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The natural environment of corn crops is being affected by climate changes. This research is aimed at evaluating the climate change scenarios resulting from the downscaling using the Eta regional climate model, nested in the global model CanESM2, and assessing the consequences of climate changes in the runoff and root water uptake of corn crops in the region of Parana, Brazil. This research also describes the climatology and the possible changes in the climate of the area, according to the different emission scenarios and infer how these changes will affect the dynamics of water in the corn crop in the region, simulated by Hydrus model. Simulations comprise of the historical period (1981–2005) and the future projections under RCP4.5 and RCP8.5, between the years 2046 to 2070. Eta model nested with the global model CanESM2 presented high ability to reproduce the climate in the region. Simulations showed changes in precipitation and an increasing trend of maximum and minimum temperatures when compared with the baseline. The root water uptake showed increasing trends predominantly in the RCP8.5 scenario. These climate changes can strongly affect corn production in the region of Parana, Brazil, as it can lead to increasing runoff and runoff extremes (runoff above 100 mm/day). This situation poses a risk to crop production since it causes losses by leaching and destruction of plants, as well as other factors such as lack of aeration and increased incidence of plant diseases. Similarly, the projected increase in temperature can result in increased evapotranspiration, which affects root water uptake, and the crop water demand.

Decision-making processes to ensure sustainability of complex agro-ecosystems must simultaneously accommodate production goals, environmental soundness, and social relevancy. This means that besides environmental indicators and human activities, stakeholders' perceptions need to be considered in the decision-making process to enable the adoption of mitigation practices. Thus, the decision-making process equates to a multi-criteria and multi-objective problem, requiring additional tools and methods to analyze the possible tradeoffs among decision alternatives based on social acceptability. This study was aimed at establishing a decision support system that integrates hydro-ecologic models and socio-cultural perspectives to identify and assess feasible land management alternatives that can enhance the Kaskaskia River Watershed (KRW) ecosystem services in Illinois (USA). The Soil and Water Assessment Tool (SWAT) was used to simulate the spatio-temporal response of nine environmental predictors to four major management alternatives (crop rotation, cover cropping, reduced tillage, modified fertilizer application) based on stakeholder acceptability and environmental soundness, under 32 distinct climate projections. The stochastic multicriteria acceptability analysis (SMAA) was then applied to classify the management alternatives from the least to the most efficient based on three preference schemes: no preference, expert stakeholders' preference, and non-expert stakeholders' preference. Results showed that preference information on watershed ecosystem services is crucial to guide the decision-making process when a broad spectrum of criteria is considered to assess the management alternatives' systemic response. The disparity between expert and non-expert stakeholders' preferences showed different rankings of alternatives across several subcatchments, where the two-year corn one-year soybean rotation scheme was expected to offer the best management alternative to ensure a sustainable agro-production system in the highly cultivated subcatchments of the KRW. In contrast, non-conventional tillage practices were expected to contravene agricultural production, and therefore should be discarded unless combined with complementary measures. This study will enable stakeholders to identify the most suitable management practices to adapt to natural and anthropogenic changes and encourage engagement between government institutions and local communities (multi-stakeholder consensus) to provide a better platform for decision-making.

Ongoing and projected changes in climate are expected to alter discharge and water temperature in riverine systems, thus resulting in degraded habitat. Climate adaptation management strategies are proposed to serve as buffers to changes in air temperature and precipitation, with these strategies potentially providing relatively stable protection for flow and thermal regimes. Using a hydrologic and water temperature modeling approach in the Meramec River basin in eastern Missouri, U.S.A., we examined the ability of forested riparian buffers to serve as a useful climate adaptation strategy against ongoing and projected changes in climate. We developed a multi-scale approach using Soil and Water Assessment Tool (SWAT) hydrologic and water temperature models as well as a Stream Network Temperature Model (SNTEMP) with different amounts of simulated riparian vegetation to estimate streamflow and water temperature variation within the Meramec River basin under both contemporary and projected future climate conditions. Our results suggest that riparian buffers offer benefits to mitigating increases in water temperature due to shading effects; however, patterns in discharge did not vary substantially based on simulations. From an ecological perspective, the addition of riparian buffers is also projected to reduce the impacts of climate change on Smallmouth Bass (Micropterus dolomieu) by decreasing the number of days water temperatures exceed the thermal tolerance of this species.

Tile drainage waters carry considerable loads of phosphorus (P) from agricultural fields to rivers and streams in the Midwestern U.S. An innovative and economical approach to monitor dissolved reactive P (DRP) flux in tile waters is needed to understand the extent of P loss in field-scale. In this study, a passive sampling technique was developed using iron oxide-coated polyacrylic/polystyrene anion exchange resins (hybrid resins) a P sink. Laboratory batch adsorption isotherm and kinetic experiments indicated that the hybrid resins had high P adsorption capacity (7.69&ndash, 19.84 mg/g) and high kinetic performance. The passive sampling method with field-calibrated hybrid polyacrylic resin and hybrid polystyrene resins (sampling rate: 0.1351 and 0.0763 L/h, respectively) predicted the average DRP concentrations of 0.006&ndash, 0.020 mg/L, which did not differ significantly (p &gt, 0.05) from the auto-sampling data. A rapid increase in DRP concentration during storm events and subsequent flooding events was also predicted well. In conclusion, a passive detection method using iron oxide coated hybrid resins can be recommended for monitoring seasonally fluctuating DRP flux in agricultural waters as long as the hybrid resins are well-calibrated under specific field conditions (e.g., flow rate and concentration range).

The Green-Ampt method is a physically based model for partitioning rainfall into surface runoff and infiltration. This method is widely used in infiltration practice because of its simplici...

Soil erosion is identified as the primary cause of soil degradatgion due to the unsustainable agricultural practices, leading to severe threat worldwide for soil health and water quality problems. Therefore, quantifying soil erosion under various conservation practices is important for watershed management and a framework that can accurately estimate the spatio-temporal dynamics of soil erosion is required. In this paper, a modeling framework that coupled physically based models, Water Erosion Prediction Project (WEPP) and MIKE SHE/MIKE 11, was presented. Daily soil loss in field scale was determined using WEPP and the transport processes of the eroded soil were simulated using an advection-dispersion equation in MIKE SHE/MIKE 11 models. The framework facilitated the physical simulation of sediment production at the field scale and transport processes across the watershed. The coupled model was tested in an intensively managed agricultural watershed in Illinois. The impacts of no-till practice on both sediment production and sediment yield were evaluated using scenario-based simulations with different fractions of no-till and conventional tillage combinations. The results indicated that if no-till were implemented for all fields throughout the watershed, 76% and 72% reductions in total soil loss and sediment yield, respectively, can be achieved. In addition, if no-till practice were implemented in the most vulnerable areas to sediment production across the watershed, a 40% no-till implementation can achieve almost the same reduction as 100% no-till implementation. Based on the simulation results, the impacts of no-till practice are more prominent if implemented where it is most needed.

Study region The Little Washita River Experimental Watershed (LWREW) is located between Chickasha and Lawton in southwestern Oklahoma, US. Study focus In this study, frequency analyses were conducted on sub-hourly precipitation event descriptors to quantify the changes in precipitation patterns commonly masked in annual analysis. Precipitation events were derived from 5-min data collected by USDA-ARS from 1961 to 2015. New hydrological insights for the region During the 1962–2015 period, this region experienced successive regional long-term wet (1962–1995) and dry (1996–2015) dominated periods of more than 20 years each. During the wet period, precipitation intensity ranging from 1 to 12 mm were 20% less likely to occur while event daily average precipitation and number of events increased by 10% and 11%, respectively. Also, the average daily precipitation occurred more often at lower intensities. In contrast, during the dry period, instantaneous intensity ranging from 1 to 12 mm became more likely to occur (64% increase; 1996–2015) while event daily average precipitation and number of events decreased by 16% and 18%, respectively. Overall, comparisons with the baseline data (1962–2015) indicated that in the last 20 years, sub-hourly precipitation intensities have increased while daily event duration and extreme 5-min precipitation intensities larger than 24 mm (precipitation intensification below extremes) have remained unchanged.

Freshwater systems are some of the most threatened ecosystems in the world. Factors contributing to their degradation can be associated with the expansion and intensification of agriculture in the 20th century, which has led to habitat degradation and water pollution. To mitigate the impacts of agricultural activities and improve stream ecosystem quality, government-funded conservation programs have promoted the implementation of best management practices (BMPs) during the last three to four decades. However, these conservation programs have been implemented within agricultural landscapes without evaluating exhaustively their potential side effects on freshwater species at the watershed scale. This study aimed to assess the changes in freshwater biodiversity in terms of fish species richness under future climate and potential conservation land-management schemes in the Kaskaskia River Watershed, Illinois, USA. Fish regression models were integrated to the Soil and Water Assessment Tool (SWAT) to simulate the responses of total- and game-fish species richness to four major management practices (crop rotation, cover cropping, reduced tillage, modified fertilizer application) identified as the most feasible in terms of stakeholder acceptability and environmental soundness, under 32 distinct climate projections. Results showed that fish species in the KRW are more sensitive to changes in the climate regime than to changes in the land-management practices. Specifically, the most likely percentage changes in fish species revealed a potential decline in richness in all stream orders over time with the worst impacts in the first and second order streams (-5%–-10% decade−1) due to the progressive increase in the temperatures (0.61 °C –0.92 °C decade−1) expected in the watershed. The long-term impacts on fish species richness may be inevitable if the proposed land-management alternatives were not accompanied by additional measures specifically design to protect aquatic life.

Riparian erosion is one of the major causes of sediment and contaminant load to streams, degradation of riparian wildlife habitats, and land loss hazards. Land and soil management practices are implemented as conservation and restoration measures to mitigate the environmental problems brought about by riparian erosion. This, however, requires the identification of vulnerable areas to soil erosion. Because of the complex interactions between the different mechanisms that govern soil erosion and the inherent uncertainties involved in quantifying these processes, assessing erosion vulnerability at the watershed scale is challenging. The main objective of this study was to develop a methodology to identify areas along the riparian zone that are susceptible to erosion. The methodology was developed by integrating the physically-based watershed model MIKE-SHE, to simulate water movement, and a habitat suitability model, MaxEnt, to quantify the probability of presences of elevation changes (i.e., erosion) across the watershed. The presences of elevation changes were estimated based on two LiDAR-based elevation datasets taken in 2009 and 2012. The changes in elevation were grouped into four categories: low (0.5 - 0.7 m), medium (0.7 – 1.0 m), high (1.0 - 1.7 m) and very high (1.7 – 5.9 m) , considering each category as a studied “species”. The categories’ locations were then used as “species location” map in MaxEnt. The environmental features used as constraints to the presence of erosion were land cover, soil, stream power index, overland flow, lateral inflow, and discharge. The modeling framework was evaluated in the Fort Cobb Reservoir Experimental watershed in southcentral Oklahoma. Results showed that the most vulnerable areas for erosion were located at the upper riparian zones of the Cobb and Lake sub-watersheds. The main waterways of these sub-watersheds were also found to be prone to streambank erosion. Approximatively 80% of the riparian zone (streambank included) has up to 30% probability to experience erosion greater than 1.0 m. By being able to identify the most vulnerable areas for stream and riparian sediment mobilization, conservation and management practices can be focused on areas needing the most attention and resources.

Evaluating the effectiveness of agricultural land management practices in minimizing environmental impacts using models is challenged by the presence of inherent uncertainties during the model development stage. One issue faced during the model development stage is the uncertainty involved in model parameterization. Using a single optimized set of parameters (one snapshot) to represent baseline conditions of the system limits the applicability and robustness of the model to properly represent future or alternative scenarios. The objective of this study was to develop a framework that facilitates model parameter selection while evaluating uncertainty to assess the impacts of land management practices at the watershed scale. The model framework was applied to the Lake Creek watershed located in southwestern Oklahoma, USA. A two-step probabilistic approach was implemented to parameterize the Agricultural Policy/Environmental eXtender (APEX) model using global uncertainty and sensitivity analysis to estimate the full spectrum of total monthly water yield (WYLD) and total monthly Nitrogen loads (N) in the watershed under different land management practices. Twenty-seven models were found to represent the baseline scenario in which uncertainty of up to 29% and 400% in WYLD and N, respectively, is plausible. Changing the land cover to pasture manifested the highest decrease in N to up to 30% for a full pasture coverage while changing to full winter wheat cover can increase the N up to 11%. The methodology developed in this study was able to quantify the full spectrum of system responses, the uncertainty associated with them, and the most important parameters that drive their variability. Results from this study can be used to develop strategic decisions on the risks and tradeoffs associated with different management alternatives that aim to increase productivity while also minimizing their environmental impacts.

The capability of hydrologic models to spatially simulate the changes in hydrologic processes, like precipitation, is an important consideration in capturing the impacts of these processes on sediment prediction across the domain. Radar-derived precipitation (RDP) provides an enhanced detail of rainfall characteristics in time and space compared to estimates from rain-gauge precipitation (RGP) commonly used in hydrologic modeling. However, the impacts of these datasets on sediment fate and transport depend on how sediment sources were conceptualized in the model. This paper developed a modeling framework to simulate sediment transport from upland to the stream and to the outlet of the watershed based on a gridded conceptualization and to examine the impacts of RGP and RDP with different types of sediment sources on sediment prediction. The Water Erosion Prediction Project (WEPP) model was used to estimate daily sediment sources in a semi-distributed and fully distributed manner using the hydrologic model, MIKE SHE and MIKE 11. Model comparison was performed in a watershed in Illinois characterized by a dominant agricultural landscape. The results indicated that the use of RDP only ensured better model performance for sediment yield with the fully distributed sediment source. That is, combining both the ability of the RDP to capture the spatial variability of rainfall across the watershed and assessing sediment production at higher resolution improved the accuracy of predictions in sediment yield while decreasing uncertainties associated with sediment simulations. Advancing modeling capabilities will require the development of new modeling platforms that aim to seamlessly integrate large-scale distributed simulations and environmental input data at finer spatial resolutions.

Soil erosion is significantly increased and accelerated by unsustainable agricultural activities, resulting in one of the major threats to soil health and water quality worldwide. Quantifying soil erosion under different conservation practices is important for watershed management and a framework that can capture the spatio-temporal dynamics of soil erosion by water is required. In this paper, a modeling framework that coupled physically based models, Water Erosion Prediction Project (WEPP) and MIKE SHE/MIKE 11, was presented. Daily soil loss at a grid-scale resolution was determined using WEPP and the transport processes were simulated using a generic advection dispersion equation in MIKE SHE/MIKE 11 models. The framework facilitated the physical simulation of sediment production at the field scale and transport processes across the watershed. The coupled model was tested using an intensively managed agricultural watershed in Illinois. The impacts of no-till practice on both sediment production and sediment yield were evaluated using scenario-based simulations with different fractions of no-till and conventional tillage combinations. The results showed that if no-till were implemented for all fields throughout the watershed, 76% and 72% reductions in total soil loss and sediment yield, respectively, can be achieved. In addition, if no-till practice were implemented in the most vulnerable areas to sediment production across the watershed, a 40% no-till implementation can achieve almost the same reduction as 100% no-till implementation. Based on the simulation results, the impacts of no-till practice are more prominent if implemented where it is most needed.

Transformations of forested areas to agricultural and urban uses are known to degrade freshwater ecosystems, in part, because of increased surface runoff and soil erosion. Changes in climate are expected to exacerbate these impacts, particularly through increases and intensification of precipitation events during various times of the year. While decreases in greenhouse gas emissions are ultimately necessary to minimize changes in climate, best management practices (BMPs), such as reforestation, can serve as watershed climate adaptation strategies to mitigate the impacts of changes in air temperature and precipitation. The Meramec River Basin (MRB) in eastern Missouri is of economic and recreational importance and supports high levels of biodiversity. While much of the MRB is forested, various land transformations are increasing sediment inputs throughout the basin, and these contributions are expected to increase as climate changes. To address the potential of riparian reforestation to serve as a climate adaptation strategy in the MRB, we developed a Soil and Water Assessment Tool model to simulate streamflow and sediment transport throughout the basin. We then used model outputs characterizing spatial variation in sediment yields to identify critical source areas (CSAs) at the subbasin level. The application of a riparian buffer BMP was simulated in each CSA to quantify the effectiveness of this strategy in reducing sediment for contemporary conditions (1990–2009) as well as under three future climate scenarios for two time periods, 2040–2059 (mid-century) and 2080–2099 (late-century). For the contemporary period, the simulated addition of a riparian buffer BMP resulted in a projected 12.1% average reduction in surface sediment yield among CSAs. For the mid-century projection, subbasin surface sediment output is projected to increase by an average of 277.5% and 221.8% for the climate change scenario and the climate change + BMP scenario, respectively. In the late-century, respective increases in sediment for CSAs are estimated to be, on average, 690.7% and 528.3% for the climate change scenario and the climate change + BMP scenario. Results suggest that surface sediment yields will increase with climate change even with riparian buffer BMP applications. While adding a riparian buffer can potentially reduce sediment outputs, the reduction, on average, is likely inadequate to fully offset the impacts from changes in climate.

Sustaining agricultural environments requires explicit recognition of the services provided by landscapes, particularly cultural ecosystem services that are contested and underrepresented in previous research. We assembled and engaged a panel of experts to identify and deliberate on the relationships among ecosystem services, threats and land management practices in an agricultural watershed using a Delphi method. We also drew from focus group results to gain an in-depth understanding of how participants valued the Kaskaskia River Watershed, Illinois. Results revealed that diverse benefits were derived from provisioning (e.g., crop production), regulating (e.g., flood prevention), supporting (e.g., soil formation), and cultural (e.g., farming lifestyle) services provided by the watershed. A disproportionately higher number of cultural services were identified and rated as highly important. Multiple threats, including erosion and nutrient loading, were associated with agricultural, forest and lake and river environments, highlighting the importance of connectivity across ecosystems. To mitigate and adapt to change, particularly around the provision of agro-ecosystem services, stakeholders benefit from collective discussions about land management practices such as reduced tillage and zoning policies. Engaging local stakeholders in deliberation provides a rich basis for understanding the multiple values of worked landscapes and establishing sustainable agricultural practices.

Groundwater resources worldwide are being depleted at alarming rates since 1960 to support agriculture, industry, and domestic water demand. Water harvesting and the implementation of reduced application or more efficient irrigation technologies were identified as two of the most efficient practices to mitigate the declining patterns on groundwater resources. However, prior to implementing these practices, understanding how groundwater interacts with surface water and responds to natural and anthropogenic stressors is crucial. Integrated modeling tools that are able to exchange fluxes in both domains are needed to assess how conservation practices will affect our water resources under different projected climate and land use scenarios. This study aimed to evaluate the most likely impacts of current land management practices under the most severe projections of future climate and quantify the potential mitigation effects of three conservation scenarios on the water resources of the Fort Cobb Reservoir Experimental Watershed (FCREW) in western Oklahoma. The semicoupled SWAT-MODFLOW (SWATmf) model was used to simulate the hydrologic responses of the FCREW to a 50% reduction in the irrigation depths and the transition of 50% and 75% of croplands to rangelands under 32 distinct climate projections. Results showed that future climate can drive a reduction in the streamflow (&minus, 18%) and an increase to the depth of the water table (99%&ndash, 120%) in the western part of the FCREW by the end of the century. The Fort Cobb Reservoir was expected to reduce its release after the mid-2060s to maintain its current target level. All the scenarios, aimed at decreasing groundwater extractions or implementing conservation measures, signaled a full recovery response in the groundwater levels 7&ndash, 10 years after the year the conservation practices were implemented. The 50% reduction in the irrigation depths was found to elicit faster hydrologic systemic responses than the two that implemented conservation measures, which contravene tradition and would imply cessation of agricultural activities. This study can enable stakeholders to formulate timely adaptation and mitigating strategies to adopt to land use changes.

Water pollution is a major global issue that has profound impact on sustainable development of our society. In this paper, land cover change trajectories of the study area over the last three decades are developed using Landsat data. Then historic land-cover and land-use change (LCLUC) patterns are used to estimate, calibrate and validate key drivers of land use change. Future likelihood of land-cover/land-use for 2021 and 2031 are simulated using state-of-art image processing techniques based on the driving factors of land use change integrated with Land Change Modeler. Hypothetical scenarios of LCLUC including a) low density of new urbanization growth and open land with vegetation cover, b) normal urbanization and, c) highly development of commercial/urban land use and impervious surfaces, are constructed during the simulations. The Soil and Water Assessment Tool (SWAT) is employed to generate total suspended sediment with the various combinations of three hypothetical scenarios mentioned above and climate change scenarios projected for 2021 and 2031. The future climate patterns for the periods of 2011-2021 and 2021-2031 are generated from the intergovernmental Panel on Climate Change (IPCC) Spatial Report for scenarios A1B, B1, and A2. A total of 19 SWAT models are generated, one for 2011, nine for 2021 and 2031 respectively. The results are then used to compare and identify the impacts of combined land use and climate change on surface water quality, to answer and confirm the hypothesis that urban sprawl developing patterns in the greater St. Louis region have significant impacts on surface water quality in specific way.

Better understanding of the vulnerability of coastal habitats to sea level rise and major storm events are aided by the use of simulation models. Since coastal habitats also undergo frequent nourishment restoration works in order to maintain their viability, vulnerability models must be able to assess the combined effects of sea level rise, storm surge, and beach nourishment. The Sea Level Affecting Marshes Model (SLAMM) was modified and applied to quantify the changes in the beach area in a 5-km stretch of beach in Santa Rosa Island, Florida due to these combined effects. A new methodology to estimate spatial erosion patterns was developed based on measured erosion during three historic storm events representing a wide range of storm intensities over the study area (named storms Ivan (H5), Dennis (H4), and Katrina (TS)). Future major storms over the 2012-2100 period were generated based on the frequency distribution of historic storms using 4000 simulations to account for uncertainty in the storms temporal distribution. Potential effects of individual, successive, and random storms occurring over the area under 0-1.5 m nourishment schemes were evaluated. The risk of losing the beach habitat in 90 years for different scenarios is studied based on probability distribution contours constructed with the model results. Simulation results suggest that without nourishment, a major storm with a category of tropical storm or higher will reduce the beach at the end of the period by 97-100%. This loss can be reduced to 60% by maintaining a 1-m beach elevation and can further be reduced to 34% with 1.5 m beach nourishment. Modification of SLAMM to include major storm events and beach restoration.Effects of sea level rise, storm events, and nourishment on beach habitat.Evaluates risk of losing beach habitat in 90 years for different scenarios.Showed restoration tradeoffs as a basis for environmental management.

Agricultural practices intended to increase productivity can adversely affect our soil and water resources. Expected changes in climate and other social pressure are anticipated to exacerbate these impacts jeopardizing the sustainability of the agro-ecosystems. Watershed Management Practices (WMPs) are meant to achieve a rational use of resources as well as enhance ecosystem resilience to climate change. However, the effectiveness of WMPs depends on the complex interactions between processes occurring across the watershed. The objective of this study was to simulate the impacts of WMPs and projected climate on the sediment and nitrate-nitrogen (NO3-N) stream loads in an intensively managed watershed. The modeling framework was developed with the physically-based distributed model Mike SHE for the Upper Sangamon River Basin (USRB), an agricultural watershed in central Illinois. The fate and transport of sediment and NO3-N in the watershed and rivers was simulated using a generic advection-dispersion equation (ADE) with NO3-N and sediment as the main species. Results showed that non-structural WMPs, such as crop rotation and cover crops, presented the highest reductions of simulated NO3-N and sediment load, respectively, while structural WMPs had higher area-efficiency performance. On the other hand, climate conditions had a strong impact on the transport of both pollutants due to water fluxes alterations especially for a future dry climate scenario. Sediment transport was shown to be more sensitive to climate given that rainfall is one of the main drivers of the erosion processes. Outcomes from this research will give a more comprehensive approach toward understanding the impacts of environmental stressors at a watershed scale, and how they may be propagated to ecological systems.

The multi-metric assessment of model performance in a dominantly single-domain modeling approach (i.e., surface) may not be sufficient to gauge the validity of the model to represent the hydrologic system. Consequently, rating metrics can mathematically validate model results as satisfactory even when some of the simulated hydrologic processes are incorrectly represented during the calibration process. In this paper, we argue that to properly represent the hydrologic system, calibration tasks focused on modifying model parameters should account for equifinality, model inadequacy, and constraint inadequacy. To demonstrate our argument, we conducted a traditional calibration using the Soil and Water Assessment Tool (SWAT) coupled to the Modular Finite-difference Flow Model (MODFLOW) to simulate the hydrologic processes in the Fort Cobb Reservoir Experimental Watershed (FCREW) in central western Oklahoma. The results indicated that model calibration based on metrics from a single domain, in this case using SWAT, did not necessarily guarantee an appropriate representation of water circulation. Moreover, unsupervised calibration techniques based on the objective-function optimization (e.g., inverse calibration using SWAT-CUP SUFI2 algorithm) may not be sufficient if model constraints in multiple domains are not properly set, resulting in distorted parameters. This practice can result in the misrepresentation of water circulation and can have adverse impacts on environmental model results used to support policies and decisions.

The use of Nitrogen (N) fertilizer boosted crop production to accommodate 7 billion people on Earth in the 20th century but with the consequence of exacerbating N losses from agricultural landscapes. Land management practices that can prevent high N load are constantly being sought for mitigation and conservation purposes. This study was aimed at evaluating the impacts of different land management practices under projected climate scenarios on surface runoff linked N load at the field scale level. A framework to analyze changes in N load at a high spatiotemporal resolution under high greenhouse emission climate projections was developed using the Pesticide Root Zone Model (PRZM) for the Willow Creek Watershed in the Fort Cobb Experimental Watershed in Oklahoma. Specifically, 12 combinations of land management and climate scenarios were evaluated based on their N load via surface runoff from 2020 to 2070. Results showed that crop rotation practices lowered both the N load and the probability of high N load events. Spring application reduced the negative effects in summer and fall from other land management practices but at the risk of increased probability of generating high N load in April and May. The fertilizer application rate was found to be the most critical factor that affected the amount and the probability of high N load events. By adopting a target application management approach, the monthly maximum N can be decreased by 13% while the annual mean N load by 6%. The model framework and analysis method developed in this research can be used to analyze tradeoffs between environmental welfare and economic benefits of N fertilizer at the field scale level.

There is a need in water sciences for computational tools to integrate large spatially distributed datasets to provide insight into the spatial and temporal domains of the data while allowing visualization, analysis in the spatial and temporal dimensions, data metrics, and pattern recognition in the same application. Spatial and temporal variability of hydrological processes as well as the associated phenomena transport is better represented in high spatio-temporal resolution datasets. A conceptual data model and analysis tool, SPELLmap, was developed at the USDA Agricultural Research Service, Grazinglands Research Laboratory using the Delphi programming language to rapidly process, manipulate, analyze, and visualize large geo-located datasets. SPELLmap integrates the spatial and temporal domains of hydrological data to perform analyses in space and time while providing data metrics. SPELLmap has the capacity to represent three or four dimensional problems using a layer data structure. Three examples to illustrate SPELLmap functionalities were provided for the raster and raster-to-network domains. SPELLmap can be used for data interpolation, visualization, gridding, pattern recognition, and data metrics in integrated environmental modeling problems.

Summary Changes in land use are likely to cause a non-linear response in watershed hydrology. Specifically, small increases in urban expansion may greatly increase surface runoff while decreasing infiltration, impacting aquifer recharge and changing streamflow regimes. Quantifying the effects of urbanization on streamflow is crucial to the development of plans to mitigate the effects of anthropogenic changes on watershed processes. This study focused on quantifying the potential effects of varying degrees of urban expansion on the frequency of discharge, velocity, and water depth using the physically-based watershed model, MIKE-SHE, and the 1D hydrodynamic river model, MIKE-11. Five land cover scenarios corresponding to varying degrees of urban expansion were used to determine the sensitivity of these flow variables in the Big River watershed located in east central Missouri, in which urban areas have increased by more than 300% in the last 15 years (1992–2006). Differences in the frequency distributions of the flow variables under each scenario were quantified using a Smirnov test. Results indicated a potential increase in the frequency of high flow events to more than 140% while decreasing the frequency of low flow events by up to 100% if the current rate of urbanization continues. In general, the frequency of low flow events decreased as urban expansion increased while the frequency of average and high-flow events increased as urbanization increased. An increase in frequency of high-flow events is expected to impact the safety of structures, sediment load, water quality, and the riparian ecosystem. This research will be valuable to assess mitigation strategies in order to protect the ecosystem, infrastructure, and livelihood in the watershed where urban development is inevitable.

The complexity of the hydrologic system challenges the development of models under changing scenarios (e.g. climate, land use, or management). Finding the most accurate model parameters becomes a time-consuming task. Practitioners select the best model either by trial and error or by optimization algorithms to determine the set of parameters with the highest metric for a given scenario. However, these parameters are expected to change when the scenario changes especially under future projections. Several parameter combinations that acceptably represent the system, i.e. equifinality, may exist but were not included during the calibration process. This fact questions the current model parametrization strategies and leads to the development of a new methodology to overcome this difficulty. In this study, a probabilistic approach using global uncertainty and sensitivity analysis was used to develop a hydrologic model. The Agricultural Policy/Environmental eXtender (APEX) model was developed for the FortCobb watershed in Oklahoma. Probabilistic inputs (e.g. parameters, rainfall, land management) were used to derive the spectrum of responses of the model. Acceptable simulations were then used to establishing the most probable values of the desired model outputs (e.g., WYLD, N load, and Crop Yield) at a given time in the study area. This methodology also evaluates the uncertainty of model parameterization and calibration by considering the multiple functional hypothesis of system behavior. This process facilitates the comprehension of the watershed response and the simulation of different land management practices scenarios.

Assessing conditional risk of impacts of climate change on water quantity and quality under climate scenarios in agricultural dominated watersheds requires a better understanding of temporal changes in the patterns of rainfall events. Occurrence of severe contaminant transport and soil erosion in Oklahoma watersheds are linked to the occurrence of high intensity, short duration rainfall events within mesoscale storms. Analog and digital rainfall datasets, collected by USDA-ARS Grazinglands Research Laboratory in the Little Washita River Experimental Watershed (LWREW) since 1960, were used in this study to characterize the temporal pattern dynamics of rainfall events at 20 sites in the LWREW. The analog rainfall data were transformed to 5-minute discrete data, and then appended to the USDA-ARS Micronet and Mesonet digital data collected for the period 1995-2013 (digital era). Rainfall events temporally disconnected by five or more minutes of non-rainfall observations were statistically characterized and clustered per season to the LWREW level (average). Preliminary results showed important shifts in rainfall patterns starting in the spring and summer seasons of 1995 and 1996, while for the fall and winter seasons changes occurred gradually along the 50-year period starting in 1960. Also, increase in variance was observed between the 1960-1994 and 1995-2013 rainfall periods for event duration and averaged amount of rainfall per event. Climate change is expected to impact the spatio-temporal rainfall characteristics at local scales in which shift in rainfall patterns and changes in variance was hypothesized to be linked to increasing seasonal temperature trends in Oklahoma.