Modeling the impact of measured and projected climate and management systems on agricultural fields: Surface runoff, soil moisture, and soil erosion.

As global climate change poses a challenge to crop production, it is imperative to prioritize effective adaptation of agricultural systems based on a scientific understanding of likely impacts. In this study, we applied an integrated watershed modeling framework to examine the impacts of projected climate on runoff, soil moisture, and soil erosion under different management systems in Central Oklahoma. The proposed model uses measured climate data and three downscaled ensembles from the Coupled Model Intercomparison Project Phase 6 (CMIP6) at the water resources and erosion watershed to understand the impact of climate change and various climate conditions under three management systems: (1) continuous winter wheat (Triticum aestivum) under conventional tillage (WW-CT; baseline system), (2) continuous winter wheat under no-till (WW-NT), and (3) cool and warm season forage cover crop mixes under no-till (CC-NT). The study indicates that the occurrence of agricultural drought is projected to increase while erosion rates will remain unchanged under the WW-CT. In contrast, climate simulations imposed on the WW-NT and CC-NT systems significantly reduce runoff and sediment while preserving soil moisture levels. Especially, implementing the CC-NT system can bolster food security and foster sustainable farming practices in Central Oklahoma in the face of a changing climate.

Agricultural conservation may not help Midwestern US freshwater biodiversity in a changing climate.

Global climate change and agricultural disturbance often drive freshwater biodiversity changes at the regional level, particularly in the Midwestern US. Agricultural conservation practices have been implemented to reduce sediment and nutrient loading (e.g., crop rotation, cover crops, reduced tillage, and modified fertilizer application) for long-term economic sustainability and environmental resilience. However, the effectiveness of these efforts on freshwater biodiversity is not conclusive. In this study, we used the Kaskaskia River Watershed, Illinois as an example to evaluate how agricultural conservation practices affects both taxonomic and functional diversity under climate changes. The measures of trait-based functional diversity provide mechanistic explanations of biological changes. In specific, we model and predict 1) species richness (SR), 2) functional dispersion (FDis), and 3) functional evenness (FEve). FDis and FEve were based on ecology (life history, habitat preference, and trophic level) and physiology (thermal preference, swimming preference, etc.). The best random-forest regression models showed that flow, temperature, nitrate, and the watershed area were among the top predictors of the three biodiversity measures. We then used the models to predict the changes of SR and FDis under RCP8.5 climate change scenarios. SR and FDis were predicted to decrease in most sites, up to 20 % and 4 % by 2099, respectively. When agricultural conservation practices were considered together with climate changes, the decreasing trends of SR and FDis remained, suggesting climate change outweighed potential agriculture conservation efforts. Thus, climate-change effects on temperature and flow regimes need to be incorporated into the design of agricultural practices for freshwater biodiversity conservation.

A decision-making framework for evaluating environmental tradeoffs in enhancing ecosystem services across complex agricultural landscapes.

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.

A comprehensive modeling framework to evaluate soil erosion by water and tillage.

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.

Assessing the potential of riparian reforestation to facilitate watershed climate adaptation.

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.

Field scale nitrogen load in surface runoff: Impacts of management practices and changing climate.

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.

Riparian erosion vulnerability model based on environmental features.

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.