research also explored the potential to use the results from multiple applications of site specific BMP models like the Source Loading and Management Model (WinSLAMM) in the development of general functional relationships that could then be used to evaluate BMP performance on a more site-specific basis. The developed EMC table and the associated BMP performance curves should provide valuable tools for use in better managing nutrient loads for urban and agricultural watersheds

Development of a Parsimonious Urban Landscape Nutrient Model using Representations of Terrestrial Denitrification Controls

Nonpoint source pollution of nitrogen (N) and phosphorus (P) creates pervasive water quality and eutrophication problems around the world, adversely affecting rivers, lakes, and estuaries. Urban land use generates excess N and P pollutants and land use conversion removes natural N and P filtration services provided by undeveloped ecosystems. Management of these problems might first be approached using scoping level nonpoint source runoff models that are defined as balancing process complexity and algorithm simplicity, as well as balancing data availability and predictive accuracy. The contributing area / dispersal area (CADA) concept brings land cover and elevation data along with runoff and filtering likelihood algorithms into the Export Coefficient (EC) model to map likely variations in nutrient loading across the landscape. In this research, we enhance scoping level models by 1) adding spatial variation through the mapping of runoff and buffering likelihoods, 2) introducing the temporal driver of rainfall intensity to enhance nutrient export, and 3) determining the environmental variables most highly correlated with denitrification. In this study, we enhance the EC model to account for spatial and temporal variations, allowing for better estimates of nutrient loading across space and time. This research also determines key predictors of denitrification potential in mixed-use watersheds, through which denitrification hotspots can be identified. The creation of spatially- and temporally-distributed scoping models for nutrient loading through the landscape will assist managers in identifying areas of high loading potential, which generate high concentrations of nutrients and have little opportunity for downslope filtration. The identification of high denitrification potential zones also allows for facilitation of nitrate removal by routing nitrate-rich water to these zones. The low-level data needs and process-based features of the scoping model allow for its implementation into the i-Tree Hydro toolkit, a peer-reviewed software suite that is used to assess the effects of management and land use change on water quality and quantity

Watershed-Scale Hybrid Stochastic-Deterministic Modeling Framework and Diffused Sources Superpositioning

Predicting hydrologic system behavior is imperative to planning and management of water resources. The study developed an integrated hybrid stochastic and deterministic framework to improve prediction accuracy for overland flow and diffused sources in a watershed. The methodology includes sampling input parameters at system level and contribution of nonpoint source from hydrologically disconnected areas (heretofore referred to as system-level approach and superpositioning respectively). System-level approach includes the integration of a topography-based sampling grid generalized linear model developed by the study and Monte Carlo methods. The superpositioning method adopts in-stream water quality equation for overland flow pollution estimation. The system-level approach was applied to the Patuxent watershed to determine runoff, phosphorus and total suspended solids using continuous rainfall. For overland flow, system-level approach (p-value of 0.68) was 0.51% off the observed flow compared with -21.9% for existing method ( p-value of 0.11). Similarly for phosphorus, the model prediction deviated from the observed by 7% compared to that of the existing method which deviated by -32%. The results indicate that the system-level method is a better predictor for overland flow and nonpoint sources. In the superpositioning approach, phosphorus contributions were added to the system-level approach using an event rainfall. The prediction error reduced from 4.82% to -0.29% when the system-level method was superpositioned with nonpoint source. Data from superpositioning analysis showed that including diffused sources contribution from hydrologically disconnected areas further improves the level of accuracy. The study demonstrates that the framework reduces prediction error and has a high accuracy in reproducing watershed response. The hybrid methodology framework is superior to existing deterministic methods. Ultimately, this dissertation shows the potential of improving prediction accuracy of hydrologic systems by incorporating the strengths of both stochastic and deterministic models. The framework serves as a background for detailed applications for the developed models

An assessment of the critical source areas and transport pathways of diffuse pollution in the Umngeni Catchment, South Africa.

Masters Degree. University of KwaZulu-Natal, Pietemaritzburg.The difficulty in locating and managing diffuse pollution sources and their transport pathways is one of the reasons for the continued degradation of surface water in South Africa. Dealing with this problem is complex, as the sources and transport pathways of the pollutants are often not known because of the diffuse nature of the pollution. This study demonstrates the constraints of conventional diffuse pollution assessment approaches in identifying the Critical Source Areas (CSAs) and transport pathways of diffuse pollution, as applied in the uMngeni Catchment, South Africa. The use of various risk-based modelling approaches are reviewed for identifying the risk of diffuse pollution generation and transportation across a catchment landscape. The Sensitive Catchment Integrated Modelling and Analysis Platform (SCIMAP) Model is a risk-based tool that was developed to give a spatial representation of diffuse pollution sources. In this study, the SCIMAP Model was applied to identify and prioritise the protection and control of nutrient CSAs and transport pathways within the uMngeni Catchment. The results of the study were displayed in a catchment scale web map. The hydrological connectivity risk in the catchment was higher in the high-lying western areas and lower in the middle-eastern areas. The upper and middle parts of the catchment that are dominated by commercial agriculture and built-up urban areas were identified as the most impactful CSAs for intervention. The results are immediately applicable to water managers in the catchment and are strongly linked to the investment efforts in ecological infrastructure. A walkover survey revealed that the SCIMAP Model was able to direct the CSA investigations to the nutrient sources at four out of five locations. The survey also revealed that the accuracy of the modelled transport pathways increased with an increase in the elevation difference. The sensitivity of the SCIMAP Model to input land cover weightings was assessed, using an objective function. A high sensitivity of the modelled high-risk areas was observed on the intermediate diffuse pollution risk map, and a slight sensitivity of the modelled high-risk areas on the final diffuse pollution risk map, when the input landcover weightings were increased and decreased by 5%, 10% and 15%. This implies that caution should be practised in the formulation of the input land cover weightings, as they are a potential source of error in the model outputs. It is concluded that SCIMAP is a valuable tool for identifying the CSAs and transport pathways of diffuse pollution in a catchment. The results of the model can better inform the management of diffuse pollution and guide investments in the protection of the ecological infrastructure in the uMngeni Catchment. However, the establishment of input land cover weightings is very important and should receive priority in similar studies in the future