Geology Reference
In-Depth Information
17
The Future Role of Information
Technology in Erosion Modelling
D.P. GUERTIN
1
AND D.C. GOODRICH
2
1
Landscape Studies Program, School of Natural Resources, University of Arizona, Tucson, AZ, USA
2
USDA-ARS, Southwest Watershed Research Center, Tucson, AZ, USA
17.1 Introduction
observation made by the National Research
Council's Committee on Watershed Management
(National Research Council, 1999). Over the last
50 years the federal government has spent mil-
lions of dollars on the creation of spatial datasets
and model development. While these simulation
models are used extensively in research settings,
they are infrequently incorporated into the
decision-making process. Another aspect of ero-
sion modelling is the continued use of simpler,
empirically-based erosion models (e.g. USLE,
RUSLE) instead of more complex, physically-
based models (e.g. WEPP, EUROSEM). Reasons
for this exclusion include: data requirements are
usually only attained in a research setting; mod-
els are complex and underlying assumptions are
poorly understood by resource managers; deriv-
ing model input parameters is extremely time-
consuming and difficult; and the models are
difficult to use with the current interfaces.
For example, Elliot (2004) reported that
between 1993 and 1998 over 200 Forest Service
specialists were trained to use the USDA Water
Erosion Prediction Project model (WEPP)
(Flanagan & Livingston, 1995; Elliot & Hall,
1997). Of those specialists, only three or four (or
2%!) subsequently applied the model because the
interface was too difficult to operate and too
much time was required to assemble the data and
interpret the results. Occasional users found it
difficult to keep track of which combinations of
input files should be used for typical forest and
range conditions. Some users were observed to
Natural resource decision-making is a complex
process requiring cooperation and communica-
tion between federal, state and local stakehold-
ers, balancing biophysical and socio-economic
concerns. Predicting soil erosion is common
practice in natural resource management for
assessing the effects of management practices
and control techniques on soil productivity,
sediment delivery and offsite water quality. Effec-
tive decision-making requires the integration of
knowledge, data, simulation models and expert
judgment to solve practical problems, and to pro-
vide a scientific basis for decision-making at the
hillslope or watershed scale (National Research
Council, 1999).
A user-friendly decision support system (DSS)
would assist different professional or stakeholder
groups to develop, understand and evaluate alter-
native soil conservation strategies. The DSS could
integrate a suite of components consisting of
database management systems (DBMS), geo-
graphic information systems (GIS), simulation
models, decision models, and easy-to-understand
user interfaces. The difficulty in developing a
DSS is not a lack of available data or simulation
models for erosion prediction, but rather making
these models available to decision-makers, a key
