Development of Protocol for Reservoir Sedimentation Prediction in 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. (Khorrami and Banihashemi, 2018) Suspended load is the most dominant material in reservoir bed. (Mulu and Dwarakish, 2015) The size of suspended load is very small, it is almost impossible to analyse by physical model. (JICA, 2007) Soil erosion potential is dynamic recently because it is influenced by land use change and precipitation dynamic. (Sukisno et al., 2021) Hydrodynamics of reservoir involves large area of water, one or several inflow(s), reservoir depth and many other factors. Those factors influence sedimentation distribution. (Hanmaiahgari et al., 2018) Modelling hydrodynamic and sediment transport of reservoir in one-dimension model is not realistic, especially because reservoir bed has three-dimensional feature. (Tadesse and Dai, 2019) Based on those reasons, sediment transport volume and distribution should be predicted more accurate for planning, operating and maintenance of the dam and reservoir, especially in Indonesia. This research developed a protocol for reservoir sedimentation prediction in Indonesia. It consists of soil erosion prediction that accommodate the change of land use and precipitation dynamic in catchment area, modelling long term sediment discharge, three-dimension reservoir sediment transport modelling, and prediction for reservoir sedimentation in the future. The aim of the research is to improve the accuracy of prediction for reservoir sedimentation volume and distribution on reservoir bed through development of protocol.  The protocol can be used to develop more effective strategy and managing during planning, operating and maintenance stage of reservoir, especially in Indonesia (Legono, 2019).

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

3.4.    Reservoir Sedimentation Prediction Result