Development of Semenyih Dam Storage Prediction Model

Transcription

1 Development of Semenyih Dam Storage Prediction Model Yong Siew Fang 1 & Yuhainis Kamardin 2 1, 2 G&P Water & Maritime Sdn Bhd Introduction Semenyih Dam is a regulating storage system to regulate the river flow for raw water abstraction at the Jenderam Hilir intake located at about 36 km downstream. Semenyih Dam is located at the upper reach of Sg Semenyih, a tributary of Sg Langat and has a catchment area of about 57 km 2. The catchment area at the intake is about 616 km2. The abstracted raw water is processed at Semenyih water treatment plant (WTP) and the treated water is supplied to the demand centres in the southwestern region of Kuala Lumpur, Petaling Jaya, Shah Alam, Klang and Putrajaya. The 2014 drought episode in Malaysia caused a great concern amongst the dam operators. Water rationing was imposed in certain states such as Negeri Sembilan, Selangor and Johor. During the critical period, the dam operators struggled between maintaining the reservoir storage while ensuring the daily demand was met. The capability to predict the dam storage changes under various rainfall conditions and release/abstraction operation became critical to optimise the limited water resources during the drought period. Semenyih Dam operator, Konsortium ABASS Sdn Bhd took the initiative to closely monitor the reservoir storage and water level, and appointed G&P Water & Maritme Sdn Bhd to develop an excelbased and easy-to-use reservoir Storage Prediction Model (SPM) for this purpose. Methodology For storage prediction purpose, there is a need to forecast the dam and the downstream incremental inflows. As the SPM is mainly dealing with the drought, inflow time series under three weather scenarios covering normal flow, 50-year low flow and no rain condition were pre-developed to serve as the model input data for reservoir storage predication purpose. The formulation of the SPM required in-depth understanding on the Semenyih Dam and Intake operation. The operations at Semenyih Dam and Jenderam Hilir Intake are clearly described in the Standard Operating Procedures of Semenyih Dam Release. As a regulating dam, the incremental flow from catchments downstream of the dam has been considered in the operation to minimise wastage of reservoir release. In addition to the release from Semenyih Dam, the intake has also been augmented by the pumping from a series of defunct mining ponds located at the downstream of Sg Langat-Sg Semenyih confluence (termed as WT1 pumping). The WT 1 pumping was in operation after the drought, which utilizes the water from Sg Langat catchment. From the operation in SOP, it is summarized that the storage of Semenyih Dam is mainly influenced by the inflow from the dam catchment, spillage, release and scouring discharge from the dam. The dam release is in turn dependant on the water abstraction at the Jenderam Hilir intake as well as the available inflow at the intake which is contributed by the incremental catchment area at the downstream of the dam and pumping from WT1 (external source from Sg Langat). The full supply level (FSL) of Semenyih Dam is at 111.0m, with a storage capacity of 61,653 ML. The dead storage level is at 84.3 m with storage capacity of 2,852 ML at which subsequently adopted as the

2 minimum operating level (MOL) in the SPM. Water supply abstraction at the intake is based on the average rate of 682 MLD. The reservoir storage shall be predicted by the SPM using reservoir water balance between the Inflows and Outflows: Reservoir Storage on day n = Inflow - Outflow Inflow = Reservoir Storage on day (n-1) + Dam Outflow Outflow = Computed Dam Release by SPM + Scouring Discharge + Reservoir Evaporation Main inputs to the SPM are the dam inflow and the incremental inflow from the catchment downstream of the dam to the intake point (hereby termed as downstream inflow ). The outputs from the SPM are the predicted reservoir storage, dam release, spillage as well the deficit at the intake. The computation of dam inflow and downstream incremental inflows via the water balance equations required the historical dam and intake operational records. Using the 20 years of available operational records, the dam and downstream inflows were computed as follow: The dam inflow is the summation of changes in reservoir storage, dam spillage, dam release, reservoir evaporation and dam scouring discharge. The downstream incremental inflow was computed by subtracting the release; spillage and scouring discharge of the dam as well as the WT1 pumping from the total flows arriving at the downstream intake. The WT1 pumping has to be subtracted as the flow comes from the external source of Sg Langat. The total flow arriving at the downstream intake is the total of the daily raw water abstraction and the daily average residual flow at the intake weir. Daily average residual flow was computed from the water level above the weir intake via the weir equation. The computed dam and incremental inflows using the dam operational records via the above described method were input to the SPM for simulation of the reservoir storage, dam release, spillage as well the deficit at the intake for model verification. The computed inflows series were also being used to developed the inflow time series under weather scenarios covering normal flow, 50-year low flow and no rain condition. The three weather conditions shall be served as the model input data for reservoir storage predication purpose. Model Verification The developed SPM was verified using the recorded reservoir storage and release in the two historical drought years of 1998 and The comparison between simulated daily reservoir storage and release with the historical records in 1998 and 2014 are illustrated in Figure 1(a), Figure 1(b), Figure 2(a) & Figure 2(b)). In general, the simulated storage by SPM matches well with the recorded storage. This shows that: The SPM algorithm is capable to reflect the current dam and intake operation practice. The computed inflow series using dam operational records represent the actual dam and incremental catchment flows. However, during the drought period, the recorded reservoir storage was lower than the simulated storage (Apr 1998 and Sept 2014). The discrepancies are mainly due to the following factors:

3 RELEASE (MLD) Storage (ML) 1. The SPM algorithm was developed based on the operating procedures. However, in the past operation during the drought, the dam owner may have released more to maintain the required abstraction at the intake. This caused the recorded reservoir storage to be lower than the simulated one by SPM. 2. There are unknown water abstraction activities by locals at the downstream of the dam as reported by the dam operator. This may cause losses from the dam release especially during the drought time which resulted more release to enable sufficient flow at the intake PREDICTED RESERVOIR STORAGE RECORDED STORAGE 5000 Dec-97 Feb-98 Apr-98 May-98 Jul-98 Sep-98 Oct-98 Dec-98 Jan-99 MONTH Figure 1(a): Recorded and Simulated Reservoir Storage in RECORDED AND COMPUTED RELEASE (1998) RECORDED RELEASE COMPUTED RELEASE FROM THE DAM Dec-97 Feb-98 Apr-98 May-98 Jul-98 Sep-98 Oct-98 Dec-98 Jan-99 MONTH Figure 1(b): Recorded and Simulated Release in 1998

4 RELEASE (MLD) Storage (ML) PREDICTED RESERVOIR STORAGE RECORDED STORAGE Nov-13 Jan-14 Mar-14 Apr-14 Jun-14 DAY Jul-14 Sep-14 Nov-14 Dec-14 Figure 2(a): Recorded and Simulated Reservoir Storage in RECORDED AND SIMULATED RELEASE (2014) RECORDED RELEASE 500 COMPUTED RELEASE FROM THE DAM Nov-13 Jan-14 Mar-14 Apr-14 Jun-14 Jul-14 MONTH Sep-14 Nov-14 Dec-14 Figure 2(b): Recorded and Simulated Release in 201 4

5 Predeveloped Inflow Series for Prediction by SPM To enable the prediction function by SPM, the inflow series under the following weather condition were developed using the computed dam and incremental inflow series: a) Normal flow condition, which is represented by a typical normal flow year. b) Any percentage of the normal flow condition, to represent the dry year flow c) 50-year low flow condition, which is represented by the 50-year low flow from the dam catchment and downstream catchments. d) No rain period condition, where the flows from dam catchment and downstream catchments are baseflow with recession. The no rain period condition shall follow specified rainfall temporal pattern. The long term mean daily flow was not adopted to represent the normal flow condition as it has normalised the daily flow variation as in the wet and dry period. To remove the normalizing effect due to the long-term averaging, the typical year of 2003, which shows daily flow variation in wet and dry periods yet has high correlation with the long term average daily inflows was selected to represent the normal flow. Storage Prediction Using Typical Normal Flow of Typical Year At the time of the development of SPM in Nov 2015, reservoir storage prediction was carried out to forecast the time required for the reservoir to recharge to FSL. Assuming typical flow of 2003 were to occur, the prediction shows that the reservoir was able to reach 95% of the FSL (58,333 ML) by 6 th February 2015 before it depleted during the dry period as expected in February and March (Figure 3). With wet month comes in April, the storage restored to its FSL by 25 th of April Figure 3: Reservoir Storage Prediction from 28th Nov th April 2015 under Typical Normal Flow Year

6 Storage Prediction using 50-Year ARI Monthly Low Flow Low flow frequency analysis was carried out on the long term monthly flow series to obtain the 50-year monthly low flow for the month of January to December. The predicted storage due to the 50-year monthly low flow (Figure 4) is found to be lower than the drought experienced in The storage shall reach 30% of FSL (18,713 ML) by the end of April Figure 4: Reservoir Storage Prediction from 28th Nov th April 2015 under 50-year Monthly Low Flow Storage Prediction under No-Rain Period Flow Condition A hypothetical no-rain period scenario, representing a worst-case scenario was developed following the rainfall temporal pattern in the catchment. Inflow series for the dam and downstream catchment resulted from the no-rain period condition was generated using rainfall-runoff modelling, with rainfall data from the rainfall stations within the dam and downstream catchment. The predicted storage using the no-rain day inflow series is the worst compared to the predicted storage under the 50-year monthly low flow and normal flow condition (Figure 5). After 28th Nov 2014, the storage rises to 92% of the FSL (56,777 ML) in mid of January 2015 contributed by the high inflows in November and December. After which, with inflow recesses to base flows in January, February and March due to no rain condition; the storage drops to 13% of the FSL (8,137 ML) at the end of April High releases from the dam are expected during this period to supplement the optimum production at the intake.

7 Figure 5: Reservoir Storage Prediction from 28th Nov th April 2015 under No Rain Period Inflow Conclusions The results show the capability of the SPM in predicting the reservoir storage which reflects the current operating procedure at the dam. It has been used as a daily operation tool by the dam operator since its development in It should be highlighted that the SPM should be used as a storage prediction tool for short term period; within 1 month to 3 months ahead. This is because the prediction accuracy decreases with the length of forecast period (lead time). The predicted storage should be updated whenever the actual recorded data is available to improve the forecast accuracy. During the pro-longed dry spells, information on when the dam storage will reach its critical level is deem important for better dam operation and planning. It is recommended that storage prediction via SPM be carried out with flow reduction in percentage on the predeveloped typical normal flow series for various scenarios assessment. The SPM is easy to operate and to be updated. It is capable of speedily producing sensible prediction on the reservoir storage for better management of the dam operation and reducing wastage in resources. The easily customizable model is highly appealing as the model set up can be easily modified to suit future changes in the dam operation, if any. The current SPM could be extended to forecast and optimize the daily dam release if sufficient telemetric rainfall stations are established in the catchment and a rainfall-runoff forecasting model for the dam and downstream catchment inflow is developed for this purpose.