Regional Assessment of Drought Impacts on Soils (RADIS)
Soils are the foundation of terrestrial ecosystems. They provide critical services including supplying a substrate and the nutrients necessary for plant growth, retaining moisture from precipitation, filtering contaminants from percolating waters, and acting as a sink of carbon. Healthy soils are key to sustaining both human and ecosystem health. However, global- and regional-scale disturbances, such as climate and land use change, have the potential to impact soil services by destabilizing the physical or chemical processes that maintain healthy soil conditions. It is imperative that we better inventory soil services and sensitivities so that we can better manage these critical resources in response to change.
Persistent drought, or aridification, in the Upper Colorado River Basin (UCRB) has made headlines for the resulting reductions in surface waters available for power production, irrigation, and recreation. These are generational issues that require the utmost attention, but they are not the only issues stemming from drought. Changes in the timing, intensity, and amount of precipitation across the UCRB are likely to have a significant impact on soil conditions with subsequent feedback on the distribution and health of plant communities. Furthermore, regional changes in terrestrial systems may lead to additional impacts on surface water through changes in soil moisture residence times and evapotranspiration. The objective of the USGS Regional Assessment of Drought Impacts on Soils (RADIS) project is to improve our inventories of soils and soil services of the UCRB and to facilitate improved forecasts of the response of soils to drought so that land and ecosystem managers may better prepare for the future.
Project Goals
The goals of the RADIS project are to (1) develop and test a spatially explicit framework for quantifying soil heterogeneity at regional scales and (2) to improve data and model infrastructure supporting forecasts of terrestrial responses to environmental drivers - particularly drought. For the first two phases of this project, we have focused primarily on characterizing the storage of organic matter in soils (SOM) – a critical function supporting ecosystem health, agricultural productivity, and climate resilience. To accomplish these goals, we integrate a data-driven sampling approach, predictive soil mapping, and laboratory-based experimentation. The result of this effort will be a data-driven, spatially explicit representation of soil properties and processes that will drive improved forecasting in support of resource management and policy decisions for UCRB.
Approach
Our approach is shaped by the need to up-scale our understanding of soil processes, which are often based on pore- and profile-scale observations, to better understand the mechanistic drivers of landscape-scale heterogeneity. This requires the integration of geospatial mapping, extensive sample collection and analyses, targeted experimentation, and process-based modeling. To accomplish this, we utilize machine learning based methods for predictive soil mapping and data clustering. Through this combination, we can more efficiently collect and analyze soils to better understand drivers of landscape-scale variation in soil properties and processes. Moreover, by using data-driven methods for identifying and mapping meaningful soil groupings, we can more efficiently and effectively parameterize regional-scale processed based models for predicting the response of soils to disturbances such as drought. Soil processing and analysis is supported by the USGS Earth Systems Biogeochemistry Laboratory.
Phase One. High-Elevation Catchments of the Upper Colorado River Basin. 2017-2023
The first phase of this work was based in Upper East River and adjacent watersheds located, near Gothic, Colorado. The Upper East River area of interest is broadly representative of high-elevation catchments of the UCRB and includes a mix of alpine, sub-alpine, and montane ecosystems. Working in collaboration with the Rocky Mountain Biological Laboratory, the Department of Energy, and individual collaborators from a variety of institutions, we leverage extensive and ongoing research in this region to test and refine our predictive soil mapping approach.
Phase Two. Drylands of the Upper Colorado River Basin. 2023-2027
In the second phase of RADIS project, we will conduct a complementary sampling and predictive soil mapping exercise for dryland ecosystems in and around Moab, UT. This region is comprised of vast tracts of public lands, which are representative of dryland settings throughout the Colorado Plateau. Working with partners from the Bureau of Land Management, the National Park Service, and other regional partners, we will implement a refined version of our predicative soil mapping approach to characterize heterogeneity of dryland soil carbon cycling, with an emphasis on better understanding the spatial relationships between soil moisture, plant communities, and carbon storage.
Project Collaborators
- Kate Maher, Stanford University, Upland Carbon Dynamics and Geochemical Weathering
- K. Dana Chadwick, NASA Jet Propulsion Laboratory, Remote Sensing of Soil Properties
- Jennifer Druhan, University of Illinois at Urbana-Champaign, Reactive Transport Modeling of Soil Carbon and Carbon Isotopes
- Matt Winnick, University of Massachusetts at Amherst, Soil Respiration, Petrogenic Carbon, and Geochemical Weathering
- Courtney Creamer, USGS Menlo Park, Soil Chronosequences and Microbe-Mineral Interactions
- Jack McFarland, USGS Menlo Park, Soil Chronosequences and Microbial Dynamics
- Richard Reynolds, USGS Emeritus, Aeolian Dust and Microplastics
- Marjorie Schulz, USGS Emeritus, Soil Chronosequences and Rhizosphere Dynamics
Related Projects and Resources
Soils are the foundation of terrestrial ecosystems. They provide critical services including supplying a substrate and the nutrients necessary for plant growth, retaining moisture from precipitation, filtering contaminants from percolating waters, and acting as a sink of carbon. Healthy soils are key to sustaining both human and ecosystem health. However, global- and regional-scale disturbances, such as climate and land use change, have the potential to impact soil services by destabilizing the physical or chemical processes that maintain healthy soil conditions. It is imperative that we better inventory soil services and sensitivities so that we can better manage these critical resources in response to change.
Persistent drought, or aridification, in the Upper Colorado River Basin (UCRB) has made headlines for the resulting reductions in surface waters available for power production, irrigation, and recreation. These are generational issues that require the utmost attention, but they are not the only issues stemming from drought. Changes in the timing, intensity, and amount of precipitation across the UCRB are likely to have a significant impact on soil conditions with subsequent feedback on the distribution and health of plant communities. Furthermore, regional changes in terrestrial systems may lead to additional impacts on surface water through changes in soil moisture residence times and evapotranspiration. The objective of the USGS Regional Assessment of Drought Impacts on Soils (RADIS) project is to improve our inventories of soils and soil services of the UCRB and to facilitate improved forecasts of the response of soils to drought so that land and ecosystem managers may better prepare for the future.
Project Goals
The goals of the RADIS project are to (1) develop and test a spatially explicit framework for quantifying soil heterogeneity at regional scales and (2) to improve data and model infrastructure supporting forecasts of terrestrial responses to environmental drivers - particularly drought. For the first two phases of this project, we have focused primarily on characterizing the storage of organic matter in soils (SOM) – a critical function supporting ecosystem health, agricultural productivity, and climate resilience. To accomplish these goals, we integrate a data-driven sampling approach, predictive soil mapping, and laboratory-based experimentation. The result of this effort will be a data-driven, spatially explicit representation of soil properties and processes that will drive improved forecasting in support of resource management and policy decisions for UCRB.
Approach
Our approach is shaped by the need to up-scale our understanding of soil processes, which are often based on pore- and profile-scale observations, to better understand the mechanistic drivers of landscape-scale heterogeneity. This requires the integration of geospatial mapping, extensive sample collection and analyses, targeted experimentation, and process-based modeling. To accomplish this, we utilize machine learning based methods for predictive soil mapping and data clustering. Through this combination, we can more efficiently collect and analyze soils to better understand drivers of landscape-scale variation in soil properties and processes. Moreover, by using data-driven methods for identifying and mapping meaningful soil groupings, we can more efficiently and effectively parameterize regional-scale processed based models for predicting the response of soils to disturbances such as drought. Soil processing and analysis is supported by the USGS Earth Systems Biogeochemistry Laboratory.
Phase One. High-Elevation Catchments of the Upper Colorado River Basin. 2017-2023
The first phase of this work was based in Upper East River and adjacent watersheds located, near Gothic, Colorado. The Upper East River area of interest is broadly representative of high-elevation catchments of the UCRB and includes a mix of alpine, sub-alpine, and montane ecosystems. Working in collaboration with the Rocky Mountain Biological Laboratory, the Department of Energy, and individual collaborators from a variety of institutions, we leverage extensive and ongoing research in this region to test and refine our predictive soil mapping approach.
Phase Two. Drylands of the Upper Colorado River Basin. 2023-2027
In the second phase of RADIS project, we will conduct a complementary sampling and predictive soil mapping exercise for dryland ecosystems in and around Moab, UT. This region is comprised of vast tracts of public lands, which are representative of dryland settings throughout the Colorado Plateau. Working with partners from the Bureau of Land Management, the National Park Service, and other regional partners, we will implement a refined version of our predicative soil mapping approach to characterize heterogeneity of dryland soil carbon cycling, with an emphasis on better understanding the spatial relationships between soil moisture, plant communities, and carbon storage.
Project Collaborators
- Kate Maher, Stanford University, Upland Carbon Dynamics and Geochemical Weathering
- K. Dana Chadwick, NASA Jet Propulsion Laboratory, Remote Sensing of Soil Properties
- Jennifer Druhan, University of Illinois at Urbana-Champaign, Reactive Transport Modeling of Soil Carbon and Carbon Isotopes
- Matt Winnick, University of Massachusetts at Amherst, Soil Respiration, Petrogenic Carbon, and Geochemical Weathering
- Courtney Creamer, USGS Menlo Park, Soil Chronosequences and Microbe-Mineral Interactions
- Jack McFarland, USGS Menlo Park, Soil Chronosequences and Microbial Dynamics
- Richard Reynolds, USGS Emeritus, Aeolian Dust and Microplastics
- Marjorie Schulz, USGS Emeritus, Soil Chronosequences and Rhizosphere Dynamics
Related Projects and Resources