Chuckwalla Valley multiple-well monitoring site, Chuckwalla Valley, Riverside County

Everett, Rhett R.

doi:10.3133/ofr20131221

Cited by 1 publication

(2 citation statements)

References 8 publications

(8 reference statements)

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“…Soil moisture data have been collected at depths of 5, 10, 20, and 50 cm below ground surface (bgs) at the SCAN stations since late 2011. A monitoring well, CWV1, was completed in 2012 to 300 m bgs, near the groundwater outflow of the basin, to collect groundwater and geophysical data in separate aquifer intervals, including natural gamma, electric resistivity, and sonic logs (Everett, 2013).…”

Section: In Situ Measurementsmentioning

confidence: 99%

“…The Process-based Adaptive Watershed Simulator coupled to the Community Land Model (PAWS+CLM) is a comprehensive and computationally efficient model representing the whole-land phase of the hydrologic cycle (Ji and Shen, 2018;Niu et al, 2017, 2013Shen and Phanikumar, 2010) and reactive transport (Niu and Phanikumar, 2015) on a rectangular grid (Figure 4a). CLM4.0 is a comprehensive community-shared land surface process model describing water, carbon, nitrogen, energy, and other cycles (Oleson et al, 2010).…”

Section: Paws+clmmentioning

confidence: 99%

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Combining a land surface model with groundwater model calibration to assess the impacts of groundwater pumping in a mountainous desert basin

Fang

Ludwig

et al. 2019

Advances in Water Resources

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The quantification of recharge and trans-valley underflow is needed in arid regions to estimate the impacts of new water withdrawals on the water table. However, for mountainous desert areas, such estimates are highly challenging, due to data scarcity, heterogeneous soils, and long residence times. Conventional assessment employs isolated groundwater models configured with simplified uniform estimates of recharge. Here, we employed a data-constrained surface-subsurface process model to provide an ensemble of spatially distributed recharge and underflow estimates using perturbed parameters. Then, the Model-Independent Parameter Estimation and Uncertainty Quantification (PEST) package was used to calibrate MODFLOW aquifer hydraulic conductivity for this ensemble and reject implausible recharge values. This novel dual-model approach, broadly applicable to mountainous arid regions, was designed to maximally exploit available data sources. It can assimilate groundwater head observations, reject unrealistic parameters, and narrow the range of estimated drawdowns due to pumping. We applied this approach to the Chuckwalla basin in California, USA to determine natural recharge. Simulated recharge concentrates along alluvial fans at the mountain fronts and ephemeral washes where runoff water infiltrates. If an evenly distributed recharge was employed as in conventional studies, it would result in regional biases in estimated drawdown and larger uncertainty bounds. We also note that the speed of groundwater recovery does not guarantee sustainability: heavy pumping induces large hydraulic gradients that initially recover quickly when pumping is halted, but the system may not ultimately recover to pre-pumping levels.

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Section: In Situ Measurementsmentioning

confidence: 99%