Water quality impacts of converting to a poultry litter fertilization strategy

When improperly managed, land application of animal manures can harm the environment; however, limited watershed-scale runoff water quality data are available to research and address this issue. The water quality impacts of conversion to poultry litter fertilization on cultivated and pasture watersheds in the Texas Blackland Prairie were evaluated in this three-year study. Edge-of-field N and P concentrations and loads in surface runoff from new litter application sites were compared with losses under inorganic fertilization. The impact on downstream nutrient loss was also examined. In the fallow year with no fertilizer application, nutrient losses averaged 3 kg N ha(-1) and 0.9 kg P ha(-1) for the cultivated watersheds and were below 0.1 kg ha(-1) for the pasture watersheds. Following litter application, PO(4)-P concentrations in runoff were positively correlated to litter application rate and Mehlich-3 soil P levels. Following litter application, NO(3)-N and NH(4)-N concentrations in runoff were typically greater from cultivated watersheds, but PO(4)-P concentrations were greater for the pasture watersheds. Total N and P loads from the pasture watersheds (0.2 kg N ha(-1) and 0.7 kg P ha(-1)) were significantly lower than from the cultivated watersheds (32 kg N ha(-1) and 5 kg P ha(-1)) partly due to lower runoff volumes from the pasture watersheds. Downstream N and P concentrations and per-area loads were much lower than from edge-of-field watersheds. Results demonstrate that a properly managed annual litter application (4.5 Mg ha(-1) or less depending on litter N and P content) with supplemental N should supply necessary nutrients without detrimental water quality impacts.     

Dry Weather Water Quality Loadings in Arid,Urban Watersheds of the Los Angeles Basin,California, USA1

Abstract: Dry weather runoff in arid, urban watersheds may consist entirely of treated wastewater effluent and/or urban nonpoint source runoff, which can be a source of bacteria, nutrients, and metals to receiving waters. Most studies of urban runoff focus on stormwater, and few have evaluated the relative contribution and sources of dry weather pollutant loading for a range of constituents across multiple watersheds. This study assessed dry weather loading of nutrients, metals, and bacteria in six urban watersheds in the Los Angeles region of southern California to estimate relative sources of each constituent class and the proportion of total annual load that can be attributed to dry weather discharge. In each watershed, flow and water quality were sampled from storm drain and treated wastewater inputs, as well as from in‐stream locations during at least two time periods. Data were used to calculate mean concentrations and loads for various sources. Dry weather loads were compared with modeled wet weather loads under a range of annual rainfall volumes to estimate the relative contribution of dry weather load. Mean storm drain flows were comparable between all watersheds, and in all cases, approximately 20% of the flowing storm drains accounted for 80% of the daily volume. Wastewater reclamation plants (WRP) were the main source of nutrients, storm drains accounted for almost all the bacteria, and metals sources varied by constituent. In‐stream concentrations reflected major sources, for example nutrient concentrations were highest downstream of WRP discharges, while in‐stream metals concentrations were highest downstream of the storm drains with high metals loads. Comparison of wet vs. dry weather loading indicates that dry weather loading can be a significant source of metals, ranging from less than 20% during wet years to greater than 50% during dry years.     

CALIBRATION OF STORM LOADS IN THE SOUTH PRONG WATERSHED,FLORIDA, USING BASINS/HSPF1

ABSTRACT: The South Prong watershed is a major tributary system of the Sebastian River and adjacent Indian River Lagoon. Continued urbanization of the Sebastian River drainage basin and other watersheds of the Indian River Lagoon is expected to increase runoff and nonpoint source pollutant loads. The St. Johns River Water Management District developed watershed simulation models to estimate potential impacts on the ecological systems of receiving waters and to assist planners in devising strategies to prevent further degradation of water resources. In the South Prong system, a storm water sampling program was carried out to calibrate the water quality components of the watershed model for total suspended solids (TSS), total phosphorous (TP), and total nitrogen (TN). During the period of May to November 1999, water quality and flow data were collected at three locations within the watershed. Two of the sampling stations were located at the downstream end of major watercourses. The third station was located at the watershed outlet. Five storm events were sampled and measured at each station. Sampling was conducted at appropriate intervals to represent the rising limb, peak, and recession limb of each storm event. The simulations were handled by HSPF (Hydrologic Simulation Program‐Fortran). Results include calibration of the hydrology and calibration of the individual storm loads. The hydrologic calibration was continuous over the period 1994 through 1999. Simulated storm runoff, storm loads, and event mean concentrations were compared with their corresponding observed values. The hydrologic calibration showed good results. The outcome of the individual storm calibrations was mixed. Overall, however, the simulated storm loads agreed reasonably well with measured loads for a majority of the storms.     

Influence of Sampling Frequency on Estimation of Annual Total Phosphorus and Total Suspended Solids Loads1

Abstract: The determination of sediment and nutrient loads is typically based on the collection and analysis of grab samples. The frequency and regularity of traditional sampling may not provide representation of constituent loading, particularly in systems with flashy hydrology. At two sites in the Little Bear River, Utah, continuous, high‐frequency turbidity was used with surrogate relationships to generate estimates of total phosphorus and total suspended solids concentrations, which were paired with discharge to estimate annual loads. The high frequency records were randomly subsampled to represent hourly, daily, weekly, and monthly sampling frequencies and to examine the effects of timing, and resulting annual load estimates were compared to the reference loads. Higher frequency sampling resulted in load estimates that better approximated the reference loads. The degree of bias was greater at the more hydrologically responsive site in the upper watershed, which required a higher sampling frequency than the lower watershed site to achieve the same level of accuracy in estimating the reference load. The hour of day and day of week of sampling impacted load estimation, depending on site and hydrologic conditions. The effects of sampling frequency on the determination of compliance with a water quality criterion were also examined. These techniques can be helpful in determining necessary sampling frequency to meet the objectives of a water quality monitoring program.     

Model Based Nitrate TMDLs for Two Agricultural Watersheds of Southeastern Minnesota1

Abstract: In this study, a set of nitrogen reduction strategies were modeled to evaluate the feasibility of improving water quality to meet total maximum daily loads (TMDLs) in two agricultural watersheds. For this purpose, a spatial‐process model was calibrated and used to predict monthly nitrate losses (1994‐96) from Sand and Bevens Creek watersheds located in south‐central Minnesota. Statistical comparison of predicted and observed flow and nitrate losses gave r² coefficients of 0.75 and 0.70 for Sand Creek watershed and 0.72 and 0.67 for Bevens Creek watershed, respectively. Modeled alternative agricultural management scenarios included: six different N application rates over three application timings and three different percentages of crop land with subsurface drainage. Predicted annual nitrate losses were then compared with nitrate TMDLs assuming a 30% reduction in observed nitrate losses is required. Reductions of about 33 (8.6 to 5.8 kg/ha) and 35% (23 to 15 kg/ha) in existing annual nitrate losses are possible for Sand and Bevens Creek watersheds, respectively, by switching the timing of fertilizer application from fall to spring. Trends towards increases in tile‐drained crop land imply that attaining nitrate TMDLs in future may require other alternative management practices in addition to fertilizer management such as partial conversion of crop land to pasture.     

INFLUENCE OF DIFFERENT TEMPORAL SAMPLING STRATEGIES ON ESTIMATING TOTAL PHOSPHORUS AND SUSPENDED SEDIMENT CONCENTRATION AND TRANSPORT IN SMALL STREAMS1

ABSTRACT: Various temporal sampling strategies are used to monitor water quality in small streams. To determine how various strategies influence the estimated water quality, frequently collected water quality data from eight small streams (14 to 110 km²) in Wisconsin were systematically subsampled to simulate typically used strategies. These subsets of data were then used to estimate mean, median, and maximum concentrations, and with continuous daily flows used to estimate annual loads (using the regression method) and volumetrically weighted mean concentrations. For each strategy, accuracy and precision in each summary statistic were evaluated by comparison with concentrations and loads of total phosphorus and suspended sediment estimated from all available data. The most effective sampling strategy depends on the statistic of interest and study duration. For mean and median concentrations, the most frequent fixed period sampling economically feasible is best. For maximum concentrations, any strategy with samples at or prior to peak flow is best. The best sampling strategy to estimate loads depends on the study duration. For one‐year studies, fixed period monthly sampling supplemented with storm chasing was best, even though loads were overestimated by 25 to 50 percent. For two to three‐year load studies and estimating volumetrically weighted mean concentrations, fixed period semimonthly sampling was best.     

Empirical models based on the universal soil loss equation fail to predict sediment discharges from Chesapeake Bay catchments

The Universal Soil Loss Equation (USLE) and its derivatives are widely used for identifying watersheds with a high potential for degrading stream water quality. We compared sediment yields estimated from regional application of the USLE, the automated revised RUSLE2, and five sediment delivery ratio algorithms to measured annual average sediment delivery in 78 catchments of the Chesapeake Bay watershed. We did the same comparisons for another 23 catchments monitored by the USGS. Predictions exceeded observed sediment yields by more than 100% and were highly correlated with USLE erosion predictions (Pearson r range, 0.73-0.92; p < 0.001). RUSLE2-erosion estimates were highly correlated with USLE estimates (r = 0.87; p < 001), so the method of implementing the USLE model did not change the results. In ranked comparisons between observed and predicted sediment yields, the models failed to identify catchments with higher yields (r range, -0.28-0.00; p > 0.14). In a multiple regression analysis, soil erodibility, log (stream flow), basin shape (topographic relief ratio), the square-root transformed proportion of forest, and occurrence in the Appalachian Plateau province explained 55% of the observed variance in measured suspended sediment loads, but the model performed poorly (r(2) = 0.06) at predicting loads in the 23 USGS watersheds not used in fitting the model. The use of USLE or multiple regression models to predict sediment yields is not advisable despite their present widespread application. Integrated watershed models based on the USLE may also be unsuitable for making management decisions.     

MASS LOAD ESTIMATION ERRORS UTILIZING GRAB SAMPLING STRATEGIES IN A KARST WATERSHED1

ABSTRACT: Developing a mass load estimation method appropriate for a given stream and constituent is difficult due to inconsistencies in hydrologic and constituent characteristics. The difficulty may be increased in flashy flow conditions such as karst. Many projects undertaken are constrained by budget and manpower and do not have the luxury of sophisticated sampling strategies. The objectives of this study were to: (1) examine two grab sampling strategies with varying sampling intervals and determine the error in mass load estimates, and (2) determine the error that can be expected when a grab sample is collected at a time of day when the diurnal variation is most divergent from the daily mean. Results show grab sampling with continuous flow to be a viable data collection method for estimating mass load in the study watershed. Comparing weekly, biweekly, and monthly grab sampling, monthly sampling produces the best results with this method. However, the time of day the sample is collected is important. Failure to account for diurnal variability when collecting a grab sample may produce unacceptable error in mass load estimates. The best time to collect a sample is when the diurnal cycle is nearest the daily mean.     

Nutrient and Sediment Production,Watershed Characteristics,and Land Use in the Tahoe Basin,California‐Nevada1

Abstract: In efforts to control the degradation of water quality in Lake Tahoe, public agencies have monitored surface water discharge and concentrations of nitrogen, phosphorus, and suspended sediment in two separate sampling programs. The first program focuses on 20 watersheds varying in size from 162 to 14,000 ha, with continuous stream gaging and periodic sampling; the second focuses on small urbanized catchments, with automated sampling during runoff events. Using data from both programs, we addressed the questions (1) what are the fluxes and concentrations of nitrogen and phosphorus entering the lake from surface runoff; (2) how do the fluxes and concentrations vary in space and time; and (3) how are they related to land use and watershed characteristics? To answer these questions, we calculated discharge‐weighted average concentrations and annual fluxes and used multiple regression to relate those variable to a suite of GIS‐derived explanatory variables. The final selected regression models explain 47‐62% of the variance in constituent concentrations in the stormwater monitoring catchments, and 45‐72% of the variance in mean annual yields in the larger watersheds. The results emphasize the importance of impervious surface and residential density as factors in water quality degradation, and well‐developed soil as a factor in water quality maintenance.     

ESTIMATING NUTRIENT AND SEDIMENT THRESHOLD CRITERIA FOR BIOLOGICAL IMPAIRMENT IN PENNSYLVANIA WATERSHEDS1

ABSTRACT: This study employs a simple nonlinear statistical approach to establish nitrogen, phosphorus, and sediment concentration and unit area load thresholds to aid in the evaluation of aquatic biological health of watersheds within the state of Pennsylvania. Flow, nitrogen and phosphorus species, sediment, basin area, land cover, and biological assessment data were assembled for 29 Pennsylvania watersheds. For each watershed, rating curves depicting flow versus load relationships were developed using the U.S. Environmental Protection Agency's (USEPA's) storage and retrieval database (STORET) flow and concentration data, then applied to daily flow data obtained from U.S. Geological Survey (USGS) daily flow gauging stations to estimate daily load between 1989 and 1999. The load estimates and concentration data were then sorted into six sets of data: mean annual unit area nitrogen, phosphorus, and sediment loads; and average nitrogen, phosphorus, and sediment concentrations. Results of Mann‐Whitney tests conducted on each of the six datasets indicate that there is a statistically significant difference between the concentrations and unit area loads of nitrogen, phosphorus, and sediment in impaired and unimpaired watersheds. Concentration thresholds, calculated as the midpoint between the impaired and unimpaired watersheds’ 95 percent confidence interval for the median, were estimated to be 2.01 mg/L, 0.07 mg/L, and 197.27 mg/L for nitrogen, phosphorus, and sediment, respectively. Annual unit area load thresholds were estimated to be equal to 8.64 kg/ha, 0.30 kg/ha, and 785.29 kg/ha, respectively, for nitrogen, phosphorus, and sediment species.     

USING FIELD SCALE MODELS TO PREDICT PEAK FLOWS ON AGRICULTURAL WATERSHEDS1

The goal of this study was to develop a methodology for generating storm hydrographs at a watershed scale based on daily runoff estimates from a field scale model. The methodology was evaluated on a small agricultural watershed using the ADAPT field scale process model. A comparison of observed and predicted peak flows for 11 of the largest events that occurred in a three year period gave r² values of 0.84, 0.82, and 0.81 when the watershed was subdivided into 1, 5, and 10 sub watersheds. However, all other statistical measures improved when the watershed was subdivided into at least five sub watersheds. Guidelines need to be developed on the use of the procedure but it first needs to be evaluated on several watersheds that exhibit a range in sizes, land uses, slopes, and soil properties.     

STORM DISCHARGE,LOADS, AND AVERAGE CONCENTRATIONS IN NORTHWEST OHIO RIVERS, 1975–19951

ABSTRACT: A computerized technique was developed to identify storm runoff episodes and calculate storm discharges, storm loads, and storm average concentrations for each event in datasets with up to 10,000 records. This technique was applied to four watersheds within the Lake Erie drainage basin and identified between 160 and 250 runoff events in each. Storm event loads and storm event mean concentrations were calculated for each runoff event for suspended solids, total phosphorus, soluble reactive phosphorus, nitrate, and total Kjeldahl nitrogen. The basic characteristics of the resulting data are described, as are systematic differences as a function of watershed size, seasonal differences, and trends over time. Many of the results of this study reflect the importance of nonpoint processes and improvements in agricultural best management practices in these watersheds.     

Effects of Impervious Area and BMP Implementation and Design on Storm Runoff and Water Quality in Eight Small Watersheds

The effects of increases in effective impervious area (EIA) and the implementation of water quality protection designed detention pond best management practices (BMPs) on storm runoff and stormwater quality were assessed in Gwinnett County, Georgia, for the period 2001‐2008. Trends among eight small watersheds were compared, using a time trend study design. Significant trends were detected in three storm hydrologic metrics and in five water quality constituents that were adjusted for variability in storm characteristics and climate. Trends in EIA ranged from 0.10 to 1.35, and changes in EIA treated by BMPs ranged from 0.19 to 1.32; both expressed in units of percentage of drainage area per year. Trend relations indicated that for every 1% increase in watershed EIA, about 2.6, 1.1, and 1.5% increases in EIA treated by BMPs would be required to counteract the effects of EIA added to the watersheds on peak streamflow, stormwater yield, and storm streamflow runoff, respectively. Relations between trends in EIA, BMP implementation, and water quality were counterintuitive. This may be the result of (1) changes in constituent inputs in the watersheds, especially downstream of areas treated by BMPs; (2) BMPs may have increased the duration of stormflow that results in downstream channel erosion; and/or (3) spurious relationships between increases in EIA, BMP implementation, and constituent inputs with development rates.     

MODELING DEVELOPED COASTAL WATERSHEDS WITH THE AGRICULTURAL NON-POINT SOURCE MODEL1

ABSTRACT: Many coastal states are facing increasing urban growth along their coast lines. The growth has caused urban non-point source nitrogen runoff to be a major contributor to coastal and estuarine enrichment. Water resource managers are responsible for evaluating the impacts from point and non-point sources in developed watersheds and developing strategies to manage future growth. Non-point source models provide an effective approach to these management challenges. The Agricultural Non-Point Source Model (AGNPS) permits the incorporation of important spatial information (soils, landuse, topography, hydrology) in simulating surface hydrology and nitrogen non-point source runoff. The AGNPS model was adapted for developed coastal watersheds by deriving urban coefficients that reflect urban landuse classes and the amount of impervious surface area. Popperdam Creek watershed was used for model parameter development and model calibration. Four additional watersheds were simulated to validate the model. The model predictions of the peak flow and total nitrogen concentrations were close to the field measurements for the five sub-basins simulated. Measured peak flow varied by 30 fold among the sub-basins. The average simulated peak flow was within 14 percent of the average measured peak flow. Measured total nitrogen loads varied over an order of magnitude among the sub-basins yet error between the measured and simulated loads for a given sub-basin averaged 5 percent. The AGNPS model provided better estimates of nitrogen loads than widely used regression methods. The spatial distribution of important watershed characteristics influenced the impacts of urban landuse and projecting future residential expansion on runoff, sediment and nitrogen yields. The AGNPS model provides a useful tool to incorporate these characteristics, evaluate their importance, and evaluate fieldscale to watershed-scale urban impacts.     

MODELING SEDIMENT AND PHOSPHORUS LOSSES IN AN AGRICULTURAL WATERSHED TO MEET TMDLs1

ABSTRACT: This paper studies the effectiveness of alternative farm management strategies at improving water quality to meet Total Maximum Daily Loads (TMDLs) in agricultural watersheds. A spatial process model was calibrated using monthly flow, sediment, and phosphorus (P) losses (1994 to 1996) from Sand Creek watershed in south‐central Minnesota. Statistical evaluation of predicted and observed data gave r² coefficients of 0.75, 0.69, and 0.49 for flow (average 4.1 m³/s), sediment load (average 0.44 ton/ha), and phosphorus load (average 0.97 kg/ha), respectively. The calibrated model was used to evaluate the effects of conservation tillage, conversion of crop land to pasture, and changes in phosphorus fertilizer application rate on pollutant loads. TMDLs were developed for sediment and P losses based on existing water quality standards and guidelines. Observed annual sediment and P losses exceeded these TMDLs by 59 percent and 83 percent, respectively. A combination of increased conservation tillage, reduced application rates of phosphorus fertilizer, and conversion of crop land to pasture could reduce sediment and phosphorus loads by 23 percent and 20 percent of existing loads, respectively. These reductions are much less than needed to meet TMDLs, suggesting that control of sediment using buffer strips and control of point sources of phosphorus are needed for the remaining reductions.     

ESTIMATION OF STREAMFLOW,BASE FLOW,AND NITRATE‐NITROGEN LOADS IN IOWA USING MULTIPLE LINEAR REGRESSION MODELS1

Nineteen variables, including precipitation, soils and geology, land use, and basin morphologic characteristics, were evaluated to develop Iowa regression models to predict total streamflow (Q), base flow (Qb), storm flow (Qs) and base flow percentage (%Qb) in gauged and ungauged watersheds in the state. Discharge records from a set of 33 watersheds across the state for the 1980 to 2000 period were separated into Qb and Qs. Multiple linear regression found that 75.5 percent of long term average Q was explained by rainfall, sand content, and row crop percentage variables, whereas 88.5 percent of Qb was explained by these three variables plus permeability and floodplain area variables. Qs was explained by average rainfall and %Qb was a function of row crop percentage, permeability, and basin slope variables. Regional regression models developed for long term average Q and Qb were adapted to annual rainfall and showed good correlation between measured and predicted values. Combining the regression model for Q with an estimate of mean annual nitrate concentration, a map of potential nitrate loads in the state was produced. Results from this study have important implications for understanding geomorphic and land use controls on streamflow and base flow in Iowa watersheds and similar agriculture dominated watersheds in the glaciated Midwest.     

Incorporating Uncertainty Into the Ranking of SPARROW Model Nutrient Yields From Mississippi/Atchafalaya River Basin Watersheds1

Abstract: Excessive loads of nutrients transported by tributary rivers have been linked to hypoxia in the Gulf of Mexico. Management efforts to reduce the hypoxic zone in the Gulf of Mexico and improve the water quality of rivers and streams could benefit from targeting nutrient reductions toward watersheds with the highest nutrient yields delivered to sensitive downstream waters. One challenge is that most conventional watershed modeling approaches (e.g., mechanistic models) used in these management decisions do not consider uncertainties in the predictions of nutrient yields and their downstream delivery. The increasing use of parameter estimation procedures to statistically estimate model coefficients, however, allows uncertainties in these predictions to be reliably estimated. Here, we use a robust bootstrapping procedure applied to the results of a previous application of the hybrid statistical/mechanistic watershed model SPARROW (Spatially Referenced Regression On Watershed attributes) to develop a statistically reliable method for identifying “high priority” areas for management, based on a probabilistic ranking of delivered nutrient yields from watersheds throughout a basin. The method is designed to be used by managers to prioritize watersheds where additional stream monitoring and evaluations of nutrient‐reduction strategies could be undertaken. Our ranking procedure incorporates information on the confidence intervals of model predictions and the corresponding watershed rankings of the delivered nutrient yields. From this quantified uncertainty, we estimate the probability that individual watersheds are among a collection of watersheds that have the highest delivered nutrient yields. We illustrate the application of the procedure to 818 eight‐digit Hydrologic Unit Code watersheds in the Mississippi/Atchafalaya River basin by identifying 150 watersheds having the highest delivered nutrient yields to the Gulf of Mexico. Highest delivered yields were from watersheds in the Central Mississippi, Ohio, and Lower Mississippi River basins. With 90% confidence, only a few watersheds can be reliably placed into the highest 150 category; however, many more watersheds can be removed from consideration as not belonging to the highest 150 category. Results from this ranking procedure provide robust information on watershed nutrient yields that can benefit management efforts to reduce nutrient loadings to downstream coastal waters, such as the Gulf of Mexico, or to local receiving streams and reservoirs.     

EFFECTS OF LAND USE AND TOPOGRAPHY ON SOME WATER QUALITY VARIABLES IN FORESTED EAST TEXAS1

ABSTRACT: Spatial variation of five water quality variables were analyzed using composite water samples collected periodically from eight small watersheds (11.4–71.6 km²) in forested East Texas during 1977 through 1980. Based on 31 observations during the four-year period the average yield of nitrate-nitrite nitrogen (NNN), total kjeldahl nitrogen (TKN), total phosphorus (PO4), chloride (CHL), and total suspended sediment (TSS) were 1.43, 21.96, 3.09, 50.11, and 90.39 ka/ha/yr, respectively. Compared to the water quality standards of the U.S. Environmental Protection Agency (1976) and the Texas Department of Water Resources (1976) for CHL, TSS, and NNN, none of the observations exceeded the limits for public water supplies. The study showed that forested watersheds normally yielded stream flow with better quality than that from agricultural watersheds. Watersheds of greater percent of pasture area, mean slope, stream segment frequency, and drainage density produced greater concentrations for these five chemical parameters in water samples. Meaningful equations were developed for estimating mean average yields for each chemical parameter for each watershed with R² ranging from 0.77 to 0.96 and standard error of estimates from 17 to 33 percent of the observed means.     

THE UNIT HYDROGRAPH: A SATISFACTORY MODEL OF WATERSHED RESPONSE?1

ABSTRACT: Some 96 flood events larger than the mean annual flood from 16 watersheds in the Commonwealth of Pennsylvania were used to derive unit hydrographs by the least-squares method. Analyses of the unit hydrographs were conducted to ascertain their response to watershed parameters, climatic and storm variables and locations within different hydrologic regions. Significant differences both within and among watersheds led to the formulation and testing of hypotheses stating that differences among watersheds are caused by physiographic differences while differences within watersheds result from climatic and storm differences. The analysis showed, that while many watersheds parameters strongly influence the shape of the unit hydrograph, only the storm variables duration and volume of precipitation excess produce significant differences. Seasonal differences were apparent but not proven statistically significant.     

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.