A monthly to daily streamflow disaggregation method is presented as part of an emerging water quality model designed to link with established monthly hydrology and yield models. The daily time step is assumed necessary for simulating water quality dynamics. The method is tested on two catchments in South Africa where observed daily flow data are available. The model includes a volume correction process to ensure daily sums are equal to input monthly flows and this reduces the sensitivity of the results to some model parameters. The sequences of events in the input daily rainfall must be representative of the catchment. Model validation against observed flows achieved Nash-Sutcliffe efficiency values ranging from 0.75 to 0.94 and initial applications of a water quality component suggested little difference between using observed and disaggregated flows. The main practical advantages are simplicity and the fact that the method builds on the experience of existing monthly models. Key words flow disaggregation; daily rainfall; incremental flow; water quality modelling Une méthode pour désagréger les débits mensuels à l'échelle journalière utilisant des observations quotidiennes de pluie : conception et tests du modèle Résumé Nous présentons une méthode de désagrégation des débits mensuels à l'échelle journalière dans le cadre d'un nouveau modèle de qualité de l'eau destiné à faire le lien avec des modèles hydrologiques et de rendement mensuels existants. Le pas de temps journalier est supposé nécessaire pour simuler la dynamique de la qualité de l'eau. La méthode a été testée sur deux bassins versants d'Afrique du Sud où les données journalières d'écoulements observés sont disponibles. Le modèle comprend un processus de correction de volume pour assurer que les sommes des débits journaliers sont égales aux débits mensuels d'entrée, ce qui réduit la sensibilité des résultats à certains paramètres du modèle. Les séquences d'événements des précipitations quotidiennes utilisées en entrée doivent être représentatives du bassin versant. La validation du modèle avec les débits observés atteint des valeurs de Nash-Sutcliffe allant de 0,75 à 0,94 et des applications préliminaires d'un composant de qualité de l'eau ont suggéré de faibles différences entre les débits observés et simulés. Les principaux avantages pratiques sont la simplicité et le fait que la méthode repose sur l'expérience de modèles mensuels existants. Mots clefs désagrégation des débits ; pluies quotidiennes ; débit incrémental ; modélisation de la qualité de l'eau
Freshwater systems in southern Africa are under threat of climate change, not only from altered flow regimes as rainfall patterns change, but also from biologically significant increases in water temperature. Statistical models can predict water temperatures from air temperatures, and air temperatures may rise by up to 7 °C by 2100. Statistical water temperature models require less data input than physical models, which is particularly useful in data deficient regions. We validated a statistical water temperature model in the lower Olifants River, South Africa, and verified its spatial applicability in the upper Klaserie River. Monthly and daily temporal scale calibrations and validations were conducted. The results show that simulated water temperatures in all cases closely mimicked those of the observed data for both temporal resolutions and across sites (NSE>0.75 for the Olifants River and NSE>0.8 for the Klaserie). Overall, the model performed better at a monthly than a daily scale, while generally underestimating from the observed (indicated by negative percentage bias values). The statistical models can be used to predict water temperature variance using air temperature and this use can have implications for future climate projections and the effects climate change will have on aquatic species.
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