Effects of Groundwater‐Surface Water Exchange Mechanism in the National Water Model over the Northern High Plains Aquifer, USA

Abstract

Surface water and groundwater are intimately connected by a two‐way flux between the stream and underlying aquifers. The National Water Model (NWM) currently only considers a one‐way flux, where groundwater can enter a stream but cannot return to the aquifer. The Northern High Plains Aquifer, USA is used as a case study to investigate the consequences of omitting two‐way stream–aquifer fluxes on streamflow prediction capabilities of the NWM during hydrologic extremes. Instead of traditional field techniques to identify stream–aquifer fluxes, this study presents an integrated approach to classify likely stream regimes using three identification methods: United States Geological Survey (USGS) gage data, simulated stream–aquifer fluxes from an existing USGS Groundwater Availability Model, and the normalized difference vegetation index from remote sensing. For flood events, the modeled flood response for losing streams is characterized by statistically significant earlier peak discharges and an overestimate of the observed flood volume when compared to gaining streams. For drought events, our study found no statistical difference between losing and gaining streams, however, modeled streamflow from the NWM overestimated the observed USGS hydrograph. The systematic overestimate of streamflow by the NWM could be, in part, due to the lack of a losing stream mechanism which was on average 0.1% streamflow loss per streamwise km along the river.

Featured Collection Introduction: National Water Model III

“…Jachens et al (2021) expanded on the work of Hansen et al (2019) by evaluating NWM predictions in the Northern High Plains Aquifer. This system is well‐studied (e.g., Peterson et al 2016; McGuire 2017) and is regionally important for both agricultural irrigation and human water supply.…”

“…This system is well‐studied (e.g., Peterson et al 2016; McGuire 2017) and is regionally important for both agricultural irrigation and human water supply. Moreover, streams in the region are known to be both losing (streamflow recharges groundwater) and gaining (groundwater discharges to the surface), with some reaches varying by season (Jachens et al 2021, figures 4 and 5). Jachens et al (2021) used a unique multi‐approach method for classifying stream reaches as losing or gaining.…”

“…Moreover, streams in the region are known to be both losing (streamflow recharges groundwater) and gaining (groundwater discharges to the surface), with some reaches varying by season (Jachens et al 2021, figures 4 and 5). Jachens et al (2021) used a unique multi‐approach method for classifying stream reaches as losing or gaining. NWM results were then compared with observations for 42 floods and 116 low‐flow periods.…”

“…Combined, the work by Hansen et al (2019), Jachens et al (2021), and Karki et al (2021) identified causes for specific deficiencies in NWM predictions and offered potential alternative approaches to existing groundwater algorithms. Moreover, this work clearly demonstrates the contributions of the SI to the water prediction enterprise in the U.S.…”

Estimating High-Resolution Groundwater Storage from GRACE: A Random Forest Approach

“…Agriculture in the NHPA is highly dependent on groundwater pumping, which plays a vital role in groundwater storage declining, both spatially and temporally. Additionally, periods of rainfall availability are out of phase with periods of water demand, which accelerates declination in the groundwater level [42]. Spatiotemporal variability in the groundwater table needs to be investigated to develop a water distribution policy to meet demand.…”