Browsing by Author "Killingtveit, A."
Now showing 1 - 6 of 6
Results Per Page
Sort Options
Item Developing an Excellent Sediment Rating Curve from one Hydrological Year Sampling Programme Data Approach(Universidade Federal da Paraíba, 2008-05-16) Ndomba, Preksedis M.; Killingtveit, A.This paper presents preliminary findings on the adequacy of one hydrological year sampling programme data in developing an excellent sediment rating curve. The study case is a 1DD1 subcatchment in the upstream of Pangani River Basin (PRB), located in the North Eastern part of Tanzania. 1DD1 is the major runoff-sediment contributing tributary to the downstream hydropower reservoir, the Nyumba Ya Mungu (NYM). In literature sediment rating curve method is known to underestimate the actual sediment load. In the case of developing countries long-term sediment sampling monitoring or conservation campaigns have been reported as unworkable options. Besides, to the best knowledge of the authors, to date there is no consensus on how to develop an excellent rating curve. Daily-midway and intermittent-cross section sediment samples from Depth Integrating sampler (D-74) were used to calibrate the subdaily automatic sediment pumping sampler (ISCO 6712) near bank point samples for developing the rating curve. Sediment load correction factors were derived from both statistical bias estimators and actual sediment load approaches. It should be noted that the ongoing study is guided by findings of other studies in the same catchment. For instance, long term sediment yield rate estimated based on reservoir survey validated the performance of the developed rating curve. The result suggests that excellent rating curve could be developed from one hydrological year sediment sampling programme data. This study has also found that uncorrected rating curve underestimates sediment load. The degree of underestimation depends on the type of rating curve developed and data used.Item Estimating Gully Erosion Contribution to Large Catchment Sediment Yield Arte in Tanzania(Elsevier, 2009-12) Ndomba, Preksedis M.; Mtalo, Felix W.; Killingtveit, A.The objective of this paper is to report on the issues and proposed approaches in estimating the contribution of gully erosion to sediment yield at large catchment. The case study is the upstream of Pangani River Basin (PRB) located in the North Eastern part of Tanzania. Little has been done by other researchers to study and/or extrapolate gully erosion results from plot or field scale to large catchment. In this study multi-temporal aerial photos at selected sampling sites were used to estimate gully size and morphology changes over time. The laboratory aerial photo interpretation results were groundtruthed. A data mining tool, Cubist, was used to develop predictive gully density stepwise regression models using aerial photos and environment variables. The delivery ratio was applied to estimate the sediment yield rate. The spatial variations of gully density were mapped under Arc View GIS Environment. Gully erosion sediment yield contribution was estimated as a ratio between gully erosion sediment yield and total sediment yield at the catchment outlet. The general observation is that gullies are localized features and not continuous spatially and mostly located on some mountains’ foot slopes. The estimated sediment yield rate from gullies erosion is 6800 t/year, which is about 1.6% of the long-term total catchment sediment yield rate. The result is comparable to other study findings in the same catchment. In order to improve the result larger scale aerial photos and high resolution spatial data on soil-textural class and saturated hydraulic conductivity – are recommended.Item A Guided SWAT Model Application on Sediment Yield Modeling in Pangani River Basin: Lessons Learnt(Universidade Federal da Paraíba, 2008-12-10) Ndomba, Preksedis M.; Mtalo, Felix W.; Killingtveit, A.The overall objective of this paper is to report on the lessons learnt from applying Soil and Water Assessment Tool (SWAT) in a well guided sediment yield modelling study. The study area is the upstream of Pangani River Basin (PRB), the Nyumba Ya Mungu (NYM) reservoir catchment, located in the North Eastern part of Tanzania. It should be noted that, previous modeling exercises in the region applied SWAT with preassumption that inter-rill or sheet erosion was the dominant erosion type. In contrast, in this study SWAT model application was guided by results of analysis of high temporal resolution of sediment flow data and hydro-meteorological data. The runoff component of the SWAT model was calibrated from six-years (i.e. 1977–1982) of historical daily streamflow data. The sediment component of the model was calibrated using one-year (1977–1988) daily sediment loads estimated from one hydrological year sampling programme (between March and November, 2005) rating curve. A long-term period over 37 years (i.e. 1969–2005) simulation results of the SWAT model was validated to downstream NYM reservoir sediment accumulation information. The SWAT model captured 56 percent of the variance (CE) and underestimated the observed daily sediment loads by 0.9 percent according to Total Mass Control (TMC) performance indices during a normal wet hydrological year, i.e., between November 1, 1977 and October 31, 1978, as the calibration period. SWAT model predicted satisfactorily the long-term sediment catchment yield with a relative error of 2.6 percent. Also, the model has identified erosion sources spatially and has replicated some erosion processes as determined in other studies and field observations in the PRB. This result suggests that for catchments where sheet erosion is dominant SWAT model may substitute the sediment-rating curve. However, the SWAT model could not capture the dynamics of sediment load delivery in some seasons to the catchment outlet.Item A Proposed Approach of Sediment Sources and Erosion Processes Identifiacation at Large Catchments(Universidade Federal da Paraíba Brasil, 2007) Ndomba, Preksedis M.; Mtalo, Felix W.; Killingtveit, A.In the subject of identifying sediment sources and erosion processes at catchment level researchers have proposed various methods. Most of the techniques have been applied in isolation. A few workers have combined some methods but still they could not ascertain their findings. As a result they recommended more sophisticated methods in order to compare the results. Little however has been done to correlate suspended sediment concentrations using spatial and temporal hydrological variables like rainfall and surface runoff at reasonable time step such as daily time series. In this study selected methods by previous workers are used and compared. The hydrological variables mapping technique has complemented the results of various renowned sediment sources identification techniques. The introduced method gives not only probable sources and processes but also it additionally identifies location based sediment sources using rainfall stations as pointers. The combined results from both methods indicate that either clay soil land plots or agricultural areas are potential sediment source areas. The result is comparable to previous researchers’ findings in the Pangani River basin that mapped the erosion zones using simple empirical and complex physics-based mathematical models. Although, the methods adopted in this study lacked high-resolution data, the authors believe that the methods and modifications applied give a quick, reliable and more insight to future sediment yield modelling efforts at a catchment level. For instance, a distributed watershed sediment yield model would be appropriate based on high spatial and temporal variation of the hydrological variables as reported in this study. Also, the results suggest that Sediment yield model that simulates sheet erosion might be an ideal tool since the major source areas of the transported sediment are topsoils or sheet erosion.Item Sediment Yield Modelling using SWAT model at Larger and Complex Catchments: Issues and Approaches. A Case of Pangani River Catchment, Tanzania(2007) Ndomba, Preksedis M.; Mtalo, Felix W.; Killingtveit, A.SWAT model is a semi-distributed, physics based water shed model. The model is now being applied/customized in Tanzania, the successful stories on SWAT applications motivated the study, unfortunately, and the model is developed from multitudes of parameters, hence complex. It’s also data expensive. Modeling uncertainty is high if not applied with caution. Unfortunately, SWAT model applications techniques have Not been adequately documented. Little has been done by other works to compare SWAT stimulations performance with data from intensive sediment sampling programme. Therefore this study used SWAT model in larger and complex catchment in order to estimate sediment yield and document application techniques and give insight to possible model customization opportunities.Item SWAT Model Application in a Data Scarce Tropical Complex Catchment in Tanzania(Elsevier, 2008) Ndomba, Preksedis M.; Mtalo, Felix W.; Killingtveit, A.This study intended to validate the Soil and Water Assessment Tool (SWAT) model in data scarce environment in a complex tropical catchment in the Pangani River Basin located in northeast Tanzania. The validation process involved the model initialization, calibration, verification and sensitivity analysis. Both manual and auto-calibration procedures were used to facilitate the comparison of the results with past studies in the same catchment. For this study, some model parameters including Soil depth (SOL_Z) and Saturated hydraulic conductivity (SOL_K) were assumed uniform within the study catchment and were therefore lumped comprising the huge computation resource requirement of the SWAT model. Results indicated that the same set of important parameters was identified with or without the use of observed flows data. Some of the parameters had physical interpretation and could therefore relate directly to hydrological controlling factors within the catchment. Despite swapping ranking importance of parameters, these results suggest the suitability of the SWAT model for identifying hydrological controlling factors/parameters in ungauged catchments. Results of calibration and validation at the daily timescale gave moderately satisfactory Nash–Sutcliffe Coefficient of Efficiency (CE) of 54.6% for calibration and 68% for validation while simulated and observed mean annual flow discharges gave an Index of Volumetric Fit (IVF) of 100%. The study further indicated the improvement of model estimation when more reliable spatial representation of rainfall was used. Although in this study SWAT model has performed satisfactorily in data poor and complex catchment, the authors recommend a wider validation effort of the model before it is adopted for operational purpose.