Tools to Models: Some Applications of Automated Resource Analysis Tools
for Ecosystem Management.

*by Jacek Blaszczynski*

*Physical Scientist*

*BLM NARSC*

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Models are essentially simplified views of the processes that we know to
occur in Nature. They often rely on several important environmental
parameters relevant to the process being analyzed and a simple "engine"
which relates these parameters to each other. For example, the Universal
Soil Loss Equation (USLE) model relies on six primary parameters which
reflect the influence on sheet and rill erosion of rainfall intensity;
soil erodibility; slope gradient; slope length; surface cover; and
erosion control practice factors. The values for each of the factors are
either measured or calculated and fit into an equation developed from
statistical analysis of 10 plot years of cropland studies. The USLE
model was also modified for rangeland applications to create the RUSLE,
or the Revised Universal Soil Loss Equation. The

USLE and the RUSLE are empirical models because their "engine" is
generated from statistical analyses

of a large number of actual experimental results. Other model "engines"
might work differently;

for example, calculating runoff values based on hydrologic equations.
Since models are essentially nothing

more than their "engine" and environmental data, they are uniquely
adaptable to being automated on computers. Then they can be used to
analyze large amounts of data that otherwise could not be easily
reviewed.

Whoever utilizes models has to be aware that they probably will not
predict unique ecological circumstances that can be found on a specific
parcel of land but provide knowledge-based predictions of the magnitude
of the likely processes that should be occuring in that area. The
accuracy of these predictions

is directly dependent on the jjhmjjquality of data. The most honest
description of modeled information

is to present it as a result of a certain logic and environmental data
combined using this logic even in choosing our sampling methods we are
already modeling because we are conceptualizing what and how specific
parameters should be measured. A model can be understood as a painting
of reality done with a limited number of colors which should not be
confused with reality itself. Taking account of these facts,

NARSC is currently engaged in combining various GIS functions and tools
into models to aid following

ecosystem analysis efforts.

**1. Identification of Similar Terrain Units (STUs)**

This project is combining watershed delineation and watershed
morphometric parameter analysis technology to derive similar areas based
on shape of terrain. It is understood that particularly in

high relief locations the shape of terrain has profound impact on
geomorphic, hydrologic, and other

ecosystem processes. Therefore, subdivision of the land surface
according to terrain characteristics

should aid in finding transitional zones in terrain and local
ecosystems. The methods involve division

of the project into mini-watersheds associated with individual reaches
of a stream network.

The morphology of each mini-basin is analyzed using morphometric
parameters that describe each

basin. The basin morphometric parameter values are then grouped to
indicate which of the miniwatersheds

are morphologically similar to each other. Morphologically similar
watersheds are grouped in clusters that represent similar terrain
characteristics within the project area. The morphologically similar
areas outlined by groups of analogous watersheds can be used to study
ecologic processes influenced by terrain shape. These include the
ecosystem processes of soil erosion and sediment yield, surface and
subsurface hydrology, solar irradiation, and evapotranspiration.

**2. Automated Erosion, Runoff, and Sediment Yield Models**

Terrain analysis tools are directly utilizable in development of GIS
interfaces to erosion, runoff, and

sediment yield models to aid prediction of the patterns of these
processes on large areas. One of

the main difficulties with application of soil erosion prediction tools
such as the RUSLE has to do with

being able to adequately account for terrain variability in the modeled
area. Various terrain analysis

capabilities, including basic watershed and flow delineation methods,
can be utilized to improve the

predictive capability of RUSLE by permitting measurement of this
variability. Beyond that data inte-gration capabilities of GIS permit
rapid analysis of terrain, soil, and vegetation data together to develop
basin and Hydrologic Response Unit (HRU) statistics required for running
of the National Resource Conservation Service Curve Number (NRCS CN)
watershed runoff model and Modified Universal Soil Loss Equation (MUSLE)
for watershed sediment yield prediction. All of these models help us to
identify land management measures required to protect soil and water
quality, both major indicators of ecosystem health.

**3. Soil survey enhancement methods**

Terrain analysis tools are important for identification of various
components of the geomorphic surface of the landscape, including the
geometry of segments of hillslopes, locations of stream reaches within
drainage networks, and the morphology of watersheds. Terrain variability
is one of the central factors influencing the development and evolution
of soils, so the soils developed on different facets of hillslopes
differ from each other and from soils developed in terrain depressions
or in the floodplains of streams. Combining terrain information with
soil and other multidisciplinary data permits further refinement of
existing soil surveys which often contain two or more related types of
soils within a single mapping unit. Mapping the distribution of these
components and inclusions will permit enhancement of existing soil
surveys to a higher degree of resolution. For more information on soil
survey enhancement contact Mr. Alan Amen, Soil Scientist, BLM NARSC.

**4. Linked watershed modeling**

Streams, channels, and hollows form drainages which are organized into
drainage networks, or linked systems of streams and watersheds usually
identified by their order in the network. A network includes streams and
watersheds all the way from a major topographic divide to the river
delta as it enters the ocean. Processes within any watershed or reach
within a network can be modeled independently, and as part of a linked
watershed system. In this way it is possible to subdivide and aggregate
the effects of various watershed processes (e.g. erosion and sediment
yield) throughout the network and calculate their cummulative impact on
the landscape within the network. An example of this type of analysis is
provided by the watershed data preparation AMLs for the Hydrologic
Modeling System (HMS) of the U.S. Army Corps of Engineers which will be
described in future editions of Resource Notes.

We invite further suggestions as to possible applications of resource
analysis tools and models to your own projects. For futher information
on the efforts describe above contact:

Jacek Blaszczynski

Physical Scientist

BLM National Science and Technology Center

Denver Federal Center, Bldg. 50

Lakewood, Colorado

\(303\) 236-5263

<jblaszcz@blm.gov>