Estimation of Base Flow by Optimal Hydrograph Separation for the Conterminous United States and Implications for National-Extent Hydrologic Models

Abstract

Optimal hydrograph separation (OHS) uses a two-parameter recursive digital filter that applies specific conductance mass-balance constraints to estimate the base flow contribution to total streamflow at stream gages where discharge and specific conductance are measured. OHS was applied to U.S. Geological Survey (USGS) stream gages across the conterminous United States to examine the range/distribution of base flow inputs and the utility of this method to build a hydrologic model calibration dataset. OHS models with acceptable goodness-of-fit criteria were insensitive to drainage area, stream density, watershed slope, elevation, agricultural or perennial snow/ice land cover, average annual precipitation, runoff, or evapotranspiration, implying that OHS results are a viable calibration dataset applicable in diverse watersheds. OHS-estimated base flow contribution was compared to base flow-like model components from the USGS National Hydrologic Model Infrastructure run with the Precipitation-Runoff Modeling System (NHM-PRMS). The NHM-PRMS variable gwres_flow is most conceptually like a base flow component of streamflow but the gwres_flow contribution to total streamflow is generally smaller than the OHS-estimated base flow contribution. The NHM-PRMS variable slow_flow, added to gwres_flow, produced similar or greater estimates of base flow contributions to total streamflow than the OHS-estimated base flow contribution but was dependent on the total flow magnitude.

Improving AI System Awareness of Geoscience Knowledge: Symbiotic Integration of Physical Approaches and Deep Learning

“…From this perspective, it is worth giving priority to the model's inherent interpretability even if it allows for some decrease in accuracy. Moreover, by dissecting the parameterization pipeline in a calibrated model, one can further explore spatial patterns of the inferred parameters, which offer insights into catchment processes and performance of the hydrologic model (e.g., Beck et al, 2013; Foks et al, 2019; Santhi et al, 2008). In this sense, the regional hybrid model can also be viewed as a streamlined parameterization module for the original hydrologic model, which is highly efficient in cross‐region applications.…”

Optimizing the Management Strategies of a Multi-Purpose Multi-Reservoir System in Vietnam

“…Since the theoretical gradient of the approximated quadratic function can be efficiently derived, the algorithm avoids the need to calculate derivatives of objective function required by the conventional gradient-based approach [47,48]. This feature allows the algorithm to be more conveniently integrated with simulation models from different engineering problems [49][50][51][52], in which derivatives on decision variables might be hard and expensive to evaluate [53]. In this study, the BOBYQA algorithm was employed for solving a nonlinear optimization problem below:…”

A novel method for cold-region streamflow hydrograph separation using GRACE satellite observations

“…Streamflow includes baseflow (the longer-term delayed flow from natural water storage such as groundwater discharge from aquifers) and quick flow (or surface runoff, the short-term response to a rainfall event or snow melt). Separating streamflow observed at a gauging site into baseflow and surface runoff helps characterize watershed hydrogeology and understand the water dynamics such as rainfall-runoff relationships and climate change impact on groundwater discharge (van Dijk, 2010;Gao et al, 2015;Rudra et al, 2015;Foks et al, 2019). Information on baseflow and surface runoff is also critical when dealing with a wide range of water-related issues such as flow regulations, water quality, habitat, reservoir design and operation, and hydroelectric power generation (Boulton and Hancock, 2006;Santhi et al, 2008;U.S.…”

“…However, these approaches basically rely on determining the points where baseflow intersects the rising and falling limbs of the surface runoff response, which are essentially arbitrary (Szilagyi and Parlange, 1998). Various digital filtering techniques with large variations in complexities have also been used for hydrograph separation, but they still suffer from the lack of hydrological basis and the disadvantage of arbitrary choice of separation parameters (Chapman, 1999;Furey and Gupta, 2001;Eckhardt, 2005;Piggott et al, 2005;Foks et al, 2019;Shao et al, 2020). The results from these approaches often need to be carefully assessed before they are considered to be hydrologically valid.…”