To help reduce future N loads entering the Gulf of Mexico from the Mississippi River 45%, Iowa set the goal of reducing non-point source N loads 41%. Studies show that implementing winter rye cover crops into agricultural systems reduces N loads from subsurface drainage, but its effectiveness in the Mississippi River Basin under expected climate change is uncertain. We used the field-tested Root Zone Water Quality Model (RZWQM) to estimate drainage N loads, crop yield, and rye growth in central Iowa corn-soybean rotations. RZWQM scenarios included baseline (BL) observed weather (1991–2011) and ambient CO₂ with cover crop and no cover crop treatments (BL_CC and BL_NCC). Scenarios also included projected future temperature and precipitation change (2065–2085) from six general circulation models (GCMs) and elevated CO₂ with cover crop and no cover crop treatments (CC and NCC). Average annual drainage N loads under NCC, BL_NCC, CC and BL_CC were 63.6, 47.5, 17.0, and 18.9 kg N ha⁻¹. Winter rye cover crop was more effective at reducing drainage N losses under climate change than under baseline conditions (73 and 60% for future and baseline climate), mostly because the projected temperatures and atmospheric CO₂ resulted in greater rye growth and crop N uptake. Annual CC drainage N loads were reduced compared with BL_NCC more than the targeted 41% for 18 to 20 years of the 21-year simulation, depending on the GCM. Under projected climate change, average annual simulated crop yield differences between scenarios with and without winter rye were approximately 0.1 Mg ha⁻¹. These results suggest that implementing winter rye cover crop in a corn-soybean rotation effectively addresses the goal of drainage N load reduction under climate change in a northern Mississippi River Basin agricultural system without affecting cash crop production.

The Southern Plains (SP) is one of 18 Long‐Term Agroecosystem Research network sites that combine strategic research projects with common measurements across multiple agroecosystems. Projects at the SP site focus on the use of indicator measurements to aid in assessment of land and nutrient management's impact on soil health, water quality, carbon and water balances, and forage biomass‐quality in diversified, adaptive crop‐livestock systems designed to overcome shifts in natural resources and climate. The prevailing treatment is tilled winter wheat (Triticum aestivum L.) that is grazed, hayed, harvested for grain, or grazed and harvested for grain. The alternative treatment is year‐round annual cover crop forage mixes for cattle (Bos taurus) production planted in fall and spring under conservation tillage management. The area is subject to variable weather and climatic shifts that reduce the potential to diversify forage crops and limit grazing in southern tall grass prairies and small grain systems. Incorporation of fertilized, rain‐fed, annual cool and warm season mixtures of cover crops could fill forage gaps. The presence of year‐round ground cover reduces sediment and nutrient loading to surface waters while enhancing soil health and water holding capacity. Tools to aid agricultural producers and land and water resource managers have been developed and implemented to determine how climate, topography, and varying conservation management practices alter hydrological structures, greenhouse gas emissions, water usage, and soil resources.

Decades-long erosion monitoring in runoff plots or small watersheds is costly and labor intensive. A cost-effective alternative erosion estimate using fallout caesium-137 (137Cs) has been explored since the 1970s. This 137Cs technique has been widely used to estimate the net (loss and gain) soil redistribution for the period from 1954 to the sampling year with a one-time field visit. However, the 137Cs technique has shortcomings in its central assumption of no 137Cs loss or redistribution during transfer from rainwater to soil. To improve the technique, we elucidate the 137Cs transfer and redistribution processes by quantifying 137Cs uptake in suspended sediment and 137Cs interception by plants during fallout. An improved 137Cs mass balance model was developed and optimized using legacy soil loss data from runoff plots along with 137Cs inventories measured during the fallout period of 1954-1976. Predicted soil loss proved highly sensitive to 137Cs redistribution in runoff and interception by plants during transfer. The two processes can be effectively simulated by two key parameters: 137Cs uptake by sediment (ψ) and 137Cs interception by plants. The optimized ψ value was negatively related to soil loss rates. When ψ is > 1, it simulates 137Cs redistribution in runoff. When ψ is < 1, it rectifies the uniform erosion assumption by accounting for rill incision from concentrated flows and can be estimated as the proportion of interrill erosion (i.e., 1 minus the rill erosion proportion). More experiments are needed to quantify ψ under different rainfall and topographic conditions to improve parameter estimation and therefore erosion prediction. It is worth noting that the processes and estimates found in this study are broadly applicable to other radionuclides commonly used for erosion prediction.

Soil moisture is a fundamental variable controlling hydrologic partitioning, land–atmosphere exchange, and biogeochemical cycling. Although widely characterized through observations, remote sensing, and data-driven approaches, the representation of soil water fluxes and subsurface processes in predictive models remains less systematically synthesized. Here, we present a structured review of widely used predictive models, focusing on their process formulations, spatial discretization, and treatment of soil water fluxes across scales. The synthesis reveals consistent trade-offs among physical realism, scalability, data intensity, and computational efficiency. Conceptual models based on tipping-bucket approaches simplify soil water movement as threshold-driven storage processes and underrepresent transient redistribution and deep soil moisture dynamics. Storage-routing models introduce flux-based redistribution but rely on empirical parameterization that dampen transient flux dynamics. Physically based models resolve hydraulic gradients and provide the highest process fidelity but require extensive data and computational resources. Across scales, the absence or simplification of preferential flow and lateral subsurface flow constitutes the dominant structural limitation, producing systematic smoothing of soil moisture variability. The review provides a comparative basis for model selection and highlights critical directions for improving the representation of subsurface hydrologic dynamics in predictive frameworks.