TAHMO

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In the Lake Kivu region, water erosion is the main driver for soil degradation, but observational data to quantify the extent and to assess the spatial-temporal dynamics of the controlling factors are hardly available. In particular, high spatial and temporal resolution rainfall data are essential as precipitation is the driving force of soil erosion. In this study, we evaluated to what extent high temporal resolution data from the TAHMO network (with poor spatial and long-term coverage) can be combined with low temporal resolution data (with a high spatial density covering long periods of time) to improve rainfall erosivity assessments. To this end, 5 minute rainfall data from TAHMO stations in the Lake Kivu region, representing ca. 37 observation-years, were analyzed. The analysis of the TAHMO data showed that rainfall erosivity was mainly controlled by rainfall amount and elevation and that this relation was different for the dry and wet season. By combining high and low temporal resolution databases and a set of spatial covariates, an environmental regression approach (GAM) was used to assess the spatiotemporal patterns of rainfall erosivity for the whole region. A validation procedure showed relatively good predictions for most months (R2 between 0.50 and 0.80), while the model was less performant for the wettest (April) and two driest months (July and August) (R2 between 0.24 and 0.38). The predicted annual erosivity was highly variable with a range between 2000 and 9000 MJ mm ha−1 h−1 yr−1 and showed a pronounced east–west gradient which is strongly influenced by local topography. This study showed that the combination of high and low temporal resolution rainfall data and spatial prediction models can be used to improve the assessments of monthly and annual rainfall erosivity patterns that are grounded in locally calibrated and validated data.

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Based in Chicago, Farm Immersive is a weekly blog by Peter Miller. His posts explore global food and agriculture innovations.

In a recent blog published on the 13th of April 2020 we got a honorary mention. In the Peter Miller’s exact words TAHMO is a bold project to build weather stations across Africa and share that data free of charge. This will greatly enhance all crop insurance modeling across the continent”.

want to read more on this beautifully written piece? click here


With the global COVID-19 pandemic, activities have been highly slowed down. However, Victor in Kenya is trying to keep things moving. Being a field engineer, it is a bit complicated for him to work from home, but during this pandemic, he adjusts and finds ways to ensure that field activities do not stop completely especially for stations that need urgent maintenance - for the data, we lose today cannot be readily regained. Read more

COVID-19

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Due to the current COVID-19 situation stations uptime might be affected. We are doing our best to maintain a very high uptime but remote stations could be affected due to restrictions on travels in these difficult times.

ENDEAVOR TO STAY SAFE
– Avoid public gatherings or crowds.
– Wash your hands with soap for at least 20seconds when you come in from public areas or use an alcohol-based (more than 60%) sanitizer.
– If there are restrictions of movement in your locality, kindly heed to them.
– Practice social distancing.


Vulnerability to Blue Tick will likely increase in the coming years in Laikipia County in Kenya unless stakeholders intervene. This is according to Peter Mbugua, a Geospatial Information Science and Remote Sensing student at Dedan Kimathi University in Nyeri, Kenya.

Influences of climate changes in the spatial and temporal variation of tick-borne diseases (TBD) are frequently overlooked by researchers. Consequently, there are no effective control strategies and measures to minimize the spread of TBD’s. This results in the loss of livestock, lower productivity, decrease in human health and reduced income from (agro)tourism.

Peter has identified areas in Kenya for low, middle and high risk of TBD. Through using GIS-based Multi-criteria evaluation – including humidity, rainfall, temperature, wetlands, rivers, and slope of the county – Peter determined that the changing trends in weather patterns in the last 15 years continues to favors parasite survival. 

These results can be used to implement measures to counter the spread. For example, high-risk areas can be sprayed and pastoralists can be informed about farm &-livestock management to prevent the spread of tick-borne diseases.

**Written by Peter Mbugua


Commissioning of the ATMOS 41 Automatic Weather Station of TAHMO.
Commissioning of the ATMOS 41 Automatic Weather Station

To keep pace with advancement in sensor design and technology on weather related issues, the Vice-Chancellor of the Federal University of Technology, Akure, Professor Joseph Fuwape has commissioned a newly installed 4th Generation ATMOS 41 Automatic Weather Station (AWS) at the WASCAL Centre, FUTA. This is an upgrade of the 1st Generation Trans-African Hydro-Meteorological Observatory (TAHMO) Automatic Weather Station (AWS) which was installed at the WASCAL Meteorological Observatory at the Federal University of Technology, Akure in 2014 as the first TAHMO Station in Nigeria.

Continue reading…


The TWIGA Kumasi Hardware Hackathon

**Written by Nick van de Giesen
TAHMO has been working with the TWIGA project since the start of 2018. An important output of the TWIGA project will be new geo-services (twenty!) based on the application of innovative sensors. In order to speed up the development of these services, a Hackathon was organized from 19 through 23 November 2018 at the Kwame Nkrumah University of Science and Technology in Kumasi Ghana. The objective was to build complete value chains, from observation to internet storage to service delivery. We aimed high on purpose to see what can and cannot be done in such a short time. The results are very promising! Continue reading on the TWIGA website…

TWIGA hackathon participants showing their environmental weather innovations.
TWIGA Hackathon participants showing their innovations!

**by Bonventure M Makhaya, TAHMO Kenya Intern

Agribusiness is emerging to be the next income generating sector whose potential is yet to be exploited fully. The wider public perceives agriculture as ‘just farming’, just raising livestock and growing crops. For most farmers in Kiambaa constituency in Kiambu County it’s a different narrative. For one James Muuga from Kamuguga village, it’s a treasure chest.

He describes Agribusiness as the farming, management, production, and marketing of agricultural commodities. He pays much attention to the ever-changing weather. In his own words; there is no proper farming without paying attention to underlying factors that may affect the end product. Mr. Muuga is a full-time farmer and he is very passionate about it, from poultry, cattle keeping, Pig rearing to kale cultivation. He believes weather plays a major role in the amount of milk produced, egg production, to prices of processed and unprocessed feeds. He, however, feels there exists a gap when it comes to dissemination of weather information. Asked about how he manages to sell all his produce, he points out Masoko as the platform he currently engages with though he has sold his produce to Twiga foods Kenya in the past. One lesson I learn is, in the 21st-century smart farming is the way to go and technology is inevitable.

I paid a visit to Mr. Gabriel Kihara in charge of research at National environmental Trust Fund (Net Fund) to get his views on the same. He starts by highlighting the achievements the entity has made. With over 4000 farmers under their watch and funding they have no regrets whatsoever .He however is quick to point that the channels used to disseminate weather information are not that efficient. He believes Weather and Agriculture are entwined and they are very open to discussion and further engagements with TAHMO. After the interactive sessions, these two questions kept crossing my mind. What is in Agribusiness for me? Which opportunities are in Agro-meteorology yet to be exploited and how can we improve on dissemination of weather information?