Accelerating warming, changes in the amount, timing, and form of precipitation, and rapidly growing populations highlight the need for improved predictions of snowmelt‐driven water supplies. Although decadal‐scale trends in reduced streamflow are common, minimal progress has been made in improving streamflow prediction on the annual time scales on which management decisions are made. Efficient allocation of dwindling supplies requires incorporating rapidly evolving knowledge of streamflow generation into parsimonious models capable of improving prediction on seasonal, annual, and multiyear time scales of water resource management. We address this need using long‐term streamflow and climate records in 12 catchments averaging 90 years of observations and totaling more than 1,080 site‐years of data. These catchments experience similar regional climate forcing each year, but are diverse enough to represent broad ranges in precipitation, temperature, vegetation, and geology characteristic of much of the western US. We find that January baseflow across all catchments exhibits a coherent, quasi‐decadal periodicity that presumably is indicative of groundwater response to decadal climate. Although the direct contribution of this discharge to streamflow is small, interannual variability in groundwater discharge is a consistently strong predictor of runoff efficiency suggesting that antecedent groundwater storage alters precipitation routing to streamflow. Incorporating antecedent groundwater storage with precipitation and melt dynamics in multiple linear regression models reduces uncertainty in annual runoff from approximately 40% to <5%. These simple models, using readily available data, provide immediately useful tools for water managers to anticipate and respond to streamflow variability on time scales of 1 to 10 years.
Large‐scale models often use a single grid to represent an entire catchment assuming homogeneity; the impacts of such an assumption on simulating evapotranspiration (ET) and streamflow remain poorly understood. Here, we compare hydrological dynamics at Shale Hills (PA, USA) using a complex model (spatially explicit, >500 grids) and a simple model (spatially implicit, two grids using “effective” parameters). We asked two questions:
- PAR ID:
- 10445065
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Water Resources Research
- Volume:
- 57
- Issue:
- 6
- ISSN:
- 0043-1397
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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