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Content:
Vol.
7, No. 2 Fall 2007
Vol.
7, No. 1 Spring 2007
Vol.
6, No. 2 Fall 2006
Vol.
6, No. 1 Spring 2006
Vol. 5, No. 2 Fall 2005
Vol.
5, No. 1 Spring 2005
Vol.
4, No. 2 Fall 2004
Vol.
4, No. 1 Spring 2004
Vol.
3, No. 2 Fall 2003
Vol.
3,
No. 1 Spring
2003
Vol. 2,
No. 2 Fall 2002
Vol. 2,
No. 1 Spring 2002
Vol. 1, No. 1 Fall 2001
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A Spatially Distributed Event-Based
Model to Predict Sediment Yield
Sreenivas Kandrika* and Venkataratnam, L.,
Agriculture & Soils Group, National Remote Sensing
Agency,
(Department of Space, Govt. of India), Balanagar,
Hyderabad – 500 037,
India.
Abstract:
A study has been conducted in three sub-watersheds to model the
spatial distribution of runoff and sediment yield. The basic
structure of the model includes generation of runoff using SCS curve
number (CN) method and soil detachment by RUSLE, MUSS and MUST
equations, which is in turn delimited by Kirkby’s transport capacity
equation. The input parameter grids – cover, practice and soil
erodibility grids were generated from satellite data with adequate
field check. Routing of runoff and sediment was done in ARC/INFO’s
GRID module. Predicted results were validated with field-measured
values. Results show that the runoff from CN method was better
estimated after accounting for depression storage. Results from two
hilly watersheds show that the standard error of sediment yield
prediction of RUSLE < MUSS < MUST equations. In a relatively flat
watershed, sediment yields were underestimated, due to
underestimation of transport capacity. Hence, there is a need to
address the transport capacity in plains and moderately sloping
areas.
Keywords: Runoff, sediment yield, GIS, remote sensing,
watershed, event-based.
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Performances of Stochastic
Approaches in Generating Low Streamflow Data for Drought Analysis
Kadri YUREKLI and Ahmet KURUNC, Gaziosmanpasa
Unıversity, Faculty of Agriculture, Department of Agricultural
Technology 60250 Tasliciftlik-Tokat/TURKEY.
Abstract:
This study analyzed the monthly-minimum daily discharge data of
each month from three gauge stations on Cekerek Stream for
forecasting using stochastic approaches. Initially non-parametric
test (Mann-Kendall) was used to identify the trend during study
period. The two approaches of stochastic modeling, ARIMA and Thomas-Fiering
models, were used to simulate the monthly-minimum daily discharge
data of each month. The error estimates (RMSE and MAE) of forecasts
from both approaches were compared to identify the most suitable
approach for reliable forecast. The two error estimates calculated
for two approaches indicate that ARIMA model appear to be slightly
better than Thomas-Fiering. However, both approaches were identified
as appropriate method for simulating the monthly-minimum daily
discharge data of each month from three gauge stations on Cekerek
Stream.
Key words:
monthly-minimum daily discharge, stochastic model, ARIMA, Thomas-Fiering
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Spatial Analysis of Urban
Stormwater Quality
M.
Ghafouri1 and C.E. Swain, 1. School of Engineering and
Technology, Deakin University, Geelong, Vic, 3217, Australia,
amrouzbe@deakin.edu.
Abstract:
Urban stormwater non-point source
pollutants are recognized as a major cause of receiving waters
quality deterioration. To date most research has focused on
specifying temporal variations of stormwater quality parameters
which includes high uncertainties and also increases the risk of
pollution control structures failure. Traditionally, the temporal
variations of quality parameters in forms of either pollutograph or
Event Mean Concentration (EMC) is obtained by sampling stormwater at
the outlet of urban catchments for quality analysis in addition to
measurement of flow rate over years. Spatial variations of the
runoff quality are the key factor in non-point source pollution
studies. This research investigates spatial variability of urban
runoff quality parameters such as Total Phosphorous (TP), Total
Nitrogen (TN), Suspended Solids (SS) and Biochemical Oxygen Demands
(BOD) in relation to land use of urban catchments. In spatial
analysis, stormwater will be sampled over the whole catchment area
for a number of rainfall events during a year without any
requirement to measure flow rate. This research showed comparable
results for average pollutant concentrations with those of other
urban catchments in Australia where traditional sampling method was
used. The research outcomes will reliably estimate pollutants
concentration for improved and efficient design of pollution control
structures for each land use.
Keywords: Spatial
analysis, temporal analysis, stormwater, Event Mean Concentration,
geostatistics, pollutants
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Spatial Modeling for Hydrological Response Behavior of an Arid
Watershed, India - Remote Sensing and GIS approach
Debashis Chakraborty1,
Dibyendu Dutta2 and H Chandrasekharan3,
1Division
of Agricultural Physics, Indian Agricultural Research Institute,
NewDelhi – 110 012, INDIA. E-mail:
debashis@iari.res.in /
debashisiari@hotmail.com ,
2Regional
Remote Sensing Service Centre (ISRO/DOS), CAZRI Campus, Jodhpur 342
003, India.,
3Water
Technology Centre, Indian Agricultural Research Institute, New Delhi
110 012, INDIA
Abstract: The
paper discusses the applications of satellite remote sensing and GIS
on characterization and spatial modeling of runoff and soil erosion
of Birantiya Kalan, an arid watershed in the district of Pali,
western Rajasthan. The watershed, with plains on the west and low to
medium hills on the east, is among the watersheds selected under the
National Watershed Development Project for Rainfed Areas by the
Government of India in 1988. Indian Remote Sensing Satellite Data
(IRS 1A/1B LISS II sensor) corresponding to pre-treatment (1988) and
post-treatment (1996) periods were used to study changes in the land
use/ land cover and vegetation status of the watershed. Suitable
weightages were given for the relative response of different land
use categories and vegetation types to various soil and water
conservation measures adopted under the said project over the years
(1988-1996). Composite values computed for land use/ land cover and
changes in vegetation vigour indicated a marginal improvement during
the period of study. Morphometric analysis revealed that the
watershed might produce moderate to peak runoff in a short period.
SCS Curve Number method and Universal Soil Loss Equation were
applied with ARC/INFO-GIS to predict the potential runoff and soil
erosion status of the watershed. An average of 50-70 mm (equivalent
of 20-30 per cent of the rainfall) runoff was predicted. Soil
erosion potential was found to be below the permissible limit and
increase in the runoff and soil erosion potential was observed in
1996. Apart from using land use and vegetation vigour information,
drainage buffer region was created to quantify the status of
vegetation along drains. This approach, coupled with analyses of the
corresponding data, could be used to suggest suitable
recommendations for furthering soil and water conservation measures.Key words: land use/ land cover, vegetation vigour, runoff,
soil erosion, remote sensing, GIS
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JoSHJournal
of Spatial Hydrology
ISSN: 1530-4736