Where to Recharge in California’s Central Valley? fastpath Products from AEM Data
An introduction to the fastpath application and an introduction to the products shown here are given at the following website
https://gemcenter.stanford.edu/harnessing-power-geophysical-imaging-recharge-californias-groundwater with details in this publication HERE. Below is a summary of key results.
SUMMARY RECHARGE MAPS
We used the fastpath application to analyze the airborne electromagnetic data from the Central Valley. We combined the three metrics described below to obtain the three maps shown above displaying suitable and unsuitable sites for recharge. These maps are based on numerous choices and assumptions made in applying the fastpath application, so please review the publication HERE where these are discussed in detail. The maps were made for three different values (20%, 50%, 80%) for the Fraction Coarse Dominated (FCD) threshold which divides all cells into those through which water will flow (FCD>FCD threshold) and those through which water will not flow (FCD<FCD threshold). As expected, we see fewer suitable regions for recharge as the FCD-threshold increases, which reduces the number of cells classified as “flow” cells. These final summary recharge maps suggest that there are many suitable locations for recharge throughout the valley. We estimate recharge at these sites can access, in the vadose zone, the storage equivalent of 30 Lake Shastas.
SUMMARY OF ANALYSIS
For this first set of fastpath products, identifying suitable sites for recharge in California’s Central Valley, our starting point was the 20,000 kilometers of airborne electromagnetic data (AEM) acquired by the California Dept of Water Resources (DWR) in the Central Valley. We began with those data to obtain images of the sediments between the ground surface and the water table, and then used the fastpath application (described in detail here) to assess the suitability of sites for surface-spreading recharge. A suitable site, shown schematically below, has pathways of coarse-grained sand and gravel that efficiently move water spread on the ground surface down to the water table. Areas dominated by fine-grained clay block the movement of water.
The DWR AEM data map out the 3D variation in electrical resistivity. Electrical resistivity is related to the type of sediment with areas dominated by coarse-grained sediments (sand and gravel) having high levels of resistivity (red/orange on the color bar) and areas dominated by fine-grained sediment (clay) having low levels of resistivity (blue on the color bar). The colors in between indicate a mixture of these two end-members.
We transformed the data to obtain a 3D map showing the composition in terms of the fraction of coarse-grained-dominated sediments, as shown on the color bar to the right. Referring to this as Fraction Coarse Dominated – FCD – this ranges from 0 in areas that are 100% dominated by fine-grained sediments to 1 in areas that are 100% dominated by coarse-grained sediments.
We then used fastpath to calculate three metrics that allowed us to evaluate every location in the Central Valley where we had AEM data within 3km. (We interpolated between acquired data points).
METRIC 1
Average Fraction Coarse Dominated (FCD) between the surface and the water table.
Given the physics of the AEM measurement, we have a high level of confidence in these average FCD values.
Preferred for Recharge: high values of Average FCD, which indicate an abundance of coarse-grained materials through which water easily flows.
METRIC 2
Normalized Pathlength between the surface and the water table. This is the pathlength divided by the depth to the water table.
How We Calculate This: We select a Flow Threshold in terms of an FCD value; classifying areas with FCD greater than that threshold to be Flow Units and areas with FCD less than that threshold to be No-Flow Units. We then use an algorithm that finds connected pathways through Flow Units from the surface to the water table.
As the threshold increases, the number of Flow Units decreases, resulting in longer pathways.
Preferred for Recharge: low values of Normalized Pathlength, where a value of 1 means a direct path from the surface to the water table.
METRIC 3
Depth to the Shallowest No-Flow Unit or the Water Table.
How We Calculate This: Using the flow thresholds from above we determined the depth to whichever is shallowest- the first No-Flow unit or the water table.
Preferred for Recharge: greater depth so as to avoid ponding at the surface.
All Metric Maps can also be viewed using the GIS Viewer HERE
Acknowledgments
This work was funded by the Gordon and Betty Moore Foundation (grant no. GBMF6189), and the United States Department of Agriculture NIFA (grant no. 2021-68012-35914); with the development of the fastpath application funded by the Accelerator in the Stanford Doerr School of Sustainability.