The presence of nutrients in snowmelt runoff from agricultural watersheds has been reported by previous studies. However, no study has answered the most important question what areas of the watershed contribute nutrients to snowmelt runoff? or addressed the factors that control snowmelt runoff water quality. This study was designed to (1) find the areas that contribute nutrient to snowmelt runoff (termed as critical source areas, CSA), and (2) understand the source and transport factors that control the snowmelt runoff water quality in the Canadian prairies. The findings of this study will provide vital information to understand snowmelt runoff water quality and for sustainable management of soil nutrients and snowmelt runoff water quality in the Canadian prairies. <p>Source and transport factors and snowmelt runoff water quality were studied for two years on shoulder, backslope and footslope landform segments. The distribution of fall soil nutrients in the top 5 cm soil layer (available soil P [ASP], nitrate [NO3-] and ammonium [NH4+]), snow depth, snow water equivalent (SWE), snowmelt runoff and snowmelt runoff water quality (total P [TP], total dissolved P [TDP], NO3-N and sediment) were studied using closed and open plots placed on each landform segment. The influence of source and transport factors was evaluated in relation to snowmelt runoff water quality. <p>The ASP had a distribution pattern of backslope < shoulder < footslope in 2003 before manure application (bma) and shoulder = backslope = footslope in 2004. The NO3- distributed as shoulder = backslope = footslope in 2003 (bma) and shoulder < backslope < footslope in 2004. However, NH4+ had a stable distribution of shoulder = backslope < footslope in 2003 bma and in 2004. The pre-melt SWE increased in the down slope direction having the lowest in the shoulder and backslope and the highest in the footslope in 2005. The average daily snowmelt runoff from 1 m2 plots did not vary between the shoulder and the backslope. Infiltration was dominant in 2004 while runoff was dominant in 2005. Of the three landform segments, the shoulder was the greatest contributor of runoff to the depression. The backslope contributed the least. <p>Hog manure injection did not seem to influence snowmelt runoff water quality. Most nutrients and sediments were from the land surface. Analysis revealed that fall soil nutrient concentrations were not a dominant factor controlling the nutrients in the snowmelt runoff in this site. However, snowmelt runoff volume controlled snowmelt runoff water quality. Snowmelt runoff water quality did not vary between the landform segments. However, as a result of the dominance of shoulder in this landscape, the total transport of nutrients and sediment was the highest from shoulder. Where landform characteristics are similar to the study watershed, it may be argued that all landform segments are CSA. Runoff volume is the most influential factor in determining the importance of CSA and controlling the snowmelt runoff water quality.

The presence of nutrients in snowmelt runoff from agricultural watersheds has been reported by previous studies. However, no study has answered the most important question what areas of the watershed contribute nutrients to snowmelt runoff? or addressed the factors that control snowmelt runoff water quality. This study was designed to (1) find the areas that contribute nutrient to snowmelt runoff (termed as critical source areas, CSA), and (2) understand the source and transport factors that control the snowmelt runoff water quality in the Canadian prairies. The findings of this study will provide vital information to understand snowmelt runoff water quality and for sustainable management of soil nutrients and snowmelt runoff water quality in the Canadian prairies. <p>Source and transport factors and snowmelt runoff water quality were studied for two years on shoulder, backslope and footslope landform segments. The distribution of fall soil nutrients in the top 5 cm soil layer (available soil P [ASP], nitrate [NO3-] and ammonium [NH4+]), snow depth, snow water equivalent (SWE), snowmelt runoff and snowmelt runoff water quality (total P [TP], total dissolved P [TDP], NO3-N and sediment) were studied using closed and open plots placed on each landform segment. The influence of source and transport factors was evaluated in relation to snowmelt runoff water quality. <p>The ASP had a distribution pattern of backslope < shoulder < footslope in 2003 before manure application (bma) and shoulder = backslope = footslope in 2004. The NO3- distributed as shoulder = backslope = footslope in 2003 (bma) and shoulder < backslope < footslope in 2004. However, NH4+ had a stable distribution of shoulder = backslope < footslope in 2003 bma and in 2004. The pre-melt SWE increased in the down slope direction having the lowest in the shoulder and backslope and the highest in the footslope in 2005. The average daily snowmelt runoff from 1 m2 plots did not vary between the shoulder and the backslope. Infiltration was dominant in 2004 while runoff was dominant in 2005. Of the three landform segments, the shoulder was the greatest contributor of runoff to the depression. The backslope contributed the least. <p>Hog manure injection did not seem to influence snowmelt runoff water quality. Most nutrients and sediments were from the land surface. Analysis revealed that fall soil nutrient concentrations were not a dominant factor controlling the nutrients in the snowmelt runoff in this site. However, snowmelt runoff volume controlled snowmelt runoff water quality. Snowmelt runoff water quality did not vary between the landform segments. However, as a result of the dominance of shoulder in this landscape, the total transport of nutrients and sediment was the highest from shoulder. Where landform characteristics are similar to the study watershed, it may be argued that all landform segments are CSA. Runoff volume is the most influential factor in determining the importance of CSA and controlling the snowmelt runoff water quality.

Critical Source Areas (CSAs) of phosphorus (P) are areas within a watershed that have a high propensity to export P to surface waters. CSAs contain two factors: source and transport factors. Source factors include soil P status and fertilizer and manure inputs, while transport factors include hydrologic and erosion processes that mobilize P. The aim of this study was to: 1) identify CSAs of P in an agricultural watershed and the stormflow dynamics controlling P export and 2) to delineate CSAs of P at the agricultural field scale using georeferenced soil test P (STP) and a digital elevation model (DEM) in a geographic information system (GIS). Soil test P (STP) along with dissolved reactive P (DRP), particulate P (PP), and total P (TP) in soil water, groundwater, and surface runoff were monitored in three small (< 8 ha) agricultural watersheds located in Decatur, Illinois, each situated within a separate experimental field. Further, volumetric water content (VWC) was continuously monitored on topographic positions, e.g. foot slopes, hill slopes, and shoulder slopes, to determine topographic position influence on soil moisture distribution. Repeated measures mixed models analysis showed that foot slopes (32.2%) had significantly higher VWC than hill slope (29.6%) and shoulder slopes (30.9%) during the growing season, while foot slopes (38.9%) and hill slopes (38.9%) had significantly higher VWC than shoulder slopes (34.9%) during the dormant season. Persistent shallow groundwater tables were implicated to control spatial and temporal VWC moisture distribution. Both foot slopes and hill slopes were implicated as transport areas. Repeated measures mixed models analysis also showed that foot slopes (73 kg ha&minus1) had significantly higher STP than hill slopes (28.9 kg ha&minus1) and shoulder slopes (33.8 kg ha&minus1) most likely due to the erosion and deposition of sediment from upper slopes to lower slopes. Foot slopes were consequently classified as source areas. A surface runoff event revealed near stream saturation and flushing of soil moisture from upper slopes to lower slopes, indicating that the watersheds are variable source area driven. The peak of PP on the rising limb of the hydrograph was attributed to near stream sediment mobility while the peak of DRP on the falling limb was attributed to flushing of upper slope soil moisture via subsurface flow. GIS delineation of CSAs at the agricultural field scale was conducted to pinpoint precise locations within a field to implement precision P management. The topographic position index (TPI) along with a modified version of the slope classification model &mdash both of which were created by Weiss (2001) and automated by Jenness (2006) &mdash were used to delineate foot slopes, hill slopes, shoulder slopes, and flat areas within a 91.2 ha agricultural field from a DEM. Transport factors were, again, identified as foot slopes and hill slopes. Further, georeferenced STP data collected in spring 2010, fall 2010, and fall 2011 were averaged and interpolated using ordinary kriging to generate a single surface that represented three year spatial soil P status within the agricultural field. Source factors were identified as areas in the field that were excessive in soil P for corn-soybean production. A CSA model was created that identified areas where both source factors and transport factors overlapped. CSAs of P occurred on 2.3 ha of the agricultural field and occurred near grass waterways and roadside drainage ditches. A one way analysis of variance (ANOVA) along with a Tukey mean separation procedure of soil P on the four topographic positions was used to characterize soil P spatial dependencies on landscape attributes associated with topographic position. Foot slopes (79.5 kg ha&minus1) and flat areas (92.9 kg ha&minus1) had significantly greater soil P than hill slopes (59.8 kg ha&minus1) and shoulder slopes (49.8 kg ha&minus1) due to depositional and sink attributes. Depositional attributes exhibit concave curvature, e.g. foot slopes. This curvature effectively reduces the velocity of surface runoff so that sediment bound P suspended in surface runoff can be deposited on the soil surface. Sink areas accrue P inputs but do not lose P to erosion via surface runoff. These areas exhibit linear, non-sloping planes, e.g. flat areas, that are not conducive to surface runoff. Although topographic position explains the spatial dependencies of source and transport factors, the CSA model was able to pinpoint where CSAs of P spatially occur within the agricultural field which can allow for precision P management.

Following over 100 years of agriculture and continuous phosphorus (P) fertilizer application in the south west of Western Australia, there is a growing risk of P transport from cropping and pasture land to streams. However, soil and landscape factors affecting the likelihood of P losses and of stream water contamination have not yet been assessed for the South coast region of Western Australia. The present investigation was conducted in the Fitzgerald River catchment located ~ 400 km south east of Perth, to identify risk of P losses from agricultural land to streams, through an understanding of how P is retained within complex landscapes and released via surface and subsurface flow paths. The 104,000 ha catchment is in a moderately dissected landscape (average annual rainfall 450 mm) and discharges into the World Heritage listed Fitzgerald Biosphere. The main use of cleared land in the catchment is broad-scale agriculture, primarily winter grain cropping and pasture for livestock. The aim of an initial study was to identify the areas with high soil P concentrations and their relationship to factors such as soil type, topography, management (e.g. fertilizer and manure inputs, and uptake by crops or forage) and how variations in soil P concentrations were related to soil physico-chemical properties, P fertilizer management and landscape position. A wide variation in P concentrations was observed across the catchment, but few of the samples exceeded Colwell extractable P levels of 30 mg/kg in the 0-10 cm layer which is regarded as a critical level for crop and pasture productivity. The western area of the catchment, which was cleared earlier (before 1966) than the eastern area had a greater prevalence of loam soils, and higher Colwell-extractable P concentrations (average)22 mg/kg vs. 13 mg P/kg) due to soil type effects and higher P accumulation over time. Risk of P loss from the east and west of the catchment is expected to vary due to textural and topographic differences and P history (P fertilizer input and uptake by crops). The CaCl2-extractable P in the catchment was negatively correlated with oxalate extractable Fe (Feox) in soils. This suggests that P may be transported as particulate P (PP) on loam and clay soils due to sorption of P on oxides surfaces, while on sand soil leaching losses may be more likely. On loam and clay soils, higher sodicity and the dispersive nature of subsoils may increase the risk of both dissolved P (DP) and PP loss due to the effects on hydraulic conductivity of the profile. Hedley's fractionation scheme was used to quantify P fractions in the order of decreasing lability, viz: resin-P > NaOH-Pi > NaOH-Po > acid-P (H2SO4-P) > residual-P. Surface soil had higher resin and NaOH-Pi, which are regarded as water-soluble and readily exchangeable P forms, respectively and expected to contribute to DP in the runoff losses. The residual P was the largest fraction followed by the hydroxide extractable organic-P fraction (NaOH-Po): the former was positively correlated (r) with clay content, organic carbon (OC) and pyrophosphate extractable Fe and Al (0.48**, 0.61**, 0.69** and 0.58**, P < 0.01). A relatively higher value of NaOH-Po in the subsurface layer and positive correlation with OC (r = 0.45**, P < 0.01) suggests potential mobility of P as soluble organic P in run-off, throughflow and leachate. Phosphorus sorption and its relationship to soil properties was used to assess the potential P release from the catchment soils. Values of P sorption maxima varied from 1111-3333 mg/kg for surface soils and 1010-2917 mg/kg for subsoils. The P sorption isotherms conformed better to the Freundlich equation than the Langmuir equation. A highly significant negative correlation between CaCl2 extractable P and Feox in surface soils (r = -0.65**, P < 0.01) suggests that P was bound to hydrated Fe oxide surfaces and this may determine the concentration and dynamics of loosely bound P equilibrating with leachates and eroded particulate materials. On the other hand, high surface organic matter and the high proportion of total dissolved P in organically bound form may inhibit P sorption on clays and sesquioxides, which would increase P mobility through leaching or runoff losses. The relationship between soil P concentration and degree of P stratification in the top 0-10 cm of soils along five toposequences was examined to predict the effect on runoff P losses. The total Colwell-P content of the 0-10 cm layer of soils in the catchment was very low in comparison to other studies on P losses from agricultural soils, but soils showed higher P concentration at 0-1 cm depth compared to 5-10 cm (average 37 mg/kg vs. 19 mg/kg). The higher extractable P concentration in the 0-1 cm layer will create a greater P mobilization risk in surface runoff and leachate than analysis of the 0-10 cm layer might suggest. Assessment of P risk using the 0-10 cm data would still be reliable as P concentration in the 0-1 cm layer was linearly related (R2 = 0.59) with concentration in the 0-10 cm layer. The sampling at varied soil depths will result in different critical P levels for estimating the risk of P enrichment in runoff. In a glasshouse study with intact soil columns, initial high P concentrations in leachate decreased with leaching events suggesting that macropore flow dominated in initial leaching events changing later to matrix flow. The hydraulic behavior of clay and loam soil below 10 cm depends largely on structure and the type of clay minerals and exchangeable Na. Higher levels of exchangeable Na in the subsoil might increase dispersion of clay particles resulting in low permeability leading to ponding of surface water or lateral movement of water at the interface of sand A and clay B horizons. Lateral water movements increase the risk of P losses in the form of DP, dissolved organic P (DOP) or PP. The P concentration in all the P forms (DRP, DOP and TDP) increased significantly with P rates of application (P < 0.01). The DRP concentration was < 2 mg/l in unfertilized columns but an increase to 11 mg/l was observed with P application at 40 kg P/ha. The higher proportion of DOP relative to DRP and its correlation with TDP indicates that the DOP was the major form of P in leachate. However, the estimation of DOP which was by subtraction of DRP from TDP generally overestimates OP concentration. The TDP load from unfertilized soil was < 0.20 mg/l in runoff and < 2.40 mg/l in throughflow but increased with P application (20, 40 kg P/ha) for both packed box and field studies. Under field conditions, higher P loss was found with broadcast P application compared to drill placement. The higher load of DOP as a proportion of TDP and its significant relationship with TDP in runoff (R2sand = 0.81; R2clay = 0.79) and throughflow (R2sand = 0.94; R2clay = 0.98) in field and box studies also suggests DOP was the major form of P loss from soil. Dissolved OP concentration increased significantly with increase in soluble organic carbon (SOC) in soil solution at 5 cm depth (P < 0.05). Consequently, the amount of organic matter dissolved in soil solution may influence P sorption and mobility. Relatively higher affinity of soil for sorption of DRP compared to DOP might allow DOP to be more mobile through the profile. Higher PP load in clay soil in throughflow indicates subsurface lateral flow along the interface with the horizon of dispersive clay might be an additional risk factor regarding P mobility in clay soils of the catchment. The runoff, throughflow and leachate were dominated by eroded particles of clay and colloidal organic materials. However, the soil solution collected though 0.1 m pores in the Rhizon samplers had a similar dominance of DOP to the < 0.45 jum filtered samples in runoff and throughflow. This reduces the likelihood that the so-called DOP fraction was mostly P associated with PP in the 0.1 to 0.45 jum size fraction. The composition of DOP in soil solution collected through Rhizon samplers (< 0.1 jum) might provide important insights for P mobility since this more effectively excluded PP than in the < 0.45 jum filtrate used for runoff and throughflow samples. The DOP in soil solution (< 0.1 jum) might be associated with fine colloidal compound such as silicates, metallic hydroxides, humic acids, polysaccharides, fulvic acids and proteins. If so, then most, but not all of the DOP fraction would be organically bound. However, this requires verification. In conclusion, soil P levels across the catchment were never very high when assessed in the 0-10 cm layer, but levels in the 0-1 cm layer were more than twice as high. Overall, < 1 % of land area of the upper Fitzgerald River catchment had Colwell-P levels > 30 mg/kg (0-10 cm) and hydrological connection to streams. In addition, another 7 % of land had Colwell-P levels > 15 mg/kg, which appears to be a change point in soils for the release of CaCl2 extractable P. These areas, which are predicted to represent critical source areas of the catchment, need careful management. The high proportions of TDP as DOP in runoff, throughflow and soil solution suggest DOP was the major form of P loss from soil. Phosphorus losses from the catchments are also likely in the form of PP in clay and loam soil but leaching losses are more likely in sand. High exchangeable Na in the subsoil of loam and clay soils increases dispersion of clay particles resulting in low permeability of subsoil and greater lateral P mobility as throughflow at the interface of sand and clay textured horizons. In general, soils of Fitzgerald River catchment had low soil P, but nevertheless significant risk of P loss at Colwell-P > 15 mg/kg. This study provides baseline information for P loss risks in the wheatbelt of WA. Stream water quality monitoring instruments were installed in the upper Fitzgerald River Catchment at 5 stream locations by CSIRO to measure base line concentrations of P. The measured P concentrations were higher than ANZECC trigger values (> 0.05 mg P/l) for management response over the three-year monitoring period (2005-07). Hence this and many other catchments on the south coast and wheatbelt of south west Western Australia need assessment for P loss risks. Previous emphasis in south west Western Australia on P losses from sandy coastal soils under pasture may need to be reconsidered. In the South coast region, cropping land in the medium rainfall zone may still represent a risk of P loss to waterways and risk to water quality. The present study evaluated the risk of P loss based on soil P forms and their mobility. It suggests greater attention needs to be given to the difference between clay and loam soils with dispersive or non-dispersive sub-soils, and to the composition and mobility of DOP. However, a more complete understanding of P loss risks depends on follow-up studies on hydrological flow and connectivity in the upper Fitzgerald River catchment and similar landscapes of south west Western Australia.

Since agriculture began, field management has been at the forefront of expanding food production beyond previous limitations. Agricultural productivity is closely related to the physical, chemical, and biological properties of the soil. Landscape position and field management are among primary factors affecting these soil properties. Delineation of topographic positions of the field surface by shape (i.e., convex, concave, and linear) characterizes areas that may accumulate or lose soil and nutrients either during a discrete event or cumulatively over several growing seasons. Increased soil compaction, degradation of soil structure, and erosion have all been attributed to declining agricultural production. In addition to the physical disturbance from cultivation, erosion and deposition of soil components in different landscape positions explain a large part of the heterogeneity of soil properties across an agriculture field. In response to this, conservation tillage techniques, precision agriculture, and other novel management strategies have been developed to reduce negative impacts conventional row crop production such as nutrient pollution and compaction while optimizing farmer inputs. The objective of this project was to evaluate effects of topographic position and conservation tillage techniques on soil physical, chemical, and biological properties on the field scale as well as correlate certain soil attributes with suspended soil runoff collected during the sprinkle infiltration test. Soil fertility sampling was completed every fall from 2011 to 2014 and additional sampling of soil physical properties was taken in the spring between 2013 and 2014. Differences between fall conservation tillage treatments, no-till (NT), AerWay® aerator (AA), and Great Plains Turbo-Till® (GP), and topographic positons, concave, convex and linear were analyzed. Sediment runoff and earthworm biomass were also collected in the fall in 2014. Results indicated a significant increase of soil organic matter (12%-24%), water stable aggregates (78%-98%), phosphorus (43%-76%), and cation exchange capacity (28%-35%) within concave over the convex landscape positions. Soil strength was significantly lower in the field managed with the GP vertical tillage disk compared with the AA field to a depth of 27.5 cm and the NT field to depth of 17.5 cm. Crop residue coverage (percent covered) was more complete in the NT field (12%) and the GP field (3%) compared with the AA field. Suspended sediment runoff was negatively correlated with water-stable aggregates, Ca, and Mg, but positively correlated with earthworm biomass. Extractable nutrients and soil physical properties were also strongly affected by air temperature and precipitation throughout the study period. Characterizing soil properties within topographic positions has potential applications in precision agriculture management, such as reducing excessive fertilization, and identifying areas of increased pollution potential. Evaluation of the tandem effects of conservation tillage tools and topographic position within central Illinois is important in order for the optimization of production and conservation of resources. Physical disturbance from tillage and the transport of sediment from eroded areas to depositional topographic positions are key factors influencing the variability of soil properties, crop productivity, and potential sediment-borne nutrient pollution within individual agricultural fields.

No description available.

Climate change impacts hydrology, nutrient cycling, agricultural conservation practices, and greenhouse gas (GHG) emissions. The Chesapeake Bay and its watershed are subject to the largest and most expensive Total Maximum Daily Load (TMDL) ever developed. It is unclear if the TMDL can be met given climate change and variability (e.g., extreme weather events). The objective of this dissertation is to quantify the impact of climate change and climate on water resources, nutrient cycling and export in agroecosystems, and agricultural conservation practices in the Chesapeake Bay watershed. This is accomplished by developing and employing a suite of modelling tools. GHG emissions from agroecosystems, particularly nitrous oxide (N2O), are an increasing concern. To quantify N2O emissions a routine was developed for the Soil and Water Assessment Tool (SWAT) model. The new routine predicts N2O and di-nitrogen (N2) emissions by coupling the C and N cycles with soil moisture, temperature, and pH in SWAT. The model uses reduction functions to predict total denitrification (N2 + N2O production) and partitions N2 from N2O using a ratio method. The SWAT nitrification routine was modified to predict N2O emissions using reduction functions. The new model was tested using GRACEnet data at University Park, Pennsylvania, and West Lafayette, Indiana. Results showed strong correlations between plot measurements of N2O flux and the model predictions for both test sites and suggest that N2O emissions are particularly sensitive to soil pH and soil N, and moderately sensitive to soil temperature/moisture and total soil C levels. The new GHG model was then used to analyze the impact of climate change and extreme weather conditions on the denitrification rate, N2O emissions, and nutrient cycling/export in the 7.4 km2 WE38 watershed in Pennsylvania. Climate change impacts hydrology and nutrient cycling by changing soil moisture, stoichiometric nutrient ratios, and soil temperature, potentially complicating mitigation measures. To quantify the impact of climate change we forced the new GHG model with downscaled and bias-corrected regional climate model output and derived climate anomalies to assess their impact on hydrology, nitrate (NO3-), phosphorus (P), and sediment export, and on emissions of N2O and N2. Model-average (± standard deviation) results indicate that climate change, through an increase in precipitation, will result in moderate increases in winter/spring flow (2.7±10.6 %) and NO3- export (3.0±7.3 %), substantial increases in dissolved P (DP, 8.8±19.8 %), total P (TP, 4.5±11.7 %), and sediment (17.9±14.2 %) export, and greater N2O (63.3±50.8 %) and N2 (17.6±20.7 %) emissions. Conversely, decreases in summer flow (-12.4±26.7 %) and the export of P (-11.4±27.4 %), TP (-7.9±24.5 %), sediment (-4.1±21.4 %), and NO3- (-12.2±31.4 %) are driven by greater evapotranspiration from increasing summer temperatures. Increases in N2O (20.1±29.3 %) and decreases in N2 (-13.0±14.6 %) are also predicted in the summer and driven by increases in soil moisture and temperature. In an effort to assess the impact of climate change at a regional level, the model was then scaled-up to the entire Susquehanna River basin and was used to evaluate if agricultural best management practices (BMPs) can offset the impact of climate change. Agricultural BMPs are increasingly and widely employed to reduce diffuse nutrient pollution. Climate change can complicate the development, implementation, and efficiency of BMPs by altering hydrology, nutrient cycling, and erosion. We select and evaluate four common BMPs (buffer strips, strip crop, no-till, and tile drainage) to test their response to climate change. We force the calibrated model with six downscaled global climate models (GCMs) for a historic period (1990-2014) and two future scenario periods (2041-2065) and (2075-2099) and quantify the impact of climate change on hydrology, NO3-, total N (TN), DP, TP, and sediment export with and without BMPs. We also tested prioritizing BMP installation on the 30% of agricultural lands that generate the most runoff (e.g., critical source areas-CSAs). Compared against the historical baseline and excluding the impact of BMPs, the ensemble model mean (± standard deviation?) predictions indicate that climate change results in annual increases in flow (4.5±7.3%), surface runoff (3.5±6.1%), sediment export (28.5±18.2%) and TN (9.5±5.1%), but decreases in NO3- (12±12.8%), DP (14±11.5%), and TP (2.5±7.4%) export. When agricultural BMPs are simulated most do not appreciably change the overall water balance; however, tile drainage and strip crop decrease surface runoff generation and the export of sediment, DP, and TP, while buffer strips reduced N export substantially. Installing BMPs on critical source areas (CSAs) results in nearly the same level of performance for most practices and most pollutants. These results suggest that climate change will influence the performance of BMPs and that targeting BMPs to CSAs can provide nearly the same level of water quality impact as more widespread adoption. Finally, recognizing that all of these model applications have considerable uncertainty associated with their predictions, we develop and employ a Bayesian multi-model ensemble to evaluate structural model prediction uncertainty. The reliability of watershed models in a management context depends largely on associated uncertainties. Our Objective is to quantify structural uncertainty for predictions of flow, sediment, TN, and TP predictions using three models: the SWAT-Variable Source Area model (SWAT-VSA), the standard SWAT model (SWAT-ST), and the Chesapeake Bay watershed model (CBP-model). We initialize each of the models using weather, soil, and land use data and analyze outputs of flow, sediment, TN, and TP for the Susquehanna River basin at the Conowingo Dam in Conowingo, Maryland. Using these three models we fit Bayesian Generalized Non - Linear Multilevel Models (BGMM) for flow, sediment, TN, and TP and obtain estimated outputs with 95% confidence intervals. We compare the BGMM results against the individual model results and straight model averaging (SMA) results using a split time period analysis (training period and testing period) to assess the BGMM in a predictive fashion. The BGMM provided better predictions of flow, sediment, TN, and TP compared to individual models and the SMA during the training period. However, during the testing period the BGMM was not always the best predictor; in fact, there was no clear best model during the testing period. Perhaps more importantly, the BGMM provides estimates of prediction uncertainty, which can enhance decision making and improve watershed management by providing a risk-based assessment of outcomes. / Ph. D. / Climate change impacts hydrology, nutrient cycling, agricultural conservation practices, and greenhouse gas (GHG) emissions. The Chesapeake Bay and its watershed are subject to the largest and most expensive Total Maximum Daily Load (TMDL) ever developed. It is unclear if the TMDL can be met given climate change and variability. The objective of this dissertation is to quantify the impact of climate change and climate on water resources, nutrient cycling and export in agroecosystems, and agricultural conservation practices in the Chesapeake Bay watershed. This is accomplished by developing and employing different modeling tools. First, GHG emissions model was developed to quantify nitrous oxide (N₂O) emissions from agroecosystems, which are an increasing concern. The new model was then tested using observed N₂O emissions data at University Park, Pennsylvania, and West Lafayette, Indiana. Results showed strong correlations between plot measurements of N₂O flux and the model predictions for both test sites. Second, the new GHG model was then used to analyze the impact of climate change and extreme weather conditions on the N₂O emissions, and nutrient cycling/export in small and regional watershed scale. To quantify the impact of climate change we forced the new GHG model with downscaled and bias-corrected regional climate model date to assess their impact on hydrology, nitrate (NO₃-), phosphorus (P), and sediment export, and on emissions of N₂O and N₂. Finally, recognizing that all of these model applications have considerable uncertainty associated with their predictions, we developed and employed a Bayesian multi-model ensemble to evaluate structural model prediction uncertainty.