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Title of Thesis
Regional Scale Sediment Yield Modeling Using Gis And Remote
Sensing |
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Author(s)
Ghulam Nabi |
Institute/University/Department
Details Centre Of Excellence In Water Resources
Engineering / University Of Engineering And Technology, Lahore |
Session 2009 |
Subject Engineering |
Number of Pages 173 |
Keywords (Extracted from title, table of contents and
abstract of thesis)
Sediment, Gis, RSSYM, Gariala, Catchment, Astor, MRSSYM, Hydrograph,
Fractal, Zhang, Correlation, statistical |
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Abstract A grid based
Regional Scale Sediment Yield Model RSSYM was setup different
catchments of Indus basin using coarse resolution grid data. When
coarse grid data is used, the land slope decreases and sediment
delivery is reduced. In this study the slope averaging effect was
minimized by using the fractal analysis approach. The fractal
constant (a) and fractal dimension (D) equations were correlated
with the standard deviation on elevation by Zhang et al. (2000).
These equations for fractal constant and fractal dimension were
developed using Digital Elevation Model of 1 km2 resolution (DEM)
for local topography. The slope was computed for 250 m and50 m
downscaling from 1 km2 grid. A comparison was made between fractal
constant equation and fractal dimension to scale down the slope
parameter. Both equations were incorporated in RSSYM. The model was
applied to Phulra catchment. The results showed that fractal
dimension equation gives better results as compared to fractal
constant. So the fractal dimension equation was incorporated in
RSSYM.
The RSSYM was applied on three catchments of Indus basin namely Soan,
Gariala and Phulra. For Phulra catchment of Siran river the total
observed sediment was 0.304 million tons whereas the simulated
sediment was 0.291 million tons. The coefficient of efficiency (COE)
was 0.85 and the coefficient of determination was 0.83 which shows
that there is a good correlation between the observed and simulated
values.
In Gariala catchment the observed sediment was 6.01 million tons
whereas simulated sediment was 6.80 million tons. The coefficient of
efficiency for Gariala catchment was 0.91 and the coefficient of
determination observed and simulated hydrograph was 0.81. Similarly
for the Soan catchment the observed sediment was 10.61 million tons
and simulated sediment was 12.29 million tons. The coefficient of
determination and coefficient of efficiency for this catchment was
0.95 and 0.98 respectively.
The snowmelt runoff model SRM was applied to Astor catchment to test
the applicability of temperature index approach for Indus basin. The
terrain is difficult to measure the hydrological and hydraulics
data. Most of the data was available at the outlet of the
catchments. The input data included daily temperature and
precipitation, dividing the catchment in to different zone depending
on the elevation difference. The elevation zones were generated from
the DEM of the area. The snow depletion curves were made for the
snow covered area derived from the satellite data analysis on
monthly basis. The model output was discharge hydrograph. The COE
was 0.91 which shows that there is a good correlation between the
observed and simulated values. The statistical test showed that
model performance was good. The results of SRM model encouraged to
use temperature index approach for snowmelt runoff estimation in the
Indus basin.
A snowmelt runoff model was developed using temperature index
approach. The model was coupled with regional scale sediment yield
model RSSYM. The coupled model was named as modified regional scale
sediment yield model (MRSSYM). The MRSSYM model was applied to Astor
and Gilgit catchments. For the Astor catchment total observed
sediment load was 3.98 million tons whereas the simulated sediment
load was 4.34 million tons. The coefficient of the model was 0.89
whereas the coefficient of determination was 0.83. Similarly for
Gilgit catchment the measured and simulated sediment loads were 4.50
and 4.48 million tons respectively. The coefficient of efficiency
and coefficient of determinations were 0.95 and 0.88 respectively.
From the results it can be concluded that MRSSYM can be applied with
confidence to various catchments of Indus basin where runoff is due
to snowfall and snow melting.
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