A new global soil and alluvial thickness dataset for terrestrial process studies

Patrick Broxton, University of Arizona, broxtopd@email.arizona.edu (Presenter)
Jon Pelletier, University of Arizona, jdpellet@email.arizona.edu
Michael Brunke, University of Arizona, brunke@atmo.arizona.edu
Pieter Hazenberg, University of Arizona, pieter.hazenberg21@atmo.arizona.edu
Xubin Zeng, University of Arizona, xubin@atmo.arizona.edu
Peter Troch, University of Arizona, patroch@hwr.arizona.edu
Guo-Yue Niu, Biosphere 2, niug@email.arizona.edu
Gochis Dave, NCAR, gochis@ucar.edu
Williams Zachary, University of Arizona, zwilliams@email.arizona.edu

Information about soil and alluvial thickness affects the water holding capacity of the soil, runoff potential, rooting depth, and soil freeze/thaw. It is also needed for land surface models (LSMs) as the underlying bedrock surface provides a crucial lower boundary condition for these models. In reality, unconsolidated material above the bedrock interface ranges from 0 (bedrock is exposed at the surface) to tens of meters or more, with upland/erosional landscapes having much shallower bedrock than lowlands/depositional landscapes. Despite this, LSMs have a uniform soil thickness due to lack of reliable global data. Here, we describe a new global 1 km pixel soil and alluvial thickness dataset that utilizes a combination of high resolution SRTM and ASTER topographic data, geologic data, and climate data. Different models are used to predict soil and alluvial thickness for upland hillslopes, upland valley bottoms, and lowlands, which are, themselves, distinguished at the 90 m pixel scale using a valley network extraction algorithm as well as geologic age and overall topographic roughness criteria. The thickness of soil/alluvium in lowlands is predicted based on a relationship with topographic curvature which is calibrated with high-density well data from four U.S. states. In upland valleys, it is predicted from the curvature of the valley bottom and the gradient of the hillslopes flanking the valley. On upland hillslopes, it is predicted using geomorphic/pedogenic models that are based on topography and climate and calibrated with soil depth data from the CONUS-Soil database. We are currently validating the dataset against depth to bedrock data from additional groundwater wells (for lowlands and valley bottoms), as well as lower-resolution soils databases (e.g. European Soils Database) that were not used for model calibration. We are also testing the new dataset in the Community Land Model (CLM) by varying the number of model soil layers such that the soil column thickness in different locations matches the average soil and alluvial thickness in the new dataset. A release of the database is planned for mid-2015.

Presentation Type:  Poster

Session:  Theme 2: Landscapes to coasts: understanding Earth system connections   (Mon 1:30 PM)

Associated Project(s): 

• Pelletier, Jon: Development of a High-Resolution Global Soil Depth Dataset ...details

Poster Location ID: 75