Could you describe how your professional and/or personal experience relate to water? Where does your interest in water resources management come from? What influenced your decision to focus your work on the use of space technology for water management? 

My upbringing on a farm set out the foundation for my interest in water resources, as I used to collect water for domestic and agricultural purposes from the streams. This led me to pursue research in the field of hydrology during my postgraduate studies, which enabled me to get a deeper understanding of the dynamics of water resources.

My interests now span from the hydrological cycle, to human infrastructure development and the encroachment on flood prone, flood  risk and runoff retention areas. The latter could be serving as important groundwater recharge potential zones. I believe that some communities’ groundwater recharge will dwindle in the coming generations as a result of encroachment on water resources’ potential zones. To contribute significantly to addressing such issues, my research focuses on delineating flood risk areas and estimating groundwater recharge, and potential zones using remote sensing, the soil and water assessment tool (SWAT) and Machine Learning (ML). This enables me to contribute to both water and disaster management efforts. 

You believe that the use of technology and its adaptation for efficient management of the environmental and natural resources would aid the implementation of local and large-scale projects in support of sustainable development. Which water-related SDG indicators could benefit from using space-based technologies and data, and what could that mean for development in Africa?

I believe that space technology and its adaptation represent a paradigm shift in the management of natural resources. Efficiently modelling groundwater, floods, and surface runoff dynamics in a catchment, watershed or basin requires the use of space technology and spatial datasets.  Space-based technologies and datasets are beneficial and sometimes even critical in mapping and modelling local and regional water stress, water management, water quality, drinking water, water bodies that are subject of transboundary issues, natural disasters, and ecosystems. Due to the encroachment on low-lying areas and climate change, perennial floods have become rampant. However, with the use of space technology and data, these areas can be mapped and buffered from infrastructural encroachment. The adaptation of space technology is also playing a major role in the development of water resources in Africa transboundary water negotiations, groundwater modelling, watershed or catchment modelling, spatial modelling of water vulnerability, drought risk assessment and monitoring because hydrologists and water policymakers rely on the results modelling using spatial datasets and techniques. 

It is important to state that, space technology and its datasets have proven significant in achieving water-related SDGs indicators such as:

  • 6.5.1: Degree of integrated water resources management, 
  • 6.4.1: Change in water-use efficiency over time, 
  • 6.6.1: Change in the extent of water-related ecosystems over time, 
  • 6.5.2: Proportion of transboundary basin area with an operational arrangement for water cooperation, and 
  • 6.4.2: Level of water stress: freshwater withdrawal as a proportion of available freshwater resources.

What are key challenges in satellite remote sensing of climate change, particularly in relation to drought and flood risk assessments? How can they be overcome?

Building and operating satellites, and even setting up receiving ground-based stations, are generally expensive, which presents difficulties for satellite remote sensing of climate change. However, climate change datasets are important for drought and flood risk modelling, and notwithstanding, high-resolution data at the local and regional scales are usually unavailable, making predictions at community level very difficult.

The era of climatic extremes has made water-related disasters unpredictable. Timely interventions are paramount to emergency response, informed decision-making, and research addressing climate change. Dataset pre-processing and validation have been a challenge in effective modelling of extreme weather events including floods, heatwaves, and droughts. 

Collaboration is a key factor in overcoming or reducing the severity of these disasters or challenges. Local, national, regional and international collaborations to share data and ensure financial aids are fundamental in our response to climate change. Moreover, I think scholars could benefit from academic institutions with ground-based satellite stations for data receiving and storage offering research opportunities including for students and other professionals.

You are currently developing your Ph.D. dissertation; can you tell us more about your research and how are you using space technologies and data? Expand on what methodology and data sources you are using in your research? So far, what are the main insights and trends you got from this research? What are main implications of the results of this research?

My PhD research focuses on hydrological dynamics in my home region, the Upper West Region of Ghana, where perennial floods have become rampant. My first objective is to conduct a spatial assessment of flood risk terrains within the region and to secondly model groundwater recharge estimation and potential using spatial datasets such as optical images, and data on soil, digital elevation models, rainfall, wind speed, relative humidity, solar radiation and temperature), GIS, soil and water assessment tool (SWAT), and machine learning techniques.

The aim of this research is to develop flood risk terrain maps and identify possible contributory factors to floods, and to assist local communities and districts in planning settlement as well as to advise farmers on the best time to commence farming during the rainy seasons. My preliminary observations indicate that several communities are located within low lying areas that serve as waterways, waterlogged and retention zones. 

Modelling groundwater recharge and potential zones is crucial because infrastructural projects have substantially been encroaching on wetlands, groundwater potential zones and the rampant drilling of boreholes. The latter could also lead to over-abstraction of water leading to the inability to supply future generations with this important resource.

Can you briefly discuss how the various applications of the technology, such as remote sensing, Earth observation, geo-information sciences, navigation, communication can assist water infrastructure/resources management and what their limitations are? 

The mentioned technologies can assist water infrastructure and resources managers by providing (near) real-time data for monitoring, early warning systems, and water resources allocation. Geospatial technology plays a major role in water resources management and infrastructure development. They are used in the conservation of watershed resources, efficient management of water resource distributions, and for delineating water resources such as groundwater potential zones, rivers, streams, lakes, ponds, and estuaries. Moreover, they are used in modelling the impacts of climate change on water resources and in developing early warning systems for floods and groundwater.

Satellite imagery helps in assessing surface water extent, monitoring and detection of water quality or pollution to enable evidence-based decision making. More importantly, geo-information sciences and navigation systems are efficient for planning water resources allocation, creating vulnerable areas maps and hydrological modelling, as well as water transportations and distribution to areas with varying demands across a catchment or communities. Similarly, communication technologies also assist stakeholders such as local communities, NGOs, and government agencies by facilitating real time data sharing on water availability and accessibility, water demands and existing water infrastructure conditions. This improves water resources management among collaborators significantly.

I would like to add that most modelling techniques are sophisticated and generally require workstations and powerful laptops for simulations; a barrier in most developing countries, including my home country, Ghana. Secondly, data accuracy and cost are also fundamental challenges for precise and evidence-based decision making. Students in developing countries too often prevented from pursuing studies on topics of their interest due to the inability to access powerful computing resources on campus.

What still needs to be explored about the use of space technology and data for water management? How will these address current water-related challenges?

There is the need for international cooperation among organizations, government departments or agencies and other involved actors to globally collect and share water-related data and research findings, which in turn can foster innovation and knowledge creation. Such an approach supports local, regional, and global scale evidence-based research, and can contribute significantly to scalable implementation of projects, a broader understanding of current water-related challenges, and in the long-run to ensuring water sustainability. 

Furthermore, machine learning, and advanced data analytics on space-based and open data, stand the paradigm shift by identifying patterns or anomalies in large data sets. 

Moreover, an improvement in spatio-temporal resolutions would allow researchers and practitioners to derive more information on water bodies, watersheds and or catchments. This can improve monitoring and quick responses to water-related issues in and around smaller water bodies and catchments – something that is especially important for local communities. 

The provision of robust Earth observation (EO) platforms or apps that can efficiently run on our phones to detect and forecast floods, would be ground-breaking. With the intensifying effects of climate change, and exacerbating natural disasters such as perennial floods, this aspect will become increasingly important. Simple EO platforms are needed for individuals without technological knowledge such as my grandmother in the village or a local community overall.

Additionally, offering research grants and fellowships in space technology for water resources modelling for postgraduate students and researchers, would greatly contribute to addressing water-related challenges. Workshops are also dynamic ways to expose researchers, managers, and policymakers in the field of water resources to the resources of space technology. 

A geographic information system (GIS)-based multi-criteria analysis approach including remote sensing data is often used for modelling optimum sites for rainwater harvesting. Briefly explain the concept, data requirements, indices and/or parameters, and the methodology for such a study.

The concept of rainwater harvesting (RWH) is the collection and storing of enough rainwater for the purposes of domestic use, irrigation, and as well as groundwater recharge. To identify the suitability of an area or site for an RWH system, several datasets, criteria, and factors that influence rainwater (RW) volume, storage potential and runoff are taken into account.

Multi-criteria analysis (MCA) is a decision making support tool that facilitates the comparison of different criteria and/or factors influencing an output variable. For example, in spatial modelling of RWH, the principles of Saaty, (1980), mathematics and a GIS based analytic hierarchy process (AHP) (a form MCA ) to strategically compare the different criterion or factors that will significantly influence rainfall availability at a given location, within a particular site, region or catchment. Datasets are basically used to generate suitability maps for RWH system projects. They include but are not limited to: slope, rainfall, land use land cover, drainage density, and soil type etc. The visualization of these generated maps aid in deciding on the optimal site for RWH projects. 

EO satellites provide frequent estimates of precipitation. Spatial modelling of high rainfall zones or catchments is integral for designing and using rainwater harvesting systems and for determining the types of crops to be planted in such areas. The integration of rainfall and other spatial datasets through the use of GIS-based MCA has improved not only rainfall modelling but also groundwater potential modelling.

As a young researcher from Ghana, how do you experience the awareness of the potential of space technology and access to space-based data in this country? What are your observations?

Classes on space technology and related topics have been taught in several universities across the country for quite some time. I started learning about space technology and space-based datasets as an undergraduate student, and later, as a teaching and research assistant. I had not been taught GIS and Remote Sensing in specific courses  but my professor, being a space technology enthusiast, exposed me to them. Later on, when enrolled in a master’s programme in water resources engineering and management, I took courses on geospatial technologies. However, the combination of space technology and modelling techniques, with machine learning algorithms and data science in is still limited in most programmes. 

I think the awareness of space technology and its usage, especially for water resources management and development, and natural resources management is very low. To allow for ground-breaking research and better methods to solve water-related challenges, everyone should have the opportunity to enrol in such courses.

In your view, what are key challenges to be addressed to sustainably manage water on Earth? 

Unregulated timber logging and mineral resources mining along and within water bodies should be stopped. It is well noted that menace from these anthropogenic activities exacerbate the current challenges of water resources management. In addition, too limited attention is given to the implementation of water resources research findings e.g. within national water resources management plans, especially in many developing countries. Therefore, it is important for researchers and academic institutions to foster collaborations with relevant stakeholders. 

Additionally, a synergy of geospatial engineers, social scientists, physical scientists, and policymakers can lead to a broader understanding and usage of space technology, which can significantly contribute to sustainable water resources management and environmental conservation.

What is your favourite aggregate state of water? 

I enjoy visiting rivers, streams and lake sites. Water nourishes the beauty of nature and that generally made me fall in love with water. Therefore, my favourite aggregate state of water is liquid.