Hi 👋, my name is Rich.
I’m broadly interested in advancing methods to measure, model, and manage the complex water and energy systems that sustain large human populations. My expertise is at the intersection of mathematical/statistical modeling, hydrogeology, geospatial programming, data science/engineering, climate change, and environmental policy.
I’ve built 3D computational fluid dynamics models to explain and predict patterns of groundwater flow and contaminant transport in heterogeneous, alluvial aquifer-aquitard complexes – thin layers of subsurface, freshwater-bearing sediment that support food supply and civilization, and which are in decline worldwide. I’ve also developed the first regional-scale models that predict the location and intensity of well failures due to drought and unsustainable water management, and which tend to disproportionately impact DACs/DVCs that depend on relatively shallow wells. Because the sustainable management of complex, heavily-used, and regulated systems of natural resources typically hinge on available information, I’ve also built online decision-support tools that leverage interactive data visualization and geospatial interfaces to tell stories and highlight tradeoffs. I’ve automated California municipal water quality reports and co-developed the nation’s largest publicly-accessible spatial database of water system spatial boundaries (now in use by the US EPA). I co-founded the Water Data Lab, a group within Convolve Collective and I also co-developed and teach R for Water Resources Data Science.
My work has appeared in Nature, the Los Angeles Times, NewScientist, and Newsweek.
Currently, I lead research and development initiatives in the energy sector. We build tools to help electric utilities adapt to climate change, assess wildfire risk, and make equitable electrification investments. When I have the time, I still enjoy contributing to literature and to open source projects. Long ago, I taught environmental science to 5th graders and led National Geographic expeditions for high school students.
This website is built with blogdown and Hugo, and deployed using Netlify.
Thanks for being here.
Selected Projects
r4wrds
R for water Resources Data Science.
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Domestic well failure prediction and cost estimates in critically overdrafted basins.
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