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Title
The 3rd ISPRS Workshop on Dynamic and Multi-Dimensional GIS & the 10th Annual Conference of CPGIS on Geoinformatics
Author
Chen, Jun

ISPRS, Vol.34, Part 2W2, “Dynamic and MultiPimensional GIS’’, Bangkok, May 23-25, 2001
• Network definition
using an approach similar to that proposed by Foster and
Wischmeier:
The stream and watershed network was determined so that
there was a single stream segment for each watershed that had
been modeled. The DEM cells that form the streams are
defined as the union of two sets of grid cells. The first set
consists of all cells whose flow accumulation is greater than a
user-defined threshold value. This set identifies the streams
with the largest drainage area, but not necessarily with the
largest flow because flow depends on other variables that are
not related exclusively to topography. The second set is defined
interactively by the user by clicking a certain point on the map,
which results in an automatic selection of all downstream cells.
To include these streams using the threshold criterion, it would
be necessary to lower the threshold value for the entire system,
thus defining unnecessarily a much more dense stream
network.
Y = EL..K { C ,P,S,
Aj (A, /22.13)" - A H (^.,/22.13)"
A,-A,
Where Yj, Kj, Cj, Pj, and Sj are the sheet and rill erosion, soil
erodibility factor, cover and management factor, practice factor
and slope factor, respectively, in the jth celJ Aj and Aj.i are the
upslope contributing areas where flow exits and enters each
cell, respectively. Ehois the rainfall energy-intensity.
The LS factor derived from unit stream power theory used with
GIS enhanced pesticides model appeared to perform
satisfactorily. It has an advantage over the traditional method in
that the inputs to the relationship are derived easily from the
terrain analysis and physically can better account for the effects
of flow convergence and divergence on erosion.
Sub-basin outlets were also defined as the union of two sets of
grid cells. The first set, based on the stream network, consists
of all cells located just upstream of the junctions. Consequently,
at a junction, two outlet cells are identified, one for each of the
upstream branches. The system outlet is also identified as an
outlet. The second set is defined interactively by the user by
clicking on any cell on the stream network such as those
associated with gages or other water control points. After the
sub-basin outlets have been defined, a unique identification
code is assigned to each stream segment connecting a
headwater cell with a sub-basin outlet, or two sub-basin outlets.
• Length-slope factor
A minimum cell area of 280mx400m was applied with
Pesticides Losses Runoff Model in this paper to allow a
representative field slope length to be used in estimating the
length-slope factor (LS) in the Universal Soil Losses Equation
(USLE). The USLE is used to calculate the sheet and rill
erosion in each cell. A theoretical equation derived from unit
stream power theory is used to estimate the lengthslope factor
in the USLE (Cialella et. al. 1997). This equation also better
represents the effects of flow convergence aid divergence on
erosion:
LS =
A, T
[ s ' n P,
.With
A,
" and S =
sin /?,
_22.13J
[o.0896j
|_22.13J
[(10896J
Where A s is the specific catchment area (=A/b), defined as the
upslope contributing area (A) per unit width normal to the flow
direction (b); p is the slope gradient in degrees; n=0.4 and
m=1.3. The within-cell sheet and rill erosion is then estimated
RESULTS AND DISCUSSION
For this paper is based on an undergoing project, there are little
results that can be showed here. Through the application of the
methods mentioned in previous section, the slope and flow
direction of the study basin were carried out (Fig.5 and Fig.6).
To evaluate the reliability of terrain analysis, the results
generated by the integration of GIS and remote sensing and the
field measured slope and direction were compared. It was
showed there were some disagreement though satisfying in
general.
Two reasons have been identified for the mismatc h between
true topographic surface form, and its representation as a DEM
within a GIS. Firstly, the methods themselves provide some
conceptual limitations. It is not possible to represent fully, a
continuous, undifferentiatable surface with a discrete, finite
resolution elevation model. Secondly, the process of elevation
interpolation required for DEM generation can lead to model
error (Garbrecht and Starks, 1995; Gong, et al., 2000).
The lack of agreement implies further refinement of thisterrain
analysis methodology may provide more insight intopesticides
losses runoff modeling. It suggests that GIS data, no matter
what specific methodology is employed, may need to be
augmented with site-specific sampling data to facilitate
pesticides control decision making. However, the important
point should be confirmed is the GIS and remote sensing
integrated modeling is a useful tool for the pesticides losses
control and the results are receivable.