Les modèles de Rejets Urbains par Temps de Pluie (MRUTP) de Matières en Suspension (MES) dans les systèmes d’assainissement urbains sont essentiels pour des raisons scientifiques, environnementales, opérationnelles et réglementaires. Néanmoins, les MRUTP ont été largement mis en question, surtout pour reproduire des données mesurées en continu à l’exutoire des grands bassins versants. Dans cette thèse, trois limitations potentielles des MRUTP traditionnels ont été étudiées dans un bassin versant de 185 ha (Chassieu, France), avec des mesures en ligne de 365 événements pluvieux : a) incertitudes des données dû aux conditions sur le terrain, b) incertitudes dans les modèles hydrologiques et mesures de pluie et c) incertitudes dans les structures traditionnelles des MRUTP. Ces aspects sont approfondis dans six apports séparés, dont leurs résultats principaux peuvent être synthétisés comme suites : a) Acquisition et validation des données : (i) quatre stratégies d’échantillonnage pendant des événements pluvieux sont simulées et évaluées à partir de mesures en ligne de MES et débit. Les intervalles d’échantillonnage recommandés sont de 5 min, avec des erreurs moyennes entre 7 % et 20 % et des incertitudes sur ces erreurs d’environ 5 %, selon l’intervalle d’échantillonnage; (ii) la probabilité de sous-estimation de la concentration moyenne dans la section transversale du réseau est estimée à partir de deux méthodologies. Une méthodologie montre des sous-estimations de MES plus réelles (vers 39 %) par apport à l'autre (vers 269 %). b) Modèles hydrologiques et mesures de pluie : (iii) une stratégie d’estimation de paramètres d’un modèle conceptuel pluie-débit est proposée, en analysant la variabilité des paramètres optimaux obtenus à partir d’un calage Bayésien évènement-par-évènement; (iv) une méthode pour calculer les précipitations moyennes sur un bassin versant est proposée, sur la base du même modèle hydrologique et les données de débit. c) MRUTP (pollutographes) : (v) la performance de modélisation à partir du modèle traditionnel courbe d’étalonnage (RC) a été supérieur aux différents modèles linéaires de fonctions de transfert (TF), surtout en termes de parcimonie et précision des simulations. Aucune relation entre les potentielles erreurs de mesure de la pluie et les conditions hydrologiques définies en (iii) et (iv) avec les performances de RC et TFs n’a pu être établie. Des tests statistiques renforcent que l’occurrence des évènements non-représentables par RC ou TF au cours de temps suit une distribution aléatoire (indépendante de la période sèche précédente); (vi) une méthode de reconstruction Bayésienne de variables d’état virtuelles indique que des processus potentiellement manquants dans une description RC sont ininterprétables en termes d’un unique état virtuel de masse disponible dans le bassin versant qui diminue avec le temps, comme nombre de modèles traditionnels l’ont supposé. / Total Suspended Solids (TSS) stormwater models in urban drainage systems are often required for scientific, legal, environmental and operational reasons. However, these TSS stormwater traditional model structures have been widely questioned, especially when reproducing data from online measurements at the outlet of large urban catchments. In this thesis, three potential limitations of traditional TSS stormwater models are analyzed in a 185 ha urban catchment (Chassieu, Lyon, France), by means 365 rainfall events monitored online: a) uncertainties in TSS data due to field conditions; b) uncertainties in hydrological models and rainfall measurements and c) uncertainties in the stormwater quality model structures. These aspects are investigated in six separate contributions, whose principal results can be summarized as follows: a) TSS data acquisition and validation: (i) four sampling strategies during rainfall events are simulated and evaluated by online TSS and flow rate measurements. Recommended sampling time intervals are of 5 min, with average sampling errors between 7 % and 20 % and uncertainties in sampling errors of about 5 %, depending on the sampling interval; (ii) the probability of underestimating the cross section mean TSS concentration is estimated by two methodologies. One method shows more realistic TSS underestimations (about 39 %) than the other (about 269 %). b) Hydrological models and rainfall measurements: (iii) a parameter estimation strategy is proposed for conceptual rainfall-runoff model by analyzing the variability of the optimal parameters obtained by single-event Bayesian calibrations, based on clusters and graphs representations. The new strategy shows more performant results in terms of accuracy and precision in validation; (iv) a methodology aimed to calculate “mean” areal rainfall estimation is proposed, based on the same hydrological model and flow rate data. Rainfall estimations by multiplying factors over constant-length time window and rainfall zero records filled with a reverse model show the most satisfactory results compared to further rainfall estimation models. c) Stormwater TSS pollutograph modelling: (v) the modelling performance of the traditional Rating Curve (RC) model is superior to different linear Transfer Function models (TFs), especially in terms of parsimony and precision of the simulations. No relation between the rainfall corrections or hydrological conditions defined in (iii) and (iv) with performances of RC and TFs could be established. Statistical tests strengthen that the occurrence of events not representable by the RC model in time is independent of antecedent dry weather conditions; (vi) a Bayesian reconstruction method of virtual state variables indicate that potential missing processes in the RC description are hardly interpretable as a unique state of virtual available mass over the catchment decreasing over time, as assumed by a great number of traditional models.

>Magister Scientiae - MSc

>Magister Scientiae - MSc / The Kuils River Catchment is an urban river catchment that forms part of the larger Kuils-Eerste River system draining the eastern half of the Cape Metropolitan Authority area and Stellenbosch Municipality. Rapid urbanisation has resulted in the encroachment of residential and industrial areas into the river system through channelization and sewage disposal. This research project intends to assess the quality of surface runoff in the Kuils River catchment and determining non-point source pollutant loading rates in the catchment using GIS-based modelling. The study results show how modelled potential sources of surface runoff and NPS pollutants using desktop GIS analysis tools in a sequential process that involved different levels of software applications could explain the characteristics of the catchment. With the help of the Expected Mean Concentration (EMC) values associated with surface runoff from land use/covers, NPS pollutant loads were assessed downstream towards the Kuils River Catchment outlet using the Nonpoint Source Pollution and Erosion Comparison Tool (N-SPECT) based in ArcGIS. The outputs from this model consist of predicted annual pollutant loading (mg/mvyear) for each Kuils-Eerste River that occurs in the catchment. The results have shown clearly the spatial distribution of sources of particular pollutants in the catchment. Further or advanced processing knowhow with this model might provide far reaching insights into the problem and it is however recommended that these results produced using N-SPECT be compared to those of other hydrologic models using the same inputs.

Intense but short-term cloudbursts may cause severe flooding in urban areas. Such short-term cloudbursts mostly are of convective character, where the rain intensity may vary considerably within relatively small areas. Using uniform design rains where maximum intensity is assumed over the whole catchment is common practice in Sweden, though. This risks overestimating the hydraulic responses, and hence lead to overdimensioning of stormwater systems. The objective of this study was to determine how the hydraulic response to cloudbursts is affected by the spatial variation of the rain in relation to the catchment size, aiming to enable improved cloudburst mapping in Sweden. Initially, the spatial variation of heavy rains in Sweden was investigated by studying radar data provided by SMHI. The distribution of rainfall accumulated over two hours from heavy raincells was investigated, based on the assumption that the intensity of convective raincells can be approximated as spatially Gaussian distributed. Based on the results, three Gaussian test rains, whose spatial variation was deemed a representative selection of the radar study, were created. In order to investigate how the hydraulic peak responses differed between the Gaussian test rains and uniform reference rains, both test and reference rains were modeled in MIKE21 Flow model. The modelling was performed on an idealised urban model fitted to Swedish urban conditions, consisting of four nested square catchments of different sizes. The investigated hydraulic peak responses were maximum outflow, proportion flooded area and average maximum water depth. In comparison with spatially varied Gaussian rains centered at the outlets, the uniform design rain with maximum rain volume overestimated the peak hydraulic response with 1-8%, independent of catchment size. Uniform design rains scaled with an area reduction factor (ARF), which is averaging the rainfall of the Gaussian rain over the catchment, instead underestimated the peak response, in comparison with the Gaussian rains. The underestimation of ARF-rains increased heavily with catchment size, from less than 5 % for a catchment area of 4 km2 to 13 - 69 % for a catchment area of 36 km2. The conclusion can be drawn that catchment size ceases to affect the hydraulic peak response when the time it takes for the whole catchment to contribute to the peak response exceeds the time it takes for the peak to be reached. How much the rain varies over the area which is able to contribute to the peak response during the rain event, can be assumed to decide how much a design rain without ARF overestimates the peak responses. If the catchment exceeds this size, an ARF-scaled rain will underestimate the peak responses. This underestimation is amplified with larger catchments. The strong pointiness of the CDS-hyetograph used in the study risks underestimating the differences in hydraulic peak responses between the test rains and a uniform rain without ARF, while the difference between test rains and uniform rains with ARF risks being overestimated. / Intensiva men kortvariga skyfall kan orsaka omfattande översvämningsproblematik i urbana områden. Trots att sådana kortvariga skyfall oftast är av konvektiv karaktär, där regnintensiteten kan variera avsevärt inom relativt små områden, används idag uniforma designregn där maxintensitet antas över hela avrinningsområdet. Detta riskerar att leda till en överskattning av hydrauliska responser, och följaktligen överdimensionering av dagvattensystem. Denna studie syftar till att utreda hur den hydrauliska responsen av skyfall påverkas av regnets spatiala variation, i relation till avrinningsområdets storlek. Ytterst handlar det om att möjliggöra förbättrad skyfallskartering i Sverige. Initialt undersöktes den spatiala variationen hos kraftiga regn i Sverige, genom en studie av radardata tillhandahållen av SMHI. Utbredningen av regnmängd ackumulerad över två timmar från kraftiga regnceller undersöktes utifrån antagandet att intensiteten hos konvektiva regnceller kan approximeras som spatialt gaussfördelad. Baserat på resultatet skapades tre gaussfördelade testregn vars spatiala variation ansågs utgöra ett representativt urval från radarstudien. För att undersöka hur de hydrauliska responserna skiljer sig åt mellan de gaussfördelade testregnen och uniforma referensregn, modellerades såväl test- som referensregn i MIKE 21 Flow model. Modelleringen utfördes på en idealiserad stadsmodell anpassad efter svenska urbana förhållanden, bestående av fyra nästlade kvadratiska avrinningsområden av olika storlekar. De hydrauliska responser som undersöktes var maximalt utflöde, maximal andel översvämmad yta samt medelvärdesbildat maximalvattendjup, alltså toppresponser. Jämfört med spatialt varierade gaussregn centrerade kring utloppen överskattade ett uniformt designregn med testregnens maximala volym de hydrauliska toppresponserna med 1-8 %, oberoende av avrinningsområdets storlek. Uniforma designregn skalade med area reduction factor (ARF), vilken medelvärdesbildar gaussregnets nederbörd över avrinningsområdet, underskattade istället toppresponsen jämfört med gaussregnen. ARF-regnets underskattning ökade kraftigt med avrinningsområdets storlek, från mindre än 5 % för ett avrinningsområde på 4 km2, till 13 - 69 % för ett avrinningsområde på 36 km2. Slutsatsen kan dras att avrinningsområdets storlek upphör att påverka den hydrauliska toppresponsen, då tiden det tar för hela avrinningsområdet att samverka till toppresponsen överstiger tiden till denna respons. Hur mycket regnet varierar över det område som under regnhändelsen hinner samverka till toppresponsen, kan antas avgöra hur mycket ett designregn utan ARF överskattar toppresponserna. Överstiger avrinningsområdet denna storlek kommer ett ARF-regn att underskatta toppresponserna, och underskattningen förstärks med ökande avrinningsområdesstorlek. Den kraftiga temporala toppigheten hos den CDS-hyetograf som användes i studien riskerar att underskatta skillnaderna i hydraulisk topprespons mellan testregnen och ett uniformt regn utan ARF, medan skillnaden mellan testregn och uniforma regn med ARF istället riskerar att överskattas.