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Catchment Rainfall-Runoff Computer Modelling Forood Sharifi University of Wollongong

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Catchment Rainfall-Runoff Computer Modelling Forood Sharifi University of Wollongong University of Wollongong Research Online University of Wollongong Thesis Collection University of Wollongong Thesis Collections 1996 Catchment rainfall-runoff computer modelling Forood Sharifi University of Wollongong Recommended Citation Sharifi, Forood, Catchment rainfall-runoff omputc er modelling, Doctor of Philosophy thesis, Department of Civil and Mining Engineering, University of Wollongong, 1996. http://ro.uow.edu.au/theses/1230 Research Online is the open access institutional repository for the University of Wollongong. For further information contact the UOW Library: [email protected] CATCHMENT RAINFALL-RUNOFF COMPUTER MODELLING 1 UNIVERSITY W j A thesis submitted in fulfilment of the requirements for the award of the degree of Doctor of Philosophy (PhD) from THE UNIVERSITY OF WOLLONGONG by Forood Sharifi B.E., Tabriz University - Iran P.G. Diploma (Hydrau. Eng.), IHE - Delft, The Netherlands M.E. (Hons), University of Wollongong DEPARTMENT OF CIVIL AND MINING ENGINEERING 1996 du/um 4/.'Ju 1 ii DECLARATION This is to certify that the work presented in this thesis was carried out by the author in the Department of Civil and Mining Engineering at the University of Wollongong and has not been submitted for a degree to any other University or Institution. /i (Forood Sharifi) iii ABSTRACT Rapid population growth has caused an increasing demand for water in both agricultural and industrial sectors. With wastage of water, deterioration of water sources through pollution and the impact of humans on the water cycle, further water shortages are expected. An increasing demand for water dictates the necessity for on-going research into the assessment and modelling of surface and subsurface water resources. As water resources have become scarcer, the trend in water resources development has shifted from large to small catchments, many of which are ungauged. In water resources design a long record of runoff is desirable, but this is not usually available in small catchments. Rainfall records are more readily available than runoff records in most situations. This emphasises the need for better and more consistent rainfall-runoff modelling. The primary objectives of this research are the assessment of currently available rainfall- runoff models. An investigation of suitably complex rainfall-runoff models, and an evaluation of the physical interpretation of the parameter values and their interactions has been carried out in order to achieve a better understanding of the rainfall-runoff processes in natural catchments. The secondary objectives involved the development of a methodology to estimate both the catchment runoff and the parameter values of the rainfall-runoff models for catchments with short records, with a view to extending the use of rainfall-runoff models to ungauged catchments. The first part of the study consists of a literature review which includes the hydrological processes, current rainfall-runoff models, and basic issues on rainfall-runoff modelling. Different models are reviewed in relation to their selection, calibration, parameter estimation, and optimisation techniques. Evaporation and transpiration, which are the most important losses in rainfall-mnoff modelling, are investigated in the next part of the study. Water balance studies in five catchments were carried out which showed that evapotranspiration accounts for more iv than 40% of total rainfall. Surface runoff, subsurface runoff and other losses are calculated as equal to 32, 16, and 12% of total rainfall respectively. Several approaches to estimating evapotranspiration are reviewed and criteria for selection of a method to be used in modelling have been investigated. Selection of an appropriate technique for the estimation of PET and evaluation of its effects in rainfall runoff-modelling has been discussed. Pan evaporation measurements and the complementary approach recommended by Morton are the most widely accepted methods for the calculation of evaporation in rainfall-runoff modelling. However, the limitations of these methods were highlighted and a methodology for converting pan evaporation to PET has been proposed. Rainfall-runoff modelling was carried out using data from eight catchments located in Australia. A description of the catchments' physical and climatic characteristics and a summary of the results is also presented. Existing models range from the simple runoff coefficient model to more complex rainfall-runoff models. Some complex models failed to recognise the spatial variability of the hydrological processes. In many cases these models estimated total streamflow values in agreement with the total recorded streamflow, but incorrectly predicted the different streamflow components. Consequently, in this study attention was focussed on the estimation of both baseflow and surface runoff. In addition, the source areas of storm runoff was investigated. Several methods for partitioning the total streamflow into baseflow and surface runoff were investigated and a number of improvements to established techniques were made. These improvements included the evaluation and modification of two methods of streamflow partitioning and the development of a new model for the separation of the baseflow from the total runoff. The model was based on the use of a streamflow recession and recharge parameter. The storage-discharge relation of the catchment was analysed by studying catchment lag parameters and their relationship to catchment characteristics. The study was conducted on the most appropriate technique for calculating streamflow recession and recharge parameters. v Two rainfall runoff models (the SFB and AWBM model) with physically-based parameters were adopted. Sensitivity analysis of the SFB and AWBM models was carried out in order to test the relative importance of parameter values and their interactions. In addition, problems associated with the models' optimisation have been highlighted and a new approach for the parameter estimation of rainfall runoff models based on separated surface runoff and baseflow was proposed. The effect of using pan evaporation data and pan evaporation data multiplied by conversion factors in model calibration was investigated. It was found that the use of conversion factors improved the accuracy of model simulation in most catchments. In most of the catchments, the physically realistic parameters of the SFB model were unable to achieve accurate predictions of runoff. Conversely, whilst the optimised parameter values gave a reasonable runoff prediction they did not have physically realistic values. The optimum values of parameters described data characteristics rather than physical characteristics. It was concluded that the optimised parameter values of this model did not truly represent the movement of water in heterogeneous catchments and could not be related to the physical characteristics of the catchments with any degree of reliability. In order to ascertain the effects of complexity in rainfall-runoff modelling the results of the SFB and AWBM models were compared with the more complex SDI model. If the models had been assessed on the basis of a comparison between recorded and predicted runoff over the calibration period, the best model would have been SDI followed by the AWBM and SFB models respectively. This demonstrates that accuracy during the calibration period increases as the number of parameters (or model complexity) increases. It was concluded that if the number of parameters are increased, the differences between predicted and actual total runoff (surface runoff plus baseflow) can easily be minimised. vi However, the error in data propagates into the estimated parameters and increases the uncertainty in optimised parameter values. Parameter estimation based solely on the total streamflow may present misleading results. In this case errors in predicted baseflow and surface runoff cancel each other and the model estimates approximately correct total flows. To avoid this problem in modelling, parameter estimation procedures utilising a separated continuous streamflow and separated individual events were proposed and shown to be promising. Contrary to the results obtained from predicting total flow, when the models were assessed on the basis of baseflow and surface runoff prediction, the AWBM model gave a significantly better performance, while the two other models gave extremely poor results. The poor performance of the SDI and the SFB models is probably due to a combination of model errors, parameter errors and input errors. Among the factors which seem to be more important is the failure of these models to consider the spatial variability in soil storage capacity of catchments. As a result, these models failed to simulate the movement of water in the catchment correctly. Consequently, the optimised parameter values of these models cannot be regarded as having a physical significance. The number of parameters is not the only requirement for modelling accuracy and it is unlikely that all of the processes incorporated in complex models can be supported by the limited information obtained from rainfall and streamflow measurement. The degree of complexity does not play a significant role in the correct calibration of the model, unless the formulation of models is based on correct assumptions. Relating model parameters to physically measurable catchment characteristics has been an important aim of many researchers over the past three decades, but has met with little success. This study showed that
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