| dc.description.abstract | Paso Ancho is run off river hydropower plant with an install capacity of 6.4MW and located in south west region of panama. The catchment area of the powerplant is highly exposed for erosion. Therefore, sedimentation is the main problem for the powerplant. Due to this several method of sediment management strategies has been applied. Such as mechanical removal, conventional dredging as well as currently installed SediCon dredging. The objective of this thesis is to estimate the sediment yield from the catchment area to the river by using RUSLE model, to evaluate sediment management strategy which is installed in the peaking pond by using RESCON 2 model. In addition, to measure and calculate the actual capacity of sediment management strategy from the field. And finally, the model results were proved to reasonably match the field data.
The required information’s and input data for this study were taken both from online sources and actual data taken during the field visit to the project area. The sediment yield estimation was done by using the RUSLE model with ArcGIS, and the result was satisfactory. The RESCON 2 model was used to evaluate the HSRS. The sediment yield to the river annually estimated around 0.089Mill.ton yr-1, which is 37,547m3 yr-1. The amount of sediment removed by HSRS from RESCON2 result is 33,771m3 yr-1 with sediment concentration through pipe of 7.78E+03ppm.
Sample taken from off-stream peaking pond shows that the sediment deposition is a mix of silt and sand. The capacity of SediCon dredging on sediment removal for 5 months shows that, 17,000 m3 of sediment removed for 382 hours with sediment concentration through pipe of 159E+03 ppm.
There is a large amount of sediment yield to the river and if 50% of it get transported to the off-stream peaking pond, then it will have significant impact on reduction of storage capacity. But the SediCon dredging which is installed in off-stream peaking pond used to remove the sediment per month is efficient and proved to perform better than the model result. | |
