Application of a Multi-Objective Optimization Method to Provide Least Cost Alternatives for NPS Pollution Control

Nonpoint source (NPS) pollutants such as phosphorus, nitrogen, sediment, and pesticides are the foremost sources of water contamination in many of the water bodies in the Midwestern agricultural watersheds. This problem is expected to increase in the future with the increasing demand to provide corn as grain or stover for biofuel production. Best management practices (BMPs) have been proven to effectively reduce the NPS pollutant loads from agricultural areas. However, in a watershed with multiple farms and multiple BMPs feasible for implementation, it becomes a daunting task to choose a right combination of BMPs that provide maximum pollution reduction for least implementation costs. Multi-objective algorithms capable of searching from a large number of solutions are required to meet the given watershed management objectives. Genetic algorithms have been the most popular optimization algorithms for the BMP selection and placement. However, previous BMP optimization models did not study pesticide which is very commonly used in corn areas. Also, with corn stover being projected as a viable alternative for biofuel production there might be unintended consequences of the reduced residue in the corn fields on water quality. Therefore, there is a need to study the impact of different levels of residue management in combination with other BMPs at a watershed scale. In this research the following BMPs were selected for placement in the watershed: (a) residue management, (b) filter strips, (c) parallel terraces, (d) contour farming, and (e) tillage. We present a novel method of combing different NPS pollutants into a single objective function, which, along with the net costs, were used as the two objective functions during optimization. In this study we used BMP tool, a database that contains the pollution reduction and cost information of different BMPs under consideration which provides pollutant loads during optimization. The BMP optimization was performed using a NSGA-II based search method. The model was tested for the selection and placement of BMPs in Wildcat Creek Watershed, a corn dominated watershed located in northcentral Indiana, to reduce nitrogen, phosphorus, sediment, and pesticide losses from the watershed. The Pareto optimal fronts (plotted as spider plots) generated between the optimized objective functions can be used to make management decisions to achieve desired water quality goals with minimum BMP implementation and maintenance cost for the watershed. Also these solutions were geographically mapped to show the locations where various BMPs should be implemented. The solutions with larger pollution reduction consisted of buffer filter strips that lead to larger pollution reduction with greater costs compared to other alternatives.     

OPTIMIZATION PROCEDURE FOR COST EFFECTIVE BMP PLACEMENT AT A WATERSHED SCALE1

ABSTRACT: A combinatorial optimization procedure for best management practice (BMP) placement at the watershed level facilitates selection of cost effective BMP scenarios to control non point source (NFS) pollution. A genetic algorithm (GA) was selected from among several optimization heuristics. The GA combines an optimization component written in the C++ language with spatially variable NFS pollution prediction and economic analysis components written within the Arc View geographic information system. The procedure is modular in design, allowing for component modifications while maintaining the basic conceptual framework. An objective function was developed to lexicographically optimize pollution reduction followed by cost increase. Scenario cost effectiveness is then calculated for scenario comparisons. The NPS pollutant fitness score allows for evaluation of multiple pollutants, based on prioritization of each pollutant. The economic component considers farm level public and private costs, cost distribution, and land area requirements. Development of a sediment transport function, used with the Universal Soil Loss Equation, allows the optimization procedure to run within a reasonable timeframe. The procedure identifies multiple near optimal solutions, providing an indication of which fields have a more critical impact on overall cost effectiveness and flexibility in the final solution selected for implementation. The procedure was demonstrated for a 1,014‐ha watershed in the Ridge and Valley physiographic region of Virginia.     

Long‐Term Water Quality and Biological Responses to Multiple Best Management Practices in Rock Creek,Idaho1

Abstract: Water quality and macroinvertebrate assemblage data from 1981 to 2005 were assessed to evaluate the water quality and biological responses of a western trout stream to the implementation of multiple best management practices (BMPs) on irrigated cropland. Data from Rock Creek near Twin Falls, Idaho, a long‐term monitoring site, were assembled from state and federal sources to provide the evaluation. Seasonal loads of the nonpoint source pollutants suspended sediment (SS), total phosphorus (TP), and nitrate‐nitrite (NN) were estimated using a regression model with time‐series streamflow data and constituent concentrations. Trends in the macroinvertebrate assemblages were evaluated using a number of biological metrics and nonmetric multidimensional scaling ordination. Regression analysis found significant annual decreases in TP and SS flow‐adjusted concentrations during the BMP implementation period from 1983 to 1990 of about 7 and 10%, respectively. These results are coincident with the implementation of multiple BMPs on about 75% of the irrigated cropland in the watershed. Macroinvertebrate assemblages during this time also responded with a change in taxa composition resulting in improved biotic index scores. Taxon specific TP and SS optima, empirically derived from a large national dataset, predicted a decrease in SS concentrations of about 37% (52 to 33 mg/l) and a decrease in TP concentrations of about 50% (0.20 to 0.10 mg/l) from 1981 to 1987. Decreasing trends in TP, SS, and NN pollutant loads were primarily the result of naturally low streamflow conditions during the BMP post‐implementation period from 1993 to 2005. Trends in macroinvertebrate responses during 1993 to 2005 were confounded by the introduction of the New Zealand mudsnail (Potamopyrgus  antipodarum), which approached densities of 100,000 per m² in riffle habitat. The occurrence of this invasive species appears to have caused a major shift in composition and function of the macroinvertebrate assemblages.     

Evaluating agricultural best management practices in tile-drained subwatersheds of the Mackinaw River, Illinois

Best management practices (BMPs) are widely promoted in agricultural watersheds as a means of improving water quality and ameliorating altered hydrology. We used a paired watershed approach to evaluate whether focused outreach could increase BMP implementation rates and whether BMPs could induce watershed-scale (4000 ha) changes in nutrients, suspended sediment concentrations, or hydrology in an agricultural watershed in central Illinois. Land use was >90% row crop agriculture with extensive subsurface tile drainage. Outreach successfully increased BMP implementation rates for grassed waterways, stream buffers, and strip-tillage within the treatment watershed, which are designed to reduce surface runoff and soil erosion. No significant changes in nitrate-nitrogen (NO-N), total phosphorus (TP), dissolved reactive phosphorus, total suspended sediment (TSS), or hydrology were observed after implementation of these BMPs over 7 yr of monitoring. Annual NO-N export (39-299 Mg) in the two watersheds was equally exported during baseflow and stormflow. Mean annual TP export was similar between the watersheds (3.8 Mg) and was greater for TSS in the treatment (1626 ± 497 Mg) than in the reference (940 ± 327 Mg) watershed. Export of TP and TSS was primarily due to stormflow (>85%). Results suggest that the BMPs established during this study were not adequate to override nutrient export from subsurface drainage tiles. Conservation planning in tile-drained agricultural watersheds will require a combination of surface-water BMPs and conservation practices that intercept and retain subsurface agricultural runoff. Our study emphasizes the need to measure conservation outcomes and not just implementation rates of conservation practices.     

Nitrogen Removal by Stormwater Management Structures: A Data Synthesis

A comprehensive synthesis of data from empirically based published studies and a widely used stormwater best management practice (BMP) database were used to assess the variability in nitrogen (N) removal performance of urban stormwater ponds, wetlands, and swales and to identify factors that may explain this variability. While the data suggest that BMPs were generally effective on average, removal efficiencies of ammonium (NH₄), nitrate (NO₃), and total nitrogen (TN) were highly variable ranging from negative (i.e., BMPs acting as sources of N) to 100%. For example, removal of NO₃ varied from (median ±1 SD) ?15 ± 49% for dry ponds, 32 ± 120% for wet ponds, 58 ± 210% for wetlands, and 37 ± 29% for swales. Across the same BMP types, TN removal was 27 ± 24%, 40 ± 31%, 61 ± 30%, and 50 ± 29%. NH₄ removal was 9 ± 36%, 29 ± 72%, 31 ± 24%, and 45 ± 34%. BMP size, age, and location explained some of the variability. For example, small and shallow ponds and wetlands were more effective than larger, deeper ones in removing N. Despite well‐known intra‐annual variation in N fluxes, most measurements have been made over short time periods using concentrations, not flow‐weighted N fluxes. Urban N export is increasing in some areas as large storms become more frequent. Thus, accounting for the full range of BMP performance under such conditions is crucial. A select number of long‐term flux‐based BMP studies that rigorously measure rainfall, hydrology, and site conditions could improve BMP implementation.     

Optimizing Agricultural Best Management Practices in a Lake Erie Watershed

Implementing agricultural best management practices (BMPs) is influenced by a balance of desired environmental outcomes, economic feasibility, and stakeholder familiarity, the latter taken to be related to BMP acceptability. To explore this balance, we developed a multi‐objective decision support system for allocating BMP type and placement by coupling the Soil and Water Assessment Tool with a nondominated sorted genetic algorithm that minimizes total phosphorus (TP) yields from agricultural hydrologic response units (HRUs) and costs, while using stakeholder BMP familiarity as a constraint; conventional tillage, no tillage, nutrient management, riparian buffers, and contour cropping were explored. Using constraints representing current conditions, the optimization resulted in 59.6 to 81.0% reduction in agricultural TP yield from HRUs at costs ranging between US $0.8 and US $5.3 million. The constrained optimization tended to select mostly single BMPs or at most two BMPs for a given HRU due to these BMPs having higher acceptability to stakeholders. In contrast, the unconstrained case, representing full familiarity, selected 2‐ and 3‐BMP applications. There was little difference in costs between the constrained and unconstrained cases below an 80% TP yield reduction; however, significant differences were found at larger reductions, supporting the value of stakeholder education and extension efforts. Editor's note : This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.     

Can constructed wetlands reduce the diffuse phosphorus loads to eutrophic water in cold temperate regions?

Construction of wetlands is a possible supplement to best management practices (BMP) at the field level to mitigate phosphorus (P) pollution from agricultural areas. In this paper, annual results from 17 intensively studied wetlands in the cold temperate or boreal climatic zone are reported and analyzed. Surface areas varied from 0.007 to 8.7% of the catchment area. The average total phosphorus (TP) retention varied from 1 to 88%, and the dissolved reactive phosphorus (DRP) retention from -19 to 89%. Retention varied substantially from site to site, indicating the existence of site-specific factors in the catchment and wetlands that influenced the P removal. Factors important for P retention in wetlands were evaluated through multiple statistical analyses by dividing P into two fractions: particulate phosphorus (PP) and DRP. Both relative (%) PP and DRP retention increased with wetland surface area. However, PP retention was not as sensitive as DRP in terms of wetland size and retention: specific PP retention (gram P retention per m(2) and year) decreased as wetland area (A(w)) increased, suggesting the existence of a site-specific optimal wetland to catchment area (A(c)) ratio. Particulate P retention decreased with increasing DRP to TP ratio, while the opposite was found for DRP. Dissolved reactive P retention was higher in new than in old wetlands, while increasing age did not influence PP retention negatively. Effective BMP in the catchment is important to keep the P loss low, because the outlet concentration of P from wetlands is often positively correlated to the input concentration. However, wetlands act as the last buffer in a catchment, since the retention often increases as the P concentration in streams increases.     

Designing management options to reduce surface runoff and sediment yield with farmers: an experiment in south-western France

To preserve the quality of surface water, official French regulations require farmers to keep a minimum acreage of grassland, especially bordering rivers. These agro-environmental measures do not account for the circulation of water within the catchment. This paper examines whether it is possible to design with the farmers agri-environmental measures at field and catchment scale to prevent soil erosion and surface water pollution. To support this participatory approach, the hydrology and erosion model STREAM was used for assessing the impact of a spring stormy event on surface runoff and sediment yield with various management scenarios. The study was carried out in collaboration with an agricultural committee in an area of south-western France where erosive runoff has a major impact on the quality of surface water. Two sites (A and B) were chosen with farmers to discuss ways of reducing total surface runoff and sediment yield at each site. The STREAM model was used to assess surface runoff and sediment yield under current cropping pattern at each site and to evaluate management scenarios including grass strips implementation or changes in cropping patterns within the catchment. The results of STREAM simulations were analysed jointly by farmers and researchers. Moreover, the farmers discussed each scenario in terms of its technical and economical feasibility. STREAM simulations showed that a 40 mm spring rainfall with current cropping patterns led to 3116 m3 total water runoff and 335 metric tons of sediment yield at site A, and 3249 m3 and 241 metric tons at site B. Grass strips implementation could reduce runoff for about 40% and sediment yield for about 50% at site A. At site B, grass strips could reduce runoff and sediment yield for more than 50%, but changes in cropping pattern could reduce it almost totally. The simulations led to three main results: (i) grass strips along rivers and ditches prevented soil sediments from entering the surface water but did not reduce soil losses, (ii) crop redistribution within the catchment was as efficient as planting grass strips, and (iii) efficient management of erosive runoff required coordination between all the farmers using the same watershed. This study shown that STREAM model was a useful support for farmers' discussions about how to manage runoff and sediment yield in their fields.     

Phosphorus load to surface water from bank erosion in a Danish lowland river basin

Phosphorus loss from bank erosion was studied in the catchment of River Odense, a lowland Danish river basin, with the aim of testing the hypothesis of whether stream banks act as major diffuse phosphorus (P) sources at catchment scale. Furthermore, the study aimed at analyzing the impact of different factors influencing bank erosion and P loss such as stream order, anthropogenic disturbances, width of uncultivated buffer strips, and the vegetation of buffer strips. A random stratified procedure in geographical information system (GIS) was used to select two replicate stream reaches covering different stream orders, channelized vs. naturally meandering channels, width of uncultivated buffer strips (≤ 2 m and ≥ 10 m), and buffer strips with different vegetation types. Thirty-six 100-m stream reaches with 180 bank plots and a total of 3000 erosion pins were established in autumn 2006, and readings were conducted during a 3-yr period (2006-2009). The results show that neither stream size nor stream disturbance measured as channelization of channel or the width of uncultivated buffer strip had any significant ( < 0.05) influence on bank erosion and P losses during each of the 3 yr studied. In buffer strips with natural trees bank erosion was significantly ( < 0.05) lower than in buffer strips dominated by grass and herbs. Gross and net P input from bank erosion amounted to 13.8 to 16.5 and 2.4 to 6.3 t P, respectively, in the River Odense catchment during the three study years. The net P input from bank erosion equaled 17 to 29% of the annual total P export and 21 to 62% of the annual export of P from diffuse sources from the River Odense catchment. Most of the exported total P was found to be bioavailable (71.7%) based on a P speciation of monthly suspended sediment samples collected at the outlet of the river basin. The results found in this study have a great importance for managers working with P mitigation and modeling at catchment scale.     

WATERSHED OPTIMIZATION OF AGRICULTURAL BEST MANAGEMENT PRACTICES: CONTINUOUS SIMULATION VERSUS DESIGN STORMS1

ABSTRACT: Nonpoint source (NPS) models and expert opinions are often used to prescribe best management practices (BMPs) for controlling NPS pollution. An optimization algorithm (e.g., a genetic algorithm, or GA) linked with a NPS model (e.g., Annualized AGricultural Nonpoint Source pollution model, or AnnAGNPS), can be used to more objectively prescribe BMPs and to optimize NPS pollution control measures by maximizing pollutant reduction and net monetary return from a watershed. Pollutant loads from design storms and annual loads from a continuous simulation can both be used for optimizing BMP schemes. However, which strategy results in a better solution (in terms of providing water quality protection) for a watershed is not clear. The specific objective of the study was to determine the differences in watershed pollutant loads, in an experimental watershed in Pennsylvania, resulting from optimization analyses performed using pollutant loads from a series of five 2‐yr 24‐hr storm events, a series of five 5‐yr 24‐hr storm events, and cumulative pollutant loads from a continuous simulation of five years of weather data. For each of these three different event alternatives, 100 near optimal solutions (BMP schemes) were generated. Sediment (Sed), sediment nitrogen (SedN), dissolved N (SolN), sediment organic carbon (SedOC), and sediment phosphorus (SedP) loads from a different five‐year period (an evaluation period) suggest that the optimal BMP schemes resulting from the use of annual cumulative pollutant loads from a continuous simulation of five years of weather data provide smaller cumulative NPS pollutant loads at the watershed outlet.     

A systematic approach for the comparative assessment of stormwater pollutant removal potentials

This paper describes the development of a methodology to theoretically assess the stormwater pollutant removal performances of structural best management practices (BMPs). The method combines the categorisation of the relative importance of the primary removal processes within 15 different BMPs with an evaluation of the ability of each process to remove a pollutant in order to generate a value representing the pollutant removal potential for each BMP. The methodology is demonstrated by applying it separately to a set of general water quality indicators (total suspended solids, biochemical and chemical oxygen demand, nitrates, phosphates and faecal coliforms) to produce a ranked list of BMP pollutant removal efficiencies. Given the limited amount of available monitoring data relating to the differential pollutant removal capabilities of BMPs, the resulting prioritization will support stakeholders in making urban drainage decisions from the perspective of pollutant removal. It can also provide inputs to existing urban hydrology models, which aim to predict the treatment performances of BMPs. The level of resilience of the proposed approach is tested using a sensitivity analysis and the limitations in terms of BMP design and application are discussed.     

Modeling Watershed‐Scale Impacts of Stormwater Management with Traditional versus Low Impact Development Design

Stormwater runoff and associated pollutants from urban areas in the greater Chesapeake Bay Watershed (CBW) impair local streams and downstream ecosystems, despite urbanized land comprising only 7% of the CBW area. More recently, stormwater best management practices (BMPs) have been implemented in a low impact development (LID) manner to treat stormwater runoff closer to its source. This approach included the development of a novel BMP model to compare traditional and LID design, pioneering the use of comprehensively digitized storm sewer infrastructure and BMP design connectivity with spatial patterns in a geographic information system at the watershed scale. The goal was to compare total watershed pollutant removal efficiency in two study watersheds with differing spatial patterns of BMP design (traditional and LID), by quantifying the improved water quality benefit of LID BMP design. An estimate of uncertainty was included in the modeling framework by using ranges for BMP pollutant removal efficiencies that were based on the literature. Our model, using Monte Carlo analysis, predicted that the LID watershed removed approximately 78 kg more nitrogen, 3 kg more phosphorus, and 1,592 kg more sediment per square kilometer as compared with the traditional watershed on an annual basis. Our research provides planners a valuable model to prioritize watersheds for BMP design based on model results or in optimizing BMP selection.     

Phosphorus loading in the Frome catchment, UK: seasonal refinement of the coefficient modeling approach

This paper describes the results of an export coefficient modeling approach to predict total phosphorus (TP) loading in the Frome catchment, Dorset, UK from point and diffuse sources on a seasonal (monthly) basis in 1998 and on an annual basis for 1990-1998. The model predicted an annual TP load of 25 605 kg yr(-1), compared with an observed (measured) value of 23400 kg yr(-1). Monthly loads calculated using the export coefficient model agreed well with monthly observed values except in months of variable discharge, when observed values were low, probably due to infrequent, and therefore unrepresentative, sampling. Comparison between filterable reactive phosphorus (FRP) and TP concentrations observed in the period 1990-1997 showed that trends in FRP could be estimated from trends in TP. A sensitivity analysis (varying individual export coefficients by +/-10%) showed that sewage treatment works (STWs) (3.5%), tilled land (2.7%), meadow-verge-seminatural (1.0%), and mown and grazed turf (0.6%) had the most significant effect (percent difference from base contribution) on model prediction. The model was also used to estimate the effect of phosphorus stripping at STWs in order to comply with a pending change in the European Union wastewater directive. Theoretical reduction of TP from the largest STW in the catchment gave a predicted reduction in TP loading of 2174 kg yr(-1). This illustrates the value of this seasonal export coefficient model as a practical management tool.     

Optimal nonpoint source pollution control strategies for a reservoir watershed in Taiwan

The purpose of this study is to develop a model for optimal nonpoint source pollution control for the Fei-Tsui Reservoir watershed in Northern Taiwan. Several structural best management practices (BMPs) are selected to treat stormwater runoff. The complete model consists of two interacting components: an optimization model based on discrete differential dynamic programming (DDDP) and a zero-dimensional reservoir water quality model. A predefined procedure is used to locate suitable sites for construction of various selected BMPs in the watershed. In the optimization model, the objective function is to find the best combination of BMP type and placement, which minimizes the total construction and operation, maintenance, and repair (OMR) costs of the BMPs. The constraints are the water quality standards for total phosphorus (TP) and total suspended solids (TSS) concentrations in the reservoir. A zero-dimensional reservoir water quality model of the Vollenweider type is embedded in the optimization framework to simulate pollutant concentrations in Fei-Tsui Reservoir. The resulting optimal cost and benefit of water quality improvement are depicted by the model-derived trade-off curves. The modeling framework developed in the present study could be used as an efficient tool for planning a watershed-wide implementation of BMPs for mitigating stormwater pollution impact on the receiving water bodies.     

Rye cover crop and gamagrass strip effects on NO3 concentration and load in tile drainage

A significant portion of the NO3 from agricultural fields that contaminates surface waters in the Midwest Corn Belt is transported to streams or rivers by subsurface drainage systems or "tiles." Previous research has shown that N fertilizer management alone is not sufficient for reducing NO3 concentrations in subsurface drainage to acceptable levels; therefore, additional approaches need to be devised. We compared two cropping system modifications for NO3 concentration and load in subsurface drainage water for a no-till corn (Zea mays L.)-soybean (Glycine max [L.] Merr.) management system. In one treatment, eastern gamagrass (Tripsacum dactyloides L.) was grown in permanent 3.05-m-wide strips above the tiles. For the second treatment, a rye (Secale cereale L.) winter cover crop was seeded over the entire plot area each year near harvest and chemically killed before planting the following spring. Twelve 30.5x42.7-m subsurface-drained field plots were established in 1999 with an automated system for measuring tile flow and collecting flow-weighted samples. Both treatments and a control were initiated in 2000 and replicated four times. Full establishment of both treatments did not occur until fall 2001 because of dry conditions. Treatment comparisons were conducted from 2002 through 2005. The rye cover crop treatment significantly reduced subsurface drainage water flow-weighted NO3 concentrations and NO3 loads in all 4 yr. The rye cover crop treatment did not significantly reduce cumulative annual drainage. Averaged over 4 yr, the rye cover crop reduced flow-weighted NO3 concentrations by 59% and loads by 61%. The gamagrass strips did not significantly reduce cumulative drainage, the average annual flow-weighted NO3 concentrations, or cumulative NO3 loads averaged over the 4 yr. Rye winter cover crops grown after corn and soybean have the potential to reduce the NO3 concentrations and loads delivered to surface waters by subsurface drainage systems.     

Results of a program to control phosphorus discharges from dairy operations in south-central Florida,USA

During 1987–1992, a mandatory program to control phosphorus discharges was implemented at dairy operations located to the north of Lake Okeechobee, Florida, USA. Thirty of 48 dairies participated in this program and implemented best management practices (BMPs), which included the construction of intensive animal waste management systems. Eighteen dairies closed their milkproducing operations under a government-funded buyout program. In this paper, we compare trends in runoff total phosphorus (TP) concentrations among the dairies that remained active and implemented BMPs. A central feature of the dairy waste management system is the high intensity area (HIA), defined as the milking barn and adjacent vegetation-free land, encircled by a drainage ditch and dike. Animal waste from the HIA is diverted into anaerobic lagoons and storage ponds, from which water is periodically removed and used for irrigation of field crops. The impacts of BMP construction on runoff TP concentrations were immediate and, in most cases, dramatic. Average TP concentrations declined significantly (P < 0.001), from 9.0 to 1.2 mg TP liter^–1 at dairies in one basin (Lower Kissimmee River), and from 2.6 to 1.0 mg TP liter^–1 in another (Taylor Creek/Nubbin Slough). Some sites experienced greater declines in TP than others. To elucidate possible causes for the difference in response, a multivariate statistical model was utilized. Independent variables included soil pH, soil drainage characteristics, spodic horizon depth, and the areas of different BMP components (pasture, HIA, spray fields). The analysis significantly separated dairies with the highest and lowest runoff TP concentrations. Lowest TP occurred at dairies having particular soil characteristic (shallow spodic horizon) and certain BMP features (large HIA and small heard pastures).     

Spatiotemporal Variability of Modeled Watershed Scale Surface‐Depression Storage and Runoff for the Conterminous United States

This study explores the viability of using simulated monthly runoff as a proxy for landscape‐scale surface‐depression storage processes simulated by the United States Geological Survey’s National Hydrologic Model (NHM) infrastructure across the conterminous United States (CONUS). Two different temporal resolution model codes (daily and monthly) were run in the NHM with the same spatial discretization. Simulated values of daily surface‐depression storage (treated as a decimal fraction of maximum volume) as computed by the daily Precipitation‐Runoff Modeling System (NHM‐PRMS) and normalized runoff (0 to 1) as computed by the Monthly Water Balance Model (NHM‐MWBM) were aggregated to monthly and annual values for each hydrologic response unit (HRU) in the CONUS geospatial fabric (HRU; n = 109,951) and analyzed using Spearman’s rank correlation test. Correlations between simulated runoff and surface‐depression storage aggregated to monthly and annual values were compared to identify where which time scale had relatively higher correlation values across the CONUS. Results show Spearman’s rank values >0.75 (highly correlated) for the monthly time scale in 28,279 HRUs (53.35%) compared to the annual time scale in 41,655 HRUs (78.58%). The geographic distribution of HRUs with highly correlated monthly values show areas where surface‐depression storage features are known to be common (e.g., Prairie Pothole Region, Florida).     

Stream Discharge and Riparian Land Use Influence In-Stream Concentrations and Loads of Phosphorus from Central Plains Watersheds

Total annual nutrient loads are a function of both watershed characteristics and the magnitude of nutrient mobilizing events. We investigated linkages among land cover, discharge and total phosphorus (TP) concentrations, and loads in 25 Kansas streams. Stream monitoring locations were selected from the Kansas Department of Health and Environment stream chemistry long-term monitoring network sites at or near U.S. Geological Survey stream gauges. We linked each sample with concurrent discharge data to improve our ability to estimate TP concentrations and loads across the full range of possible flow conditions. Median TP concentration was strongly linked (R ² = 76%) to the presence of cropland in the riparian zones of the mostly perennial streams. At baseflow, discharge data did not improve prediction of TP, but at high flows discharge was strongly linked to concentration (a threshold response occurred). Our data suggest that on average 88% of the total load occurred during the 10% of the time with the greatest discharge. Modeled reductions in peak discharges, representing increased hydrologic retention, predicted greater decreases in total annual loads than reductions of ambient concentrations because high discharge and elevated phosphorus concentrations had multiplicative effects. No measure of land use provided significant predictive power for concentrations when discharge was elevated or for concentration rise rates under increasing discharge. These results suggest that reductions of baseflow concentrations of TP in streams without wastewater dischargers may be managed by reductions of cropland uses in the riparian corridor. Additional measures may be needed to manage TP annual loads, due to the large percentage of the TP load occurring during a few high-flow events each year.     

Linking dissolved and particulate phosphorus export in rivers draining California's Central Valley with anthropogenic sources at the regional scale

Pollution of water resources by phosphorus (P) is a critical issue in regions with agricultural and urban development. In this study, we estimated P inputs from agricultural and urban sources in 24 catchments draining to the Central Valley in California and compared them with measured river P export to investigate hydrologic and anthropogenic factors affecting regional P retention and export. Using spatially explicit information on fertilizer use, livestock population, agricultural production, and human population, we calculated that net surface balances for anthropogenic P ranged from -12 to 648 kg P km yr in the early 2000s. Inorganic P fertilizer and manure P comprised the largest fraction of total input for all but two catchments. From 2000 to 2003, a median of 7% (range, -287 to 88%) of net annual anthropogenic P input was exported as total P (TP). Yields (kg P km yr) of dissolved inorganic P (DIP), dissolved organic P, particulate P, and TP were not significantly related to catchment-level, per area anthropogenic P input. However, there were significant relationships between mean annual P concentrations and P input from inorganic fertilizers and manure due to the concentration of agricultural land near catchment mouths and regional variation in runoff. Catchment-level P fertilizer and manure inputs explained 4 to 23% more variance in mean annual DIP and TP concentrations than percent of catchment area in agriculture. This study suggests that spatially explicit estimates of anthropogenic P input can help identify sources of multiple forms of P exported in rivers at management-relevant spatial scales.     

Sensitivity Analysis of Best Management Practices Under Climate Change Scenarios1

Woznicki, Sean A. and A. Pouyan Nejadhashemi, 2011. Sensitivity Analysis of Best Management Practices Under Climate Change Scenarios. Journal of the American Water Resources Association (JAWRA) 48(1): 90‐112. DOI: 10.1111/j.1752‐1688.2011.00598.x Abstract: Understanding the sensitivity of best management practices (BMPs) implementation as climate changes will be important for water resources management. The objective of this study was to determine how the sensitivity of BMPs performance vary due to changes in precipitation, temperature, and CO₂ using the Soil and Water Assessment Tool. Sediment, total nitrogen, and total phosphorus loads on an annual and monthly basis were estimated before and after implementation of eight agricultural BMPs for different climate scenarios. Downscaled climate change data were obtained from the National Center for Atmospheric Research Community Climate System Model for the Tuttle Creek Lake watershed in Kansas and Nebraska. Using a relative sensitivity index, native grass, grazing management, and filter strips were determined to be the most sensitive for all climate change scenarios, whereas porous gully plugs, no‐tillage, and conservation tillage were the least sensitive on an annual basis. The monthly sensitivity analysis revealed that BMP sensitivity varies largely on a seasonal basis for all climate change scenarios. The results of this research suggest that the majority of agricultural BMPs tested in this study are significantly sensitive to climate change. Therefore, caution should be exercised in the decision‐making processes.