Feasibility analysis of using inverse modeling for estimating natural groundwater recharge from a large-scale soil moisture monitoring network

Tiejun Wang, Trenton E. Franz, Weifeng Yue, J. Szilagyi, Vitaly A. Zlotnik, Jinsheng You, Xunhong Chen, Martha D. Shulski, Aaron Young

Research output: Contribution to journalArticle

22 Citations (Scopus)

Abstract

Despite the importance of groundwater recharge (GR), its accurate estimation still remains one of the most challenging tasks in the field of hydrology. In this study, with the help of inverse modeling, long-term (6years) soil moisture data at 34 sites from the Automated Weather Data Network (AWDN) were used to estimate the spatial distribution of GR across Nebraska, USA, where significant spatial variability exists in soil properties and precipitation (P). To ensure the generality of this study and its potential broad applications, data from public domains and literature were used to parameterize the standard Hydrus-1D model. Although observed soil moisture differed significantly across the AWDN sites mainly due to the variations in P and soil properties, the simulations were able to capture the dynamics of observed soil moisture under different climatic and soil conditions. The inferred mean annual GR from the calibrated models varied over three orders of magnitude across the study area. To assess the uncertainties of the approach, estimates of GR and actual evapotranspiration (ETa) from the calibrated models were compared to the GR and ETa obtained from other techniques in the study area (e.g., remote sensing, tracers, and regional water balance). Comparison clearly demonstrated the feasibility of inverse modeling and large-scale (>104km2) soil moisture monitoring networks for estimating GR. In addition, the model results were used to further examine the impacts of climate and soil on GR. The data showed that both P and soil properties had significant impacts on GR in the study area with coarser soils generating higher GR; however, different relationships between GR and P emerged at the AWDN sites, defined by local climatic and soil conditions. In general, positive correlations existed between annual GR and P for the sites with coarser-textured soils or under wetter climatic conditions. With the rapidly expanding soil moisture monitoring networks around the globe, this study may have important applications in aiding water resources management in different regions.

Original languageEnglish
Pages (from-to)250-265
Number of pages16
JournalJournal of Hydrology
Volume533
DOIs
Publication statusPublished - Feb 1 2016

Fingerprint

recharge
soil moisture
groundwater
modeling
soil property
weather
evapotranspiration
monitoring network
analysis
soil
water budget
hydrology
tracer
spatial distribution
remote sensing
climate

Keywords

  • Automated Weather Data Network
  • Groundwater recharge
  • Inverse modeling
  • Soil moisture
  • Vadose zone model

ASJC Scopus subject areas

  • Water Science and Technology

Cite this

Feasibility analysis of using inverse modeling for estimating natural groundwater recharge from a large-scale soil moisture monitoring network. / Wang, Tiejun; Franz, Trenton E.; Yue, Weifeng; Szilagyi, J.; Zlotnik, Vitaly A.; You, Jinsheng; Chen, Xunhong; Shulski, Martha D.; Young, Aaron.

In: Journal of Hydrology, Vol. 533, 01.02.2016, p. 250-265.

Research output: Contribution to journalArticle

Wang, Tiejun ; Franz, Trenton E. ; Yue, Weifeng ; Szilagyi, J. ; Zlotnik, Vitaly A. ; You, Jinsheng ; Chen, Xunhong ; Shulski, Martha D. ; Young, Aaron. / Feasibility analysis of using inverse modeling for estimating natural groundwater recharge from a large-scale soil moisture monitoring network. In: Journal of Hydrology. 2016 ; Vol. 533. pp. 250-265.
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AU - Zlotnik, Vitaly A.

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