Volume 5, Issue 1, January – 2020 International Journal of Innovative Science and Research Technology

ISSN No:-2456-2165

Rainfall-Runoff Relationship in Ungauged River

Basin: A Case Study of Shivganga Catchment in
Western Upland Maharashtra, India
Prashant P. Magar
Associate Professor
PG Dept. of Geography
Govt. Vidarbha Institute of Science & Humanities
Amravati (MAH), India 444604.

Abstract:- For all hydrologic analyses, a watershed I. INTRODUCTION

constitutes the spatial unit, and all hydrologic problems
are solved in the context of this spatial unit. There are Runoff characteristics are influenced by soil type,
number of indices, which can be defined to illustrate slope, vegetation, and many other conditions. Generally,
variability of hydrologic behavior such as rainfall, drainage basins behave differently based on these factors
runoff, evaporation, infiltration, peak discharge, unit and runoff varies greatly between mountain and valley
hydrograph, groundwater table and its fluctuation, areas. Steep canyon walls and channel slopes rapidly
movement to name but a few. An estimate of runoff concentrate storm runoff in mountainous areas. Runoff
volume from a drainage basin involves precipitation, concentrates rapidly in hilly areas. Valley areas are affected
infiltration, evaporation, transpiration, interception, by development. In highly developed valley areas, local
depression storage, each of which is complex and can runoff volumes increase as impervious materials replace the
interact with the other variables to either enhance or soil. Peak runoff rates for valley areas increase due to the
reduce runoff. These variables are variously distributed elimination of natural ponding areas and improved
within a drainage basin. The manner in which these hydraulic efficiency. Conveyances, such as streets and
variables interact in time and space makes a direct storm drain systems carry the water to the ocean more
determination of runoff very difficult. Therefore we rapidly and do not allow infiltration. The spatial extent and
estimate runoff by using methods that reflects combined pattern of runoff-contributing areas are affected by climate,
effect of the variables on an individual drainage basin. soil, and terrain characteristics.
Because no two drainage basins are exactly alike, no
two solutions can be exactly alike. The present chapter II. STUDY AREA
incorporates various methods used to estimate runoff in
the Shivganga drainage basin. The results obtained by The drainage basin taken up for the present study is
analyzing basin hydrological parameters such as situated in southwestern part of Pune district, Maharashtra.
rainfall, evaporation and infiltration have been Geographically it extends between 18° 13’ north to 18° 24’
presented in detail on the basis of field data and the north latitude and 73°45’ east to 73°56’ east longitude.
data obtained from various government agencies and Total geographical area of the basin is 131.25 km2. The
institutes. climate of the study area is tropical and semi-arid type.

Keywords:- Discharge, Evaporation, Interception,

Hydrology, Hydrograph, Runoff.

Fig 1:- Location Map of the Study Area

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Volume 5, Issue 1, January – 2020 International Journal of Innovative Science and Research Technology
ISSN No:-2456-2165
The basin receives about 600 mm of rainfall annually, about 90 percent of rain occurs during June to September. July and
August are the rainiest months. This proportion of rainfall decreases towards the eastern part of the basin. July is the rainiest
month throughout the basin, and accounts for 25% to 30% of the total annual rainfall. In absence of rainfall data from the
Shivganga Basin, the mean areal rainfall figures have been estimated from the surrounding raingauge sites (Velhe, Bhor and
Saswad). Since, the areal distance of these sites from the basin centre is 10 to 12km (fig.2).

Saswad
(600 mm)

Isohyet (mm)

Rainguage Station
with Ava. Annual Rf. (mm)

Velhe
(1300 mm)

Bhor (800 mm)

Fig 2:- Isohyetal Mean Areal Rainfall Distribution in Shivganga Basin and Location of Raingauge Stations (Source &
modified: IMD, Pune)

Table 1 show annual total and 24 hour peak rainfalls in the respective wet years (1985-1999) for above raingauge stations,
whereas table 2 shows the average annual rainfall for three raingauge stations of the surrounding area of the basin. These figures
of average annual rainfall have been obtained from India Metrological Department, Pune.

Water Raingauge Station

Year Bhor (South) Saswad (East) Velhe (SW)
ARF mm) HRF (mm) ARF (mm) HRF (mm) ARF (mm) HRF (mm)
1985 856.5 83.0 374.8 33.6 1922.6 143.0
1986 956.8 59.6 399.5 45.0 3389.0 283.0
1987 1506 134 839.2 183.2 1888.0 139.0
1988 897.5 105 1134.3 149.0 2567.0 297.0
1989 787.2 79.0 965.8 100.7 2259.0 230.0
1990 1027.8 87.0 824.5 156.0 2904.0 215.0
1991 1352.7 148.0 475.0 35.0 2437.0 210.0
1992 1136.4 103.0 539.2 36.5 2391.3 178.0
1993 1754.2 401.0 678.5 80.2 2050.0 100.0
1994 1773.5 175.0 734.1 58.0 4131.0 345.0
1995 742.9 62.0 554.7 39.0 1906.0 124.0
1996 1177.1 68.0 854.0 155.0 2403.0 284.0
1997 1401.0 77.0 530.0 53.0 3345.0 184.0
1998 1186.0 81.0 773.0 65.6 2456.0 107.0
1999 1654.0 145.0 589.5 42.8 3324.4 256.0
Table 1:- Annual Total and 24 Hrs Peak Rainfall (mm) of Rain gauge Stations Surrounding to the Shivganga Basin

(Data source: IMD; Based on 15 years of Record,

ARF=Annual Rainfall Total in mm, Water Year =from 01 June to 31 May of Next Year)
HRF= 24 Hours heaviest total rainfall in mm,

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Volume 5, Issue 1, January – 2020 International Journal of Innovative Science and Research Technology
ISSN No:-2456-2165
Rain gauging Station Location w. ref. Average Annual Rainfall
to Basin (Distance in km) (mm)
Bhor South (10) 800
Saswad East (10) 600
Velhe Southwest (12) 1300
Table 2:- Average Annual Rainfall of Three Raingauge Stations

(Data source: IMD; Based on 15 years of Record),

See: Fig. 2 for location of stations.

Isohyetal method has been used to estimate rainfall yield of the Shivganga Basin. This method is more appropriate for
computing mean areal rainfall in hilly and rugged topographical area (Suresh, 2005). As per IMD recommendations, in a region of
average elevation (500 to 1000m ASL) and in hilly areas one raingauge station should be available for the area of 130 to 260 sq.
km (Suresh, 2005). Isohyets have been drawn for Shivganga Basin on the basis of rainfall data available from surrounding
stations. The mean areal rainfall for study area has been determined by measuring the area of successive Isohyets. Thus the mean
areal rainfall values obtained for Shivganga Basin are shown in table 3.

Isohyets (mm) Area Enclosed Rainfall Volume (Cu. M) Mean Areal Rainfall
(Sq. km) (Area Enclosed X Mean Areal Rainfall) (mm)
A B C
800 10.0 8000.0
700 36.0 25200.0 =B/A
600 40.0 24000.0
500 45.0 22500.0 = 608.3
Total 131.0 79700.0
Table 3:- Mean Areal Rainfall by Isohyet Method
(Data source: IMD; Based on 15 years of Record)

Average areal rainfall computed from Isohyetal  Rainfall Frequency & Recurrence Interval
method is 608 mm. Fig. 2 shows the distribution of mean Frequency of rainfall event of a specified period is
areal rainfall and location of three raingauge sites expressed in terms of recurrence interval. Estimation of
surrounding the basin. Main stream of the Shivganga River recurrence interval of extreme maximum or extreme
originates in the heavy rainfall zone, whereas Shindewadi minimum rainfall event is useful for watershed planning
and Degaon sub basins heads in the medium to low rainfall and development. The probability of these extreme rainfall
zone in the eastern part of the basin. The orographic effect events is most significant while designing hydraulic
of the Singhgad-Katraj hill range in the western part is structures, implementing soil conservation practices etc. 24
responsible for enhancing the higher monsoon rainfall. In hours peak rainfall values from three raingauge stations
addition to this, the geographical location and the east-west were used to estimate the recurrence interval, that is the
orientation of the Shivganga Basin also determines the time span after which an event of similar or greater
distribution of rainfall over the entire basin. Thus spatial magnitude of the observed event is likely to occur –
variation of rainfall is controlled by orographic effect on
one side and the east west orientation of basin on the other, T= 1/p …………. (Eq. 1 – IV)
which is reflected in the isohyetal pattern of the basin. The
isohyetal pattern (Fig. 2) displays a marked spatial Where, T is the recurrence interval in years, p is the
variation in the basin form west to east. The source areas of plotting position of the event, which can be obtained by
Kondhanpur, Kelawade sub basin receive more than 800 using following formula -
mm rainfall. The amount of rainfall gradually decreases p (%)= m/n+1*100 …………. (Eq. 2 – IV)
towards east (Degaon, Shindewadi) i. e. less than 600 mm.
However, in this part, the drainage area is very less. The Where, m is the rank number of event after arranging
area of lowest rainfall (<500 mm) is situated along the rainfall data in descending order by their magnitude and ‘n’
eastern divide margin of Karha-Saswad plateau The is the total number of years of record. This method is
seasonal pattern is almost similar to the annual distribution referred as Weibull’s method (Singh, 1994). It is used to
of rainfall, since more than 90% of the annual rainfall is calculate the return periods of expected maximum rainfall
concentrated during the monsoon season. for a specified recurrence interval. Fig. 3 illustrates the
plots of three sites namely Bhor, Saswad and Velhe and
table 4 gives the recurrence intervals for different rainfall
maxima of respective raingauge stations.

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Volume 5, Issue 1, January – 2020 International Journal of Innovative Science and Research Technology
ISSN No:-2456-2165
100 100
Saswad
Bhor

Probability %
Probability %

y = -44.316Ln(x) + 237.23
2
10 R = 0.9498
10

1 1
50 100 150 200 250 300 350 400 30 50 70 90 110 130 150 170 190
Rainfall in mm Rainfall (mm)

100
Velhe
probability %

y = -70.678Ln(x) + 421.81
R2 = 0.9805
10

1
90 140 190 240 290 340
Rainfall (mm)

Fig 3:- Rainfall Frequency Curve for 24 Hours Peak Rainfall

(Based on Rainfall Data Analysis)

Raingauge Station Rainfall (mm) Probability ( %) Recurrence Interval (T) Years

400 06 16
200 10 9
Bhor 150 25 2
100 45 1
50 94 1
400 5 16
Velhe 150-250 50 2-3
100-150 95 1
180 5 16
Saswad 100 30 3
30-40 90 1
Table 4:- Recurrence Interval for Different rainfall maxima at Three Stations
(Source: Computed by Author)

III. RESULTS AND DISCUSSION associated with producing large runoff. Hence, the analysis
of the daily rainfall data reemphasizes the fact that high
The result demonstrate that although the maximum daily rainfall totals do not necessarily indicate the
24-hr rainfall values are associated with storm events over occurrence of flashy discharge or runoff in the Shivganga
the area surrounding to the Shivganga Basin, the upper River, if the storm event is localized and is of a short-
reaches (Kalyan, Kondhanpur), the middle reaches duration. Wet spells that are widespread, of a longer
(Shivapur, Khed), and lower reaches (Kelawade, Salwade, duration (2-3 day) are generally responsible for the high
Nasrapur) has significant impact in the form of rainfall to runoff.
have large flashy floods from the source to the confluence.
At Bhor and Velhe stations, 5 to 6 percent probability of Hydrologic Abstractions: Amount of precipitation,
400 mm rainfall in 24 hours has a recurrence interval of 16 which does not appear as overland flow or runoff, is
years while the probability of 100mm or less rainfall occurs considered as hydrologic abstractions. Evaporation and
every year whether the rainfall is above or below normal. infiltration are the most important abstractions in the
At Saswad station rainfall more than 100mm occurs once in hydrologic-budget equation. These abstractions are very
three years. This clearly indicates that, Shindewadi and small as compare to runoff event hence can be neglected.
Degaon (eastern sub basins) has very low probability of The bulk of evaporation takes place before runoff events is
100mm rain as compare to Kondhanpur and Kelawade sub usually long. Whereas infiltration occurs or commences as
basins, which are having greater probability of 100 mm soon as overland flow initiates. These losses have
rainfall i.e. every year. This indicates that highest daily significant influence in the available volume of water in the
precipitation totals do not necessarily indicate the basin. Therefore abstractions i. e. evaporation and
occurrence of highest runoff. Therefore, it is evident from infiltration losses must be considered in order to understand
the above discussion that though the magnitude of the 24-hr the total surface runoff generated from the rainfall.
rainfall is more at particular station, it may not be always

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Volume 5, Issue 1, January – 2020 International Journal of Innovative Science and Research Technology
ISSN No:-2456-2165
Evaporation Loss: Evaporation is an important the vicinity to about of 12 km areal distance in the north
hydrologic loss that affects the hydrological output or having similar climatic conditions. Mean monthly average
runoff of a river basin. Evaporation over the entire drainage pan evaporation values for the year 2005 have been
basin varies with season and is inversely related to rainfall. considered to obtain average annual evaporation for the
In order to know about evaporation losses of the Shivganga entire area. Table 5 shows monthly pan evaporation values
Basin, mean monthly pan evaporation data from Velhe for the year 2005.
station has been used, as the Shivganga Basin is situated in

Month (Evaporation Year 2005) Mean Monthly Evaporation (mm)

January 3.1
February 4.0
March 5.3
April 8.2
May 9.7
June 5.3
July 4.2
August 4.0
September 4.3
October 4.6
November 3.5
December 3.0
Table 5:- Mean Monthly Evaporation at Velhe
(Data Source: Tehsil Office, Velhe)

10

8
Pan Evaporation (mm)

ar
y ry ch r il ay ne ly st be
r
be
r
be
r
be
r
nu ua ar Ap M Ju Ju gu to
Ja br M Au em Oc e m em
Fe pt ov ec
Months (Year 2005) Se N D

Fig 4:- Mean Monthly Evaporation (mm) in Shivganga Basin

(Source: IMD, Pune)

On the basis of above values, average daily pan the statistics with Groundwater Survey and Development
evaporation of the Shivganga Basin comes fluctuates Agency, Pune (Sarbukan, 2001) and, Pune Z. P. Village-
around 5.0mm per day, and average annual evaporation is Shivar Water Content Computation Chart (2003), nearly
around 1800mm per year. Fig 4 reveals that summer 40% of the total rainfall loss is due to evaporation and 15%
months experience higher evaporation losses because of infiltration loss enhances the groundwater storage.
high temperatures, and negligible rainfall. The graph also Considering these 55% losses, net 45% rainfall is available
shows drastic reduction of evaporation during monsoon only for runoff.
season (June to September) whereas in winter also declines
after October maxima and gradual rise after January. As per

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Volume 5, Issue 1, January – 2020 International Journal of Innovative Science and Research Technology
ISSN No:-2456-2165
REFERENCES

[1]. Bhar, K.K. (2006). Watershed models for estimation

of discharge from ungauged basins. In ‘Predictions in
Ungauged Basins for Sustainable Water resource
Planning and Management’. Ed. By K. Srinivasa Raju.
Jain Brothers, New Delhi. pp.99-110.
[2]. Bhaskar, N. R.; Parida, B. P.; Nayak, A. K. 1997.
Flood Estimation for Ungauged Catchments Using the
GIUH. Journal of Water Resources Planning and
Management., ASCE 123(4): 228-238.
[3]. Bhatia, S.K. (2006). Predictions in Ungauged Basins
and Sustainable Water Resources- A overview. In
‘Predictions in Ungauged Basins for Sustainable
Water resource Planning and Management’. Ed. By K.
Srinivasa Raju. Jain Brothers, New Delhi. pp.1-16.
[4]. Chorley, R. J. (1957). Climate and morphometry,
Journal of Geology. 65. pp. 628-668.
[5]. Chorley, R. J. (1969). Water Earth and Man A
Synthesis of Hydrology, Geomorphology, and
Socioeconomic Geography. Methuen, London, pp.1-4.
[6]. Garde, R. J.; Kothyari, U. C. 1990. Flood estimation
in Indian catchments, Journal of Hydrology, 113: 135-
146.
[7]. Garg, D. M. (1977). Principles of Hydrology. Water
Information Centre, Hutington, New York. USA.
[8]. Goel, N. K. 1998. Flood Estimation in Sub-Himalayan
Region Using L-Moments. International Symposium
of ‘Hydrology of Ungauged Streams in Hilly Regions
for Small Hydro-Power Development’, New Delhi,
INDIA.
[9]. Goel, N. K.; Chander, S. 2002. Regionalisation of
Hydrological Parameter. State of Art Report No.
INCOH/SAR-24/ 2002, INCOH Secretariat, NIH,
Roorkee, India.
[10]. Sarbhukan, M. M. (2001). Water resources planning:
for sustainable development in Maharashtra. Publisher
A. M. Sarbhukan, Pune. Pp.37-52.
[11]. Suresh, R. (2005). Watershed Hydrology. Standard
Publishers, New Delhi. pp. 44-105.

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