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Abstract For evaluating the climatic and landscape controls on long‐term baseflow, baseflow index (BFI, defined as the ratio of baseflow to streamflow) and baseflow coefficient (BFC, defined as the ratio of baseflow to precipitation) are formulated as functions of climate aridity index, storage capacity index (defined as the ratio of average soil water storage capacity to precipitation), and a shape parameter for the spatial variability of storage capacity. The derivation is based on the two‐stage partitioning framework and a cumulative distribution function for storage capacity. Storage capacity has a larger impact on BFI than on BFC. When storage capacity index is smaller than 1, BFI is less sensitive to storage capacity index in arid regions compared to that in humid regions; whereas, when storage capacity index is larger than 1, BFI is less sensitive to storage capacity index in humid regions. The impact of storage capacity index on BFC is only significant in humid regions. The shape parameter plays an important role on fast flow generation at the first‐stage partitioning in humid regions and baseflow generation at the second‐stage partitioning in arid regions. The derived formulae were applied to more than 400 catchments where storage capacity index was found to follow a logarithmic function with climate aridity index. The role of climate forcings at finer timescales on baseflow were quantified, indicating that seasonality in climate forcings has a significant control especially on BFI.
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A Three‐Stage Partitioning Framework for Modeling Mean Annual Groundwater Evapotranspiration
Abstract An analytical model is developed for mean annual groundwater evapotranspiration (GWET) at the watershed scale based on a three‐stage precipitation partitioning framework. The ratio of mean annual GWET to precipitation, defined as GWET ratio, is modeled as a function of climate aridity index (CAI), storage capacity index, the shape parameter ‘a’ for the spatial distribution of storage capacity, and the shape parameter ‘b’ for the spatial distribution of available water for GWET. In humid regions, GWET ratio tends to increase with increasing CAI due to the limited energy supply and shallower depth to water table (DWT) for a given storage capacity index. In contrast, in arid regions, the GWET ratio tends to decrease as the CAI increases because of the limited water availability and the presence of a deeper DWT for a given storage capacity index. In arid regions, the GWET ratio decreases as the parameter ‘a’ increases, mainly because of increased ET from a thicker unsaturated zone in environments with a deeper DWT. GWET ratio increases as parameter ‘b’ increases due to more watershed area with larger available water for GWET. The storage capacity index and shape parameters are estimated for 31 study watersheds in Tampa Bay Florida area based on the simulated GWET from an integrated hydrologic model and for 21 watersheds from literature. A possible correlation has been identified between the two shape parameters in the Tampa Bay watersheds. The analytical model for mean annual GWET can be further tested in other watersheds if data are available.
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- Award ID(s):
- 2124849
- PAR ID:
- 10556383
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Water Resources Research
- Volume:
- 60
- Issue:
- 11
- ISSN:
- 0043-1397
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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