(Srm) model application:
 SRM was developed by Martinec (1975) in small European basins.
 With the progress of satellite remote sensing of snow cover, SRM has been
applied to larger and larger basins.
 The Snowmelt-Runoff Model (SRM) is designed to simulate and forecast daily
stream flow in mountain basins where snowmelt is a major runoff factor.
 Most recently, it has also been applied to evaluate the effect of a changed climate
on seasonal snow cover and runoff.
 Recently, the runoff was modeled in the basin of the Ganges River, which has an
area of 917,444 km2 and an elevation range from 0 to 8,840 m, m.s.l.
 Contrary to the original assumptions, there appear to be no limits for application
with regard to the basin size and the elevation range.
Snowmelt Runoff Modeling
INPUT
STAGE
Basin
Elevation
DERIVATION
STAGE
MODEL
STAGE
SRTM Digital
Elevation
Model (DEM)
Slope &
Aspect.
Landsat 8
(OLI/TIRS
Bands)
Watershe
d
Snow cover
Mapping for
2013
Ancillary
Data
0.25˚ gridded
Daily Rainfall
Data_2013
Derivation of Parameters, Variables &
Constants
Qn+1 = {[CSn.an (Tn + ΔTn) Sn+
CRn.Pn].A.(10000/86400).(1-kn+1)}+ Qn.kn+1.
OUTPUT
STAGE
Daily Discharge Simulation
Daily
Temperatur
e for 2013
Snowmelt runoff model:
Qn+1 = {[CSn.an (Tn + ΔTn) Sn+ CRn.Pn].A.(10000/86400).(1-kn+1) }+ Qn
kn+1.
where:
Q
= average daily discharge [m3s-1]
C
= runoff coefficient expressing the losses as a ratio (runoff/precipitation),
with CS referring to snowmelt and CR to rain
a
= degree-day factor [cm oC-1d-1] indicating the snowmelt depth resulting from
1 degree-day
S
= ratio of the snow covered area to the total area
P
= precipitation contributing to runoff [cm].
A preselected threshold temperature, TCRIT, determines whether this contribution is
rainfall and immediate. If precipitation is determined by TCRIT to be new snow, it is
kept on storage over the hitherto snow free area until melting conditions occur.
A
= area of the basin or zone [km2]
Source: Jaroslav Martinec, Albert Rango & Ralph Roberts ., S R M - SNOWMELT RUNOFF MODEL,
USER’S MANUAL - UPDATED EDITION FOR WINDOWS, WinSRM Version 1.11 ., February, 2008.
T
= number of degree-days [oC d]
Δ T = the adjustment by temperature lapse rate when extrapolating the
temperature from the station to the average hypsometric elevation of the
basin or zone [oC d] (0.67 oC lapse per 100m rise in elevation) (17)
k
n
= recession coefficient indicating the decline of discharge in a period
without snowmelt or rainfall:
k = (m, m + 1 are the sequence of days during a true
recession flow period).
= sequence of days during the discharge computation period. Equation is
written for a time lag between the daily temperature cycle and the
resulting discharge cycle of 18 hours. In this case, the number of degreedays measured on the nth day corresponds to the discharge on the n + 1
day. Various lag times can be introduced by a subroutine.
10000
= conversion from cmkm2d-1 to m3 s-1
86400
 T, S and P are variables to be measured or determined each day, cR, cS, lapse rate
to determine T, TCRIT, k and the lag time are parameters which are characteristic
for a given basin or, more generally, for a given climate.
 If the elevation range of the basin exceeds 500 m, it is recommended that the
basin be subdivided into elevation zones of about 500 m each. For an elevation
range of 1500 m and three elevation zones A, B and C, the model equation
becomes:
A 1000

Qn 1  cSAna An Tn  TAn S An  cRAn PAn  A

86400

cSBnaBn Tn  TBn S Bn  cRBn PBn  AB 1000 
86400
AC 1000 
cSCn aCn Tn  TCn SCn  cRCn PCn 
 1  k n 1   Qn k n 1
86400 
Snowmelt runoff model necessities for execution:
1. Basin characteristics
1.1 Basin and zone areas
1.2 Aspect
1.2 Area-elevation curve (Hypsometric Mean)
2. Variables
2.1 Temperature,˚C
2.2 Precipitation, P
2.3 Snow covered area, S
3. Parameters
3.1 Runoff coefficient, c
3.2 Degree-day factor, a
3.3 Temperature lapse rate,
3.4 Critical temperature, TCRIT
3.5 Rainfall contributing area, RCA
3.6 Recession coefficient, k
3.7 Time Lag, L
4. SRM For Windows (Winsrm 1.11)
Basin Characteristics
Table 6: Showing area and % area of 6 elevation zones
S.no
Elevation Zones
Area in Sq.km
% Area
1
1158- 3000
186.76
13.68
2
3000 - 3500
138.96
10.18
3
3500 - 4000
166.45
12.19
4
4000 - 4500
213.38
15.63
5
4500 - 5000
305.63
22.38
6
5000 - 6772
354.35
25.95
Area Elevation curve – hypsometric mean elevation
8000
y = -0,0012x2 + 4,7025x + 1845,7
Area of Different Elevation Zones showing hypsometric mean
7000
elevation of each Zones
Elevation im "m"
6000
5000
4000
3000
2000
1000
Mean
Hypsometric
% Area
Area
Mean Elev.(m)
186.76
13.68
93.37
2557.33
3000 - 3500
138.96
10.18
256.19
3260.55
3
3500 - 4000
166.45
12.19
408.95
3764.79
4
4000 - 4500
213.38
15.63
598.86
4273.69
5
4500 - 5000
305.63
22.38
856.37
4766.4
6
5000 - 6672
354.35
25.95
1118
5263.19
Elevation
Area
Zone
in m
Sq.km
1
1158 - 3000
2
Ряд1
0
0,00
200,00
400,00
600,00
800,00 1000,00 1200,00 1400,00 1600,00
Area in Sq.km
in
zone wise aspect and its corresponding area
Daily temperature data
Daily minimum, Maximum values are collected and average is taken
as input
T
+T
Min
T = Max
2
Temperature - Extrapolation
T =   (h st - h ) .

h st
h
1
100
= temperature lapse rate [C per 100 m]
= altitude of the temperature station [m]
= hypsometric mean elevation of a zone [m]
Rainfall
 Distribution of rainfall varies in the different area of the catchment.
 0.25 degree gridded rainfall gives number of observations in the different zones of the
catchment.
 Each elevation zone covers 2 or 3 grids in the catchment.
 In that case average rainfall of number of grids is considered for each elevation zones in
rainfall derivations.
Snow cover Area
Multi temporal Satellite data used
APPLICATION OF SRM
Step 1: Entering of basin characteristics derived using DEM.
Step 2: It is add stimulation stage which is the second stage of adding constant parameters.
Step 3: Addition of variables are proceeded through clicking Data -> Variables-> period of
record, the table opened, from which the records prepared for 365 days san be added zone
wise.
Step 4: It involves in running the simulation to get the Discharge for the entire year. It can
be done by clicking Run -> Simulation -> Year Round Simulation using the model.
Discharge calculated for the year 2013
using this model and software
application gives quantum of annual
discharge of 2531.812 million cubic
meters in the Dhauliganga catchment.
Average discharge of about 80.283 m³/s
inferred from the simulated values.
Basin Discharge Simulation Results
 The discharge derived from the software for the year 2013 shows peak discharge of
1110 m³/s in the mid of June where the peaks of snow melt as well as rainfall occurs
together with total yearly discharge of 2531.28 Million m³ .
 Daily average discharge for the year is 80.283 m³/s where as 80% discharge occurs
in the month of June, July and August at an average rate of 200 to 450 m³/s.
conclusion
 Snowmelt runoff modeling for the Dhauliganga catchment area is done effectively by
integrated Remote Sensing based snow cover assessment, DEM and hydro
meteorological data in temperature index model.
 Further improvements can be made for achieving better results by validating the
model with observed discharge data, running the model for longer duration about 5 to
10 years and usage of high resolution optical cloud free data or microwave data for
snow melt runoff assessment.