Journal of Green Engineering (JGE)

Volume-11, Issue-3, March 2021

Hydrological Characteristic of Surface

Runoff in Saka River Basin
1
Rosmalinda Permatasari, 2Yuanita Windusari, 3Reni Andayani, 4Ani
Firda
1,3,4
Faculty of Engineering, University of Tridinanti Palembang, Indonesia
2
Faculty of Math and Science, University of Sriwijaya, Indonesia
2
E-mail:ywindusari@yahoo.com

Abstract

Water is very important for the existence of life and various purposes such as
for household needs, irrigation, industry, hydropower, and others. Changes in
the hydrological regime due to changes in land cover and climate could
endanger the sustainability of existing water resources. Integrated river basin
planning is needed in determining the correct policy in optimizing limited
water resources to meet the ever-increasing needs. The object of research is
the Saka River, especially the Komering watershed with a coverage of 1,240
km2. The purpose of this study was to define the hydrological characteristics
of the flow in the Saka River to hold and ensure the sustainability of water
resources. Most of the data used are secondary data. The results of the
analysis show that the largest flow rate occurred in January at 185,592 m3 / s
and the smallest in August at 17,942 m3 / s. The largest reliable discharge
occurred in January at 184,743 m3 / s, and the smallest reliable discharge
occurred in October at 5,784 m3 / s. Saka river water sources are not
sufficient for clean water because in April the river flow rate is smaller than
the dependable flow (Q90), while for the supply of clean water the flow rate
must be greater than the dependable flow (Q90) throughout the year.

Keywords: hydrology, surface runoff, dependable flow, Saka River Basin

Journal of Green Engineering, Vol. 11_3, 2626-2638.

© 2021 Alpha Publishers. All rights reserved
2627 Rosmalinda Permatasari et al.

1 Introduction

The existence of water plays a major role for all organisms and
humans needed for their survival. Although only about 2.5% is fresh water in
much of the water on earth, most of it is stored as glaciers or deep
groundwater and only a small part is accessible [1,2]. The water circulation
will form a hydrological cycle, where small changes in the hydrological
cycle and its system will have an impact (directly or indirectly) on global
climate change [3, 4]. Also, climate change in an area can have a major effect
on the hydrological characteristics of its watershed, which significantly
affects the timing and volume of runoff [5, 6]. Changes in water availability
and surface runoff will affect the extent of land cover and land use. Changes
in the land cover area and land use contribute to changes in the
characteristics of runoff from its watershed drainage (which in turn affects
the availability of surface water and groundwater) [7, 8, 9]. Therefore, it is
important to find out the magnitude of the runoff characteristics both as a
whole down to the sub-watershed level.

Figure 1 Map of Study Area

 Hydrological Characteristic of Surface Runoff in Saka River Basin 2628

The study above, which was carried out in the Saka River Basin, South
Sumatra, is part of the Komering River Basin with an area of 1,239.41 km2.
This study primarily aims to identify runoff hydrology in global land cover
and land use and water flows. The availability of water in the Sakariver is
needed for irrigation, drinking water, and ecosystem services. Consistent
water supply from upstream hilly areas is essential for downstream areas.
Sustainability in the management of drinking water in the catchment
area must be endeavored to ensure the availability of water in the long term
for industrial and urban fulfillment. Hydrology is very important for river
catchments in the management of integrated water resources and
hydrological processes play a major role in the assessment of water quantity
and quality as a result of rapid population changes and land use (in
developing watershed areas) [8, 10, 11 ]. River flow patterns are influenced
by rock types and the topography of the Komering watershed [12]. The
subsurface topography has a major influence on water storage (through the
flow path), so that geomorphic and topography affect the hydrology of
surface water or bottom flow in basins [13, 14]. Limestone and shale are
characteristic in the basin. The basin has two distinct forms of flow pattern,
medium and medium-smooth rectangular dendrite. Flow patterns affect
drainage system efficiency and hydrographic characteristics [15].

2 Methodology

2.1 Data

The model requires data on land, weather, and land use. Land use is
required for the simulating of a watershed hydrologically, while the soil
profile for simulating its hydrological characteristics.

Figure 2 Map of Land Use and Land Cover

2629 Rosmalinda Permatasari et al.

2.2 Models

Hydrological models (with their surface runoff and system balance)

are based on flow and precipitation, where one of the important indicators in
analyzing the impacts of climate change is the change of its hydrological
variables. For hydro-meteorological studies, the availability of continuous
and reliable flow data is needed, where the flow data is obtained from the
Department of Rivers and Watersheds (for the period 2008-2017). [15]
Model assumptions are used in the development of hydrological
models for the identification and assessment of surface flow in the Saka
watershed. The research phase is based on the development of the database in
the preparation of the river flow (along with the physical characteristics of
the watershed), and the evaluation and validity of the equation
The research phase is based on the development of the database in the
preparation of the river flow (along with the physical characteristics of the
watershed), and the evaluation and validity of the equation.

2.3 Evaluation of Runoff Simulation

For monthly data (2008-2017), surface runoff is obtained from the

rainfall calibration model [16]. The stages of research are as follows [17, 18,
19, 20]:
1. Monthly flow analysis on main flow characteristics follows the average,
maximum, or minimum and reliable flow in the Saka Basin.
2. The frequency distribution analysis flow is calculated following the
statistical distribution and conformity test program model.
3. Analysis of flow variation coefficients is calculated following the ratio of
standard deviation and the average flow rate in a watershed respectively
fluctuation or flow stability.
Cv = x 100%
(1)
Cv = Coefficient of variation
Sd = Standard deviation
CV < 10% good
CV > 10% poor
4. Coefficient of flow regime analysis is computed follows the ratio
maximum flow (Qmax) and minimum flow (Qmin). The formula
respectively as:
KRS =
(2)
KRS = Coefficient of flow regime
Qmax = maximum flow
Qmin = minimum flow
 Hydrological Characteristic of Surface Runoff in Saka River Basin 2630

KRS < 50 good

KRS = 50 – 120 moderate
KRS > 120 poor

3 Results and Discussion

3.1 Land Use and Land Cover of the Basin

Land-use change is a factor that affects changes in hydrological

function [7,8,9] which are presented in Table 1 and Figure 2 below:

Table 1 Land Use and Land Cover in Saka Basin

Percentage
No Land use Area (Ha)
(%)
1 Secondary forest 211.44 17.06
2 Shrub 279.36 22.54
3 Plantation 13.8 1.11
4 Mixed farming 232.39 18.75
5 Primary forest 83.66 6.75
6 Paddy field 15.37 1.24
7 Coffee farming 403.3 32.54
Total 1239.32 100

This study aims to assess changes in land use and land cover in recent
decades that affect the characteristics of the runoff. The analysis table shows
most of the land is used for coffee farming and shows 32.54% of the total
area. Primary and secondary forests are only 23.81% of the total area and
ideal conditions are below 30%, besides that, shrubs have a large number of
22.54%. The utilization of land, especially for plantations and rice fields, has
a small amount of 1.11% for plantations and 1.24% for rice fields. The global
results in the analysis of changes in land use and cover refer to the
hydrological correlations of the study area affecting dependable flow, return
periodic flooding,and flow regime coefficients in terms of land use and
cover.

Figure 3 Pie Chart Distribution of Land Use and Land Cover

2631 Rosmalinda Permatasari et al.

3.2 Discharge/ Flow Analysis

Hydrological analysis in Saka Basin implements discharges based on

rainfall and transforms them to flow. Discharge or flow data used in the
analysis is maximum flow in a year, daily flow data, and minimum flow data.
A maximum flow is used for flood discharge analysis onsite, whereas daily
flow to compute dependable flow and flow duration curve (probability and
discharge relation). The variance flow data are needed to classified and
accurate data analysis in particular to calculate runoff coefficient and
hydrograph time series [21,22]. Time series flow in the study area is present
in Figure 4.

Figure 4 Time Series Flow Data

Furthermore, time-series flow data is utilized to calculate average,

minimum, maximum, dependable flow 80% and 90%, and monthly standard
deviation. The results are presented in Table 2 and Figure 5.

Table 2 Discharge / Flow Data

Year Jan Feb Mar Apr May Jun Jul Ags Sep Oct Nov Dec
2008 184.65 118.43 80.21 86.16 42.17 50.72 24.54 22.06 12.11 36.77 43.3 30.21
2009 196.64 145.68 91.24 81.56 48.25 49.16 24.42 14.65 9.09 7.26 21.39 36.91
2010 238.93 213.26 147.57 85.64 71.64 44.5 63.46 47.49 72.62 32.81 46.41 21.74
2011 210.2 140.83 75.01 81.11 48.27 29.66 37.5 18.26 11.32 11.48 32.39 67.59
2012 191.83 194.89 99.71 100.68 57.82 34.29 19.91 11.95 7.41 14.47 53.86 70.91
2013 216.19 158.89 111.48 105.51 96.65 60.16 69.24 50.47 61.41 37.45 53.66 69.4
2014 202.4 130.4 102.79 78.83 66.8 46.73 46.02 38.9 20.79 12.07 54.65 44.11
2015 205.24 160.66 11.57 89.48 65.15 36.53 28.55 15.61 9.68 5.62 30.5 57.24
2016 217.52 179.51 153.79 161.41 104.11 74.35 50.95 36.51 49.58 63.09 106.97 46.86
2017 185.59 149.37 88.13 70.76 77.88 55.25 30.4 17.94 25.12 32.36 69.74 53.68
Max 238.93 213.26 153.79 161.41 104.11 74.35 69.24 50.47 72.62 63.09 106.97 70.91
Min 184.65 118.43 11.57 70.76 42.17 29.66 19.91 11.95 7.41 5.62 21.39 21.74
Avg 204.92 159.19 96.15 94.11 67.87 48.14 39.50 27.38 27.91 25.34 51.29 49.87
Q
80% 191.83 140.83 80.21 81.11 48.27 36.53 24.54 15.61 9.68 11.48 32.39 36.91
Q
90% 185.59 130.4 75.01 78.83 48.25 34.29 24.42 14.65 9.09 7.26 30.5 30.21
 Hydrological Characteristic of Surface Runoff in Saka River Basin 2632

Figure 5 Monthly Flow

The dependable flows are 80% and 90% (Q80 and Q90) from
discharge data in 10 years (2008 – 2017). The result shown (based on Table 2
and Figure 5) the maximum flow occurred in January in value 238.93 m3/s
and the minimum was in October at 5.78 m3/s. The average flow in 10 years
period shown number 74.31 m3/s.

3.3 Dependable Flow

Dependable flow means the proper water availability or the certain

flow sustainability for water requirements such as irrigation, drinking,
industrial, electricity generation, and ecosystem river service [11,12]. Flow
duration curve present in Table 3 and Figure 6.

Table 3 Dependable Flow

Percentage Flow mm/day

(%) (m3/sec)
10 114.93 1.39
20 97.60 1.18
30 86.62 1.05
40 78.09 0.95
50 73.83 0.89
60 67.42 0.82
70 64.30 0.78
80 59.12 0.72
90 55.71 0.67
100 45.44 0.55
2633 Rosmalinda Permatasari et al.

Figure 6 Flow Duration Curve

Based on Table 3, it is showed dependable flow 80% (Q80) used to be

chosen for design discharge of drinking water demand (at number 59.12
m3/sec or 0.72 mm/day). On the other hand, dependable flow 90% (Q90)
used to be for design discharge of irrigation, electricity, and others at number
55.71 m3/sec or 0.67 mm/day.

3.4 Design Flood Discharge / Flow

Flood, either observed from the beginning or synthetic, is determined

as a reference for the design of the hydraulic structure [23]. The designed
flood flow usually uses the maximum discharge/flow in the annual period
and is calculated following the statistical distribution and the conformity test
program model [15, 16, 17]. The results are presented in Table 4 and Figure
7.

Table 4 Return Period

Return
(m3/sec) m3/sec/Km2 mm/day
Period
2 205.23 16.56 2.48
5 219.05 17.68 2.65
10 226.28 18.26 2.74
20 232.25 18.74 2.81
50 238.97 19.28 2.89
100 243.45 19.64 2.95
 Hydrological Characteristic of Surface Runoff in Saka River Basin 2634

Figure 7 Return Period

Table 4 shows the return period-flow for design flood, particularly for
drainage infrastructure to hold on runoff for a short period before release to
the natural watercourse. Designed flood discharge for major drainage utilizes
a return period of 5 – 10 years, and macro drainage (especially for
catchments area) uses a return period of 50 – 100 years [19, 21]. On the
table, the return period (in 5 years) is 219.05 m3/sec and 226.28 m3/sec (in
10 years). Furthermore, design flood discharge macro at 238.97 m3/sec in
return period 50 years and 243.45 m3/sec in return period 100 years.

3.5 Basin Regime Coefficient Analysis

Basin regime coefficient analysis to identification and classification

basin performs, particularly fluctuation and discharge/ flow sustainability
[20]. Flow regime a range of stream flows having similar bedforms, flow
resistance, and means of transporting sediment [23]. Table 5 and Figure 8
represent the result analysis.

Table 5 Basin Regime Coefficient Analysis

Max Min Average

Year (m3/sec) (m3/sec) (m3/sec) StDev CV Coeff
2008 184.65 12.11 60.94 49.67 81.49 15.25
2009 196.64 7.26 60.52 59.10 97.66 27.09
2010 238.93 21.74 90.51 71.19 78.66 10.99
2011 210.20 11.32 63.64 59.13 92.92 18.57
2012 194.89 7.41 71.48 65.23 91.26 26.30
2013 216.19 37.45 90.88 51.89 57.10 5.77
2014 202.40 12.07 70.37 53.18 75.56 16.77
2015 205.24 5.62 59.65 63.49 106.44 36.52
2016 217.52 36.51 103.72 60.69 58.52 5.96
2017 185.59 17.94 71.35 50.65 70.99 10.35
2635 Rosmalinda Permatasari et al.

Figure 8 Coefficient Basin Regime

The range value of the basin regime (as well as analysis of the physical
condition of Saka Basin) can be a reference for the classification of
fluctuation or flow sustainability. According to Table 5, the analysis results
during 10 years (2008-2017) clarifies that The Saka basin is in poor
classification. From the data analysis, the coefficient variant at up 10% (CV
> 10%). The verified classification explains the bearing capacity of Saka
Basin and degradation level or accomplish. Furthermore, the determination
classification needs advanced identification by reviewing the ultimate
carrying capacity of the watershed in water availability and level of
watershed damage [12].

4 Conclusions

The land use and land cover in Saka Basin consist of secondary forest,
shrub, plantation, mixed farming, primary forest, paddy field, and coffee
farming. The result analysis shows mostly land used for coffee farming
32.54% from the total area, primary and secondary forest neither ideal
condition only 23.81% from the total area and land covered shrub at amount
22.54%. Moreover, land use particularly for plantation and paddy field with
area 1.11% for plantation and 1.24% for paddy fields.
Hydrological analysis of the Saka Basin based on rainfall transfer to
discharge/ flow data. The maximum flow occurred in January in value
238.93 m3/s, thus the minimum flow was in October at 5.78 m3/s. The
average flow in 10 years period shown number 74.31 m3/s. In general critical
water, availability begins from August to October. Dependable flow for
water requirement show result from dependable flow 80% (Q80) that used to
 Hydrological Characteristic of Surface Runoff in Saka River Basin 2636

design discharge drinking water demand at number 59.12 m3/sec or 0.72

mm/day and dependable flow 90% (Q90) that used to design discharge
irrigation, electricity and others at number 55.71 m3/sec or 0.67 mm/day.
Design flood discharge for drainage or other water infrastructure
shows a return period at 5 years at 219.05 m3/sec and a return period at 10
years at 226.28 m3/sec. Furthermore design flood discharge macro at 238.97
m3/sec in return period 50 years and 243.45 m3/sec in return period 100
years. The results of the basin regime analysis during 10 years (2008-2017)
the coefficient variant at up 10% (CV > 10%) and it indicates that river
condition in the critical or poor category.

Acknowledgments

This paper is supported by the University of Tridinanti Palembang and

part of a research publication funded by YayasanTridinanti Palembang.

References

[1]R. Naiman, D. Dudgeon, “Global Alteration of Freshwaters: Influences on

Human and Environmental Wellbeing”, Ecol. Res., Vol. 26, pp. 865–
873, 2011.
[2] P.Singh, U. K. Haritashya, N. Kumar, Y. Singh, “Hydrological
Characteristics of the Gangotri Glacier, Central Himalayas, India”,
Journal of Hydrology., Vol. 327, no. 1-2, pp. 55-67, 2006.
[3] B.C. Bates, Z.W. Kundzewicz, S. Wu, J.P. Palutikof, “Climate Change
and Water”, Intergovernmental Panel on Climate Change, 2008.
[4] J.R. Thompson, A.J. Green, D.G. Kingston, “Potential Evapotranspiration
Related Uncertainty in Climate Change Impacts on River Flow: An
Assessment for The Mekong River Basin”, Journal of Hydrology., Vol.
510, pp. 259-279, 2014.
[5] Y.N. Chen, C.C. Xu, Y.H.Yang, et al., “Hydrology and Water Resources
Variation and Its Responses to Regional Climate Change in Xinjiang”,
Journal of Geogr. Scien., Vol. 20, pp. 599-561, 2010.
[6] X. Ma, J. Xu, Y. Luo, S. Prasad, Aggarwal, J. Li, “Response of
Hydrological Processes to Land Cover and Climate Changes in Kejie
Watershed, South‐West China”, Hydrological Processes., Vol. 23, no. 8,
pp. 1179-1191, 2009.
[7] N.Sajikumar, R.S. Remya, “Impact of Land Cover and Land Use Change
on Runoff Characteristics”, Journal of Environmental Management, Vol.
161, pp. 460-468, 2015.
[8] A. Gustard, A.J. Wesselink, “Impact of Land Use Change on Water
Resources – Balquhidder Catchments”, Journal of Hydrology, Vol. 145,
no. 3-4, pp. 389–401, 1993.
2637 Rosmalinda Permatasari et al.

[9] F.Githui, F. Mutua, W.Bauwens, “Estimating The Impacts of Land Cover

Change on Runoff Using The Soil and Water Assessment tool (SWAT):
Case Study of Nzoia Catchment, Kenya”, Hydrol. Sci. J., Vol. 54, no. 5,
pp. 899-908, 2009.
[10] S. Sun, H. Chen, W. Ju, M. Yu, W. Hua, Y. Yin, “On The Attribution of
The Changing Hydrological Cycle in Poyang Lake Basin, China”,
Journal of Hydrology., Vol. 514, pp. 214–225, 2014.
[11] K.W . Potter, “Small Scale, Spatially Distributed Water Management
Practices: Implications for Research in The Hydrologic Sciences”, Water
Resources Research, Vol. 42, pp. 1-2, 2006.
[12] R. Permatasari, Arwin, D.K. Natakusumah, H. Samaulah, “Effect of
Watershed Topography and Land Use on Baseflow Hydrology in
Upstream Komering South Sumatera, Indonesia”., International Journal
of Geomate., Vol. 17, no. 59, pp.28 – 33, 2019.
[13] K. D. Adams, D. W. Sada, “Surface Water Hydrology and Geomorphic
Characterization of a Playa Lake System: Implications for Monitoring
The Effects of Climate Change”, Journal of Hydrology, Vol. 510, pp. 92-
102, 2014.
[14] R. A. Brown, G. B. Pasternack, “Hydrologic and Topographic
Variability Modulate Channel Change in Mountain Rivers”, Journal of
Hydrology, Vol. 510, pp. 551-564, 2014.
[15] Anonimous, “River Watershed Measurement and Monitoring Data”,
Major River Basin Organization (BBWS) 2007.
[16] Anonimous, “Climatology Data”, Meteorological, Climatological, and
Geophysical Agency (BMKG), Available Online:
https://www.bmkg.go.id/?lang=EN
[17] M.R. Spiegel, “Schaum’s Outline of Theory and Problems of
Probability and Statistics”, McGraw-Hill, 1976.
[18] V.T. Chow, D.R. Maidment, , L.W.Mays, “Handbook Applied
Hydrology”, McGraw-Hill, 2017.
[19] I. M. Kamiana, “Teknik Perhitungan Debit Rencana Bangunan Air”,
Graha Ilmu Yogyakarta, 2010.
[20] C. Asdak, “Hidrologi dan Pengolahan Daerah Aliran Sungai (DAS)”,
UGM Press, 2002.
[21] G.T. Aronica, A. Candela, “Derivation of flood frequency Curves in
Poorly Gauged Mediterranean Catchments Using a Simple Stochastic
Hydrological Rainfall-Runoff Model”, Journal of Hydrology., Vol. 347,
no. 1-2, pp. 132– 142, 2007.
[22] T. Karmaker, S. Dutta, “Generation of Synthetic Seasonal Hydrographs
for A Large River Basin”, Journal of Hydrology, Vol. 381, no. 3-4, pp.
287-296, 2010.
[23] H. Sianawati, “Kamus Istilah Hidrologi Teknik”, Gramedia Pustaka
Utama, 2009.
 Hydrological Characteristic of Surface Runoff in Saka River Basin 2638

Rosmalinda Permatasari, Faculty of Engineering, University of Tridinanti

Palembang, Indonesia

Yuanita Windusari, Faculty of Math and Science, University of Sriwijaya,

Indonesia

Reni Andayani, Faculty of Engineering, University of Tridinanti

Palembang, Indonesia

Ani Firda, Faculty of Engineering, University of Tridinanti Palembang,

Indonesia