Impact of Changing Climate and Land Cover on Flood Magnitudes in the Delaware River Basin,USA

Changing climate and land cover are expected to impact flood hydrology in the Delaware River Basin over the 21st Century. HEC‐HMS models (U.S. Army Corps of Engineers Hydrologic Engineering Center‐Hydrologic Modeling System) were developed for five case study watersheds selected to represent a range of scale, soil types, climate, and land cover. Model results indicate that climate change alone could affect peak flood discharges by ?6% to +58% a wide range that reflects regional variation in projected rainfall and snowmelt and local watershed conditions. Land cover changes could increase peak flood discharges up to 10% in four of the five watersheds. In those watersheds, the combination of climate and land cover change increase modeled peak flood discharges by up to 66% and runoff volumes by up to 44%. Precipitation projections are a key source of uncertainty, but there is a high likelihood of greater precipitation falling on a more urbanized landscape that produces larger floods. The influence of climate and land cover changes on flood hydrology for the modeled watersheds varies according to future time period, climate scenario, watershed land cover and soil conditions, and flood frequency. The impacts of climate change alone are typically greater than land cover change but there is substantial geographic variation, with urbanization the greater influence on some small, developing watersheds.     

Response of Nitrogen Loading to the Chesapeake Bay to Source Reduction and Land Use Change Scenarios: A SPARROW‐Informed Analysis

In response to concerns regarding the health of streams and receiving waters, the United States Environmental Protection Agency established a total maximum daily load for nitrogen in the Chesapeake Bay watershed for which practices must be in place by 2025 resulting in an expected 25% reduction in load from 2009 levels. The response of total nitrogen (TN) loads delivered to the Bay to nine source reduction and land use change scenarios was estimated using a Spatially Referenced Regression on Watershed Attributes model. The largest predicted reduction in TN load delivered to the Bay was associated with a scenario in which the mass of TN as fertilizer applied to agricultural lands was decreased. A 25% decrease in the mass of TN applied as fertilizer resulted in a predicted reduction in TN loading to the Bay of 11.3%, which was 2.5–5 times greater than the reductions predicted by other scenarios. Eliminating fertilizer application to all agricultural land in the watershed resulted in a predicted reduction in TN load to the Bay of 45%. It was estimated that an approximate 25% reduction in TN loading to the Bay could be achieved by eliminating fertilizer applied to the 7% of subwatersheds contributing the greatest fertilizer‐sourced TN loads to the Bay. These results indicate that management strategies aimed at decreasing loading from a small number of subwatersheds may be effective for reducing TN loads to the Bay, and similar analyses are possible in other watersheds.     

Assessment of a turfgrass sod best management practice on water quality in a suburban watershed

The disposal of manure on agricultural land has caused water quality concerns in many rural watersheds, sometimes requiring state environmental agencies to conduct total maximum daily load (TMDL) assessments of stream nutrients, such as nitrogen (N) and phosphorus (P). A best management practice (BMP) has been developed in response to a TMDL that mandates a 50% reduction of annual P load to the North Bosque River (NBR) in central Texas. This BMP exports composted dairy manure P through turfgrass sod from the NBR watershed to urban watersheds. The manure-grown sod releases P slowly and would not require additional P fertilizer for up to 20 years in the receiving watershed. This would eliminate P application to the sod and improve the water quality of urban streams. The soil and water assessment tool (SWAT) was used to model a typical suburban watershed that would receive the sod grown with composted dairy manure to assess water quality changes due to this BMP. The SWAT model was calibrated to simulate historical flow and estimated sediment and nutrient loading to Mary's Creek near Fort Worth, Texas. The total P stream loading to Mary's Creek was lower when manure-grown sod was transplanted instead of sod grown with inorganic fertilizers. Flow, sediment and total N yield were the same for both cases at the watershed outlet. The SWAT simulations indicated that the turfgrass BMP can be used effectively to import manure P into an urban watershed and reduce in-stream P levels when compared to sod grown with inorganic fertilizers.     

FORECASTING FUTURE LAND USE FOR WATERSHED ASSESSMENT1

ABSTRACT: Protecting surface water quality in watersheds undergoing demographic change requires both the management of existing threats and planning to address potential future stresses arising from changing land use. Many reservoirs and threatened waterbodies are located in areas undergoing rapid population growth, and increases in density of residential and commercial land use, accompanied by increased amount of impervious surface area, can result in increased pollutant loading and degradation of water quality. Effective planning to address potential threats, including zoning and growth management, requires analytical tools to predict and compare the impacts of different management options. The focus of this paper is not on developing demographic projections, but rather the translation of such projections into changes in land use which form the basis for assessment of future watershed loads. Land use change can be forecast at a variety of spatial and temporal scales. A semi-lumped, GIS-based, transition matrix approach is recommended as consistent with the level of complexity achievable in most watershed models. Practical aspects of forecasting future land use for watershed assessment are discussed. Several recent reservoir water supply projection studies are used to demonstrate a general framework for simulating changes in land use and resulting impacts on water quality. In addition to providing a technical basis for selecting optimal management alternatives, such a tool is invaluable for demonstrating to different stakeholder groups the trade-offs among management alternatives, both in terms of water quality and future land use patterns within the watershed.     

Climate Sensitivity of Phosphorus Loadings to an Urban Stream

We investigate the sensitivity of phosphorus loading (mass/time) in an urban stream to variations in climate using nondimensional sensitivity, known as elasticity, methods commonly used by economists and hydrologists. Previous analyses have used bivariate elasticity methods to represent the general relationship between nutrient loading and a variable of interest, but such bivariate relations cannot reflect the complex multivariate nonlinear relationships inherent among nutrients, precipitation, temperature, and streamflow. Using fixed‐effect multivariate regression methods, we obtain two phosphorus models (nonparametric and parametric) for an urban stream with high explanatory power that can both estimate phosphorus loads and the elasticity of phosphorus loading to changes in precipitation, temperature, and streamflow. A case study demonstrates total phosphorus loading depends significantly on season, rainfall, combined sewer overflow events, and flow rate, yet the elasticity of total phosphorus to all these factors remains relatively constant throughout the year. The elasticity estimates reported here can be used to examine how nutrient loads may change under future climate conditions.     

Detecting Temporal Change in Watershed Nutrient Yields

Meta-analyses reveal that nutrient yields tend to be higher for watersheds dominated by anthropogenic uses (e.g., urban, agriculture) and lower for watersheds dominated by natural vegetation. One implication of this pattern is that loss of natural vegetation will produce increases in watershed nutrient yields. Yet, the same meta-analyses also reveal that, absent land-cover change, watershed nutrient yields vary from one year to the next due to many exogenous factors. The interacting effects of land cover and exogenous factors suggest nutrient yields should be treated as distributions, and the effect of land-cover change should be examined by looking for significant changes in the distributions. We compiled nutrient yield distributions from published data. The published data included watersheds with homogeneous land cover that typically reported two or more years of annual nutrient yields for the same watershed. These data were used to construct statistical models, and the models were used to estimate changes in the nutrient yield distributions as a result of land-cover change. Land-cover changes were derived from the National Land Cover Database (NLCD). Total nitrogen (TN) yield distributions increased significantly for 35 of 1550 watersheds and decreased significantly for 51. Total phosphorus (TP) yield distributions increased significantly for 142 watersheds and decreased significantly for 17. The amount of land-cover change required to produce significant shifts in nutrient yield distributions was not constant. Small land-cover changes led to significant shifts in nutrient yield distributions when watersheds were dominated by natural vegetation, whereas much larger land-cover changes were needed to produce significant shifts when watersheds were dominated by urban or agriculture. We discuss our results in the context of the Clean Water Act.     

Modeling Streamflow and Water Quality Sensitivity to Climate Change and Urban Development in 20 U.S. Watersheds

Watershed modeling in 20 large, United States (U.S.) watersheds addresses gaps in our knowledge of streamflow, nutrient (nitrogen and phosphorus), and sediment loading sensitivity to mid‐21st Century climate change and urban/residential development scenarios. Use of a consistent methodology facilitates regional scale comparisons across the study watersheds. Simulations use the Soil and Water Assessment Tool. Climate change scenarios are from the North American Regional Climate Change Assessment Program dynamically downscaled climate model output. Urban and residential development scenarios are from U.S. Environmental Protection Agency's Integrated Climate and Land Use Scenarios project. Simulations provide a plausible set of streamflow and water quality responses to mid‐21st Century climate change across the U.S. Simulated changes show a general pattern of decreasing streamflow volume in the central Rockies and Southwest, and increases on the East Coast and Northern Plains. Changes in pollutant loads follow a similar pattern but with increased variability. Ensemble mean results suggest that by the mid‐21st Century, statistically significant changes in streamflow and total suspended solids loads (relative to baseline conditions) are possible in roughly 30‐40% of study watersheds. These proportions increase to around 60% for total phosphorus and total nitrogen loads. Projected urban/residential development, and watershed responses to development, are small at the large spatial scale of modeling in this study.     

Evaluation of regression methodology with low-frequency water quality sampling to estimate constituent loads for ephemeral watersheds in Texas

Water quality regulation and litigation have elevated the awareness and need for quantifying water quality and source contributions in watersheds across the USA. In the present study, the regression method, which is typically applied to large (perennial) rivers, was evaluated in its ability to estimate constituent loads (NO(3)-N, total N, PO(4)-P, total P, sediment) on three small (ephemeral) watersheds with different land uses in Texas. Specifically, regression methodology was applied with daily flow data collected with bubbler stage recorders in hydraulic structures and with water quality data collected with four low-frequency sampling strategies: random, rise and fall, peak, and single stage. Estimated loads were compared with measured loads determined in 2001-2004 with an autosampler and high-frequency sampling strategies. Although annual rainfall and runoff volumes were relatively consistent within watersheds during the study period, measured annual nutrient and sediment concentrations and loads varied considerably for the cultivated and mixed watersheds but not for the pasture watershed. Likewise, estimated loads were much better for the pasture watershed than the cultivated and mixed landuse watersheds because of more consistent land management and vegetation type in the pasture watershed, which produced stronger correlations between constituent loads and mean daily flow rates. Load estimates for PO(4)-P were better than for other constituents possibly because PO(4)-P concentrations were less variable within storm events. Correlations between constituent concentrations and mean daily flow rate were poor and not significant for all watersheds, which is different than typically observed in large rivers. The regression method was quite variable in its ability to accurately estimate annual nutrient loads from the study watersheds; however, constituent load estimates were much more accurate for the combined 3-yr period. Thus, it is suggested that for small watersheds, regression-based annual load estimates should be used with caution, whereas long-term estimates can be much more accurate when multiple years of concentration data are available. The predictive ability of the regression method was similar for all of the low-frequency sampling strategies studied; therefore, single-stage or random strategies are recommended for low-frequency storm sampling on small watersheds because of their simplicity.     

Modeling Nutrient Export From Coastal California Watersheds

Nitrate and phosphate export coefficient models were developed for coastal watersheds along the Santa Barbara Channel in central California. One approach was based on measurements of nutrient fluxes in streams from specific land use classes and included a watershed response function that scaled export up or down depending on antecedent moisture conditions. The second approach for nutrient export coefficient modeling used anthropogenic nutrient loading for land use classes and atmospheric nutrient deposition to model export. In an application of the first approach to one watershed, the nitrate and phosphate models were within 20% of measured values for most storms. When applied to another year, both nitrate and phosphate models generally performed adequately with annual, storm‐flow, and base‐flow values within 20% of measured nutrient loadings. Less satisfactory results were found when applied to neighboring watersheds with difference percentages of land use and hydrologic conditions. Application of the second approach was less successful than the first approach.     

SIMULATING HYDROLOGIC AND WATER QUALITY IMPACTS IN AN URBANIZING WATERSHED1

ABSTRACT: The Hydrologic Simulation Program‐Fortran (HSPF) was calibrated and used to assess the future effects of various land development scenarios on water quality in the Polecat Creek watershed in Caroline County, Virginia. Model parameters related to hydrology and water quality were calibrated and validated using observed stream flow and water quality data collected at the watershed outlet and the outlets of two sub water sheds. Using the county's Comprehensive Plan, land use scenarios were developed by taking into account the trends and spatial distributions of future development. The simulation results for the various land use scenarios indicate that runoff volume and peak rate increased as urban areas increased. Urbanization also increased sediment loads mainly due to increases in channel erosion. Constituent loads of total Kjeldal nitrogen, orthophosphorus, and total phosphorous for Polecat Creek watershed slightly decreased under future development scenarios. These reductions are due to increases in urban areas that typically contribute smaller quantities of nitrogen and phosphorous, as compared to agricultural areas. However, nitrate loads increased for the future land use scenarios, as compared to the existing land use. The increases in nitrate loads may result from increases in residential land and associated fertilizer use and concurrent decreases in forested land. The procedures used in this paper could assist local, state, and regional policy makers in developing land management strategies that minimize environmental impacts while allowing for future development.     

Estimating Potential Climate Change Effects on the Upper Neuse Watershed Water Balance Using the SWAT Model

Climate change poses water resource challenges for many already water stressed watersheds throughout the world. One such watershed is the Upper Neuse Watershed in North Carolina, which serves as a water source for the large and growing Research Triangle Park region. The aim of this study was to quantify possible changes in the watershed’s water balance due to climate change. To do this, we used the Soil and Water Assessment Tool (SWAT) model forced with different climate scenarios for baseline, mid‐century, and end‐century time periods using five different downscaled General Circulation Models. Before running these scenarios, the SWAT model was calibrated and validated using daily streamflow records within the watershed. The study results suggest that, even under a mitigation scenario, precipitation will increase by 7.7% from the baseline to mid‐century time period and by 9.8% between the baseline and end‐century time period. Over the same periods, evapotranspiration (ET) would decrease by 5.5 and 7.6%, water yield would increase by 25.1% and 33.2%, and soil water would increase by 1.4% and 1.9%. Perhaps most importantly, the model results show, under a high emission scenario, large seasonal differences with ET estimated to decrease by up to 42% and water yield to increase by up to 157% in late summer and fall. Planning for the wetter predicted future and corresponding seasonal changes will be critical for mitigating the impacts of climate change on water resources.     

LAND COVER AS A FRAMEWORK FOR ASSESSING RISK OF WATER POLLUTION1

ABSTRACT: A survey of numerous field studies shows that nitrogen and phosphorous export coefficients are significantly different across forest, agriculture, and urban land‐cover types. We used simulations to estimate the land‐cover composition at which there was a significant risk of nutrient loads representative of watersheds without forest cover. The results suggest that at between 20 percent and 30 percent nonforest cover, there is a 10 percent or greater chance of N or P nutrient loads being equivalent to the median values of predominantly agricultural or urban watersheds. The methods apply to environmental management for assessing the risk to increased nonpoint nutrient pollution. Interpretation of the risk measures are discussed relative to their application for a single watershed and across a region comprised of several watersheds.     

MODELING FRAMEWORK FOR MANAGING COPPER RUNOFF IN URBAN WATERSHEDS1

ABSTRACT: A modeling framework was developed for managing copper runoff in urban watersheds that incorporates water quality characterization, watershed land use areas, hydrologic data, a statistical simulator, a biotic ligand binding model to characterize acute toxicity, and a statistical method for setting a watershed specific copper loading. The modeling framework is driven by export coefficients derived from water quality parameters and hydrologic inputs measured in an urban watershed's storm water system. This framework was applied to a watershed containing a copper roof built in 1992. A series of simulations was run to predict the change in receiving stream water chemistry caused by roof aging and to determine the maximum copper loading (at the 99 percent confidence level) a watershed could accept without causing acute toxicity in the receiving stream. Forecasting the amount of copper flux responsible for exceeding the assimilation capacity of a watershed can be directly related to maximum copper loadings responsible for causing toxicity in the receiving streams. The framework developed in this study can be used to evaluate copper utilization in urban watersheds.     

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.     

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.     

Linking Biological Integrity and Watershed Models to Assess the Impacts of Historical Land Use and Climate Changes on Stream Health

Land use change and other human disturbances have significant impacts on physicochemical and biological conditions of stream systems. Meanwhile, linking these disturbances with hydrology and water quality conditions is challenged due to the lack of high-resolution datasets and the selection of modeling techniques that can adequately deal with the complex and nonlinear relationships of natural systems. This study addresses the above concerns by employing a watershed model to obtain stream flow and water quality data and fill a critical gap in data collection. The data were then used to estimate fish index of biological integrity (IBI) within the Saginaw Bay basin in Michigan. Three methods were used in connecting hydrology and water quality variables to fish measures including stepwise linear regression, partial least squares regression, and fuzzy logic. The IBI predictive model developed using fuzzy logic showed the best performance with the R ² = 0.48. The variables that identified as most correlated to IBI were average annual flow, average annual organic phosphorus, average seasonal nitrite, average seasonal nitrate, and stream gradient. Next, the predictions were extended to pre-settlement (mid-1800s) land use and climate conditions. Results showed overall significantly higher IBI scores under the pre-settlement land use scenario for the entire watershed. However, at the fish sampling locations, there was no significant difference in IBI. Results also showed that including historical climate data have strong influences on stream flow and water quality measures that interactively affect stream health; therefore, should be considered in developing baseline ecological conditions.     

WATER QUALITY MODELING OF ALTERNATIVE AGRICULTURAL SCENARIOS IN THE U.S. CORN BELT1

ABSTRACT: Simulated water quality resulting from three alternative future land‐use scenarios for two agricultural watersheds in central Iowa was compared to water quality under current and historic land use/land cover to explore both the potential water quality impact of perpetuating current trends and potential benefits of major changes in agricultural practices in the U.S. Corn Belt. The Soil Water Assessment Tool (SWAT) was applied to evaluate the effect of management practices on surface water discharge and annual loads of sediment and nitrate in these watersheds. The agricultural practices comprising Scenario 1, which assumes perpetuation of current trends (conversion to conservation tillage, increase in farm size and land in production, use of currently‐employed Best Management Practices (BMPs)) result in simulated increased export of nitrate and decreased export of sediment relative to the present. However, simulations indicate that the substantial changes in agricultural practices envisioned in Scenarios 2 and 3 (conversion to conservation tillage, strip intercropping, rotational grazing, conservation set‐asides and greatly extended use of best management practices (BMPs) such as riparian buffers, engineered wetlands, grassed waterways, filter strips and field borders) could potentially reduce current loadings of sediment by 37 to 67 percent and nutrients by 54 to 75 percent. Results from the study indicate that major improvements in water quality in these agricultural watersheds could be achieved if such environmentally‐targeted agricultural practices were employed. Traditional approaches to water quality improvement through application of traditional BMPs will result in little or no change in nutrient export and minor decreases in sediment export from Corn Belt watersheds.     

MODELING ACTUAL EVAPOTRANSPIRATION FROM FORESTED WATERSHEDS ACROSS THE SOUTHEASTERN UNITED STATES1

ABSTRACT: About 50 to 80 percent of precipitation in the southeastern United States returns to the atmosphere by evapotranspiration. As evapotranspiration is a major component in the forest water balances, accurately quantifying it is critical to predicting the effects of forest management and global change on water, sediment, and nutrient yield from forested watersheds. However, direct measurement of forest evapotranspiration on a large basin or a regional scale is not possible. The objectives of this study were to develop an empirical model to estimate long‐term annual actual evapotranspiration (ART) for forested watersheds and to quantify spatial AET patterns across the southeast. A geographic information system (GIS) database including land cover, daily streamflow, and climate was developed using long term experimental and monitoring data from 39 forested watersheds across the region. Using the stepwise selection method implemented in a statistical modeling package, a long term annual AET model was constructed. The final multivariate linear model includes four independent variables—annual precipitation, watershed latitude, watershed elevation, and percentage of forest coverage. The model has an adjusted R² of 0.794 and is sufficient to predict long term annual ART for forested watersheds across the southeastern United States. The model developed by this study may be used to examine the spatial variability of water availability, estimate annual water loss from mesoscale watersheds, and project potential water yield change due to forest cover change.     

Modeling Climate Change Impacts on Hydrology and Nutrient Loading in the Upper Assiniboine Catchment1

Shrestha, Rajesh R., Yonas B. Dibike, and Terry D. Prowse, 2011. Modeling Climate Change Impacts on Hydrology and Nutrient Loading in the Upper Assiniboine Catchment. Journal of the American Water Resources Association (JAWRA) 48(1): 74‐89. DOI: 10.1111/j.1752‐1688.2011.00592.x Abstract: This paper presents a modeling study on climate‐induced changes in hydrologic and nutrient fluxes in the Upper Assiniboine catchment, located in the Lake Winnipeg watershed. The hydrologic and agricultural chemical yield model, Soil and Water Assessment Tool (SWAT) was employed to model a 21‐year baseline (1980‐2000) and future (2042‐2062) periods with model forcings for future climates derived from three regional climate models (RCMs) and their ensemble means. The modeled future scenarios reveal that potential future changes in the climatic regime are likely to modify considerably hydrologic and nutrient fluxes. The effects of future changes in climatic variables, especially precipitation and temperature, are clearly evident in the resulting snowmelt and runoff regimes. The future hydrologic scenarios consistently show earlier onsets of spring snowmelt and discharge peaks, and higher total runoff volumes. The simulated nutrient loads closely match the dynamics of the future runoff for both nitrogen and phosphorus, in terms of earlier timing of peak loads and higher total loads. However, nutrient concentrations could decrease due to the higher rate of runoff increase. Overall, the effects of these changes on the nutrient transport regime need to be considered together with possible future changes in land use, crop type, fertilizer application, and transformation processes in the receiving water bodies.     

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.