Testing alternative uses of electromagnetic data to reduce the prediction error of groundwater models

In spite of geophysics being used increasingly, it is often unclear how and when the integration of geophysical data and models can best improve the construction and predictive capability of groundwater models. This paper uses a newly developed HYdrogeophysical TEst-Bench (HYTEB) that is a collection of geological, groundwater and geophysical modeling and inversion software to demonstrate alternative uses of electromagnetic (EM) data for groundwater modeling in a hydrogeological environment consisting of various types of glacial deposits with typical hydraulic conductivities and electrical resistivities covering impermeable bedrock with low resistivity (clay). The synthetic 3-D reference system is designed so that there is a perfect relationship between hydraulic conductivity and electrical resistivity. For this system it is investigated to what extent groundwater model calibration and, often more importantly, model predictions can be improved by including in the calibration process electrical resistivity estimates obtained from TEM data. In all calibration cases, the hydraulic conductivity field is highly parameterized and the estimation is stabilized by (in most cases) geophysics-based regularization. For the studied system and inversion approaches it is found that resistivities estimated by sequential hydrogeophysical inversion (SHI) or joint hydrogeophysical inversion (JHI) should be used with caution as estimators of hydraulic conductivity or as regularization means for subsequent hydrological inversion. The limited groundwater model improvement obtained by using the geophysical data probably mainly arises from the way these data are used here: the alternative inversion approaches propagate geophysical estimation errors into the hydrologic model parameters. It was expected that JHI would compensate for this, but the hydrologic data were apparently insufficient to secure such compensation. With respect to reducing model prediction error, it depends on the type of prediction whether it has value to include geophysics in a joint or sequential hydrogeophysical model calibration. It is found that all calibrated models are good predictors of hydraulic head. When the stress situation is changed from that of the hydrologic calibration data, then all models make biased predictions of head change. All calibrated models turn out to be very poor predictors of the pumping well's recharge area and groundwater age. The reason for this is that distributed recharge is parameterized as depending on estimated hydraulic conductivity of the upper model layer, which tends to be underestimated. Another important insight from our analysis is thus that either recharge should be parameterized and estimated in a different way, or other types of data should be added to better constrain the recharge estimates.HyGEM, Integrating geophysics, geology, and hydrology [11-116763]; Danish Council for Strategic ResearchOpen access.This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Voxel inversion of airborne electromagnetic data for improved groundwater model construction and prediction accuracy

We present a workflow for efficient construction and calibration of large-scale groundwater models that includes the integration of airborne electromagnetic (AEM) data and hydrological data. In the first step, the AEM data are inverted to form a 3-D geophysical model. In the second step, the 3-D geophysical model is translated, using a spatially dependent petrophysical relationship, to form a 3-D hydraulic conductivity distribution. The geophysical models and the hydrological data are used to estimate spatially distributed petrophysical shape factors. The shape factors primarily work as translators between resistivity and hydraulic conductivity, but they can also compensate for structural defects in the geophysical model. The method is demonstrated for a synthetic case study with sharp transitions among various types of deposits. Besides demonstrating the methodology, we demonstrate the importance of using geophysical regularization constraints that conform well to the depositional environment. This is done by inverting the AEM data using either smoothness (smooth) constraints or minimum gradient support (sharp) constraints, where the use of sharp constraints conforms best to the environment. The dependency on AEM data quality is also tested by inverting the geophysical model using data corrupted with four different levels of background noise. Subsequently, the geophysical models are used to construct competing groundwater models for which the shape factors are calibrated. The performance of each groundwater model is tested with respect to four types of prediction that are beyond the calibration base: a pumping well's recharge area and groundwater age, respectively, are predicted by applying the same stress as for the hydrologic model calibration; and head and stream discharge are predicted for a different stress situation. As expected, in this case the predictive capability of a groundwater model is better when it is based on a sharp geophysical model instead of a smoothness constraint. This is true for predictions of recharge area, head change, and stream discharge, while we find no improvement for prediction of groundwater age. Furthermore, we show that the model prediction accuracy improves with AEM data quality for predictions of recharge area, head change, and stream discharge, while there appears to be no accuracy improvement for the prediction of groundwater age.HyGEM, integrating geophysics, geology, and hydrology [1115116763]; Danish Council for Strategic ResearchOpen Access JournalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Ubiquitous Fractal Scaling and Filtering Behavior of Hydrologic Fluxes and Storages from A Mountain Headwater Catchment

We used the weighted wavelet method to perform spectral analysis of observed long-term precipitation, streamflow, actual evapotranspiration, and soil water storage at a sub-humid mountain catchment near Tucson, Arizona, USA. Fractal scaling in precipitation and the daily change in soil water storage occurred up to a period of 14 days and corresponded to the typical duration of relatively wet and dry intervals. In contrast, fractal scaling could be observed up to a period of 0.5 years in streamflow and actual evapotranspiration. By considering long-term observations of hydrologic fluxes and storages, we show that, in contrast to previous findings, the phase relationships between water balance components changed with component period and were not perfectly in or out of phase at all periods. Self-averaging behavior was apparent, but the temporal scales over which this behavior was applicable differed among the various water balance components. Conservative tracer analysis showed that this catchment acted as a fractal filter by transforming white noise in the precipitation input signal to a 1/f flicker in the streamflow output signal by means of both spatial and temporal subsurface advection and dispersion processes and soil wetting properties. This study provides an improved understanding of hydrological filtering behavior in mountain critical zones that are critical sources of water and ecosystem services throughout the world.Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Vegetation source water identification using isotopic and hydrometric observations from a subhumid mountain catchment

This study coupled long‐term hydrometric and stable water isotope data to identify links between subsurface water storage and vegetation in a subhumid mountain catchment in Arizona, USA. Specific observations included catchment‐scale hydrologic fluxes and soil water storage and stable water isotopes from stream water, soil water, groundwater, and sap water from Arizona pine (Pinus arizonica) and Douglas fir (Pseudotsuga menziesii) individuals. Here, we find that tightly bound soil water was sufficient to meet dry period vegetation water demand when the former was defined in terms of field capacity as opposed to a matric tension threshold. This water was a mixture of summer and winter precipitation that predominates in both shallow and deep soil waters, and contributed significantly to streamflow. We also identified a less common mobile water type that did not contribute significantly to streamflow and was related to infiltration during isotopically depleted precipitation events. Although each water type was used by both Arizona pine and Douglas fir vegetation, the second water type was dominant in Douglas fir sap water. Therefore, we conclude that Arizona pine and Douglas fir can occupy different ecohydrological niches at this subhumid mountain location. Further, a lack of isotopic distinction between tightly bound and inferred mobile soil water signals that the ecohydrological water source separation hypothesis is not entirely applicable at this site. The results of this study broadly highlight how alternative definitions of tightly bound water can influence interpretation of data, and contribute to a more thorough understanding of interactions between subsurface storage and plant water dynamics.12 month embargo; published online: 30 October 2019This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]