Published at : 10 Jul 2024
Volume : IJtech
Vol 15, No 4 (2024)
DOI : https://doi.org/10.14716/ijtech.v15i4.5622
Arbor Reseda | Department of Civil Engineering, Faculty of Engineering Universitas Indonesia, Depok 16424, Indonesia |
Dwita Sutjiningsih | Department of Civil Engineering, Faculty of Engineering Universitas Indonesia, Depok 16424, Indonesia |
Setyo Sarwanto Moersidik | Department of Civil Engineering, Faculty of Engineering Universitas Indonesia, Depok 16424, Indonesia |
Dead storage of reservoir usually designed by soil
erosion rate of catchment area result in certain year without considering land
use and precipitation dynamic in the catchment and sedimentation distribution
analysis at the bottom of the reservoir as well. Development of protocol is
needed for more accurate prediction of reservoir sediment transport to describe
the real condition and accommodate data limitations. It will give good
perspective in design, operation and maintenance strategy for reservoir. The
proposed protocol is consisted of long-term soil erosion prediction, modelling
long-term sediment discharge, modelling spatial-temporal reservoir sediment
transport and predicting reservoir sediment volume and distribution in the
future. The case study is in Wonogiri reservoir, Indonesia. Simulation of the
proposed protocol at the case study began by obtaining long-term soil erosion
prediction from 1993 – 2019. Sediment discharge was modelled from soil erosion
and synthetic long-term hydrographs using the FJ Mock method and validated with
sediment rate measured directly in the field. Reservoir sediment transport
model was using MIKE software. The simulation gives volume and distribution of
sedimentation validated by bathymetry result of the reservoir. Prediction of
future sedimentation was using the modular regression method. This protocol
promotes spatial reservoir sediment transport model and sedimentation
prediction by modular regression. The prediction result of reservoir sediment
volume in 2069 is 146.7 million m³.
Reservoir sedimentation prediction; Reservoir sediment transport; Sediment discharge
Reservoirs play significant role
for water resources management to fulfil the need for irrigation, raw water
supply, flood control, hydro power, etc. Process of planning, operation and
maintenance play significant role to ensure reservoir lifetime. Sedimentation
is reservoir problem that can reduce its lifetime service. Based on previous
research result in Indonesia, sedimentation is reducing reservoir volume about
1-3% every year (Armidoa et al., 2020; Brontowiyono,
2019; Sucahyanto, Setiawan, and
Septiani, 2018;
Fauzi and Wicaksono, 2016; JICA, 2007). The other problem to manage sedimentation in Indonesia is
limited data especially for continues discharge and sediment rate data. (Sutjiningsih Soeryantono, and Anggraheni, 2015) Material
of soil erosion in catchment area of reservoir is transported by river
discharge to become bed load and suspended load. Meanwhile bed load deposited
in the upper side of river, suspended load transport to reservoir and when it
meets zero velocity in reservoir area, it will be deposited in reservoir bed by
gravity.
Case study for this research is
Wonogiri reservoir, built in the eighties and located in Wonogiri Regency,
Central Java Province, Indonesia. Catchment area of Wonogiri Reservoir is about
1,350 km² and reservoir area is about 88,000 ha. Wonogiri Reservoir is chosen
because it has got complicated sedimentation problems in recent years. There
are six main inflows to Wonogiri reservoir, which are Keduang river, Tirtomoyo
river, Patemon River, Bengawan Solo River, Alang river and Wuryantoro river.
Therefore, it will give a good perspective for sedimentation distribution
analysis. (Susilo, Wicaksono, and Yanti, 2016)
Bathymetry data of Wonogiri reservoir is sufficient for calibration and
validation, since there are three-year available data which are 1993, 1998 and
2004. (JICA, 2007) Until now, reservoir
sedimentation analysis based on soil erosion of catchment area in certain year.
In recent year when land use and precipitation radically change in a lot of
area in Indonesia, it is needed to revise the prediction of potential soil erosion
for reservoir. (Sudarsono, Sukmono, and Santoso, 2017)
Reservoir hydrodynamic phenomena involves certain forces like velocity from
inflow and sediment discharge in x,y,z vectors, tension from reservoir banks
controlled by shape and size of reservoir, particle size and gravity force at
very least (Imanshoar et al., 2014).
Figure
1 Flow Chart
of Protocol for Reservoir Sedimentation Prediction
2.1. Method
for soil erosion prediction
Yearly soil erosion potential is
analysed using USLE method. USLE method is used to accommodate lack of data,
especially run off and discharge data. (Gwapedza, Hughes,
and Slaughter, 2018) To accommodate precipitation and land use
dynamic in catchment area, soil erosion is analysed in long term, at least ten
years, using land use map and precipitation data in the same years. (Abdulkareem et al., 2019) Precipitation is factor that
always change from time to time. (Anggraheni et
al., 2018) Precipitation data based on climatology data in catchment
area can be input. (Juniati et al., 2019) The
change of precipitation’s trend will give influence to amount of soil erosion
potential. (Sardar
et al., 2014) Land use in reservoir catchment area in Indonesia
changes rapidly. Land use change is exercised in yearly basis. Analysis trend
of land use change in USLE method, represented in C and P, is basic concept to
analyse dynamic soil erosion potential in reservoir catchment area. Since USLE
method is used, it is assumed the only external force for soil erosion is
precipitation (Abdulkareem
et al., 2019; Pham, Degenera, and Kappasa, 2018).
2.2.
Method for
Sediment Discharge Modelling
Reservoir hydrodynamic analysis
is very important step in this improved protocol. One of main input for
reservoir hydrodynamic process is long term sediment discharge, from every
inflow to reservoir. By using continues inflow discharge data and sediment concentration,
measured from reservoir site, sediment discharge can be modelled comfortably. (JICA, 2007) The problem is limited long term
inflow discharge data in most of reservoir in Indonesia, some method should be
created to model sediment discharge which is transformed from yearly soil
erosion result as the steps is described in Figure 2.
Figure
2 Steps for
Daily sediment discharge model
2.2. Method for
Reservoir Hydrodynamic Modelling
Figure 3 Steps for reservoir sedimentation
hydrodynamic model
2.2.
Method for Reservoir Volume Prediction in the Future
Figure 4 Steps for Reservoir Volume Prediction in the
Future
3.1. Soil Erosion
Prediction Result
USLE method is used for soil erosion
prediction in Wonogiri reservoir catchment area from 1993 to 2019, that said 27
years data. From those data some interesting result can be found, such as:
· Soil erosion fluctuating result
is influenced by dynamic precipitation and land use change. From 2017 and 2018,
land use was drastically changed, C and P values increased. In 2019, there was
replantation effort in catchment area, so C and P values decreased. See Table
1.
· There is very low erosion rate in
1997 while in the contrary in 2010 the rate is very high. Those numbers are
highly influenced by yearly precipitation value. Soil erosion prediction is not
only influenced by land use change but also influenced by precipitation.
· Dead storage designed by only one
year soil prediction to represent reservoir lifetime is not appropriate. Long
term yearly soil erosion prediction is mandatory to design dead storage and
sediment transport prediction, especially in recent time.
Figure 5 Soil erosion prediction in year 1993 – 2019
3.2.
Sediment
Discharge Model Result
Modelling sediment discharge from
yearly soil erosion prediction is one of main contribution of this research
since it bridges the gap between limited data and requirement of sediment
discharge as the important input in modelling three-dimension sediment
transport analysis. Sediment discharge is analysed from three variable, which
are soil erosion result, hydrograph from FJ Mock method and inflow sediment
concentration, measured from six inflow to reservoir. Daily discharge
hydrograph model from each inflow by FJ Mock method is representative since it
considers baseflow, so there is no zero discharge in the hydrograph. Daily sediment rate was measured
from the field from March, 7th 2021 to March, 25th 2021. Soil erosion
prediction is analysed from 1993 – 2019. Measured sediment rate data is
validated with Oceanic Nino Index. Index of March 2021 is similar to March 2018.
Sediment discharge equation is modelled from sediment rate to erosion rate
curve. Correlation coefficient value is 0.7861,
see Figure 6. More data of inflow sediment concentration will increase
correlation number. Correlation and determination value of sediment discharge
equation is less than 1 indicating that soil erosion prediction and sediment
flowing to reservoir is not same amount. This happens because of:
·
It is not every eroded soil flowed to the river
·
Eroded river bed and river bank material is not calculated in USLE
method
Figure 6 soil
erosion-discharge curve by power function
3.3. Spatial-temporal
Reservoir Sediment Transport Analysis Result
Sediment transport
model use MIKE software to process in three-dimension model. Sediment transport
is analyzed from 1993 to 2019 and sediment volume result is validated by
bathymetry data measured in 1998, and 2004. Determination coefficient is 0.93
and 0.84. Based on Size and shape of Wonogiri reservoir, it requires 0.1 s time
step process. Outflow is assumed 29.3 m³/second, requirement for hydropower in
Wonogiri reservoir. Evaporation and precipitation in reservoir are negligible
since reservoir area is relatively very small compared to catchment area
(8.8/1,350). Sediment transport analysis in Wonogiri reservoir using MIKE
software. See Table 3 and Figure 7. More detail topography result will give
more efficient time process. By the result, it is understood that sediment from
Keduang River gave influence to reservoir life time more than other rivers
based on its position and sediment supply because it can cover intake of the
dam faster than sediments from other rivers.
Figure 7 Sediment
transport analysis result in year 1993 (left) and 2019 (right)
Table
4 Result
Comparison from other studies
Study |
Prediction |
JICA
1974 |
5.2
million/year |
Research
and Development Center of Water Resources, 1982 and 1984 |
1.2
million/year |
Faculty of Geography, Gajahmada
University, 1984 and 1985 |
6.6
million/year |
Bengawan Solo Project and
Brantas Project, 1985 |
8.1
million/year |
BRLKT Watershed Solo, 1985 |
6.6
million/year |
JICA, 2000 |
4.5
million/year |
JICA 2007, 1993-2004 |
2.9 million/year |
This Research |
3.14
illion/year |
3.4.
Reservoir Sedimentation
Prediction Result