Quantitative Estimation of Reservoir Sedimentation from Three Typhoon Events

Abstract

Study of soil erosion in the reservoir watershed, the main source of reservoir sedimentation that affects the reservoir's lifespan and capacity, is of vital importance for watershed management. Due mainly to the lack of data, empirical formulas are commonly used to estimate reservoir sedimentation. However, these estimations are far from accurate. Field measurements data of discharge and suspended sediment were collected during three typhoon events in Shihmen Reservoir watershed, Taiwan. Temporal variations of water surface elevation, discharge, and concentration of suspended sediment were measured. A numerical model, Hydrological Simulation Program Fortran ͑HSPF͒, developed by the USEPA was adopted to simulate the sediment yield. However, as calibration and verification data are not always available and the parameter-calibration process is complicated and tedious for novice users of the model, an artificial neural network ͑ANN͒ model was proposed. Significant amount of the synthetic data from the calibrated HSPF model were first generated to train the ANN model, which in turn was used to estimate the sediment yield. Comparisons of the sediment yield using both the HSPF and ANN model give correlation coefficients of 0.96 for training and 0.93 for validation. Without the complicated parameter calibration process, the ANN model was faster and easier to use than the HSPF model.

Reservoir infill by hyperpycnal deltas over bedrock

“…In Taiwan, a Gilbert‐type delta similar to case A has led to the recent infill of the small Ronghua reservoir, upstream of the large Shimen reservoir [ Capart et al , 2007]. In the Ronghua case, river inflow is highly turbid during flood [ Lee et al , 2006], yet homopycnal conditions prevail because the small reservoir rapidly becomes turbid itself, blurring the density contrast between inflow and lake. The large Shihmen reservoir, on the other hand, features deposits similar to case D, which become thicker rather than thinner going into the lake.…”

Modeling the sediment yield from landslides in the Shihmen Reservoir watershed, Taiwan

“…With advances in user-interaction, geographic information systems (GIS): and database technology, the current version of the HSPF 12 is integrated as a submodel in Better Assessment Science Integrating Point and Nonpoint Sources (BASINS) developed by the US Environmental Protection Agency (EPA). The HSPF model has been widely and successfully applied to the prediction of fluvial sediment transport (Moore et al, 1988;Chew et al, 1991;Laroche et al, 1996;Lee et al, 2006).…”

DAMP: A protocol for contextualising goodness-of-fit statistics in sediment-discharge data-driven modelling

“…However, numerous DDM solutions can be made explicit, by adjusting software settings, or by means of some minor re-coding, such that their internal structures and parameters can be extracted/exported and reported/shared. For example, Lee et al (2006) provided a neural network (NN) equation for estimating reservoir sedimentation due to typhoon events in Taiwan; provided a NN equation for estimating daily reference crop evapotranspiration in California, USA -albeit that the correctness of the latter has been placed in doubt (Abrahart et al, 2009). The alternative but less attractive option in such cases is to simply run a regular series through each original computer model and publish that paired input-output sequence in a spreadsheet.…”