Sediment yield prediction based on analytical methods and mathematical modelling

[摘要] ENGLISH ABSTRACT: A study of the state of reservoir sedimentation in South Africa based on reservoirsediment deposit data, has shown that a considerable number of reservoirs haveserious sedimentation problems. The analysis of the reservoir sediment deposit datashowed that almost 25% of the total number of reservoirs have lost between 10 to30% of their original storage capacity. The average storage loss due to sedimentationin South African reservoirs is approximately 0.3% per year while the average annualstorage loss for all the reservoirs in the world is 0.8%.The aim of this research was to develop sediment yield prediction methods based onanalytical approaches and mathematical modelling. The sediment yield predictionmethods can be used in planning and management of water resources particularly inreservoir sedimentation control. The catchment erosion and sediment yield modellingmethods can be applied in temporal and spatial analysis of sediment yields whichresults are essential for detailed design of water resources, particularly in theidentification of critical erosion areas, sediment sources and formulation of catchmentmanagement strategies.Current analytical methods for the prediction of sediment yield have been reviewed.Nine sediment yield regions have been demarcated based on the observed sedimentyields and catchment characteristics. Empirical and probabilistic approaches wereinvestigated. The probabilistic approach is based on analysis of the observedsediment yields that were calculated from reservoir sediment deposit, river suspendedsediment sampling data and soil erodibility data. The empirical equations have beenderived from regression analysis of the variables that were envisaged to have asignificant effect on erosion and sediment yields in South Africa. Empirical equationshave been developed and shown to have accurate and reliable predictive capability insix of the nine regions.The probabilistic approach has been recommended for the prediction of sedimentyields in the remaining three regions where reliable regression equations could not bederived. The predictive accuracy of both the probabilistic and empirical approaches waschecked and verified using the discrepancy ratio and graphs of the observed andcalculated data.While the analytical methods are needed to predict the sediment yield for the wholecatchment, mathematical modelling to predict sediment yields is applied for moredetailed analysis of sediment yield within the catchment. An evaluation of availablecatchment sediment yield mathematical modelling systems was carried out. The maincriteria for the choice of a numerical model to be adopted for detailed evaluation wasbased on the following considerations: the model's capabilities, user requirementsand its application. The SHETRAN model (Ewen et al., 2000) was thereforespecifically chosen because of its ability to simulate relatively larger catchment areas(it can handle catchment scales from less than 1km2 to 2500km2), its ability tosimulate erosion in channels, gullies and landslides, its applicability to a wide rangeof land-use types and ability to simulate land use changes. Another model, ACRU(Smithers et al., 2002) was also reviewed.The aim of the model evaluation was to provide a conceptual understanding ofcatchment sediment yield modelling processes comprising model set up, calibration,validation and simulation. The detailed evaluation of the SHETRAN model was donethrough a case study of Glenmaggie Dam in Australia. The flow was calibrated andvalidated using data from 1975 to 1984, and 1996 to 2006 respectively. The resultsfor both the calibration and validation were reasonable and reliable. The sedimentload was validated against turbidity derived sediment load data from 1996 to 2006.The model was used to identify sources of sediment and areas of higher sedimentyield. The land use of a selected sub-catchment was altered to analyse the impact ofland use and vegetative cover on the sediment yield. Based on the results, theSHETRAN model was confirmed to be a reliable model for catchment sediment yieldmodelling including simulation of different land uses.

[发布机构] Stellenbosch University