 You can start. This is the microphone. Get to set. Forward backwards, finding the screen. 10 minutes, and I will give you a word. Yeah, thank you very much, Erica. And good morning, everybody. My name is Alexis Zengham from Uganda. And I hold a PhD in soil water management. So I work on maize and changing climate in Uganda. And also I study the impacts of climate smart agriculture practices, which have been adopted in the rain-fed conditions in Uganda. So the outline of this presentation will look at basically the impacts of climate change on yield, grain yield, and water use efficiency. So in this presentation, the focus was basically on the impacts. How yield is projected to decrease globally due to climate change effects. And Uganda is part of those countries which will be affected, given the fact that maize is one of the major food security crops. Also, in terms of employment, agriculture also employs a large number of people. This is some of the ongoing studies about the variability in precipitation and also change, computed from long-term years so far. And there is evidence that at least there is a change in the climate. To address the issue, especially in agriculture, we adopted climate smart agriculture practices as one of the approaches for increasing food security. But the focus of this is basically to increase soil water management. And also, these practices have been recommended by FAO. However, they have been inadequately instrumented in rain-fed cropping systems. So we tried to tease out a number of practices. For example, mulching, permanent planting benzene pits, half-moon pits. And they were compared with the conventional practices. Basically, the aim, we want to realistically bring out the scientific contribution in terms of improvement in yield and soil water storage, which is highly needed for a high water use crop like maize, for example. And also looking at the role of CSA practices, they can address the issue of limited rainfall because practices like mulch insulates the soil surface and decreases soil evaporation. And also in terms of water use still, transpiration, when there is availability of water, the storage, there is high chances of water use and uptake to the crop so that you limit water stress. So CSA is supposed to address that, especially, sorry. CSA is supposed to address that kind of challenge like soil evaporation and also limited rainfall so that the water use is increased. So this was just the kind of experimental design which we used. Personally, I instrumented these practices into a long-term experiment. Like it was two years, and we tried to study these practices. And control is the conventional practice by the farmers, smallholder, and the half-moon pits represented by HM and PPB. They are permanent planting bensini pits. And also mulch. These are some of the practices which are recommended by FAO in the Tropical Agricultural Climate. So mulch here was valid in different variations, 2-centimeter, 4-centimeter, and 6-centimeter. Basically, this experiment, basically the experiment, it helped in parametrizing the model because we obtained the seasonal data. But basically, we wanted to collect the observations from this experiment so that we parametrized the aqua crop model in the seasons. And this is how we did it, basically for calibration in purposes. And the season three was used for calibration in season one and season two were used for validation of the model. Aqua crop model was chosen because it is a water-driven crop model. And since they started basically measured on crop water use efficiency, that's why I adopted the aqua crop model. After getting the observations for the crop, basically it was an input for the aqua crop model in the crop file. But we needed climate as a driver for this kind of activity. And I employed the GSM model by first downscaling using the Agimep protocol procedure. And for Agimep, it is agricultural intercomparisoning improvement model project, which has been implemented in Eastern Africa. And basically, these were models integrated at the regional level to study the impacts of climate change in agricultural sector, livestock, and livestock. So basically here, we downscaled. And the models were clustered into different regimes, as you can see. And all these regimes represent different, they are represented by different models. And the color also responds to different climate regimes. So basically, this one helps us to select which models using the assemble mean, which models really are near to the climate of the study area. But remember, in the downscaling, we used third-year data, climate data, from the study area where the experiment was done. On the results, basically, the grain yield was impacted, it was simulated. And we show how the CSA practices, which are down here, how they influenced the yield, how they impacted the yield, and also the contributions of these practices towards yield enhancement. And also, the same thing on water use efficiency, also, under projects of the climate change scenarios, also the impact was simulated. And clearly, we see that there is an advantage of using these practices in terms of increasing water use efficiency. Some of these results, 15 minutes, is not enough to present the whole work of like two to three years. But these results have been published. And actually, they can be found in this journal, so they could be accessed. Also, as I complete, we are trying to move this project ahead, first, by trying to use now SIMI-6 to simulate the impacts of soil water management. And this one is currently starting to do it with the assistance from Alex Rayne. And we are trying to use intersectoral model ISMIP projects to study the impacts using SIMI-6. Thank you very much for listening. Thank you. Question?