CHARACTERIZING AND MAPPING SOIL CLIMATE
NORTHERN PLAINS REGION
W.J. Waltman, H.R. Sinclair, and S.W. Waltman
USDA Natural Resources Conservation Service
Northern Plains Regional Office and National Soil Survey Center
The landscapes of the Northern Plains reflect a complex history of geomorphic and climatic events, which have also significantly affected soil and ecosystem development. The interaction of soils, climate, vegetation/animals, topography, human impacts, and time produces considerable natural and agricultural resource diversity that results in a complex pattern of soil landscapes and conservation strategies.
The Northern Plains region consists of roughly 420 million acres distributed across 57 Major Land Resource Areas. A good indicator of regional land resource diversity is expressed in the soil resource base. The Northern Plains landscape is collectively represented by more than 4427 soil series and 48,165 soil map units . Soil moisture regimes range from aridic to udic and soil temperature regimes extend from thermic to pergelic. In addition, the topography ranges from elevations of 4500 m above sea level (14,433 ft) on Mt. Elbert, Colorado, to 213 m (< 800 ft) in Kansas. Seventy percent of the region has elevations below 1500 m (4,920 feet) and only 4 percent of the land area occurs above 2743 m (9,000 ft). However, due to the broad topographic range and its accompanying orographic effects, precipitation ranges from 142 mm (< 6 in) in the Bighorn Basin of Wyoming to 1110 mm (44 in) in southeastern Kansas. Given this range of climatic environments and their inherent variability, conservation management of both natural and agricultural ecosystems across these landscapes is a difficult challenge.
In both concepts of the Land Resource Regions and Major Land Resource Areas (Soil Survey Staff, 1981), the boundaries and characteristics have been be viewed as rather static in time and space. Similarly, soil moisture and temperature regimes have been traditionally mapped as static delineations. Although Marbut (1935) and Jenny (1941) clearly recognized the importance of climate in soil formation, the ability to map soil climate characteristics and articulate its variability or behavior has been lacking in the soil survey process.
The challenge for the Natural Resources Conservation Service (NRCS) was to derive new indicators for soil climate changes, capture and articulate aspects of the soil climate variability, develop a methodology to better represent soil climate characteristics, which can be integrated to create agro-climatic regions across the Northern Plains region.
The objectives for our research and their application were: 1) to develop an index of inherent
soil quality suitable for mapping soil productivity and agro-climatic regions, 2) to design
relatively simple indices to represent changes in soil moisture and temper-ature regimes, and 3)
to terrain model soil-climate parameters and their shifts from existing geospatial databases.
Soil Ratings for Plant Growth
For soil constraints or qualities, the "Soil Ratings for Plant Growth" (SRPG) was used to group about 25 soil properties into a soil productivity or inherent soil quality index cal-culated for components of STATSGO map units. The SRPG calculations followed the "Storie Index Soil Rating" (Storie and Weir, 1958; Storie, 1978), which was based on soil characteristics that govern the land's potential utilization and productive capacity. The Storie Index was originally adapted to semiarid and arid regions and included profile characteristics that influenced effective rooting depth and the quality of the root zone, subsurface properties (permeability, available water-holding capacity, drainage class, soluble salts), and landscape properties such as slope, microrelief, and the degree of erosion (Miller and Donahue, 1990). However, in the SRPG, Sinclair and Terpstra (1995) also considered soil climate regimes as an additional factor in calculating the index, which is a particularly significant parameter, given the wide range in soil climate across the Northern Plains region. The SRPG tables for STATSGO were developed by the Iowa State University Statistical Laboratory (Sinclair and Terpstra, 1995).
The SRPG wascombined with the USGS Land Use and Land Cover (LUDA) to identify
croplands with similar agronomic behavior or soil productivity (Figure 1). SRPG values ranging
from 0 to 30 were considered unsustainable for agronomic crop production (Storie, 1978; Miller
and Donahue, 1990), but these soil ratings still represent productive range ecosystems. SRPG
values from 31 to 50 generally grouped soils with marginal suitability for agronomic production.
The most highly productive soil areas have ratings greater than 70. The SRPG classes grouped
on the basis of 10 units (i.e. 1 to 10, 11 to 20) seemed to provide reasonable subdivisions of
MLRAs and a basis for soil productivity regions. From the SRPG calculations, soil management
groups began to emerge, which could relate to areas where particular conservation tillage
practices are adaptable. The primary underlying assumption of the SRPG reflects the concept
that soils with the greatest "effective rooting depth" and root zone available water-holding
capacity are the most productive. The SRPG sub-calculations of effective rooting depth and root
zone available water-holding capacity are needed for modeling soil moisture regimes, but also
have value for identifying soil landscapes with limited soil water retention characteristics.
The Newhall Simulation Model
The Newhall Simulation Model (NSM) has long been used by the USDA Natural Resources
Conservation Service to estimate soil moisture regimes as defined in Soil Taxonomy (Soil
Survey Staff, 1975, 1993; Newhall and Berdanier, 1992). Van Wambeke et al. (1992) modified
the original model and introduced new subdivisions of soil moisture regimes and variable soil
moisture storage. Van Wambeke (1981, 1982, and 1985) applied the model to map soil
moisture regimes across Africa, South America, and Asia. The NSM was designed to run on
monthly normals for precipitation and temperature; generally 30 year normals were most
reasonable and appropriate to derive estimations of soil moisture and temperature regimes, as
well as biological windows.
Soil Moisture Regimes
Soil moisture regime refers to the presence or absence of soil water held at a tension of <15 bars (or between field capacity and permanent wilting point) in specific horizons during key periods of the year (Soil Survey Staff, 1975). Soil moisture regime is an important soil property because of its impact on cropping systems, tillage/conservation practices, as well as natural plant communities. Tables 1 and 2 summarize the soil moisture regime changes over time for the Mead Agronomy Laboratory (Mead, NE) and the Akron 1 N (CO) weather stations. The interannual variability of soil moisture regimes can be useful indicators of soil climate shifts at local or large map scales.
From the soil moisture regime calculations, the "Pedocal/Pedalfer" boundary (Marbut, 1935; Jenny, 1941) can be terrain modeled to illustrate changes in soil forming pro-cesses. The Pedocal/Pedalfer Boundary is a theoretical threshold where precipitation equals potential evapotranspiration, and defines the boundary between soils in a leaching versus base accumulating (CaCO3) environment (Figure 2).
Table 1. Soil Climate Characteristics of Mead Agronomy Laboratory, Nebraska.
|YEAR||PREC||PET||AMD||MSD||Dry Days||M/D Days||BIO5||Soil Moisture Regime|
PREC = Precipitation PET = Potential Evapotranspiration AMD = Annual Moisture Deficit MSD = Mean Summer Deficit Dry Days = Days the Soil Moisture Control Section is Dry M/D Days = Days the Soil Moisture Control Section is Partly Moist and Dry BIO5 = Biological Window at 5 oC
Table 2. Soil Climate Characteristics of Akron 1 N, Colorado.
|YEAR||PREC||PET||AMD||MSD||Dry Days||M/D Days||BIO5||BIO8||Soil Moisture Regime|
PREC = Precipitation PET = Potential Evapotranspiration AMD = Annual Moisture Deficit MSD = Mean Summer
Deficit Dry Days = Days the Soil Moisture Control Section is Dry M/D Days = Days the Soil Moisture Control Sectio is
Partly Moist and Dry BIO5 = Biological Window at 5 oC BIO8 = Biological Window at 8 oC
The Newhall simulation estimates the cumulative days that the soil moisture control section is moist and greater than 5 oC, as well as the highest number of consecutive days that the moisture control section is both moist in some parts and greater than 8 oC. Both of these estimates are defined as "biological windows" of plant and microbial activity. The concept of biological windows may serve as a useful bioclimatic indicator of inherent soil quality, since it integrates both soil moisture and temperature, as well as the window of time available for root and microbial activity. The biological window calculation would relate to soil processes, such as the mineralization of organic matter, soil carbon storage, herbicide degradation, and nitrification. Tables 1 and 2 also summarize the interannual variability of biological windows for the Mead Agronomy Laboratory and the Akron 1 N weather stations.
The biological window concept is indirectly expressed in Soil Taxonomy (Soil Survey Staff, 1975;
Smith, 1986), but the calculation can be derived through the NSM and terrain modeled to USGS
DEMs (Figure 3).
A terrain modeling approach was used together with the NSM (Van Wambeke et al., 1992)
results to spatially extend climatic parameters onto the landscape. These climatic parameters
included: mean annual precipitation, air temperature, potential evapo-transpiration, annual
moisture surplus/deficit, mean summer moisture deficit, moisture index, biological windows,
growing-degree days, frost-free period, and soil climate regimes. The transfer of climatic
parameters to terrain (1:250000 USGS digital elevation models or DEMs) followed the
methology described by Ollinger et al. (1995). Regression equations were derived from a
population of 875 weather stations with 1961 to 1990 normals in Northern Plains states. The
regression equations were based upon five land-scape parameters: easting (longitude),
northing (latitude), elevation, slope, and aspect. From these equations, continuous surfaces of
the climatic parameters provided a better fit to the terrain while capturing local orographic
SUMMARY AND CONCLUSIONS
The SRPG or inherent soil quality index, clearly defines soil productivity regions or soil management groups (in a non-political context) within the Northern Plains and should provide global change modelers with reasonable, quantitative values for effective rooting depth and root zone available water-holding capacity across soil landscapes.
Soil moisture and temperature regimes, the Pedocal/Pedalfer Boundary, and biological windows,
are useful indicators of soil climate shifts in the Northern Plains.
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