Real-Time Hydrologic Modelling and Floodplain Modelling in the Kafue River Basin, Zambia

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Real-Time Hydrologic Modelling and Floodplain Modelling in the Kafue River Basin, Zambia Research Collection Doctoral Thesis Real-time hydrologic modelling and floodplain modelling in the Kafue river basin, Zambia Author(s): Meier, Philipp Publication Date: 2012 Permanent Link: https://doi.org/10.3929/ethz-a-007578064 Rights / License: In Copyright - Non-Commercial Use Permitted This page was generated automatically upon download from the ETH Zurich Research Collection. For more information please consult the Terms of use. ETH Library DISS. ETH NO. 20421 REAL-TIME HYDROLOGIC MODELLING AND FLOODPLAIN MODELLING IN THE KAFUE RIVER BASIN, ZAMBIA A dissertation submitted to ETH ZÜRICH for the degree of Doctor of Sciences presented by PHILIPP MEIER Dipl. Ing. ETH Zürich born 22. September 1979 citizen of Zürich accepted on the recommendation of Prof. Dr. Wolfgang Kinzelbach Prof. Dr. Dr.-Ing. András Bárdossy 2012 Abstract Hydropower dams make an important contribution to the economic development of many countries. However, in too many cases the negative impacts outweigh the positive ones. A river where the negative impacts of dams are visible is the Zambezi river basin in Southern Africa. A fundamental prerequisite for a holistic management is a good knowledge of the physical system. Long term forecasts on the inflow of a dam and a model predicting the downstream effects of a dam can help improving the operation of a dam, thus minimising the negative impacts. A set of tools for dam management is presented in this thesis using the example of the Kafue river system, the largest tributary of the Zambezi. Since a dam divides the physical system of the river basin into two parts, an upstream and a downstream part, they have to be modelled separately. The upstream part consists of a forecasting framework for river discharges at a specific location. A simple conceptual model, which is solely based on remote sensing data providing soil moisture and rainfall estimates, builds the core of the framework. Sequential data assimilation using the Ensemble Kalman Filter provides a tool that is both efficient and robust for real-time modelling. The soil moisture product used is based on the back-scattering intensity of a radar signal measured by a radar scatterometer. These soil moisture data correlate well with the measured discharge of the corresponding watershed if the data are shifted by a time lag. This time lag is the basis for the applicability of the soil moisture data for hydrological forecasts. The applied conceptual model features two storage compartments. Its processes modelled involve evaporation losses, infiltration and percolation. The application of this model in a real-time modelling framework yields good results. The lead time of the forecast is dependent on the size and the retention capacity of the watershed. For the largest watershed a forecast over 40 days can be provided. The quality of the forecast increases significantly with decreasing prediction time. In a watershed with a small retention storage and a quick response to rainfall events, the performance is relatively poor and the lead time is as short as 10 days only. The downstream part aims at predicting the flooding patterns in the Kafue Flats in Zambia correctly. The progression of flooding is assessed using data retrieved from remote sensing satellites. Two methods for the recognition of flooding patterns are used, one based on data from a passive satellite system operating in the optical range, the second on an active microwave system. The classification applied for the optical data involves a simple numerical indicator for the presence of liquid water. The classification of the active microwave data is more complex. A stepwise approach based on the backscattering intensity, inundation probability maps and the spatial arrangement of the single pixels is applied. Despite their drawbacks both methods are suited to retrieve information about the flooding patterns, though not comparable. To model the flooding extent, strategies can range from simple conceptual black-box models to one-dimensional hydraulic models and fully distributed hydrological models. The most promising modelling approach was found to be a distributed model based on MODFLOW. It consists of two layers: a subsurface layer, representing the saturated flow in the groundwater, and a surface water layer representing the flow on the flooded surface. In between these two layers the unsaturated zone is modelled. A module was developed to handle the coupling of the two layers. The flow in the main river channel of the Kafue is simulated explicitly. The model cells have a size of 1 × 1 km2. This model is calibrated using the flooding patterns derived from active microwave data. After calibration the model is found to be able to reproduce the seasonal progression of the flooding in the Kafue Flats. Some shortcomings of the model unveiled after calibration can be addressed by improving the structure of the model, as well as by using a better digital elevation model. ii Zusammenfassung In zahlreichen Ländern ist die Stromproduktion aus Wasserkraft ein wichtiger ökonomis- cher Faktor, dessen durchwegs positiven Effekte in vielen Fällen durch negative Folgen der Wasserkraftnutzung aufgewogen werden, so zum Beispiel im Einzugsgebiet des Sambesi im südlichen Afrika. Eine alle Faktoren umfassende Bewirtschaftung eines solch kom- plexen Flusssystems muss sich auf eine fundierte Kenntnis des hydrologischen Systems abstützen. So bieten längerfristige Prognosen der Zuflüsse eines Stausees, sowie die detail- lierte Vorhersage der hydrologischen Prozesse unterhalb des Wasserspeichers eine wertvolle Hilfe zur Verminderung negativer Auswirkungen. Im Rahmen dieser Arbeit werden solche Werkzeuge am Beispiel des Kafue River entwickelt. Der physikalischen Trennung des hy- drologischen Systems oberhalb und unterhalb eines Staudammes, wird durch eine geson- derte Betrachtung Rechnung getragen. Zur Vorhersage des Zuflusses eines Staudammes, wird ein Prognosesystem basierend auf einem einfachen hydrologischen Modell und der Datenassimilierung mittels Ensemble Kalman Filter erstellt. Als Eingangsdaten dienen ausschliesslich aus Fernerkundungsdaten abgeleitete Grössen, wie Bodenfeuchte und Niederschlag. Die Bodefeuchte wird bestimmt, indem die Streuung eines Radarsignals an der Erdoberfläche gemessen wird. Der so er- mittelte Wassergehalt des Bodens weist eine gute Korrelation mit gemessenen Abfüssen auf, wenn die Zeitreihen um einen bestimmten Betrag zueinander verschoben werden. Diese zeitliche Verschiebung bildet die Grundlage einer Prognose. Das verwendete hy- drologische Modell besteht aus zwei Linearspeichern und bildet die wichtigsten Prozesse, wie Verdunstung, Infiltration und Zwischenabfluss, ab. Die so erhaltene Prognose ist all- gemein von guter Qualität. Es können, abhängig von der Grösse eines Einzugsgebietes, Prognosehorizonte von bis zu 40 Tagen erreicht werden, jedoch ist die Prognose für näher- liegende Ereignisse wesentlich genauer. Problematisch ist die Anwendung des Systems auf Einzugsgebiete mit geringer Bodenmächtigkeit und folglich schnellem Abfliessen nach Re- genereignissen. Die Einflüsse des durch Staudämme veränderten Abflussregimes macht sich im Kafue- Einzugsgebiet vor allem im grössten Feuchtgebiet, den Kafue Flats, bemerkbar. Um die Dynamik der jährlichen Überflutung in Raum und Zeit abzuschätzen, werden zwei Metho- den vorgestellt, welche die überfluteten Flächen anhand optischer und radar-gestützter Fernerkundungsdaten bestimmen können. Aus den optischen Satellitendaten wird die Überflutung anhand eines einfachen Index berechnet. Die Klassifikation der Radar-Daten ist um einiges aufwändiger und berücksichtigt neben der Intensität des zurückgestreuten Radar-Signals auch deren räumliche Verteilung und Informationen zur erwarteten Über- flutungshäufigkeit. Obwohl beide Methoden nicht direkt vergleichbar sind, können beide erfolgreich zur Bestimmung der Überschwemmungsdynamik eingesetzt werden. Um die überfluteten Flächen zu modellieren, bieten sich verschiedene Konzepte an, die von einer einfachen Bilanzbetrachtung, über eindimensionale, hydraulische Modelle bis zu komplexen, räumlich aufgelösten, physikalischen Modellen reichen. Ein räumlich verteiltes Modell basierend auf MODFLOW erlaubt eine zuverlässige Simulation der über- fluteten Flächen. Es besteht einer Grund- und einer Oberflächenwasserschicht, und der ungesättigte Zone dazwischen. Für die Kopplung der hydrologischen Prozesse in beiden Schichten wird MODFLOW um ein Modul erweitert. Dieses Modell erlaubt die explizite Simulation der Abflüsse im Hauptfluss und der Überflutung im angrenzenden Feuchtge- biet mit einer Auflösung von 1 × 1 km2. Kalibriert wird es anhand der Flächen, die aus den Radar-Satellitendaten extrahiert wurden. Auch wenn nach der Kalibrierung einige Schwächen dieses Modellansatzes hervortreten, kann die komplexe saisonale Dynamik der Überschwemmungen in den Kafue Flats nachgebildet werden. Eine Verbesserung der Re- sultate könnte durch eine optimierte Modellstruktur erreicht werden, vor allem aber durch die Verwendung eines genaueren topographischen Datensatzes. iv Contents 1 Introduction1 1.1 Water for life – water for the environment............1 1.2 Outline...............................3 1.3 The Zambezi river system.....................4 1.3.1 Geomorphology and geology................4 1.3.2 Climate...........................6 1.4 The Kafue river basin.......................6 1.4.1 Headwaters.........................6 1.4.2 Kafue Flats.........................7 1.4.3 Reservoirs..........................9 2 Real-time Prediction of River Discharge
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