12 May 2021

The Demonstration and Validation of a Linked Watershed-Riverine Modeling System for DoD Installations: User Guidance Report Version 2.0

Abstract: A linked watershed model was evaluated on three watersheds within the U.S.: (1) House Creek Watershed, Fort Hood, TX; (2) Calleguas Creek Watershed, Ventura County, CA; and (3) Patuxent River Watershed, MD. The goal of this demonstration study was to show the utility of such a model in addressing water quality issues facing DoD installations across a variety of climate zones. In performing the demonstration study, evaluations of model output with regards to accuracy, predictability and meeting regulatory drivers were completed. Data availability, level of modeling expertise, and costs for model setup, validation, scenario analysis, and maintenance were evaluated in order to inform installation managers on the time and cost investment needed to use a linked watershed modeling system. Final conclusions were that the system evaluated in this study would be useful for answering a variety of questions posed by installation managers and could be useful in developing management scenarios to better control pollutant runoff from installations.

14 Oct 2020

The Demonstration and Validation of a Linked Watershed-Riverine Modeling System for DoD Installations – Patuxent Watershed, Maryland

Abstract: This work evaluated a linked watershed and riverine modeling system for the Patuxent River Watershed, Maryland against observed field data and model output from a watershed model. The performance objectives were computed for streamflow, sediment, total phosphorus, orthophosphorus, total nitrogen, ammonium, and nitrate using daily and monthly average model predictions and measured data. Hydrological Simulation Program – Fortran (HSPF) was used to compute runoff, sediment, and nutrient loadings, whereas the Hydrologic Engineer Center – River Analysis Sys-tem (HEC-RAS) was used to evaluate in-stream flow, channel sedimentation, and the fate/transport of nutrients. Model results were successful for calibration, validation, and management scenario analysis. Contaminants were not simulated for this watershed due to a lack of observed data to compare against. The study identified two implementation issues. First, while the Patuxent River did not experience dry bed conditions, where a stream may be intermittent, one can incorporate a very narrow slot at the low point in the cross-section to numerically keep the channel wet during very low flows. Second, to set up the linked model, there needs to be more observed water quality data to better constrain the HSPF output being used as boundary conditions to the HEC-RAS model.

22 Apr 2020

PUBLICATION NOTICE: Nested Physics-Based Watershed Modeling at Seven Mile Creek: Minnesota River Integrated Watershed Study

ABSTRACT: The Minnesota River Basin (MRB) Integrated Study Team (IST) was tasked with assessing the condition of the MRB and recommending management options to reduce suspended sediments and improve the water quality in the basin. The Gridded Surface Subsurface Hydrologic Analysis (GSSHA) was chosen by the IST as the fine scale model for the Seven Mile Creek Watershed to help quantify the physical effects from best management practices within the MRB. The predominately agricultural Seven Mile Creek Watershed produces high total suspended solids and nutrients loads, contributing roughly 10% of the total load to the Minnesota River. GSSHA models were developed for a small experimental field research site called Red Top Farms, a Hydrologic Unit Code (HUC)-12 model for the entire Seven Mile Creek Watershed, a sub-basin of the Seven Mile Creek Watershed. After calibration, the resulting models were able to simulate measured tile drain flows, stream flow, suspended sediments, and to a lesser extent, nutrients. A selected suite of alternative land-use scenarios was simulated with the models to determine the watershed response to land-use changes at the small and medium scale and to test whether the type, size, and spatial distribution of land uses will influence the effectiveness of land management options.