Search

Societal risks from flooding are evident at a range of spatial scales and climate change will exacerbate these risks in the future. Assessing flood risks across broad geographical regions is a challenge, and often done using streamflow time-series records or hydrologic models. In this study, we used a national-scale hydrological model to identify, assess, and map 16 different streamflow metrics that could be used to describe flood risks across 34,987 HUC12 subwatersheds within the Mississippi-Atchafalaya River Basin (MARB). A clear spatial difference was observed among two different classes of metrics. Watersheds in the eastern half of the MARB exhibited higher overall flows as characterized by the mean, median, and maximum daily values, whereas western MARB watersheds were associated with flood indicative of high extreme flows such as skewness, standardized streamflow index and top days. Total agricultural and building losses within HUC12 watersheds were related to flood metrics and those focused on higher overall flows were more correlated to expected annual losses (EAL) than extreme value metrics. Results from this study are useful for identifying continental scale patterns of flood risks within the MARB and should be considered a launching point from which to improve the connections between watershed scale risks and the potential use of natural infrastructure practices to reduce these risks. [ABSTRACT FROM AUTHOR]

We present a new calibration strategy guide for coupled surface–subsurface hydrologic models. The goal is to reduce bias in environmental modeling and make calibration processes more consistent. The strategy guide enhances model efficiency and accuracy by focusing on changes to channel, soil, landscape, and aquifer properties. This approach is particularly beneficial when simulating important hydrologic features like baseflow and peaks and across different watersheds. Developed using the Soil and Water Assessment Tool (SWAT+) and the new gwflow module in six diverse US watersheds, each with unique hydrologic characteristics, the guide encourages improved calibration through routine use. It addresses specific issues related to the temporal distribution of streamflow and offers a robust method for enhancing model performance across a wide range of hydrologic conditions. By employing parameter estimation and sensitivity analysis, the approach ensures rigorous and objective calibration of SWAT+ and other models that include land, soil, aquifer, and water processes, leading to more accurate hydrologic modeling. [ABSTRACT FROM AUTHOR]

Floodplains are essential ecosystems that provide a variety of economic, hydrologic, and ecologic services. Within floodplains, surface water‐groundwater exchange plays an important role in facilitating biogeochemical processes and can have a strong influence on stream hydrology through infiltration or discharge of water. These functions can be difficult to assess due to the heterogeneity of floodplains and monitoring constraints, so numerical models are useful tools to estimate fluxes, especially at large spatial extents. In this study, we use the SWAT+ (Soil and Water Assessment Tool) ecohydrological model to quantify magnitudes and spatiotemporal patterns of floodplain surface water‐groundwater exchange in a mountainous watershed using an updated version of the gwflow module that directly calculates floodplain‐aquifer exchange rates during periods of floodplain inundation. The gwflow module is a spatially distributed groundwater modelling subroutine within the SWAT+ code that uses a gridded network and physically based equations to predict groundwater storage, groundwater head, and groundwater fluxes. We used SWAT+ to model the 7516 km2 Colorado River headwaters watershed and streamflow data from USGS gages for calibration and testing. Models that included floodplain‐groundwater interactions outperformed those without such interactions and provided valuable information about floodplain exchange rates and volumes. Our analyses on the location of floodplain fluxes in the watershed also show that wider areas of floodplains, "beads" (e.g., like beads on a necklace), exchanged a higher net and per area volume of water, as well as higher rates of exchange, compared to narrower areas, "strings." Study results show that floodplain channel‐groundwater exchange is a valuable process to include in hydrologic models, and model outputs could inform land conservation practises by indicating priority locations, such as beads, where substantial hydrologic exchange occurs. [ABSTRACT FROM AUTHOR]

Parameter sensitivity analysis plays a critical role in efficiently determining main parameters, enhancing the effectiveness of the estimation of parameters and uncertainty quantification in hydrologic modeling. In this paper, we demonstrate an uncertainty and sensitivity analysis technique for the holistic Soil and Water Assessment Tool (SWAT +) model coupled with new gwflow module, spatially distributed, physically based groundwater flow modeling. The main calculated groundwater inflows and outflows include boundary exchange, pumping, saturation excess flow, groundwater–surface water exchange, recharge, groundwater–lake exchange and tile drainage outflow. We present the method for four watersheds located in different areas of the United States for 16 years (2000–2015), emphasizing regions of extensive tile drainage (Winnebago River, Minnesota, Iowa), intensive surface–groundwater interactions (Nanticoke River, Delaware, Maryland), groundwater pumping for irrigation (Cache River, Missouri, Arkansas) and mountain snowmelt (Arkansas Headwaters, Colorado). The main parameters of the coupled SWAT + gwflow model are estimated utilizing the parameter estimation software PEST. The monthly streamflow of holistic SWAT + gwflow is evaluated based on the Nash–Sutcliffe efficiency index (NSE), percentage bias (PBIAS), determination coefficient (R2) and Kling–Gupta efficiency coefficient (KGE), whereas groundwater head is evaluated using mean absolute error (MAE). The Morris method is employed to identify the key parameters influencing hydrological fluxes. Furthermore, the iterative ensemble smoother (iES) is utilized as a technique for uncertainty quantification (UQ) and parameter estimation (PE) and to decrease the computational cost owing to the large number of parameters. Depending on the watershed, key identified selected parameters include aquifer specific yield, aquifer hydraulic conductivity, recharge delay, streambed thickness, streambed hydraulic conductivity, area of groundwater inflow to tile, depth of tiles below ground surface, hydraulic conductivity of the drain perimeter, river depth (for groundwater flow processes), runoff curve number (for surface runoff processes), plant uptake compensation factor, soil evaporation compensation factor (for potential and actual evapotranspiration processes), soil available water capacity and percolation coefficient (for soil water processes). The presence of gwflow parameters permits the recognition of all key parameters in the surface and/or subsurface flow processes, with results substantially differing if the base SWAT + models are utilized. [ABSTRACT FROM AUTHOR]

Tile drainage is a common practice to increase agricultural productivity in regions with high water tables. Ecohydrological models, such as the Soil and Water Assessment Tool (SWAT), are key tools used to simulate these subsurface drainage structures and their corresponding management effects on water balance. This study is an investigation of the application of two different SWAT tile-drain calculation methods (empirically and physically-based) in simulating the streamflow of the Des Moines River Basin (DMRB), central Iowa, USA. The model was calibrated for the DMRB outlet and validated across 24 monitoring stations. We found that both empirical function and physically-based methods have satisfactory model performance for monthly and daily calibration (NSE > 0.5; KGE > 0.6; Pbias < ±25%). The daily validation process showed that the physically-based method had more accurate spatial variability in representing the hydrological processes and a better representation of the annual tile-drain flow. The findings in this study reinforce the importance of spatial validation in assessing model performance and ensuring its suitability for practical applications. [ABSTRACT FROM AUTHOR]

Subsurface (or tile) drainage improves land productivity by enhancing soil aeration and preventing water-logged conditions. However, the continuous expansion of drained agricultural lands and reliance on synthetic fertilizer in the Midwestern United States have increasingly facilitated nitrate transport from agricultural fields to surface water bodies. Hence, there is a need to implement various agricultural best management practices (BMPs) in order to reduce the adverse water quality impacts resulting from excess nitrate, such as eutrophication and the formation of hypoxic zones. In this study, we used a SWAT+ model to assess the overall impacts on the riverine nitrate load and crop yield in the corn–soybean cropping system based on a combination of different management practices. The corn and soybean yields simulated with the model were found to be in good agreement with the observed yields for both the calibration and validation periods. The long-term simulation over a period of 30 years showed a reduction in the nitrate load of up to 32% without impacting the crop yield. The model results suggest that by reducing the current N application rate by 20% and using a 40:60 split between spring pre-plant and side-dressing N applications combined with cereal rye as a cover crop in corn–soybean rotation, one can potentially reduce nitrate losses without impacting crop yields. This study will help researchers, stakeholders, and farmers to explore and adopt alternative management practices beneficial for offsetting the environmental impacts of agricultural productions on the watershed scale. [ABSTRACT FROM AUTHOR]