Linking crop yield to seasonal climate variations in Gamo Highlands, Ethiopia Analysis using an Ecophysiological (GECROS) and the Weather Research and Forecasting (WRF) Models WAGENINGEN UR August 27, 2014 Thomas Torora Minda i Thesis Supervisors Dr. J (Jordi) Vilà-Guerau de Arellano Associate professor of boundary layer meteorology Meteorology and Air Quality Group E-mail: [email protected] Wageningen University and Research Center The Netherlands Dr. Ir. MK (Michiel) van der Molen Assistant professor of land-use change and mesoscale meteorology Meteorology and Air Quality Group E-mail: [email protected] Wageningen University and Research Center The Netherlands Linking Seasonal Climate Variations to Crop Yield in Gamo Highlands, Ethiopia Analysis using an Ecophysiological (GECROS) and the Weather Research and Forecasting (WRF) Models TT Minda Thesis, Wageningen University and Research center E-mail: [email protected]; [email protected] ii WAGENINGEN UR Linking crop yield to seasonal climate variations in Gamo Highlands, Ethiopia Analysis using an Ecophysiological (GECROS) and the Weather Research and Forecasting (WRF) Models A Minor-thesis for the partial fulfillment of the degree of master in Climate Studies (MCL), specialization: Atmospheric Chemistry and Air Quality August 27, 2014 Thomas Torora Minda Thesis Supervisors Dr. J (Jordi) Vilà-Guerau de Arellano Dr. Ir. MK (Michiel) van der Molen Meteorology and Air Quality (MAQ) Wageningen, the Netherlands iii Dedication May God Bless the Dutch and its land iv ACKNOWLEDGMENTS I have always impressed with perfect supervision of professors of the meteorology and air quality (MAQ) chair group, Wageningen University and Research Center (WUR). As usual, I express my heartfelt thanks to Dr. Jordi Vilà and Dr.Ir. Michiel van der Molen. The high temporal (10 years) and spatial (2-by-2 km2) resolution of WRF model runs conducted in the National Center for Atmospheric research (NCAR), Boulder, CO, USA. I express my wholehearted appreciations and thanks to Dr. Pedro A. Jimenez, project scientist at the Research Application Laboratory, NCAR. At the beginning of this thesis work, I had limited knowledge in crop science and modelling. Thanks to Marie Combe (PhD candidate) for her immense support in GECROS model understanding and python scripting. I’m also so thankful to Prof P.C. Struik (professor of crop physiology) for his fundamental comments and ideas for future directions. From the beginning of my study in WUR, his regular advisory services and encouragements helped me a lot. You are right person at right position. I want to express my gratitude to Dr. Ir. Rudi Roijackers! You both shared not only your offices, but your seats too. I have no words to express your lovely helps during this work! Thank you Syioum Gizachew and Teklu Teshome, college of Medicine, Arba Minch University. The deans of Arba Minch College of Heath Sciences, Yosph Sonko, Ashenafi Abosa, and Mesirach Hailu allowed me to work in the college offices. I express my thanks to you all! The medical laboratory staffs have shared their offices and seats. I have special thanks to Hallelujah Getachew, Temesgen Eticha, Zeleke Gizachew, Abate Atimut, Shemlis Sheferaw, Bereket Workalemaw, and Derib Alemu. My study in such globally leading education institute, WUR, is sponsored by the Netherlands Organization for International Cooperation in Higher Education (nuffic). The last two years were one of the critical transition states in my life! I have no word to express my deep feeling to the organization and the Dutch people and their land! I have shared your good thoughts and prosperity! Thank you God, the Holy Spirit, the Creator, Owner, and Sustainer of the Universe. These all are because of you. Thank you so much. v ABSTRACT Climate change posed huge lose in crop productivity, mainly in the developing world. This study aimed at identifying drought seasons/years; best potato (Solanum tuberosum L.) sowing dates; and locations for optimum yield in the Gamo highlands (locations around Arba Minch town), Ethiopia. High temporal and spatial resolutions were applied for weather and crop yield modelling. The Weather Research and Forecasting (WRF) model was used to simulate the seasonal inter-climatology. Hourly outputs of 10 years (2001 – 2010) model run were made. The inner most model domain (d04) was centered at Arba Minch and mainly covered (resolution of 2x2 for 84x84 km2 area) the Gamo highlands. Series of 48 hours runs were conducted, in which the first 24 hours (the previous day) taken as model spin-up period. Daily weather outputs of (maximum and minimum temperatures, rainfall, wind speed, the incoming shortwave radiation, and vapor pressure deficit), radiation budget, and the surface energy balance were extracted. The Standardized Precipitation Index (SPI), anomalies in temperature, radiation, and surface energy balances were considered to identify drought during potato sowing season (Belg, which is from February to May). An ecophysiological (GECROS) model was implemented to reproduce productivity. The WRF model outputs were considered as input for GECROS. A 10-by-10 km2 resolution was modelled in the WRF’s model domain. Model sensitivity experiments of sowing dates (Jan 15, Feb 01, Feb 15, and Mar 01); climate change assumptions (increased temperatures, and rainfall); and crop management option (application of fertilizer) were considered. The WRF model overestimated rainfall, wind speed, and underestimated temperatures. However, the model was capable to reproduce the drought year 2009 in Arba Minch and its vicinity. The GECROS productivity maps showed that areas with altitude ≥ 2000m above sea level identified as climatologically potential potato growing locations in the Gamo highlands. Early potato sowing, before the start of the Belg, was preferred as it gives relatively higher yield and less exposed to plant diseases. Crop-management sensitivity experiment showed that application of fertilizers was the best way to robust productivity. We suggest further model experiments for optimum fertilizer rate application. Model experiments in climate change assumptions showed decline in productivity for highlands, and sever decline for the lowlands. The yield declined is mainly explained by decreasing the number of harvest days. Key words: Potato (Solanum tuberosum L.), WRF, SPI, GECROS, yield, climate change. vi TABLE OF CONTENTS ACKNOWLEDGMENTS .................................................................................................... v ABSTRACT ........................................................................................................................ vi LIST OF FIGURES ............................................................................................................. ix LIST OF TABLES................................................................................................................ x LIST OF APPENDICES ..................................................................................................... xi LIST OF ABBREVIATIONS AND ACRONYMS ...........................................................xii 1 INTRODUCTION ......................................................................................................... 1 1.1 Objectives ....................................................................................................................... 2 1.2 Research Questions ......................................................................................................... 2 1.3 Hypothesis....................................................................................................................... 3 1.4 Research Approach ......................................................................................................... 3 2 METHODS ................................................................................................................... 4 2.1 The Study Area ............................................................................................................... 4 2.2 The Ethiopian Climate and Climatic Zones .................................................................... 6 2.3 Agro-meteorological Models: WRF and GECROS ........................................................ 8 2.3.1 WRF Model setup ................................................................................................................. 9 2.3.2 The GECROS Model .......................................................................................................... 10 2.4 Design of Model Experiments ...................................................................................... 12 2.5 Data Analysis ................................................................................................................ 13 2.5.1 Data Analysis: Meteorological ............................................................................................ 13 2.5.2 Data Analysis: Crop yield ................................................................................................... 14 2.5.3 The Principal Component Analysis: Weather Vs Yield...................................................... 14 3 RESULTS ................................................................................................................... 15 3.1 WRF Model Outputs ..................................................................................................... 15 3.1.1 Model Performance ............................................................................................................