Muskingum-Cunge model is based on kinematic wave theory
and is available alternative to the classıcal Muskingum method
(Chow, 1959) particularly for the cases where hydrologic data
i.e. stream flow data are not available, but where hydraulic data
(cross sectional data and channel slopes) can be readily
ascertained. In many instances, the Muskingum-Cunge method
is also an alternative to the more complex dynamic wave
models, while lack robustness and have significant data
requirements.
Advances in distributed parameter hydrologic modelling and its
integration with Geographical Information Systems (GIS) have
led to the development of powerful tools for predicting runoff
and simulating the physical, chemical and biochemical
processes that govern the transport of contaminants in
watersheds. Many researchers (White 1988; Stuebe and
Johnston 1990; Chowdary et al, 2004; Pandey et al, 2008)
used land use/land cover information derived from satellite data
of Landsat, SPOT, and Indian Remote Sensing Satellite (IRS)
and integrated them with GIS to estimate SCS CNs and runoff.
Several hydrologic models include ANSWERS (Areal Nonpoint
Source Watershed Environment Response Simulation) (Beasely
et al., 1980), AGNPS (Agricultural Nonpoint Source Pollution)
Young et al., 1987), WEPP (Water Erosion Prediction Project)
(Foster and Lane, 1987), and SWAT (Soil Water Assessment
Tool) (Arnold et al., 1995) are extensively being used for runoff
and sediment simulation.
The present study was taken with a specific objective of runoff
simulation from ungauged lateral inflows from sub watersheds
into main channel using USDA SCS-CN technique. In addition,
the Muskingum-Cunge method, which continues to be popular
for routing of runoff in river networks, was used to route surface
runoffs from different sub basin outlet points up to the outlet
point of the catchment. Effect of model grid sizes on runoff
simulation was also studied with varied grid sizes of 23, 46, 92,
184, 368, 736, 1472 m resolution.
2. METHODOLOGY
In the present study, overland flow in terms of direct runoff
from storm rainfall was computed using USDA Soil
Conservation Services (SCS) curve number technique and
subsequently it served as input to channel routing model. For
simulation of overland flow, spatially distributed curve numbers
for different antecedent moisture conditions serve as major
input to SCS-CN technique. For channel flow routing,
Muskingum-Cunge flood routing technique was used,
specifically to route surface runoff from the different sub
watershed outlet points to the outlet point of the watershed.
Muskingum technique allows the entire hydrograph to be
obtained at required cross sections instead of requiring solution
over entire length of channel for each time step as in kinematic
wave method. The ability of the proposed distributed rainfall-
runoff model to simulate spatial hydrological processes are
verified using storm events. Four of them were arbitrarily
chosen for model calibration and the others were used for model
verification. RMSE and CMR most widely used statistics
reported for hydrology model calibration and validation were
used in the present study.
2.1 Overland flow using SCS-CN technique
One of the most widely used technique for estimating storm
runoff depths; USDA Soil Conservation Service (SCS) Curve
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B8, 2012
XXII ISPRS Congress, 25 August — 01 September 2012, Melbourne, Australia
Number (CN) method was adopted. The basic assumption of the
SCS curve number is that, for a single storm event, potential
maximum soil retention is equal to the ratio of direct runoff to
available rainfall. This relationship, after algebraic manipulation
and inclusion of simplifying assumptions, results in the
following equations (USDA-SCS, 1972), where curve number
represents a convenient representation of potential soil retention
(Ponce and Hawkins, 1996). SCS-CN method is given as
follows:
(P-025/ .
= if P>025
o P 4 0.88. 4 (Eq. 1)
0=0 O.W.
gis 25100 sd (Eq. 2)
CN
where, P is rainfall in mm Q is runoff in mm, S is potential
maximum soil retention in mm and CN is Curve Number ranges
from 0 to 100, whose values were developed from annual flood
rainfall-runoff data from the literature for a variety of
watersheds generally less than one square km in area (USDA-
SCS, 1972) for different combinations of land use and soil.
After assigning the curve number for a unique combination of
soil hydrologic group, land use/cover and Antecenedent
moisture conditions, the potential maximum soil retention (S)
was calculated for each Hydrologic Response Unit (HRU).
Initially, the study watershed was decomposed into sub
watersheds and subsequently, sub watershed was delineated into
Hydrologic Response Unit (HRU) (Maidment, 1991), which
involves the aggregation of areas located with a unique
combination of soil and land use regardless of their spatial
position in the watershed in the GIS environment. An HRU
does not correspond to a physical location in the watershed,
routing between these units cannot be simulated. The estimated
runoff from each HRU is simply added together to obtain the
estimated flow at the watershed outlet.
2.1.1 Curve numbers adjusted with Antecedent Moisture
Condition (AMC)
The curve number varies for different antecedent moisture
conditions (AMC) and these conditions reflect the impact of
previous rainfall events on the soil’s moisture holding capacity.
The curve number shown in the equation 2 is for normal
antecedent moisture condition (AMC II), for dry condition
(AMC I) and wet condition (AMS III), equivalent curve
numbers can be computed by
_ 42CN2) _ 2ŒND
Ns “™ CN
(Eq. 3 and Eq. 4)
2.2 Muskingum-Cunge channel flood routing technique
The Muskingum-cunge method is a variant of the Muskingum
method (Chow, 1959) developed by Cunge (1969) and
documented in the Flood Studies report (Natural Environment
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