How do you personally and professionally relate to water? Where does your interest in water come from?

I relate to water in many ways. As I was born and raised in a farming community, I am aware of water scarcity, and the critical need for clean water for humans and livestock. Since my childhood, I have been aspiring to contribute my part to sustainable development, especially in water resource management in the local community where water has a special role. For instance, a few decades ago, the upper Omo-Gibe Basin (i.e., the locality where I was born and grew up) had a good balance of surface and underground water resources. However, the area is currently experiencing water shortages due to natural factors and overexploitation to feed an increasing human and livestock population. The water levels of most of the streams, wetlands, and rivers have declined drastically in the area. Some of the wetlands and streams have even dried up. For instance, the tributaries to Gibe River including Kulit, Walga and Darge rivers have hugely declined in stream flows and are eventually drying up during the dry season (i.e., winter). As a result, the local people are experiencing critical shortages of water and opting to use alternative sources for drinking and livestock. The local farmers are shifting their livelihoods due to water and feed resource shortages and some are ceasing the rearing of livestock.  Therefore, I have a strong interest in applying remote sensing and GIS skills and knowledge to assess water resources and water quality of the watersheds and then to implement rehabilitation and restoration of the degraded. Moreover, the basin is located at an economically, socially, environmentally, and politically important location where Gibe-Sheleko National Park and Gibe-hydroelectric dams (I, II, and III) are downstream. The watershed is highly susceptible to land degradation due to natural and anthropogenic factors. Forestland and shrublands are converted into agriculture and settlements. The change in land use/land cover has led to land degradation in the area resulting in a decrease of soil fertility, crop production, and productivity.

As a leader of the Earth Observation Training, Education and Capacity Development Network (EOTEC DevNet) Africa Region Community of Practice Task Team, how do you think we can best assess EO-related capacity building needs in African countries? What approach do you suggest?

In my opinion, effective capacity development in Africa should address the user requirements and impact at the grassroots level.  Despite the enormous potential of EO to solve real world problems, there is a significant misfit between needs at grassroots level and the EO solutions presented to users. Demand driven capacity building trainings may allow to address the problems on the ground. For instance, in the case of crop monitoring in Africa, the participation of subsistent farmers and development workers in the design of EO applications/solutions is crucial to have an impact. These are the primary users and the one who make decisions related to climate, agriculture, and disaster risks at the farm level and more impacted therefore, the capacity development needs must be demand-driven

and impact-oriented. Stakeholder participation and coordination during problem identification, requirement analysis and the subsequent phases may address challenges that current capacity development activities are facing. Today, despite availability of free online trainings, EO data, products and services to improve skills and knowledge and achieve sustainable development in Africa, there is still significant gap on the use and usability of EO for solving societal problems such as flooding, droughts, earthquakes, locust, invasive weed infestations, agriculture …etc. I think, we can assess EO-related capacity building needs in African countries following an open, participatory and inclusive approaches that engage the users more. Addressing capacity development gaps in Africa requires a shift in thinking and making specific focus towards a problem to be solved than adopting approaches that worked somewhere rather co-creating/developing of a new EO solutions that address complex emerging issues including climate change, disasters, water issues, environmental degradation and pollutions is urgently required. 

What do you think are currently the biggest capacity building gaps in African countries, when it comes to using space-based technologies for water (here I speak of all water-related aspects that can benefit from space technology)?   

I think, the main gaps in capacity development in African countries related to the use of EO and space technology for water resources are failing to meet the user needs and lack of focus. There is also lack of coordination and the resulting duplication of efforts. Earth observation capacity-building ecosystems offer numerous free opportunities. However, they should address user needs at a local level. Trainees can easily transfer skills and knowledge they obtained into local applications that impact the local community bringing societal benefits and meeting sustainable development goals such as water quality and quantity monitoring in Africa. In Sub-Sahara Africa the most commonly used EO products are freely available datasets such as Landsat and Sentinel based products with medium spatial resolution. For applications requiring more precision, the resolutions of these products may not meet the needs. Another challenge is the lack of policy, political commitment and investment in EO.

What do you consider the key water-challenges to be solved in Ethiopia? How can space technology help address them? 

Ethiopia currently faces many water resource challenges including shortages of fresh water. Overexploitation of water resource to satisfy ever increasing demand of a growing population and livestock is the main cause for the decline of water resources. Additionally, the water resource of the country has been affected by the expansion of agricultural and urban lands, siltation, industrialization, infrastructural development, watershed degradation, climate change and water pollutions. Even though, there are promising efforts to restore water resources in the country, the efforts still need to improve and sustain to combat deteriorating water quantity and quality. There is also lack of coordination among stakeholders at the federal, regional, and local level including resource-dependent communities, private sector, civil society organizations, media, development organizations, and others. 

For instance, during June 2023, I moderated one session of a stakeholders’ policy consultation meeting in Addis Ababa that was held in collaboration with Digital Earth Africa and Association for Strengthening Agricultural Research in Eastern and Central Africa (ASERACA). Governmental agencies and non-governmental organizations (NGOs) that work in EO related fields had a policy dialogue to scale up the utilization of EO for Agriculture in Ethiopia. After an interesting dialogue, the takeaway points were: there is a promising progress in the use of EO in various sectors; a huge need to improve the use of EO in crop monitoring, water resource management…etc., as well as improved coordination and collaboration to remove duplications. 

The use of space technology can improve the monitoring of surface and ground water resources. It also fosters the resilience to disaster risks by allowing prediction of extreme drought, flooding events that frequently happen in the country capacitating decision makers to take appropriate preparedness and mitigation measures. In this aspect, Ethiopian Metrological Institute (EMI) is increasing the use of EO products to monitor water resources, but it can do even more to mitigate the risks associated to hydrological variability and to improve decision making. For instance, water bodies in the country have been exposed to siltation, pollution, invasive weed infestation, and water level reduction while assessments are mainly done via surveying methods. These phenomena can be better monitored using space-based and machine/deep learning modeling approaches. 

What are you currently researching? 

Currently, I am researching the seasonal dynamics of water quality and lake level changes in selected lakes of Rift-Valley Lakes Basin (RVLB). Additionally, I am assessing the infestations of these lakes by water hyacinth..

If funding was not an issue, what would be the topic of your choice in your research and why? 

Obviously, funding is the major challenges to do research, implement theories and scientific findings. Currently, we have limitations of budget to do scientific research and to implement the findings. Similarly, I have ideas and developed some proposals based on the local problems. For instance, I want to model the hydrology of the upper Omo-Gibe Basin and evaluate the state of fresh water using machine/deep learning and combining remote sensing and multisource data. Fresh water is becoming extremely scarce resource in upper-stream areas of the Basin. Population increases and continuous encroachment in the area coupled with climate change is causing scarcity of the water resource. Even though water scarcity is a global phenomenon calling for timely interventions and sustainable solutions, the upper stream areas of the Omo-Gibe basin need immediate interventions such as restoration, protection, conservation and appropriate management of rivers, wetlands, other water resources. 

You have been a technical team member and coordinator of Project Development Team of Rift-Valley Lakes Basin Development Project 2021-2035 (Arsi-Cluster). Can you elaborate on the project, describe the challenges within the basin and the approach taken to develop the basin? 

The Rift Valley Lakes Basin is located in the South-West of Ethiopia covering 53,000 km2 area with the potential of 5.6 BM3 annual water resource. The basin has four sub-basins with seven major lakes, 14 watersheds and major rivers feeding the lakes. A series of lakes in the basin are connected and hydrologically sensitive. The lakes in the basin are becoming pollutant sinks, the water quantity and quality is declining. Population pressure, agricultural expansion, urbanization and infrastructural developments are posing increasing pressure in the basin. As water is the central element of Integrated Water Resources Management, its quality, quantity, allocation, ecosystem services, extreme events, and similar issues need to be strategically managed. As a team member in Rift-Valley Lakes Basin Development Project 2021-2035, we have developed: i) Ziway-Shalla Lakes Sub-Basin Strategic Plan (2021-2035), ii) Rift valley Lakes Basin Watershed Management Thematic Plan for 2021/2022, iii) Rift valley Lakes Basin Watershed Management Implementation Plan 2022/2023, iv) A Watershed Development-Mega Project 2022/2023 (i.e., Integrated Watershed Management for Sustainable Water Resource Development in Katar and Meki Watersheds, Rift Valley Lakes Basin, Ethiopia), and v) Five Projects on Rift valley Lakes Basin Watershed Management 2022/2023. However, for the implementation of basin development plan, lack of funding and coordination of stakeholders are some of the major challenges.  

What are the key challenges in watershed management, and how can space-technologies help? 

The key challenges in watershed management include: population growth, increased economic activity, overuse of water resources, pollution, watershed degradation, climate change, and scarcity of fresh water, to name just a few. Water quantity and quality have been declining impacting sustainable development and causing severe deterioration of ecosystems. Therefore, immediate action needs to be taken to minimize the impacts. At watershed and basin level, strategic planning to implement Integrated Water Resource Management is key to achieve the sustainable development. To facilitate a watershed development plan and to implement key integrated watershed development activities, EO plays an important role. For instance, to perform watershed situation assessment and to identify hotspot intervention areas the use of space technologies is imperative. To assess the current state of a watershed, descriptions of location, geographic coverage, physiography, assessment of surface and ground water resources situation (e.g., potential and quality), existing practices within watershed land use/cover, level of erosion, sedimentation, deforestation, overgrazing, flood, drought can be identified and quantified using EO/space technology. Remote sensing-based watershed assessment can provide insightful and precise information to design strategies for integrated watershed development and management.

With a very versatile skillset ranging from IT, remote sensing, GIS applications and applying those to various aspects of water management and management of aquatic ecosystems, what would you recommend young professionals to develop their skills in the use of space-based technology and data for water? 

I advise young professionals to focus on the emerging, innovative and applicable space-based technologies for specific use. For instance, on skillsets that can readily be applied to solve the local problems of agriculture, environment, urbanization…etc. For instance, farmers in the SSA region have been increasingly facing challenges related to the changing climate, emergence of new pests, infestation of water bodies with emerging weeds, locust, drought and short rainfall, flooding, unpredictable onset and cessation, etc. I strongly recommend the young professionals to focus not only on the hard skillsets but also look at what societal impact they may contribute to and the theory of change. 

The new challenges and problems faced nowadays require utilization and application of advanced and innovative technologies such as space technology/EO, big data mining and Artificial Intelligence (AI), which offer tremendous capabilities and functionalities. Nowadays, a comprehensive skillset ranging from programming/coding, scripting, analysis, image processing, pre-processing to presentation and communication skills are highly needed. For instance, to use remote sensing data, professionals need to have image pre-processing skills such as: such as masking for invalid retrievals, or computation for anomalies, since some datasets provided by space agencies are not analysis ready. Users can choose among many platforms, data, products and services to satisfy their needs. Examples include: Sentinel Hub (SH) and Google Earth Engine platforms providing Sentinel data access, visualization and scripting services. A wholistic skillset of digital image processing (DIP), scripting, and coding is relevant. In an everchanging technological ecosystem, EO experts should possess multidisciplinary skills including soft-skills that help to understand the business side or to solve a given problem. 

In my view, learning should never cease by obtaining degrees or certificates but should continue everyday adding new key skills that may contribute for the improvement of the living condition of global society. In an ever-changing world, I recommend young professionals to develop their skills such as: geospatial artificial intelligence and the various uses of space-based technology and data for water.

What are the key ingredients to develop a good model? 

Although most of the EO data, products and services such as (medium resolution LANDSAT and Sentinel images and products) are in the open domain, there is still huge gap in terms of the full utilization of EO data, products and services for decision making, especially at local level or at farm scale in Africa. This is due to many contributing factors including a mismatch between the developed models and local problems, digital divide, shortage of skilled manpower and lack of awareness. Additionally, there is huge lack of coordination and commitment to use EO among policy makers, ministries, state and non-state actors partly because the information provided by EO may not exactly fit to the existing problems. For instance, in Sub-Sahara Africa the application of EO for monitoring of crops at field level where most of the fields are fragmented and farmers practice inter-cropping and mixed-cropping systems may face challenges. It may need high spatial resolution products and data than provided by freely available. It is also difficult to discriminate, verify and validate since most pixels may likely show mixed crops. Furthermore, scientific studies and the models developed often fail to take into account farmers’ needs. For instance, the primary stakeholders (i.e., smallholding farmers and development agents) may have low literacy to use the results of scientific models. 

Therefore, to support farmers the developed model should address the farmers need at grassroot level. For instance, in Ethiopia, farmers use their indigenous knowledge to determine various farming decisions including: the on-set and cessation date of rainfall, the dry spells and soil moisture conditions, planting time, selection of crop varieties, and farming practices. The model should be able to solve the problems as precisely as possible. 

In my opinion a good model should be usable and impactful. However, to develop a good model there are requirements including availability of quality data, for instance, for watershed management model a key element such as: precipitation, evaporation, transpiration, soil water, baseflow, streamflow, etc. should be integrated. EO may not be able to provide data for all, and at the same time it is difficult to take a number of ground control samples for large areas. In modeling, dense ground-based validation datasets are required. EO based models for water resource management can be improved by integrating multi-sensor and multi-source data. 

What are the essentials of image analysis that everyone using EO data should know about? Can you recommend any online training sources to acquire these skills? 

To develop a skillset in remote sensing image analysis there are numerous online resources for learning such as: webinars, MOOCS, online trainings, conferences, and workshops. Additionally, cloud-based analysis tools and computing platforms including Google Earth Engine (GEE), European Space Agency Data and Information Access Services (ESA DIASs), open-source interface between Earth Observation (OpenEO), Microsoft Azure, Amazon Web Services (AWS), etc. provide essential platforms. Currently, EO is generating data in Peta-bytes and cloud computing enables efficient storage and exploitation of big-datasets. Since, the current advances in EO and image analysis require continuous learning, everyone interested can use online learning materials. Modelling approaches in EO are also changing from process based into data-driven approaches such as machine/deep learning approaches that have capability to deal with the complexity of real-world problems and the large volume of EO data. Emerging problems need an innovative and new way of thinking, skillsets, and knowledge that should be updated continuously. 

Additionally, there are interesting initiatives and networks such as the Earth Observation Training, Education, and Capacity Development Network (EOTEC DevNet) which are providing information on a list of opportunities for capacity building trainings and courses. I suggest everyone interested in EO to become an active member of EOTEC DevNet by signing up for the EOTEC DevNet Community (  

What do you need to innovate? 

My personal ambition and career goal is to contribute my part for the betterment of human life in general. I have been aspiring to improve the decision making of subsistent farming society, where most of agricultural practices are performed using traditional methods. So, I need to innovate on the ways to improve the decision making of smallholder farmers in Sub-Saharan Africa. Africa faces complex problems caused by a changing climate and environmental degradation. I want to contribute my part for wise use of the valuable natural resource. I sincerely seek to improve myself continuously in my professional career and want to be a change agent and contribute my part for achievements of SDG-2 zero hunger goals. I want food self-sufficiency to be achieved in Africa, and I earnestly think that application of EO solutions to support agriculture, environment and development can produce good future.

What is your favourite aggregate state of water? 

At the moment I am most interested using EO to study water management including quality and quantity monitoring of inland lakes, rivers, streams and wetlands. That means, I favor studying water at fluid state.