Informations et ressources scientifiques
sur le développement des zones arides et semi-arides

Accueil du site → Doctorat → Australie → Estimation of the spatio-temporal heterogeneity of rainfall and its importance towards robust catchment simulation, within a hydroinformatic environment

University of New South Wales Australie (2002)

Estimation of the spatio-temporal heterogeneity of rainfall and its importance towards robust catchment simulation, within a hydroinformatic environment

Umakhanthan, Kanagaratnam

Titre : Estimation of the spatio-temporal heterogeneity of rainfall and its importance towards robust catchment simulation, within a hydroinformatic environment

Auteur : Umakhanthan, Kanagaratnam >

Université de soutenance : University of New South Wales

Grade : Doctor of Philosophy PhD 2002

Résumé
Rainfall is a natural process, which has a high degree of variability in both space andtime. Information on the spatial and temporal variability of rainfall plays an importantrole in the process of surface runoff generation. Hence it is important for a variety ofapplications in hydrology and water resources management. The spatial variability ofrainfall can be substantial even for very small catchments and an important factor in thereliability of rainfall-runoff simulations. Catchments in urban areas usually are small,and the management problems often require the numerical simulation of catchmentprocesses and hence the need to consider the spatial and temporal variability of rainfall.A need exists, therefore, to analyse the sensitivity of rainfall-runoff behaviour ofcatchment modelling systems (CMS) to imperfect knowledge of rainfall input, in orderto judge whether or not they are reliable and robust, especially if they are to be used foroperational purposes.Development of a methodology for identification of storm events according to thedegree of heterogeneity in space and time and thence development of a detailed spatialand temporal rainfall model within a hydroinformatic environment utilising real-timedata has been the focus of this project. The improvement in runoff prediction accuracyand hence the importance of the rainfall input model in runoff prediction is thendemonstrated through the application of a CMS for differing variability of real stormevents to catchments with differing orders of scale.The study identified both spatial and temporal semi-variograms, which were producedby plotting the semi-variance of gauge records in space and time against distance andtime respectively. These semi-variograms were utilised in introducing estimators tomeasure the degree of heterogeneity of each individual storm events in their space andtime scale. Also, the proposed estimators use ground based gauge records of the realstorm events and do not rely on delicate meteorological interpretations. As the results ofthe investigation on the developed semi-variogram approach, real storm events werecategorised as being High Spatial-High Temporal (HS-HT) ; High Spatial-LowTemporal ; (HS-LT) ; Low Spatial-High Temporal (LS-HT) ; and Low Spatial-LowTemporal variability.A comparatively detailed rainfall distribution model in space and time was developedwithin the Geographical Information Systems (GIS). The enhanced rainfallrepresentation in both space and time scale is made feasible in the study by the aid ofthe powerful spatial analytic capability of GIS. The basis of this rainfall model is anextension of the rainfall model developed by Luk and Ball (1998) through a temporaldiscretisation of the storm event. From this model, improved estimates of the spatiallydistributed with smaller time steps hyetographs suited for especially the urbancatchments could be obtained.The importance of the detailed space-time rainfall model in improving the robustness ofrunoff prediction of CMS was investigated by comparing error parameters forpredictions from CMS using alternate rainfall models, for various degrees of spatiotemporalheterogeneity events. Also it is appropriate to investigate whether the degreeof this improvement to be dependent on the variability of the storm event which isassessed by the adopted semi-variogram approach. From the investigations made, it wasfound that the spline surface rainfall model, which considered the spatial and temporalvariability of the rainfall in greater detail than the Thiessen rainfall model resulted inpredicted hydrographs that more closely duplicated the recorded hydrograph for thesame parameter set. The degree of this improvement in the predicted hydrograph wasfound to be dependent on the spatial and temporal variability of the storm event asmeasured by the proposed semi-variogram approach for assessing this feature of a stormevent.The analysis is based on forty real events recorded from the Centennial Park Catchment(1.3km2) and the Upper Parramatta River Catchment (110km2) in Sydney, Australia.These two case study catchments were selected to ensure that catchment scale effectswere incorporated in the conclusions developed during the study.

Mots clés : Watershed management — Computer simulation ; Rain and rainfall — Computer simulation ; Runoff — Computer simulation ; Rain and rainfall — New South Wales

Présentation

Version intégrale

Page publiée le 14 avril 2009, mise à jour le 11 juillet 2017