Chapter 23: Soil drought probability for Pacific Northwest forests

Dataset Overview

This dataset represents the likelihood that forest soils experience prolonged summer drying. The dataset was developed using a model that incorporated variables including soil depth, available water supply, and evapotranspiration (see chapter glossary for definitions of terms). The model was calibrated using soil profiles and laboratory data for 25 sites from various forests in the Pacific Northwest to estimate the number of days per year on average that soil moisture drops below the permanent wilting point. The soil drought probability values (i.e., droughty soil index) in this dataset represent the degree to which a soil has chronically low seasonal moisture levels such that the soil would be particularly vulnerable to drought conditions during climatically dry periods (figure 23.1).

Data Access:

Figure 23.1


Conservation Applications

Potential conservation applications of this dataset could include the following:

  • This dataset can provide important information to complement climate-based approaches to assessing drought vulnerability for Pacific Northwest forests. For example, forests with dry climate and deep soils with relatively large water-storage capacities may be less prone to drought stress than would be expected based on climate variables alone. Conversely, forests in climates without severe moisture limitation but with shallow soils that hold relatively little water might be more vulnerable to drought stress than would be predicted solely based on climate variables. Ringo et al. (2018) suggested that forest managers could use this dataset to prioritize forests for treatments such as thinning to reduce vegetation drought stress by reducing competition for soil moisture reserves. It could also be used to help improve wildfire prediction models by helping refine predictions of fuel moisture content.

Applicable scales for detailed spatial assessments:

  • For conservation applications requiring detailed assessment of spatial variation of the dataset within a geographic boundary (such as a protected area), the following geographic scales may be most appropriate (see appendix 3 for more information).
  • At the scale of: a state park or state wildlife area, a local watershed (12-digit hydrologic unit code [HUC-12]), a Bureau of Land Management (BLM) district, a river watershed (8-digit hydrologic unit code [HUC-8]), an individual county, a national forest, a level-3 ecoregion (e.g., the North Cascades), a single state (Washington or Oregon), a region (Washington and Oregon).

Applicable scales for assessing general patterns:

  • Due to spatial resolution, the dataset may not show detailed spatial variation at the following geographic scales, however, the dataset may be useful to assess general patterns or for comparison to other locations (see appendix 3 for more information).
  • At the scale of a small (< 1 km2) nature preserve.

Use of the dataset in conservation applications may be limited by the following considerations:

  • Because this dataset primarily represents the soil component of forest ecosystems, there are other important factors influencing forest drought sensitivity that are not represented, including forest community composition (the mix of tree species present), demographics (size and age classes of trees), stand density, physiological adaptations to drought stress and chronic water limitation, and interactions between droughts and other disturbance dynamics such as fires and insect outbreaks. Also, in planning for climate-change impacts, regional variability in projected changes to temperature and precipitation patterns are important and not captured by this dataset. Therefore, forest managers should consult a variety of locally relevant information sources (e.g., climate projections and forest stand characteristics) in conjunction with the soil drought vulnerability information in this dataset.

Past or current conservation applications:

  • This dataset has not yet been used in any on-the-ground conservation applications to the knowledge of the authors of this chapter.

Dataset citation:

Ringo, C., K. Bennett, J. Noller, D. Jiang, and D. Moore. 2018. Modeling droughty soils at regional scales in Pacific Northwest Forests , USA. Forest Ecology and Management 424:121–135.

Dataset documentation link: (subscription or fee required)

Data access:

The dataset can be downloaded from:

The dataset is not available for interactive online map viewing.

Metadata access:

Formal metadata is attached to the raster dataset and may be exported to XML format using Esri ArcCatalog.

Dataset corresponding author:
Chris Ringo
Oregon State University

Data type category (as defined in the Introduction to this guidebook): Topoedaphic

Species or ecosystems represented: This dataset represents the physical soil component of forest ecosystems.

Units of mapped values: unitless

Range of mapped values: 0 to 100
The dataset values are depicted on a 0 to 100 scale in Ringo et al. (2018).

Spatial data type: a raster dataset (grid)

Data file format(s): File geodatabase raster

Spatial resolution: 30 m

Geographic coordinate system: North American Datum of 1983

Projected coordinate system: North American Datum of 1983 Oregon Washington Albers

Spatial extent: Regional

Dataset truncation: The dataset is truncated along the USDA Forest Service, Pacific Northwest Region boundary (States of Washington and Oregon, plus a small area in northern California).

Time period represented: Static (relatively unchanging over time)

Methods overview:

A geospatial dataset was compiled representing available water supply to a depth of 150 cm or to a root-restricting layer (whichever was less). Several data sources were compiled to calculate available water supply, including from the Soil Survey Geographic (SSURGO) Database (Natural Resource Conservation Service, 2014a), provisional (unpublished) SSURGO data, State Soil Geographic (STATSGO) Database (Natural Resource Conservation Service, 2014b), and the USDA Forest Service's Soil Resource Inventory. With the exception of STATSGO, these datasets were also used to estimate soil depth. To represent climatic moisture limitation, the ratio of actual evapotranspiration (AET) to potential evapotranspiration (PET) was calculated using averages from July through September 2000 through 2014. A model representing soil moisture was constructed using soil depth, available water supply, and AET/PET ratio, and was calibrated using daily soil moisture observations from the network of Snow Telemetry (SNOTEL) sites in Oregon and Washington. For each SNOTEL site used for calibration, laboratory data were used to estimate the permanent wilting point, and the soil moisture data were used to calculate the average number of days per year that soil moisture dropped below the permanent wilting point. For more information, please consult the dataset citation listed in section 2 of this chapter.

Major input data sources for this dataset included: Historical climate observations or models, soil characteristics

The mapped values of the dataset may be interpreted as follows:

High values indicate forest soils that have a high probability of being "droughty," defined as having soil moisture below the permanent wilting point for an average of at least 10 weeks per year. Lower values indicate lower likelihood of a forest soil being "droughty" according to this definition.

Representations of key concepts in climate-change ecology:

This dataset represents a component of climate-change sensitivity, specifically the sensitivity of soils to drying during droughts. Forest ecosystems in drought-vulnerable soil areas may be especially vulnerable to drought intensification and long-term climatic drying. By contrast, less "droughty" soils may demonstrate greater resistance to droughts (maintaining greater soil moisture for vegetation) and may aid forest resilience in recovering from droughts. As described in chapter 22, soil properties that influence soil sensitivity to droughts and other disturbances have potentially important implications for terrestrial ecosystems and for aquatic ecosystems in streams that may receive sediment from eroding soils. Soil properties thus represent an important link between the meteorological effects of climate change (e.g., changes in timing and magnitude of precipitation) and the hydrologic and ecological effects experienced by natural communities.

This dataset involves the following assumptions, simplifications, and caveats:

To represent climatic moisture limitation, the analysis that produced this dataset relied on fairly coarse-resolution (1-km) estimates of actual and potential evapotranspiration from a global model that may not accurately represent local climate conditions. Also, although soil depth can be an important constraint on availability of soil moisture for vegetation, some trees are able to access deep-water sources (e.g., deep soil layers, water tables, and weathered bedrock) that were not accounted for in this dataset. For the 25 SNOTEL sites used for calibration, most were predicted accurately by the model that produced this dataset, however, a few sites were not accurately modeled (e.g., a site in coarse volcanic soils and sites with local variation in canopy cover). In general, sites with coarse volcanic soils may be inaccurately represented by this dataset due to the difficulties in calibrating soil-moisture sensors in soils with high porosities.

Quantification of uncertainty:

In the study that produced this dataset, soil "droughtiness" was defined as a binary category (whether soil moisture falls below the permanent wilting point for more than 10 weeks per year on average). Uncertainty related to this classification is represented as a probability that a given site is "droughty".

Field verification:

The model that produced this dataset was calibrated using soil variables from 25 SNOTEL sites throughout the Pacific Northwest. However, the model was not independently validated because the number of available sites with soil variables in the study area did not allow for an independent dataset for model validation.

Prior to dataset publication, peer review was conducted by external review (at least two anonymous reviewers, each from a different institution).

Natural Resource Conservation Service. 2014a. Soil Survey Geographic (SSURGO) Database.

Natural Resource Conservation Service. 2014b. U.S. General Soil Map (STATSGO2) Database.

Ringo, C., K. Bennett, J. Noller, D. Jiang, and D. Moore. 2018. Modeling droughty soils at regional scales in Pacific Northwest Forests , USA. Forest Ecology and Management 424:121–135.