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Motivation: Ethiopia is one of the Sub-Saharan countries that are strongly influenced by climate fluctuations. These meteorological changes directly affect agriculture and consequently cause disturbances on the regional and local economy. To pinpoint a few crucial issues: (1) the agricultural sector in Ethiopia accounts for 80% of the employment and contributes 45% of the GDP. A relevant factor in relation to this PhD thesis is that the country’s agriculture is by 95% rainfed agronomy. (2) The Ethiopian landscape is composed of complex terrains of the East African mountain system – the Ethiopian Highlands (40% of the Ethiopia’s landmass is elevated more than 1500 m above sea level). This complex orography modulates weather and climate at scales ranging from local to regional. In the region, weather dynamics are mainly driven by both synoptic (e.g. Intertropical Convergence Zone – ITCZ) and mesoscale flows (e.g. lake and mountain breezes). These weather scales ultimately influence the way crops grow. The aim of this study was to evaluate how weather and crop growth vary in a complex terrain and heterogeneous landscape. I focus on the Gamo Highlands, south-west Ethiopia, a mountainous region with two large Rift-Valley lakes in Ethiopia. The crop of interest was potato – a crop that has become popular in Ethiopia, significantly contributing to food security and income, but sensitive to climatic variations. As a research method, I deployed a high-resolution weather and crop modelling approach to describe how the growth and yield of the potato crop depend on the variations in weather. For observation-based studies and for testing the models’ performance, six automatic weather stations were installed and field crop experiments were conducted near the stations. More specifically, this thesis addresses the role of meteorological crop drivers (e.g. the incoming shortwave radiation (SW↓), maximum temperature (Tmax), minimum temperature (Tmin) and precipitation (PPT)) and edaphic variables (soil moisture and soil temperature) on the yield and growth of the Ethiopian potato cultivars. Research methods and findings: In Chapter 1, I reviewed the contemporary global environmental challenge, the Anthropocene geologic era, in relation to the food system in perspective. In this chapter, I cascaded the problem from the global to the local scale. The chapter argued that the global weather models need to be downscaled to the local scales in order to study weather and climate impacts on crop dynamics in complex topographic landscapes such as Ethiopia. In Chapters 2 and 3, I presented the model-observation combined research strategy implemented in this thesis. The temporal and spatial variations in weather and crop dynamics are analysed using data from 2001 to 2010. To this end, the Weather Research and Forecasting (WRF) model is used to simulate weather at coarse (54 × 54 km2) and fine (2 × 2 km2) resolutions during the 10-years. The model is validated with in situ data. The meteorological crop growth drivers (SW↓, Tmax, Tmin, PPT, vapour pressure deficit and wind speed) and soil data from the ISRIC soil database are supplied as inputs to a process-based crop model called GECROS. The 10-year belg seasons WRF model analysis is showed large temporal and spatial variabilities in SW↓, Tmax, Tmin and PPT in the Gamo Highlands. For example, Tmax ranged from 10 °C on the summit of mount Guge to 30 °C in the valley around Lake Abaya and Lake Chamo. Temporally, the belg season of 2006 is identified as climatologically normal whilst the 2008 (driest) and 2010 (wettest) belg seasons are categorized as anomalous years. The temporal variations in simulated attainable potato yield showed a high yield (~20 to 30 t ha-1) during the normal belg season whereas the yield was lower (5 to 10 t ha-1 less than in the normal year) for the anomalous belg seasons (Chapter 2). As compared to the coarse resolution domain, the fine resolution domain is better represented topography and weather variations. Because of the improved representation of topography and weather in the fine resolution domain, the leaf area index (LAI) and the length of the growing season (LGS) simulated by the GECROS model were in the recommended range for potato (LAI of 3 m2 m-2 and LGS of 120 days are simulated). For comparison, modelled values were unacceptably low in the coarse resolution domain (LAI of 1.0 m2 m-2 and LGS of 60 days). It is also interesting to see that temperature and precipitation played opposing roles in the modelled yield, a phenomenon I called a compensating effect. To explain the term, moving up the mountains, the temperature decreases – with a positive effect on yield, and precipitation increases with a negative effect on yield. The lower temperature at higher elevation increases the LGS; as a result, more carbon is allocated to the tubers than in a shorter growing season. The higher precipitation at higher elevation may give rise to soil nutrient loss caused by leaching. Aloft the highlands, temperature and PPT are showed opposite trends, but their effects are balanced out in the ultimate yield (Chapter 3). Chapter 4 presented the Gamo Highlands Meteorological Stations (GEMS) – a network of six automatic weather stations, which were operational since April 2016 in two transects of the highlands. Near to the GEMS network, potato field trials are conducted. I used the GEMS data to study both the mesoscale and synoptic weather scales influencing the Gamo Highlands. Furthermore, I deployed the in situ data to the GECROS crop model. The GEMS data are analysed for belg-2017 showed major differences between the start (February) and the end (May) of the belg season. February and May are more mesoscale and synoptic scale weather system dominated months, respectively. During February, the day-night wind sources showed strong variation. Strong south to south-easterly lake breezes are observed during daytime; whereas, weak and more localised mountain winds are identified during the night-time. In May, the day-night flow contrast was small and the dominant flows were southerly. The location of ITCZ calculated by the NOAA (National Oceanic and Atmospheric Administration) and the GEMS observed sea-level-pressure (SLP) data showed strong correlation. My analysis showed that the low-pressure system (ITCZ) and the rainbelt are not coincided in the Gamo Highlands. The maximum PPT is received in May where the ITCZ is located on average nearly 6° (north) away from Gamo Highlands. During the maximum PPT in May 2017, the southerly moist air masses from the moisture sources (e.g. Indian Ocean) may move to the low-pressure system located to the north of the study area. During the daytime, PPT is less probable as cloud formation was less likely due to the enhanced solar radiation. However, during night-time, the southerly moisture can be trapped in the highlands and orographic PPT can be triggered. This PPT is locally modulated due to the presence of the Gamo Highlands and presence of the lakes. The moisture is crucial for potato agronomy during the belg season. The GECROS model sensitivity analysis, using the GEMS data, showed that model input of constant PPT (belg-averaged) gave the highest crop yield due to improved soil moisture throughout the growing season. Chapter 5 dealt with investigating the role of environmental factors on potato yield and growth in the Gamo Highlands. Here, the GEMS weather and edaphic data are correlated with crop growth variables such as plant height, canopy cover, yield and yield traits. The GEMS and crop observation datasets showed that plant height and canopy cover are strongly correlated with temperature sum (Tsum) with an r2 > 0.95 during the canopy buildup phase (P1). Tsum (d °C) is defined as the sum of the daily average temperatures during the growing season. The crop growth - Tsum correlation is further explained in terms of SW↓ and soil moisture, in which an improved (Gudene) and a local (Suthalo) cultivar showed different responses to SW↓ and soil moisture regimes. Data also showed that tuber yield is poorly explained by meteorological and edaphic data, suggesting further research activity in this regard. When the number of days to crop maturity was between 100-110 days, an optimal tuber yield is obtained. Chapter 6 presented the main findings of the thesis in perspective. Finally, Chapter 7 discussed the key findings in-line with the research questions stated in Chapter 1. Conclusions and perspectives: In complex terrain, weather/climate varies over short distances affecting crop growth. To describe crop growth and yield in the region, a high-resolution weather model, coupled to a crop model is needed. The weather model outputs can be used as input to the crop model. A dense station network installed in a complex topographic region can give us insights on mesoscale flows (e.g. lake-mountain flows), synoptic systems (e.g. south-north movement of the ITCZ) and crop growth (e.g. LGS and LAI). Additional weather stations (e.g. on the lee-side of the Gamo Highlands and east of the Lakes Abaya and Chamo) can give us improved understanding of weather scales and crop growth. Tsum during the P1 is found to be a good predictor of plant height and canopy cover for the Ethiopian potato cultivars. The poor correlation between environmental variables and yield and yield traits suggests more dedicated field experiments should be designed. One of the suggested field experiments is continuous monitoring of the partitioning of dry matter to the tubers to study how crop yield varies as a function of elevation and meteorology.

Weather and crop dynamics in a complex terrain, the Gamo Highlands – Ethiopia : Towards a high-resolution and model-observation based approach