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A Comparison of Remotely-Sensed Precipitation Estimates with Observed Data from Rain Gauges in the Western Cape, South Africa

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A Comparison of Remotely-Sensed Precipitation Estimates with Observed Data from Rain Gauges in the Western Cape, South Africa A COMPARISON OF REMOTELY-SENSED PRECIPITATION ESTIMATES WITH OBSERVED DATA FROM RAIN GAUGES IN THE WESTERN CAPE, SOUTH AFRICA. by Sagwati Eugene Maswanganye Thesis submitted in fulfilment of the requirements for the degree of MASTER of SCIENCE in the Department of Earth Sciences, University of the Western Cape Supervisor: Dr. Michael Grenfell Co-Supervisor: Prof. Dominic Mazvimavi 2018 Declarations "I declare that the thesis entitled” A comparison of remotely-sensed precipitation estimates with observed data from rain gauges in the Western Cape, South Africa” is my own work, that it has not been submitted before for any degree or examination in any other university, and that all the sources I have used or quoted have been indicated and acknowledged by means of complete references." Sagwati Eugene Maswanganye 2017 Signed:………………………… i http://etd.uwc.ac.za/ Abstract Precipitation data are critical for management of water resources. Precipitation can be measured through ground measurement by means of rain gauges and by remote sensing techniques. Rain gauges often give accurate measurements, however networks of rain gauges are often sparse as they are costly and cannot be placed at all the desirable locations. The alternative is remotely-sensed data which have large spatial coverage and high temporal resolution. Remotely-sensed estimates need to generate realistic and reliable data in order to be used in water resource assessments. Therefore there is need to evaluate the accuracy of remote sensing techniques. This study investigated the reliability of the following satellite derived rainfall estimates; Multi-Sensor Precipitation Estimator (MPE), Tropical Applications of Meteorology using SATellite (TAMSAT) and Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) in areas with contrasting topographical and climatic characteristics in the Western Cape Province of South Africa. This study evaluated the accuracy of remotely-sensed precipitation estimates with ground observations from the most representative rain gauge in different two catchments at daily, monthly and yearly level. The study showed that there is general underestimation by remotely-sensed products in these catchments. For the mountainous Jonkershoek catchment, the observed annual total from March 2015 to February 2016 was 993 mm/year whereas TAMSAT and CHIRPS estimated 93 and 692 mm/year respectively. Therefore, TAMSAT and CHIRPS underestimated by 820 and 222 mm/year respectively. For the flat Heuningnes catchment located in the Cape Agulhas plains, the observed annual total from March 2015 to February 2016 was 633 mm/year whereas TAMSAT and CHIRPS estimated 114 and 532 mm/year respectively. Therefore TAMSAT and CHIRPS underestimated by 519 and 101 mm/year respectively. MPE had Missing data therefore it was analysed separately; However it also underestimated the actual amount of rainfall in both catchment. The study further determined the ability of these remotely-sensed precipitation products to distinguish between non-raining and raining events. The findings showed that TAMSAT, CHIRPS and the MPE were poor at distinguishing between rainy and non-rainy days. TAMSAT had a possibility of detection (POD) of 0.15(15%), CHIRPS had a POD of 0.28 and the MPE had POD of 0.31 in Jonkershoek. In the Heuningnes catchment; TAMSAT, CHIRPS and the MPE had a POD of 0.16, 0.21 and 0.28 respectively. Therefore, it was concluded that the underestimation by the three remotely-sensed products is due to poor ii http://etd.uwc.ac.za/ detection of rain-bearing clouds, which may be linked to frontal and orographic rainfall which are common in the area. Keywords: Rainfall, Remotely-sensed precipitation, satellite derived rainfall estimates, CHIRPS, TAMSAT, Multi-sensor precipitation Estimators. iii http://etd.uwc.ac.za/ Acknowledgements First and for most, I will like to thank Dr. Grenfell and Prof Mazvimavi (Environmental and Water Sciences department, UWC) for their expertise, guidance, assistance throughout the process of writing this thesis. Thank you for being more than supervisors, in you I had mentors and father that I looked up to. I want to extend my gratitude to Alliance for Collaboration on Climate and Earth Systems Science (ACCESS) for funding this project. Secondly I will like to extend my appreciation to Abri and South African Environmental Observational Networks (SAEON) for the provision of rainfall data for the Jonkershoek catchment. I would like to also send my thanks you to my friends and colleagues at the EWS department (S. Siwa, Y. Mkunyana, F. Jumbi and S. Gxokwe) whom I shared the struggle with, your assistance was helpful and together we can achieve more. A special thanks to my family (Dad, Mom, Khanyisa, Bumani, Migingiriko and Nhlalala) for your sincere support and prayers, without you I would not have made this far. iv http://etd.uwc.ac.za/ Abbreviations CHIRPS Climate Hazards Group InfraRed Precipitation with Stations CSIR Council of Science Industrial Research of South Africa CMORPH Climate Prediction Center (CPC) MORPHing technique CPC Climate Prediction Center DWAF Department of Water and Forestry EUMETSAT European Organization for the Exploitation of Meteorological Satellites FEWS NET Famine Early Warning System Network GPCP Global Precipitation Climatology Project GSoD Global Summary of the Day IR Infrared MW Microwave MPE Multi-sensor Precipitation Estimator NRL-blended Naval Research Laboratory’s blended technique NOAA National Oceanic and Atmospheric Agency PERSIANN Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks Ppt Precipitation RADAR RAdio Detection And Ranging RG Rain Gauge RFE Rainfall Estimate SAWS South African Weather Service v http://etd.uwc.ac.za/ SD Standard Deviation TAMSAT Tropical Applications of Meteorology using SATellite TCI (3G680) Temperature Condition Index TIR Thermal Infrared TRMM Tropical Rain Measuring Mission USGS United States Geological Survey VIR Visible Infrared VIS Visible WMO World Meteorological Organisation Measurements: m Metre mm Millimetres m.a.s.l Metres above sea level km Kilo metres ha Hectare vi http://etd.uwc.ac.za/ Table of contents Declaration……………………………………………………………………………………..i Abstract ...................................................................................................................................... ii Acknowledgements ................................................................................................................... iv Abbreviations ............................................................................................................................. v Table of contents ...................................................................................................................... vii List of Figures ........................................................................................................................... ix List of Tables ........................................................................................................................... xii Chapter 1: Introduction .............................................................................................................. 1 1.1 Background ...................................................................................................................... 1 1.2. Research questions .......................................................................................................... 4 1.3. Aim and objectives .......................................................................................................... 4 1.4. The significance of the study .......................................................................................... 4 1.5. Thesis outline .................................................................................................................. 5 Chapter 2: Literature Review ..................................................................................................... 6 2.1 Introduction ...................................................................................................................... 6 2.2 Historical development .................................................................................................... 6 2.3 Remote-sensing applications in Hydrology ..................................................................... 7 2.4 Precipitation Measurement ............................................................................................... 8 Chapter 3: Regional Setting and Research Site Description .................................................... 21 3.1 Introduction .................................................................................................................... 21 3.2 Regional setting: Western Cape ..................................................................................... 21 3.3 Research sites ................................................................................................................. 26 Chapter 4: Methodology .......................................................................................................... 31 4.1 Introduction .................................................................................................................... 31 4.2 Research design .............................................................................................................. 31 4.3 Selection of the study and sampling sites....................................................................... 33 vii
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