2 resultados para streamflow

em Aston University Research Archive


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Soil erosion is one of the most pressing issues facing developing countries. The need for soil erosion assessment is paramount as a successful and productive agricultural base is necessary for economic growth and stability. In Ghana, a country with an expanding population and high potential for economic growth, agriculture is an important resource; however, most of the crop production is restricted to low technology shifting cultivation agriculture. The high intensity seasonal rainfall coincides with the early growing period of many of the crops meaning that plots are very susceptible to erosion, especially on steep sided valleys in the region south of Lake Volta. This research investigated the processes of soil erosion by rainfall with the aim of producing a sediment yield model for a small semi-agricultural catchment in rural Ghana. Various types of modelling techniques were considered to discover those most applicable to the sub-tropical environment of Southern Ghana. Once an appropriate model had been developed and calibrated, the aim was to look at how to enable the scaling up of the model using sub-catchments to calculate sedimentation rates of Lake Volta. An experimental catchment was located in Ghana, south west of Lake Volta, where data on rainstorms and the associated streamflow, sediment loads and soil data (moisture content, classification and particle size distribution) was collected to calibrate the model. Additional data was obtained from the Soil Research Institute in Ghana to explore calibration of the Universal Soil Loss Equation (USLE, Wischmeier and Smith, 1978) for Ghanaian soils and environment. It was shown that the USLE could be successfully converted to provide meaningful soil loss estimates in the Ghanaian environment. However, due to experimental difficulties, the proposed theory and methodology of the sediment yield model could only be tested in principle. Future work may include validation of the model and subsequent scaling up to estimate sedimentation rates in Lake Volta.

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Techniques are developed for the visual interpretation of drainage features from satellite imagery. The process of interpretation is formalised by the introduction of objective criteria. Problems of assessing the accuracy of maps are recognized, and a method is developed for quantifying the correctness of an interpretation, in which the more important features are given an appropriate weight. A study was made of imagery from a variety of landscapes in Britain and overseas, from which maps of drainage networks were drawn. The accuracy of the mapping was assessed in absolute terms, and also in relation to the geomorphic parameters used in hydrologic models. Results are presented relating the accuracy of interpretation to image quality, subjectivity and the effects of topography. It is concluded that the visual interpretation of satellite imagery gives maps of sufficient accuracy for the preliminary assessment of water resources, and for the estimation of geomorphic parameters. An examination is made of the use of remotely sensed data in hydrologic models. It is proposed that the spectral properties of a scene are holistic, and are therefore more efficient than conventional catchment characteristics. Key hydrologic parameters were identified, and were estimated from streamflow records. The correlation between hydrologic variables and spectral characteristics was examined, and regression models for streamflow were developed, based solely on spectral data. Regression models were also developed using conventional catchment characteristics, whose values were estimated using satellite imagery. It was concluded that models based primarily on variables derived from remotely sensed data give results which are as good as, or better than, models using conventional map data. The holistic properties of remotely sensed data are realised only in undeveloped areas. In developed areas an assessment of current land-use is a more useful indication of hydrologic response.