Sustainably manage forests, combat desertification, halt and reverse land degradation, halt biodiversity loss
Forests cover 30.7 per cent of the Earth’s surface and, in addition to providing food security and shelter, they are key to combating climate change, protecting biodiversity and the homes of the indigenous population. By protecting forests, we will also be able to strengthen natural resource management and increase land productivity.
At the current time, thirteen million hectares of forests are being lost every year while the persistent degradation of drylands has led to the desertification of 3.6 billion hectares. Even though up to 15% of land is currently under protection, biodiversity is still at risk. Deforestation and desertification – caused by human activities and climate change – pose major challenges to sustainable development and have affected the lives and livelihoods of millions of people in the fight against poverty.
Efforts are being made to manage forests and combat desertification. There are two international agreements being implemented currently that promote the use of resources in an equitable way. Financial investments in support of biodiversity are also being provided.
The Lion’s Share Fund
On 21 June, 2018, the United Nations Development Programme (UNDP), FINCH and founding partner Mars, Incorporated, announced the Lion’s Share, an initiative aimed at transforming the lives of animals across the world by asking advertisers to contribute a percentage of their media spend to conservation and animal welfare projects. The Lion’s Share will see partners contribute 0.5 percent of their media spend to the fund for each advertisement they use featuring an animal. Those funds will be used to support animals and their habitats around the world. The Fund is seeking to raise US$100m a year within three years, with the money being invested in a range of wildlife conservation and animal welfare programs to be implemented by United Nations and civil society organizations.
Facts and Figures
Forests
Around 1.6 billion people depend on forests for their livelihood, including 70 million indigenous people.
Forests are home to more than 80 per cent of all terrestrial species of animals, plants and insects.
Between 2010 and 2015, the world lost 3.3 million hectares of forest areas. Poor rural women depend on common pool resources and are especially affected by their depletion.
Desertification
6 billion people depend directly on agriculture, but 52 per cent of the land used for agriculture is moderately or severely affected by soil degradation.
Arable land loss is estimated at 30 to 35 times the historical rate
Due to drought and desertification, 12 million hectares are lost each year (23 hectares per minute). Within one year, 20 million tons of grain could have been grown.
74 per cent of the poor are directly affected by land degradation globally.
Biodiversity
Illicit poaching and trafficking of wildlife continues to thwart conservation efforts, with nearly 7,000 species of animals and plants reported in illegal trade involving 120 countries.
Of the 8,300 animal breeds known, 8 per cent are extinct and 22 per cent are at risk of extinction.
Of the over 80,000 tree species, less than 1 per cent have been studied for potential use.
Fish provide 20 per cent of animal protein to about 3 billion people. Only ten species provide about 30 per cent of marine capture fisheries and ten species provide about 50 per cent of aquaculture production.
Over 80 per cent of the human diet is provided by plants. Only three cereal crops – rice, maize and wheat – provide 60 per cent of energy intake.
As many as 80 per cent of people living in rural areas in developing countries rely on traditional plant-‐based medicines for basic healthcare.
Micro-organisms and invertebrates are key to ecosystem services, but their contributions are still poorly known and rarely acknowledged.
Space-based Technologies for SDG 15
Protecting nature and biodiversity is an increasingly important challenge for humanity.
Satellite technology can be used to track endangered species and disrupt the poaching activities that drive the illegal wildlife trade.
UNOOSA helps stakeholders in biodiversity and wildlife management use space applications to monitor, assess and manage biodiversity and ecosystems. http://www.unoosa.org/oosa/en/ourwork/psa/emnrm/biodiversity.html
In this interview, we discuss how time-series of satellite data can be used to monitor the environmental, and more specifically the water domain, using the data cube technology.
Professor Wagner holds a Ph.D. in remote sensing. He gained his experience at renowned institutions, including academia, space agencies and international organisations. He is the Dean of the Faculty for Mathematics and Geoinformation and cofounder of the Earth Observation Data Centre for Water Resources among other affiliations.
The following interview with Dr. Sherine Ahmed El Baradei is focusing on water quality and its relation to space technology. Water is the essence of life. Thus preservation of water quality is of a big concern to human health and to fauna and flora in water bodies. The interview explains what is water quality and what are water quality parameters of water bodies. Furthermore, the importance of using space technologies and applications in contributing to water quality monitoring and determination of hydraulic and hydrologic conditions is thoroughly discussed. For example, temporal resolution of satellites and their role in obtaining accurate imaging and data is clarified and the satellites concerned with water quality monitoring are pointed out. Considering the important role of groundwater in arid regions, the use of GRACE Mission data in Egypt is mentioned. Moreover, key influences on water quality in Egypt are discussed and the relation of water quality to water scarcity in the country and ways to preserve water quality is being discussed. Furthermore, the potential of space-based monitoring used to address water issues from hydrological to water resources issues in the country or region is pointed out. The challenges of the use of space technology for hydrology and water-related topics in the MENA region is also discussed. Light is shed on the project done by NASA to recycle astronauts’ waste into energy and power. Sustainability is of a great importance to or communities, and thus it is discussed how sustainable it is to build cities in the desert, or to divert water to where people are instead of moving people to existing water sources. Finally, a discussion about ways we can employ to improve awareness and capacity building on the use of space technology for water and challenges in this field are discussed.
Ailin Sol Ortone Lois is a Remote Sensing specialist at Remote Sensing Center of the Argentinian Air Force, where she applies space technologies to monitor Natural Areas of the Defense. She is the Director of Synthetic Aperture Radar Research Group at the National University of Technology (UTN), where she leads a project related to glacier monitoring and mass balance calculations using free open remote sensing sources. Ailin also teaches physics at UTN and geomatics at the National University of Luján, in Buenos Aires.
How do you personally and professionally relate to water?
Growing up in Israel, water scarcity was a constant backdrop to my childhood. The arid climate and frequent droughts shaped my relationship with water from an early age. One vivid memory that remains stamped in my mind is the series of TV campaigns highlighting the importance of water conservation. I recall sitting in front of the television, concerned by the urgency conveyed in those campaigns. The images of dry landscapes and the emphasis on every drop of water as precious left a lasting impression.
Sawaid Abbas, Assistant Professor at the Centre for Geographical Information System, University of the Punjab, Lahore, Pakistan discussed his extensive work in addressing water-related challenges through the nexus between smart sensing and space technologies. His thematic focus spans water scarcity, food security, climate risks, and environmental monitoring with an emphasis on the Asia-Pacific region, including Pakistan and China. Key Sustainable Development Goals (SDGs) guiding his work include SDG2 (Zero Hunger), SDG13 (Climate Action), SDG15 (Life on Land), and SDG11 (Sustainable Cities and Communities).
Abbas's passion for water emerged during his early career at the World Wide Fund for Nature (WWF), where he was involved in Pakistan’s Wetland Program and witnessed the impact of water on associated ecosystems. This sparked his interest in understanding and managing water, forestry, and wildlife resources. He recently studied coastal ecosystems and their responses to climate and anthropogenic stressors in the Asia-Pacific region. The Living Indus – Investing in Ecological Restoration has become a new focus of interest for him, addressing sustainability challenges related to food security, river basin management, and efficient water use in alignment with the UN Decade of Ocean objectives.
Abbas shared his fascination with water, recognizing its complex and essential nature. He is captivated by its beauty in all forms and acknowledges its fundamental importance for life on Earth. This water connection further motivates his commitment to addressing global water challenges and promoting sustainable water use through innovative solutions.
Sawaid Abbas's work, stimulated by both professional commitment and personal fascination, stresses the critical role of space technologies, particularly earth observation, smart sensing nexus, and artificial intelligence in addressing water-related challenges. His research contributes to the development of innovative solutions for sustainable water use, environmental protection, and disaster response, aligning with global goals for a more resilient and water-secure future.
The impacts of climate change are ever more apparent. The frequency and scale of devastation and destruction of weather hazards are on an increasing trend. According to the latest Intergovernmental Panel on Climate Change Report (IPCC, 2021) climate change is intensifying the water cycle. This will cause more intense droughts in many regions. Moreover, water-related extremes impact the quality of life disproportionately strong. Drought accounts for 25% of all losses from weather-related disasters in the United States of America (Hayes et al., 2012).
On 2 February 2020, we celebrate World Wetlands Day to raise global awareness about the vital role of wetlands for people and our planet. This year’s edition highlights the connection between water, wetlands, and life.
Since ancient times, people have established communities in river deltas because it provides water, fertile land, and transportation access, making them an ideal place to live. This pattern has been carried forward to the present. With nearly 6 billion people living in river deltas, they are one of the most densely populated places on Earth (Kuenzer and Renaud, 2011). However, they are facing threats such as climate change, sea level rise, land use changes, and ecosystem degradation.
Forest cover refers to the extent of land area covered by forests. It can be expressed either as a percentage relative to the total land area or in absolute terms measured in square kilometers or square miles (ScienceDirect). As of 2020, globally, forests account for 31 percent of the land area with roughly half of this area considered relatively intact. The total forest coverage is 4.06 billion hectares.
Do you know that about 70% of the Earth’s surface is covered in water, yet it remains unmapped? As NASA oceanographer Dr. Gene Feldman said,
“We have better maps of the surface of Mars and the moon than we do of the bottom of the ocean.”
But can all these vast blue portions of the universe be explored and mapped like the Mars, which is 54.6 million kilometers away from us, but have nearly 90% of its surface mapped? "Well, that's the million-dollar question, isn't it?"
El 2 de febrero de 2020 celebramos el Día Mundial de los Humedales para concienciar al mundo sobre el papel vital de los humedales para las personas y nuestro planeta. La edición de este año destaca la conexión entre el agua, los humedales y la vida.
Have you ever heard the phrase "All the rivers run into the sea"? In most cases, this statement holds, with one exception: rivers that end up in lakes. If you imagine mountain ranges as the walls of a bathtub, the ocean is like the bottom of the bathtub, collecting all the water from the bathtub. No matter where you live, you inhabit a land area where all the water, above and below ground, converges into a common body of water (Figure 1). We call this area a watershed. Watersheds vary in size.
As population becomes larger the demand for water soars, including water needed for domestic, industrial and municipal uses (Mogelgaard 2011). One example of that, is India, where on 20 June 2019 the city of Chennai almost run out of water. Satellite images show the extent of the water shortage in the city (figure 1). While people are queuing up to get water from water trucks that transfer water to the city, the greatest struggle is taking place in the city’s municipal buildings and businesses. Hospitals are facing the threat of not having enough water to treat patients and to clean equipment, and businesses are forced to shut down and wait until the crisis is over.
Recently, in July 2021, destructive and deadly floods occurred in Western Europe. The estimated insured losses only in Germany could approach 5 billion Euros (AIR Worldwide, 2021). However, the total amount of the damage is currently not foreseeable due to the variety and complexity of the damage patterns and the unbelievable extent of the disaster. It seems the socio-economic losses will dramatically increase and break a new record in the insurance industry after evaluating the complete record of damages’ reports (see Figure 1).
Snow has a crucial contribution to Earth’s climate and helps to maintain the Earth’s temperature. When snow melts, it aids in providing water to people for their livelihood and affects the survival of animals and plants (National Snow and Ice Data Center). Approximately 1.2 billion people - constituting one-sixth of the global population - depend on snowmelt water for both agricultural activities and human consumption (Barnett et al., 2005).
From 10 to 13 May 2022, the United Nations Officer for Outer Space Affairs organized the 5th International conference on the use of space technology for water resources management. The conference was hosted in a hybrid format in Accra, Ghana, by the University of Energy and Natural Resources, Sunyani on behalf of the Government of Ghana. The event was attended by several senior government representatives of the host country including Dr. Mahamudu Bawumia, Vice President of the Republic of Ghana, the Honorary Minister of Education Dr.
As population becomes larger the demand for water soars, including water needed for domestic, industrial and municipal uses (Mogelgaard 2011). One example of that, is India, where on 20 June 2019 the city of Chennai almost run out of water. Satellite images show the extent of the water shortage in the city (figure 1). While people are queuing up to get water from water trucks that transfer water to the city, the greatest struggle is taking place in the city’s municipal buildings and businesses. Hospitals are facing the threat of not having enough water to treat patients and to clean equipment, and businesses are forced to shut down and wait until the crisis is over.
Climate has become a subject of global concern, especially in recent decades. Climate models are practical tools that can simulate physical processes and predict future change. However, because of the complexity of atmospheric, ocean, and land processes, scientists are faced with significantly large uncertainties in climate models. As world leaders grapple with the urgency of climate action, the role of space-based technology and data has become increasingly critical. Various observed climatic variables (e.g.
In 2019, floods caused 43.5% of all deaths due to natural disasters and thereby represent the deadliest type of disaster with an increasing number of events compared to previous years (CRED, 2019). Floods furthermore lead to the highest number of people affected compared to other disasters as they affect human activities and the economy (CRED, 2019; Elagib et al. 2019).
Plus la population augmente, plus la demande en eau augmente, notamment l'eau nécessaire aux usages domestiques, industriels et municipaux (Mogelgaard 2011). L'Inde en est un bon exemple : le 20 juin 2019, la ville de Chennai a failli manquer d'eau. Des images satellites ont montré l'ampleur de la pénurie d'eau dans la ville (schéma 1). Alors que les habitants faisaient la queue pour de l'eau stockée dans des camions-citernes qui la rendaient disponible dans la ville, le véritable défi de gestion concernait les bâtiments municipaux et les entreprises de la ville. La pénurie d´eau a gravement affecté la capacité des hôpitaux à soigner les patients et à nettoyer les équipements, et a contraint les entreprises à fermer leurs portes jusqu'à la fin de la crise.
Claudia Ruz Vargas is a civil engineer, graduated from the University of Santiago, Chile, with an international master’s degree in Groundwater and Global change. Her master thesis focused on groundwater modelling for recharge and saline intrusion risk assessment under climate change scenarios, in Cape Verde. Claudia has six years of work experience as a project engineer and researcher. She is currently a researcher at the International Groundwater Resources Assessment Centre (IGRAC), where she is involved in projects of high impact on the groundwater sector. In this interview, we talked to her about her career path, and how she has contributed to an improved and more sustainable management of groundwater resources, at a regional and global levels.
Short description of community and hydrogeology of the area
Yucatan is located in the southeast portion of Mexico. The total area of Yucatan is 124, 409 km2 and the population (by 2018) was ca. 2.1 million inhabitants. The landscape of the area is defined by a highly permeable karstic soil, a notable absence of rivers or permanent freshwater resources in the surface, and a high number of natural wells or sinkholes (locally called cenotes, from the Maya word t´sonot).
Rebecca Gustine is currently a PhD student at Washington State University in the Department of Civil and Environmental Engineering studying civil engineering with a focus on water resources. She is also an intern at NASA JPL where she is a member of the ECOSTRESS applied science mission team working with local agencies to inform resource management and conservation efforts. We talked to her about her interdisciplinary research experiences through her undergraduate and graduate school.
Lukas Graf used to take clean drinking water for granted. As he grew up, and conversations around climate change and environmental destruction became increasingly intense, he started to become more aware of the importance and scarcity of water resources. Around a similar time, he became increasingly enthusiastic about space, realising that space technologies could be used to explore many of the pressing topics that he was interested in. He has participated in research projects that used remote sensing methods to study the effects of global change on ecosystems and especially on water availability. Lukas is interested in a range of topics from virtual water and water quality to irrigation and agriculture. He believes that interdisciplinary approaches and mutual dialog with societies and stakeholders need to be deepened for sustained resource management.
In this interview, we discuss how time-series of satellite data can be used to monitor the environmental, and more specifically the water domain, using the data cube technology.
Ayan Santos Fleischmann is a hydrologist with a particular interest in wetlands and large-scale basins, mainly in South America and Africa, and in the context of human impacts on water resources. His main study approaches involve remote sensing techniques and hydrologic-hydrodynamic modeling, as well as interdisciplinary collaborations with other disciplines such as ecology and social sciences. Currently, he is a researcher at the Mamirauá Institute for Sustainable Development (Tefé, Amazonas, Brazil), where he leads the Research Group in Geospatial Analysis of the Amazonian Environment and Territory. He also leads the Conexões Amazônicas initiative for science communication about the Amazon Basin. Ayan holds a PhD degree from UFRGS, with a collaborative period at Université Toulouse III – Paul Sabatier (France). His Ph. D. thesis focused on the hydrology of the South American wetlands. Ayan holds an Environmental Engineering degree from the Universidade Federal do Rio Grande do Sul (UFRGS), with a research stay at the University of East Anglia in the United Kingdom. In this interview, we talked to him about his career path, the work he has been developing in Brazil with wetlands and floods, and his work in the Amazon River basin.
In the interview, Hafsa Aeman discusses her passion for integrating water resource management with space technologies. She uses remote sensing and AI to tackle challenges like seawater intrusion and coastal erosion, focusing on vulnerable coastal ecosystems. By leveraging satellite data, her work provides critical insights for sustainable water management, crucial for communities impacted by climate change.
Ms Aeman highlights the significant role of space technology in water management, especially through remote sensing, which helps monitor precipitation, soil moisture, and groundwater levels. Her proudest achievement is a publication on seawater intrusion, recognized for its innovative use of AI and remote sensing, contributing to Pakistan’s Living Indus initiative.
At the International Water Management Institute (IWMI), Hafsa’s research integrates AI and remote sensing to optimize water and irrigation management systems. She emphasizes the importance of addressing seawater intrusion, which poses threats to agriculture, ecosystems, and global food security.
She also underscores the role of community engagement in sustainable water management through capacity-building workshops for farmers, promoting smarter irrigation practices. She advocates for leadership opportunities for young scientists and believes AI can revolutionize water management by enabling more accurate and efficient data analysis. Rain, symbolizing renewal and sustenance, is her favorite aggregate state of water.
Professor Wagner holds a Ph.D. in remote sensing. He gained his experience at renowned institutions, including academia, space agencies and international organisations. He is the Dean of the Faculty for Mathematics and Geoinformation and cofounder of the Earth Observation Data Centre for Water Resources among other affiliations.
The following interview with Dr. Sherine Ahmed El Baradei is focusing on water quality and its relation to space technology. Water is the essence of life. Thus preservation of water quality is of a big concern to human health and to fauna and flora in water bodies. The interview explains what is water quality and what are water quality parameters of water bodies. Furthermore, the importance of using space technologies and applications in contributing to water quality monitoring and determination of hydraulic and hydrologic conditions is thoroughly discussed. For example, temporal resolution of satellites and their role in obtaining accurate imaging and data is clarified and the satellites concerned with water quality monitoring are pointed out. Considering the important role of groundwater in arid regions, the use of GRACE Mission data in Egypt is mentioned. Moreover, key influences on water quality in Egypt are discussed and the relation of water quality to water scarcity in the country and ways to preserve water quality is being discussed. Furthermore, the potential of space-based monitoring used to address water issues from hydrological to water resources issues in the country or region is pointed out. The challenges of the use of space technology for hydrology and water-related topics in the MENA region is also discussed. Light is shed on the project done by NASA to recycle astronauts’ waste into energy and power. Sustainability is of a great importance to or communities, and thus it is discussed how sustainable it is to build cities in the desert, or to divert water to where people are instead of moving people to existing water sources. Finally, a discussion about ways we can employ to improve awareness and capacity building on the use of space technology for water and challenges in this field are discussed.
Ailin Sol Ortone Lois is a Remote Sensing specialist at Remote Sensing Center of the Argentinian Air Force, where she applies space technologies to monitor Natural Areas of the Defense. She is the Director of Synthetic Aperture Radar Research Group at the National University of Technology (UTN), where she leads a project related to glacier monitoring and mass balance calculations using free open remote sensing sources. Ailin also teaches physics at UTN and geomatics at the National University of Luján, in Buenos Aires.
How do you personally and professionally relate to water?
Growing up in Israel, water scarcity was a constant backdrop to my childhood. The arid climate and frequent droughts shaped my relationship with water from an early age. One vivid memory that remains stamped in my mind is the series of TV campaigns highlighting the importance of water conservation. I recall sitting in front of the television, concerned by the urgency conveyed in those campaigns. The images of dry landscapes and the emphasis on every drop of water as precious left a lasting impression.
Padmi is currently reading for her Ph.D. focusing on Nature-based Solutions (NbS) for climate change risk reduction and resilience cities. She believes NbS can reduce hydro-meteorological hazards such as floods, droughts, and landslides in the long run. It is a strategy to minimize the gaps in decarbonizing and reducing greenhouse gases and a path to Net-zero cities. NbS, are actions to protect, sustainably manage, and restore natural and modified ecosystems that address societal challenges effectively and adaptively, benefiting people and nature (IUCN & World Bank, 2022). Ecosystem-based adaptation (EbA), ecosystem-based disaster risk reduction (Eco-DRR), ecosystem-based mitigation (EbM), and green infrastructure are some branches under the umbrella of NbS. NbS include conserving forests, mangroves, and wetland ecosystems, halting deforestation, increasing reforestation, climate-smart agriculture, and opening green spaces. According to her, space technology is integral to planning, monitoring, and analysis. Space technology today is so advanced that it can capture and predict changes in the water cycle, climate change variables and so forth. Remote sensing data and satellite-derived information are essential in obtaining accurate data on a specific site anywhere on the Earth's surface. Most recently, she has been involved in projects utilizing urban NbS such as the conservation of Ramsar-Colombo to mitigate urban floods and adapt to climate change. To conduct wetland inventories, space-based data and GIS techniques can be utilized to detect the presence of wetlands and/or water in wetlands. Though there can be some challenges encountered such as limited coverage of specific areas within the wetland, clouds often hiding images, and the low resolution of data making it difficult to differentiate floral species. Unmanned Aerial Vehicles (drones) can provide enhanced accuracy and consistency in measuring wetlands, as well as the presence of water in wetlands, using space technologies. Data and technologies from space contribute to watershed management, sediment measurements and many other environmental aspects.
Shaima Almeer is a young Bahraini lady that works as a senior space data analyst at the National Space Science Agency. At NSSA she is responsible for acquiring data from satellite images and analyzing them into meaningful information aiming to serve more than 21 governmental entities. Shaima is also committed to publishing scientific research papers, aiming to support and spread the knowledge to others.
In addition, she has recently graduated from a fellowship program at Bahrain’s Prime Minister’s Office. Shaima was selected among more than 1000 individuals to spend a year working as full-time research fellow, benefiting from advanced training in writing skills, research methods and policy analysis. The fellowship forms a core pillar of HRH the CP and PM initiative to improve national skills and support the Kingdom’s growing cadre of young government professionals. Part of the fellowship program is to work as a supervisor at the COVID-19 War Room.
Shaima has obtained her bachelor’s degree in the field of Information and Communication Technology from Bahrain Polytechnic and is currently pursuing her Msc. degree in Management Information System from the University College of Bahrain.
Prior to obtaining her bachelor’s degree, Shaima was titled as the first robotics programmer in the Kingdom of Bahrain and also won the title “Pioneering Women in Technology”. She has recently also won the “Women Innovator of the Year 2023 Award” in New Dehli.
Sawaid Abbas, Assistant Professor at the Centre for Geographical Information System, University of the Punjab, Lahore, Pakistan discussed his extensive work in addressing water-related challenges through the nexus between smart sensing and space technologies. His thematic focus spans water scarcity, food security, climate risks, and environmental monitoring with an emphasis on the Asia-Pacific region, including Pakistan and China. Key Sustainable Development Goals (SDGs) guiding his work include SDG2 (Zero Hunger), SDG13 (Climate Action), SDG15 (Life on Land), and SDG11 (Sustainable Cities and Communities).
Abbas's passion for water emerged during his early career at the World Wide Fund for Nature (WWF), where he was involved in Pakistan’s Wetland Program and witnessed the impact of water on associated ecosystems. This sparked his interest in understanding and managing water, forestry, and wildlife resources. He recently studied coastal ecosystems and their responses to climate and anthropogenic stressors in the Asia-Pacific region. The Living Indus – Investing in Ecological Restoration has become a new focus of interest for him, addressing sustainability challenges related to food security, river basin management, and efficient water use in alignment with the UN Decade of Ocean objectives.
Abbas shared his fascination with water, recognizing its complex and essential nature. He is captivated by its beauty in all forms and acknowledges its fundamental importance for life on Earth. This water connection further motivates his commitment to addressing global water challenges and promoting sustainable water use through innovative solutions.
Sawaid Abbas's work, stimulated by both professional commitment and personal fascination, stresses the critical role of space technologies, particularly earth observation, smart sensing nexus, and artificial intelligence in addressing water-related challenges. His research contributes to the development of innovative solutions for sustainable water use, environmental protection, and disaster response, aligning with global goals for a more resilient and water-secure future.
How do your professional career and/or your personal experience relate to space technologies and water?
My interest in water is deeply rooted in my personal life. I grew up on an island in the Philippines where a lot of people depend on water as a source of livelihood. From fishing in the open sea to fish breeding, water has always been a source of income at home. Aside from this, the small community where I grew up struggled with access to running water.
How do you professionally relate to water and/or space technologies?
As a hydrologist, I’ve always been fascinated by the potential of space technologies in transforming water resource management. My work integrates satellite-based Earth Observation (EO) data with hydrological modelling, particularly for drought and flood monitoring, and water availability assessments in regions with scarce ground data. EO technologies allow me to capture real-time, high-resolution data, critical for climate resilience, especially in Sub-Saharan Africa.
Are you interested in leveraging public Earth observation data and visualization techniques to contribute to SDGS? You have until 26 January 2024 to sign-up to the PaleBlueDot challenge organized on behalf of NASA and the US mission to international organization in Vienna.
Are you an indigenous women or in touch with indigenous communities. Don't miss this chance to make the voices of indigenous women heard. We would like to contribute to closing the digital divide, as well as to raise the voices of indigenous women on their views realated to water and the environment.
Spread the word about this opportunity so we can reach as many Indigenous women as possible.
San José, Costa Rica, 7-10 May 2024 (with a possibility of online attendance)
Hosted and supported by the Inter-American Institute for Cooperation on Agriculture (IICA)
Co-sponsored by the Prince Sultan Bin Abdulaziz International Prize for Water (PSIPW)
Venue: Inter-American Institute for Cooperation on Agriculture Headquarters, San José, Costa Rica
Lukas Graf used to take clean drinking water for granted. As he grew up, and conversations around climate change and environmental destruction became increasingly intense, he started to become more aware of the importance and scarcity of water resources. Around a similar time, he became increasingly enthusiastic about space, realising that space technologies could be used to explore many of the pressing topics that he was interested in. He has participated in research projects that used remote sensing methods to study the effects of global change on ecosystems and especially on water availability. Lukas is interested in a range of topics from virtual water and water quality to irrigation and agriculture. He believes that interdisciplinary approaches and mutual dialog with societies and stakeholders need to be deepened for sustained resource management.
Ayan Santos Fleischmann is a hydrologist with a particular interest in wetlands and large-scale basins, mainly in South America and Africa, and in the context of human impacts on water resources. His main study approaches involve remote sensing techniques and hydrologic-hydrodynamic modeling, as well as interdisciplinary collaborations with other disciplines such as ecology and social sciences. Currently, he is a researcher at the Mamirauá Institute for Sustainable Development (Tefé, Amazonas, Brazil), where he leads the Research Group in Geospatial Analysis of the Amazonian Environment and Territory. He also leads the Conexões Amazônicas initiative for science communication about the Amazon Basin. Ayan holds a PhD degree from UFRGS, with a collaborative period at Université Toulouse III – Paul Sabatier (France). His Ph. D. thesis focused on the hydrology of the South American wetlands. Ayan holds an Environmental Engineering degree from the Universidade Federal do Rio Grande do Sul (UFRGS), with a research stay at the University of East Anglia in the United Kingdom. In this interview, we talked to him about his career path, the work he has been developing in Brazil with wetlands and floods, and his work in the Amazon River basin.
In the interview, Hafsa Aeman discusses her passion for integrating water resource management with space technologies. She uses remote sensing and AI to tackle challenges like seawater intrusion and coastal erosion, focusing on vulnerable coastal ecosystems. By leveraging satellite data, her work provides critical insights for sustainable water management, crucial for communities impacted by climate change.
Ms Aeman highlights the significant role of space technology in water management, especially through remote sensing, which helps monitor precipitation, soil moisture, and groundwater levels. Her proudest achievement is a publication on seawater intrusion, recognized for its innovative use of AI and remote sensing, contributing to Pakistan’s Living Indus initiative.
At the International Water Management Institute (IWMI), Hafsa’s research integrates AI and remote sensing to optimize water and irrigation management systems. She emphasizes the importance of addressing seawater intrusion, which poses threats to agriculture, ecosystems, and global food security.
She also underscores the role of community engagement in sustainable water management through capacity-building workshops for farmers, promoting smarter irrigation practices. She advocates for leadership opportunities for young scientists and believes AI can revolutionize water management by enabling more accurate and efficient data analysis. Rain, symbolizing renewal and sustenance, is her favorite aggregate state of water.
Padmi is currently reading for her Ph.D. focusing on Nature-based Solutions (NbS) for climate change risk reduction and resilience cities. She believes NbS can reduce hydro-meteorological hazards such as floods, droughts, and landslides in the long run. It is a strategy to minimize the gaps in decarbonizing and reducing greenhouse gases and a path to Net-zero cities. NbS, are actions to protect, sustainably manage, and restore natural and modified ecosystems that address societal challenges effectively and adaptively, benefiting people and nature (IUCN & World Bank, 2022). Ecosystem-based adaptation (EbA), ecosystem-based disaster risk reduction (Eco-DRR), ecosystem-based mitigation (EbM), and green infrastructure are some branches under the umbrella of NbS. NbS include conserving forests, mangroves, and wetland ecosystems, halting deforestation, increasing reforestation, climate-smart agriculture, and opening green spaces. According to her, space technology is integral to planning, monitoring, and analysis. Space technology today is so advanced that it can capture and predict changes in the water cycle, climate change variables and so forth. Remote sensing data and satellite-derived information are essential in obtaining accurate data on a specific site anywhere on the Earth's surface. Most recently, she has been involved in projects utilizing urban NbS such as the conservation of Ramsar-Colombo to mitigate urban floods and adapt to climate change. To conduct wetland inventories, space-based data and GIS techniques can be utilized to detect the presence of wetlands and/or water in wetlands. Though there can be some challenges encountered such as limited coverage of specific areas within the wetland, clouds often hiding images, and the low resolution of data making it difficult to differentiate floral species. Unmanned Aerial Vehicles (drones) can provide enhanced accuracy and consistency in measuring wetlands, as well as the presence of water in wetlands, using space technologies. Data and technologies from space contribute to watershed management, sediment measurements and many other environmental aspects.
Shaima Almeer is a young Bahraini lady that works as a senior space data analyst at the National Space Science Agency. At NSSA she is responsible for acquiring data from satellite images and analyzing them into meaningful information aiming to serve more than 21 governmental entities. Shaima is also committed to publishing scientific research papers, aiming to support and spread the knowledge to others.
In addition, she has recently graduated from a fellowship program at Bahrain’s Prime Minister’s Office. Shaima was selected among more than 1000 individuals to spend a year working as full-time research fellow, benefiting from advanced training in writing skills, research methods and policy analysis. The fellowship forms a core pillar of HRH the CP and PM initiative to improve national skills and support the Kingdom’s growing cadre of young government professionals. Part of the fellowship program is to work as a supervisor at the COVID-19 War Room.
Shaima has obtained her bachelor’s degree in the field of Information and Communication Technology from Bahrain Polytechnic and is currently pursuing her Msc. degree in Management Information System from the University College of Bahrain.
Prior to obtaining her bachelor’s degree, Shaima was titled as the first robotics programmer in the Kingdom of Bahrain and also won the title “Pioneering Women in Technology”. She has recently also won the “Women Innovator of the Year 2023 Award” in New Dehli.
How do your professional career and/or your personal experience relate to space technologies and water?
My interest in water is deeply rooted in my personal life. I grew up on an island in the Philippines where a lot of people depend on water as a source of livelihood. From fishing in the open sea to fish breeding, water has always been a source of income at home. Aside from this, the small community where I grew up struggled with access to running water.
How do you professionally relate to water and/or space technologies?
As a hydrologist, I’ve always been fascinated by the potential of space technologies in transforming water resource management. My work integrates satellite-based Earth Observation (EO) data with hydrological modelling, particularly for drought and flood monitoring, and water availability assessments in regions with scarce ground data. EO technologies allow me to capture real-time, high-resolution data, critical for climate resilience, especially in Sub-Saharan Africa.
Claudia Ruz Vargas is a civil engineer, graduated from the University of Santiago, Chile, with an international master’s degree in Groundwater and Global change. Her master thesis focused on groundwater modelling for recharge and saline intrusion risk assessment under climate change scenarios, in Cape Verde. Claudia has six years of work experience as a project engineer and researcher. She is currently a researcher at the International Groundwater Resources Assessment Centre (IGRAC), where she is involved in projects of high impact on the groundwater sector. In this interview, we talked to her about her career path, and how she has contributed to an improved and more sustainable management of groundwater resources, at a regional and global levels.
Rebecca Gustine is currently a PhD student at Washington State University in the Department of Civil and Environmental Engineering studying civil engineering with a focus on water resources. She is also an intern at NASA JPL where she is a member of the ECOSTRESS applied science mission team working with local agencies to inform resource management and conservation efforts. We talked to her about her interdisciplinary research experiences through her undergraduate and graduate school.
The United Nations Office for Outer Space Affairs (UNOOSA) and the Government of Ghana are jointly organizing a Conference with the support of the Prince Sultan Bin Abdulaziz International Prize for Water (PSIPW) to promote the use of space technology in water management to the benefit of developing countries.
The Conference will be held in Accra, Ghana, from 10- 13 May 2022, hosted by the University of Energy and Natural Resources on behalf of the Government of Ghana.
Space4Water stakeholders, featured young professionals and professionals, join us in Vienna at the 1st Space4Water Stakeholder Meeting.
Dates and location
The workshop will take place on 27-28 October 2022 at the Vienna International Centre, with an opportunity to host it online, should COVID prevent travels in October.
Registration
To be considered for participation Space4Water stakeholders and featured professionals can register here.
The United Nations Office for Outer Space Affairs (UNOOSA), the Government of Costa Rica, and the Prince Sultan Bin Abdulaziz International Prize for Water (PSIPW) were jointly organizing a conference to promote the use of space technology in water management to the benefit of developing countries.
The Conference was heldin San José, Costa Rica, from 7-10 May 2024, hosted by and with the support of the Inter-American Institute for Cooperation on Agriculture (IICA) on behalf of the Government of Costa Rica.
This event is restricted to Space4Water stakeholders, featured professionals, young professionals and representatives of Indigenous communities featured on the portal.
Registration for speakers submitting technical presentations closes on 15 April 2023.
Registration for all other participants closes on 30 April 2023.
The 2ndSpace4Water Stakeholder Meeting was hosted by the United Nations Office for Outer Space Affairswith its partner, the Prince Sultan Bin Abdulaziz InternationalPrizeforWateronline 11–12
What began as the development of a cubesat (BIRD-5) at the Kyushu Institute of Technology in Japan took off on a spacecraft to the International Space Station from the Mid-Atlantic Regional Spaceport at the National Aeronautics and Space Administration's (NASA's) Wallops Flight Facility in Virginia, US on 6 November 2022 (watch the video of the launch of the CRS2 NG-18 (Cygnus) Mission (Antares), in the video below the article).
The Committee on the Peaceful Uses of Outer Space in its sixty-fourth session, which took place form 25 August-3 September 2021 in Vienna, adopted the below on its agenda item "Space and water":
The Committee considered the agenda item entitled “Space and water”, in accordance with General Assembly resolution 75/92.
This event is restricted to Space4Water stakeholders, featured professionals, young professionals and representatives of Indigenous communities featured on the portal.
The Office for Outer Space Affairs and the Prince Sultan Bin Abdulaziz International Prize for Water organized the third Space4Water stakeholder meeting hosted in Vienna on 24 and 25 October 2023 in a hybrid format.
The present report describes the objectives of the meeting and includes details of attendance and a summary of the presentations, discussions and interactive sessions, as well as the conclusions.
Short description of community and hydrogeology of the area
Yucatan is located in the southeast portion of Mexico. The total area of Yucatan is 124, 409 km2 and the population (by 2018) was ca. 2.1 million inhabitants. The landscape of the area is defined by a highly permeable karstic soil, a notable absence of rivers or permanent freshwater resources in the surface, and a high number of natural wells or sinkholes (locally called cenotes, from the Maya word t´sonot).
Develop skills to use remote sensing for land cover classification, estimating evapotranspiration, water productivity, irrigation performance assessment & irrigation water accounting.
Water Productivity and Water Accounting using WaPOR (the portal to monitor Water Productivity through Open-access of Remotely sensed derived data) is an open online course targeting practitioners and academicians who are working in water resources management and related fields and have interest in applying open access remote sensing data and other open data to assess the water resources situation and water productivity and the extent to which water productivity increases have an effect on different water users in a river basin context.
These webinars are available for viewing at any time. They provide basic information about the fundamentals of remote sensing, and are often a prerequisite for other ARSET trainings.
Welcome to the open access course Use of FAO WaPOR Portal from IHE Delft Institute for Water Education and the Food and Agricultural Organization of the United Nations (FAO). WaPOR is the portal to monitor Water Productivity through Open-access of Remotely sensed derived data and has been developed by FAO. The FAO’s WaPOR programme assists countries in monitoring water productivity, identifying water productivity gaps, proposing solutions to reduce these gaps, and contributing to a sustainable increase in agricultural production.
This online training introduces participants to the data and applications of the Global Precipitation Measurement (GPM) mission. GPM is an international satellite mission that provides next-generation observations of rain and snow worldwide every three hours.
Data recipes are video tutorials that include step-by-step instructions to help users learn how to discover, access, subset, visualize and use Earth science data, information, tools and services. These recipes cover many different data products across the Earth science disciplines and different processing languages/software.
register here until 21 August 2022 - if you would like to be considered for funding
In many places around the world women are responsible for water collection, a responsibility that globally takes them 200 million hours annually. It often leaves them with little to no time for school, work or to spend time with their family. Furthermore, indigenous communities' cultural heritage and knowledge about natural resources, including water, urgently needs to be considered and protected.
Currently, WHOS makes available three data portals allowing users to easily leverage common WHOS functionalities such as data discovery and data access, on the web by means of common web browsers. For more information on WHOS data and available tools, please refer to the Section WHOS web services and supported tools.
WHOS-Global Portal provides all hydrometeorological data shared through WHOS. WHOS-Global Portal is implemented using the Water Data Explorer application.
e-shape is a unique initiative that brings together decades of public investment in Earth Observation and in cloud capabilities into services for the decision-makers, the citizens, the industry and the researchers. It allows Europe to position itself as global force in Earth observation through leveraging Copernicus, making use of existing European capacities and improving user uptake of the data from GEO assets. EuroGEO, as Europe's contribution to the Global Earth Observation System of Systems (GEOSS), aims at bringing together Earth Observation resources in Europe.
The emerging demand of GIS and Space Applications for Climate Change studies for the socio-economic development of Pakistan along with Government of Pakistan Vision 2025, Space Vision 2047 of National Space Agency of Pakistan, and achievement of UN Sustainable Development Goals (SDGs) impelled the Higher Education Commission of Pakistan (HEC) to establish Remote Sensing, GIS and Climatic Research Lab (RSGCRL) at University of the Punjab, Lahore, Pakistan.
Satsense Solutions Limited is a start-up company that uses satellite earth observation to develop business and governance solutions addressing the challenges of resource management, climate change and sustainable development. It has developed and deployed several applications in the Water Resources, Hydropower, Mining and Infrastructure sectors. These include assessments of eutrophication levels in lakes and reservoirs and sedimentation rates at hydropower plants. Identification of pollution in rivers, acid mine drainage and tailings at mining sites.
The Institute of Forestry, Pokhara Campus (IOF-PC), Quality Assurance Accreditation (QAA) certified institution by the UGC, Nepal in September 2022, was established in 1981 as the Central Campus of the Institute of Forestry, one of the five technical institutes under Tribhuvan University, Nepal. The IOF, founded as Nepal Forestry Institute in Singh Durbar, Kathmandu, in 1947, was shifted to Suping (BhimPhedi) in 1957 and again to Hetauda in 1965.
The United Nations University Institute on Comparative Regional Integration Studies (UNU-CRIS) is a research and training institute of the United Nations University. UNU is a global network of institutes and programs engaged in research and capacity development to support the universal goals of the UN. It brings together leading scholars from around the world with a view to generate strong and innovative knowledge on how to tackle pressing global problems. UNU-CRIS focuses on the study of processes of global cooperation and regional integration and their implications.
ISME-HYDRO is a platform that helps monitor water resources of dams, thus enabling water resources managers to better execute their duties. It employs linked data infrastructure integrating in-situ measurements, satellite data, GIS data, domain knowledge, deep learning, and provides capabilities of forecasting of water volumes, of alerting for hazardous situations, of interaction with the data through four kinds of search and GIS interactivity. The platform is easily extendable and customizable.
Note: this description is a work in progress developed by the collaborating entities in a workshop. If you would like to contribute reach out to office@space4water.org, or your trusted Space4Water point of contact.
Required Software
Google Earth Engine
Google Earth Engine Apps - Global Forest Change
1. Data collection
To collect historic and high-resolution up-to-date imagery over the area, UNOOSA contacted the Land and Information New Zealand Data Service, which provided both historical aerial imagery and LIDAR data sources.
HydroSHEDS: The core data products of HydroSHEDS are a series of gridded datasets designed for use in hydro-environmental model development and custom GIS applications. Data layers include the original digital elevation model (DEM) that underpins HydroSHEDS, a hydrologically conditioned version of the DEM, the derived flow direction and flow accumulation grids, as well as land mask and sink grids. These data products form the digital foundation of the derived secondary data products. HydroSHEDS core data products are currently available for HydroSHEDS v1 only, which is mostly based on SRTM elevation data. HydroSHEDS v2, which is derived from TanDEM-X elevation data, is currently under development and is scheduled for release in 2022.
A digital elevation model (DEM) is available at 30m resolution by Copernicus is available at the Terrascope website.
Figure 1: Screenshot of the New Zealand Data Service, Waikato Rural areal PhotosFigure 2: Retrolens New Zealand Service
Figure 3: Google Earth Engine Apps - Global Forest Change with an overlay of the hydrograph developed in the solution linked below, as well as the boundary of the Maori communtiy in the Ngutunui region, New ZealandFigure 4: Changes in tree cover derived from Google Earth Engine Apps - Global Forest ChangeFigure 5: NDVI Analysis of the area
2. Mapping the historical land use and land cover surrounding the river (in progress)
No other change in the land use is observed upstream the Ngutunui region between 1985-1999.
According to the vegetation cover analysis, there have not been many changes over the past 20+ years. It has been observed that the Manori community and the surrounding area have maintained almost the same vegetation cover, however some patches adjacent to the community boundary downstream have caused some distractions.
Limitation- In the case of a small land mass and narrow river, limits many satellite-based analyses.
Other methods - Conducting a community survey
To obtain historical knowledge on the identification of vegetation, tree species, a community survey appears to be the only option available, since the challenge requires data extending back 50 years. While space-based data (aerial photos) are available, the possibility of identifying each species of tree is very limited, because of the canopy layer, understory plant species cannot be seen.
This approach will enable to gather data on dominant plant species, their abundance, tree diameters, and the boundaries between different vegetation.
Data obtained from the community survey provide a valuable historical record of vegetation patterns over the decades and help identify any changes or disruptions.
"i-nature" app- tree species can be identified by taking a simple picture of a leaf. The app then provides a detailed description of the identified tree species, including information about its characteristics and habitat.
Further information on vegetation identification
Using NDVI allows for identifying the type of vegetation but not the specific species. One can see whether the type of vegetation has changed from trees to grassland, but specific plants cannot be seen.
Retrolense provides aerial photographs taken from an aeroplane at which the relevant bands for NDVI calculation (infrared and red) are missing.
We can examine vegetation cover over the last 30+ years using NDVI with Landsat data.
A study called Aerial photography for assessing vegetation change: A Review of applications and the relevance of findings for Australian vegetation history by Fensham and Fairfax published in 2022 in the Australian Journal of Botany and on the CSIRO page is accessible here.
To address the challenge of water security in Bahrain, this solution integrates space-based technologies and geospatial analysis to identify and monitor potential water resources, particularly shallow groundwater. The methodology involves the use of satellite-derived datasets and terrain modelling tools to analyse hydrological behaviour, soil moisture, and elevation-based drainage characteristics.
Three main data sources were incorporated into the solution:
GRACE (Gravity Recovery and Climate Experiment) data is used to assess changes in terrestrial water storage at the regional scale by detecting gravity anomalies related to mass variations in groundwater. GRACE data is retrieved and visualised through platforms such as Google Earth Engine and ArcGIS Pro, enabling temporal monitoring of water resources.
HAND (Height Above Nearest Drainage) modelling was employed to identify topographic wetness and assess the hydrological potential of the landscape. HAND normalises elevation relative to the nearest drainage, highlighting areas where water is more likely to accumulate or infiltrate. This method supports the identification of suitable zones for groundwater recharge, such as infiltration basins or artificial wetlands, especially in an arid environment like Bahrain. The HAND model was derived using the GLO-30 Copernicus DEM (2023_1 DGED version), processed through the TerraHidro platform, and included the generation of essential layers such as flow direction (D8), contributing area (D8CA), slope, and drainage networks with thresholds of 10, 100, and 300 pixels.
Soil moisture analysis was conducted using two approaches:
SAR (Synthetic Aperture Radar) data from the Sentinel-1 constellation, which provides all-weather, day-and-night measurements of surface moisture conditions.
Optical-based soil moisture estimation, calculated from Landsat-8 imagery using vegetation and thermal indices (e.g., Normalized Difference Vegetation Index (NDVI), Land Surface Temperature (LST)). This dual approach allows for consistent monitoring of surface moisture, which is crucial for assessing recharge potential and supporting irrigation planning.
Together, these tools provide a multi-faceted view of Bahrain's hydrological landscape, enabling decision-makers to strategically identify areas with groundwater potential and implement more sustainable water resource management practices.
Solution requirements
Gravity Recovery and Climate Experiment (GRACE)
GRACE is a joint mission by the National Aeronautics and Space Administration (NASA) and the German Aerospace Center (DLR) to measure Earth's gravity field anomalies from its launch in March 2002 to the end of its mission in October 2017. The GRACE Follow-On (GRACE-FO) is a continuation of the mission launched in May 2018. GRACE provides information on how mass is distributed and is varied over time through its detection of gravity anomalies. Because of this, a significant application of GRACE is groundwater anomalies detection. Hence, GRACE data has been explored as a solution for this challenge.
Two software platforms have been utilised to download and visualise GRACE data for Bahrain:
Google Earth Engine (GEE): A cloud-based platform that facilitates remote sensing analysis with a large catalogue of satellite imagery and geospatial datasets. The platform is free for academic and research purposes.
QGIS: A desktop application that allows the exploration, analysis and visualisation of geospatial data. This application is open source.
Height Above Nearest Drainage (HAND)
The Height Above Nearest Drainage (HAND) is a terrain model that normalises elevation data relative to the local drainage network, offering a hydrologically meaningful representation of the landscape. By calculating the vertical distance between each point on the terrain and the nearest drainage channel, HAND allows for the identification of topographic wetness zones and the classification of soil water environments. It has shown strong correlation with water table depth and has been effectively validated in various catchments, particularly in the Amazon region. The HAND model supports physically based hydrological modelling and has broad applicability in areas such as flood risk assessment, soil moisture mapping, and groundwater dynamics, using only remote sensing-derived topographic data as input.
Soil moisture using Synthetic Aperture Radar (SAR) imagery
SAR data from Sentinel-1 constellation was used to generate relative soil moisture values. Seninel-1 is a radar-based satellite which acquires data with 6 days repeat cycle, and is neither affected by clouds, weather nor time of the day. Being a dual-polarimetric platform, it acquires data in VV (Vertical-transmit and Vertical received) polarization and VH (Vertical-transmit and Horizontal received) polarization. The data was analysed in GEE.
Soil moisture using multispectral and thermal imagery (Optical)
The data utilised to detect soil moisture are satellite imagery from Landsat-8 downloaded through GEE. Landsat-8 provides multispectral and thermal satellite imagery with 16 days repeat cycle. The specific bands required to calculate soil moisture index are the red, near-infrared bands and thermal infrared bands.
Solution outline and steps
GRACE
Figure 1 illustrates the steps taken to extract the recent GRACE Monthly Mass Grids Version 04 - Global Mascon (CRI Filtered) Dataset from GEE.
Figure 1. Download steps for GRACE Data
HAND
The elevation data downloaded and processed for the region of interest were derived from the GLO-30 dataset. The Copernicus DEM, a Digital Surface Model (DSM), represents the Earth's surface, including features such as buildings, vegetation, and infrastructure. This DSM is based on the WorldDEM product, which has undergone extensive editing to ensure the flattening of water bodies, consistent river flow representation, and correction of terrain anomalies, including shorelines, coastlines, and features like airports. The WorldDEM itself was generated using radar satellite data from the TanDEM-X mission, a Public Private Partnership between the German Aerospace Centre (DLR) and Airbus Defence and Space. The GLO-30 data used in this work corresponds to the 2023_1 version of the Defence Gridded Elevation Data (DGED), provided via ESA’s https PRISM service and made accessible through OpenTopography.
The following products were processed using the TerraHidro software from the GLO-30 dataset: removepits.tif, d8.tif, d8ca.tif, slope.tif, drainage_10.tif, drainage_100.tif, and drainage_300.tif, as well as the HAND-derived products hand_10.tif, hand_100.tif, and hand_300.tif. Each product has a specific role in hydrological modeling:
removepits: This process modifies the original Digital Elevation Model (DEM) to eliminate depressions or pits that are not hydrologically realistic, ensuring that every cell has a defined downstream flow direction.
d8: The D8 (Deterministic 8) flow direction model calculates the steepest descent path from each pixel to one of its eight neighbors, indicating the primary direction of surface water flow.
d8ca: The D8 Contributing Area represents the number of upstream cells that contribute flow to each cell, allowing the identification of areas of potential accumulation and drainage.
slope: This product calculates the slope of the terrain in degrees, essential for understanding runoff velocity and erosion potential.
drainage_10, drainage_100, and drainage_300: These are drainage networks derived from the D8 contributing area, using threshold values of 10, 100, and 300 pixels, 0.9ha, 9ha and 27ha, respectively. They represent streams formed when the contributing area exceeds the specified number of pixels, with higher thresholds resulting in more generalised drainage networks.
From these products, the following HAND (Height Above Nearest Drainage) models were generated:
hand_10, hand_100, and hand_300: These datasets represent the vertical distance (in meters) from each pixel to the nearest drainage cell identified in the corresponding drainage network (with thresholds of 10, 100, and 300 pixels, respectively). These HAND maps are used to characterise terrain wetness, identify flood-prone areas, and support soil moisture and hydrological modeling.
Several steps were executed to derive the mean soil moisture conditions over the study area between 2017 and 2024. A step-by-step guide is shown in Figure 2. The values of soil moisture estimated is relative to the maximum soil moisture recorded in the region such that the wettest will be the maximum and the driest will be the minimum. These are used to normalise the final output into values between 0 and 1 where 0 is the driest and 1 is the wettest.
Figure 2. Processing steps for SAR soil moisture
Soil moisture (Optical)
Similar to the soil moisture calculation with SAR, an average of the soil moisture from 2017 to 2024 has been derived. The interrelations between the derived vegetation through the Normalized Difference Vegetation Index (NDVI) as well as Land Surface Temperature (LST) have been the basis for generating the soil moisture map. Figure 3 demonstrates the steps followed to generate optical soil moisture.
Figure 3. Processing steps for optical soil moisture
Shallow groundwater locations/recharge areas
To estimate potential suitable locations for shallow groundwater or groundwater rechange, the results from the HAND, SAR and optical soil moisture have been aggregated to formulate a final classification map. To perform this, the following has been done:
Classification of HAND, SAR and optical soil moisture results to ranges from 1-5, with 5 being the most suitable region based on the related values.
Spatial modelling of these three classifications to formulate a final suitability value from 1-5 with 5 being the most suitable region overall. HAND has been given a weightage of 50 per cent while SAR and optical soil moisture have been given a weightage of 25 per cent each to represent 50 per cent overall for soil moisture.
Map generation
Different maps have been generated for each component of this solution (HAND, SAR soil moisture, optical soil moisture, shallow groundwater locations/recharge areas). The subsequent steps illustrate the steps needed to develop the maps for this solution:
A basemap is added to the map for visualisation purposes. This is done through using the QGIS plugin called QuickMapServices. To install plugins, go to the Plugins tab and select Manage and Install Plugins.
Figure 4. Map generation - Step 1
In the search box of the Plugins window, search for QuickMapServices and install the plugin.
Figure 5. Map generation - Step 2
The plugin logo should appear in the QGIS panel. Click on the logo for Search QMS Panel. This label would appear if you hovered over the logo.
Figure 6. Map generation - Step 3
In the Search QMS Panel on the right, search for Google Satellite and add the basemap. It should appear in the list of layers.
Figure 7. Map generation - Step 4
Now we have a base layer that we can place our analysis on top of. Add the layer to the QGIS project if it is not already added. This can be done through drag and drop.
Figure 8. Map generation - Step 5
Right click on the layer and select Properties to adjust visualisation parameters.
Figure 9. Map generation - Step 6
In the Layer Properties window, click on Symbology and discover the most appropriate visualisation method for the data layer. This is an example for the set classifications for the HAND.
Figure 10. Map generation - Step 7
Once the layer visualisation has been set, the map layout can be generated. Go to Project > New Print Layout and name the layout.
Figure 11. Map generation - Step 8
Figure 12. Map generation - Step 8
In the Layout window, items such as the layers map, legend, scales can be added. This is accessed through the Add Item tab.
Figure 13. Map generation - Step 9
The items added to the map can then be moved and arranged by selecting the Edit tab then either Select/Move Content to move the locations of the specific content or Move Content to move the position/scale of the map.
Figure 14. Map generation - Step 10
Each item’s properties such as size, colour and fonts can also be edited in the Item Properties panel in the right.
Figure 15. Map generation - Step 11
The final generated layout is then exported in the desired format: png, pdf or svg. This is achieved through clicking on the Layout tab.
Figure 16. Map generation - Step 12
Results and maps
GRACE
The GRACE data has been downloaded and analysed through GEE. The main limitation of this dataset is its course resolution of 55.6 km2 as downloaded from the platform. This is due to the small geographical area of Bahrain at around 800 km2, causing water storage monitoring in specific locations to be a difficult task. Figure 17 demonstrates the span of GRACE data relative to the area of Bahrain.
Figure 17.GRACE Mascon- 2002 to 2024 Bahrain
HAND
The HAND model shown in the figure 18 provides valuable insights for addressing water scarcity in Bahrain. The low-lying areas highlighted in blue indicate regions where water tends to accumulate or water table is relatively shallow, suggesting potential zones for managed aquifer recharge (MAR) or stormwater harvesting. These areas could be prioritised for infiltration basins, recharging wells, or constructed wetlands to enhance groundwater storage. Conversely, the higher elevation zones in grey are less likely to retain surface water but could be strategically used for runoff collection and diversion to recharge areas. Given Bahrain’s arid climate and dependence on non-conventional water sources, integrating HAND-based terrain analysis into water resource planning can support more resilient, localised, and efficient water management strategies, particularly in optimising land use for recharge, storage, and flood mitigation purposes.
Figure 18. HAND results map
Soil moisture (SAR)
Figure 19 shows the mean soil moisture values of different regions of Bahrain. The southern regions seem to be drier while most central regions are wet. The analysis excluded urban regions.
Figure 19. SAR soil moisture results map
Soil moisture (Optical)
Figure 20 illustrates the soil moisture map with optical imagery for Bahrain. The results here highlight the northern west regions with high soil moisture values and the central, southern regions as dry with some specific location in the central and southern regions as wet.
Figure 20. Optical soil moisture results map
Shallow groundwater locations/recharge areas
Through Figure 5, the combinations of HAND, SAR and optical soil moisture has yielded to the potential locations for shallow groundwater locations/recharge areas. The areas highlighted in red represent the locations with highest potential.
Figure 21. Shallow groundwater locations/recharge areas results map
Solution impact
With the establishment of a methodology that identifies locations of shallow groundwater or recharge, significant information is being derived about the hydrological state of the country. This importance is placed due to the lack of remote sensing data that enables direct measurement of groundwater in the area. Hence the information extracted from this methodology can be initially integrated with sample in-situ data to calibrate the model; and then, be relied on solely for future measurements. Additionally, with the country’s rigorous focus on addressing groundwater scarcity, this type of information can greatly support decision-making when it comes to the formulation and execution of different projects and policies related to this matter.
Future work
To enhance the accuracy, applicability, and long-term impact of this solution in addressing water scarcity in Bahrain, several future developments are proposed:
Integration of additional remote sensing products: Incorporate higher-resolution satellite data to improve spatial resolution in soil moisture and elevation analyses, enabling finer-scale hydrological modeling and more localised identification of recharge zones. Moreover, the inclusion of land cover and geological characteristics can enhance the spatial modelling conducted.
Validation with in-situ data: Collaborate with local water authorities to collect and integrate ground-truth data such as groundwater levels, soil profiles, and well yields to validate and calibrate the HAND model and soil moisture outputs. This is also vital to assess the suitable weightage and classification for spatial modelling to be done to combine all three products generated.
Development of a Decision Support System (DSS): Create an interactive platform or dashboard that integrates HAND, GRACE, and soil moisture maps to assist policymakers in identifying priority areas for groundwater recharge, stormwater harvesting, and drought preparedness.
Temporal analysis and trend monitoring: Implement time-series analyses of GRACE and soil moisture data to detect trends, seasonal variations, and anomalies in water availability, supporting early warning systems and long-term planning.
Hydrological modelling coupling: Link HAND-derived terrain data with physically based hydrological models (e.g., SWAT, DHSVM) to simulate runoff, infiltration, and recharge scenarios under different land use and climate conditions.
Community engagement and capacity building: Conduct training workshops and knowledge-sharing activities with national institutions and stakeholders to build local capacity in geospatial water resource monitoring using open-source and space-based tools.
By pursuing these developments, the solution can evolve into a comprehensive and replicable model for sustainable groundwater resource management in water-scarce regions worldwide.
Relevant publications
Related space-based solutions
Sources
Nobre, A. D., Cuartas, L. A., Hodnett, M., Rennó, C. D., Rodrigues, G., Silveira, A., Waterloo, M., & Saleska, S. “Height Above the Nearest Drainage – a hydrologically relevant new terrain model.” Journal of Hydrology 404, no. 1–2 (2011): 13–29. https://doi.org/10.1016/j.jhydrol.2011.03.051.
The historical disasters of the study region, the Garhwal Himalaya, were collected, and the types of hydrometeorological disasters (HMD) were tabulated with location, attribute, morbidity, and extent from 1803 to 2025. The Garhwal region has been divided into 58 tehsils (sub-administrative regions). For analysing past HMDs and to map Multi-Hazard Susceptibility Zonation on the tehsil level, QGIS, Google Earth Engine, satellite data, k-means clustering, and AHP techniques were used.
Requirements
Data
Survey of India map of the study area
Shuttle Radar Topography Mission (SRTM) Digital Elevation Model (DEM)
Tropical Rainfall Measuring Mission (TRMM) rainfall data
Sentinel-2 Land Use / Land Cover (LULC) data
Global Land Ice Measurements from Space (GLIMS) Glacier data
National Bureau of Soil Survey & Land Use Planning (NBSS&LUP) Soil data
Disaster data from Emergency Events Database (EM-DAT)
National Disaster Management Authority (NDMA)
Various research publications
Along with regional newspapers
Software
QGIS
Google Earth Engine (GEE)
Steps to a solution
Study Area
The Garhwal region is spread over approximately 32,366 square kilometres in northwestern Uttarakhand and comprises 58 sub-administrative divisions (tehsils). This region is a major part of the Indian Himalayan Region (IHR) and has steep slopes, rugged terrain, and a geologically fragile structure, and hence is highly vulnerable to natural hazards. Though associated with steep topography, its intense monsoonal rainfall, changing land use patterns, and glacial influence all make the region highly vulnerable to hydrometeorological disasters (HMDs) such as floods, flash floods, landslides, GLOFs, cloud bursts, and avalanches.
Figure 1. Google Earth satellite image of the Garhwal region
Figure 2. DEM of Garhwal region
Figure 3. Spatial distribution of HMDs and fatalities in the Garhwal Himalayas (1803–2025)
Collecting and processing
Historical HMD data for the Garhwal region (1803–2025) have been collected from a variety of sources, including EM-DAT, scientific publications, NDMA, SDMA, and regional media reports.
Table 1. Geospatial Datasets Used in the Study
S.No.
Dataset / Layer
Source / Method
Resolution / Format
Year / Period
1
Study Area Shapefile
Survey of India / Custom Digitisation
Vector (Shapefile)
Latest Available
2
Digital Elevation Model (DEM)
NASADEM
30 m (Raster)
2020
3
Slope and Elevation
Derived from NASADEM using QGIS
30 m (Raster)
2020 (Processed)
4
Monsoon Rainfall
TRMM via GEE
Monthly, ~25 km (Raster)
1998-2015
5
Land Use / Land Cover (LULC)
ESA WorldCover (Sentinel-2)
10 m (Raster)
2021
6
Glacier Cover
GLIMS / ESA
~30 m (Raster)
Latest Available
7
Proximity to Rivers
HydroSHEDS
Variable (Rasterised)
Processed Layer
8
Soil Erosion Class
NBSS&LUP Database, India
Vector -> Raster Conversion
Latest Available
How Thematic Layer Preparation Works
Seven thematic layers were created for the Garhwal region using satellite remote sensing data in QGIS and the GEE environment:
Slope
Elevation
Rainfall
Land Use/Land Cover (LULC)
Soil Erosion
The region’s closeness to rivers
Glacier Proximity
The thematic layers were created using the data sourced from Table 1. Thematic layers were brought to the same scale (1–5) and brought together using AHP to develop a single risk zonation map.
The k-means clustering is done on the QGIS 3.42.3 platform using K-Means Clustering ABC (Attribute-based clustering) tab in the processing toolbox. The attributes were selected like location, elevation, and impact severity.
Application of AHP
To evaluate HMD susceptibility using AHP, the main influencing factors were selected: slope, elevation, rainfall, LULC, soil erosion, rivers and glacier proximity. To create these layers, data from DEM for slope and elevation, image data from satellites for LULC, and hydrological data are used. Based on AHP, a table is filled, with one factor compared to another according to Saaty’s 1–9 scale to decide their relative weight. Weights are calculated with an eigenvector analysis, and a small consistency ratio (less than 0.1) indicates sensible conclusions. Finally, using an AHP weighted overlay in GIS, all the relevant layers are combined, and the outcome is a map showing where HMD susceptibility is highest.
Figure 4. Methodology Flowchart
Results
Most (77.6 per cent) HMDs happened during the Monsoon season, followed by pre-monsoon (14.3 per cent), Winter season (6.1 per cent), and the post-monsoon season (2 per cent).
The K-means clustering of disaster events in the Garhwal Himalayas yielded the clusters-based partitioning them based on shared characteristics (e.g., elevation, impact severity, location).
The multi-hazard zonation using the AHP system shows that the north eastern or north tehsils like Joshimath and Chamoli have very high levels of risk, while places like Haridwar and Roorkee in the south have much lower risks.
Figure 5. AHP-Based Multi-Hazard Risk Zonation in the Garhwal Himalayas
Future work
Access and incorporation of socio-economic and infrastructure vulnerability cum exposure data for risk zonation
Combining GIS outputs with participatory approaches to validate and refine vulnerability maps on the ground
Make the methodology suitable and easily workable for the entire Himalayan Region to strengthen resilience against disasters
Future climatic scenario along with ML to recognize and forecast disaster patterns
Using space-based techniques for ecosystem-based disaster reduction
To establish an integrated monitoring and decision-support system that uses Earth Observation data and machine learning to track the status of Lake Ol' Bolossat, enabling evidence-based conservation and sustainable development actions.
Requirements
Data
Below is a table showing the data requirements and sources.
Data source
Use case
Period
JRC GSW
Historical water extents
1984 - 2023
Sentinel-1 SAR
Water extent during cloud-cover seasons
2014 - present
Sentinel-2 2 MSI
Habitat classification, NDVI, MNDWI, NDBI
2015 - present
MODIS
NDVI/ET anomalies and drought indicators
2000 - present
Rainfall and climate (CHIRPS/ERA5)
Climate trend correlation with hydrological changes
1984 - present
Population/Human settlement (WorldPop, GHSL)
Land use pressure mapping
2000 - present
Field surveys and local NGO data
Validation and community-level observations
As available
Software
The analysis is being done using open-source platforms and software: Google Earth Engine and QGIS.
To access Google Earth Engine, one needs a Google account that will be linked to the platform link. If you are new to the platform, create an account, and you can start using it. If you already have an account, just sign in and be directed to the code editor. If you are new to the software, you can access the training manual here.
To access QGIS, you need to download it as it is a software, link. If you are new to the software, you can access the training manual here.
Physical
Establishment of Ground Monitoring Stations
Purpose: To validate satellite data and collect real-time, on-the-ground water level, rainfall, and biodiversity observations.
Components: Water gauges, weather sensors, camera traps for biodiversity, and simple soil moisture probes.
Community Information Boards or Digital Kiosks
Purpose: To display maps, water level trends, and habitat updates to residents in a simplified, accessible format.
Location: Strategic points around the lake (e.g., near schools, water collection points, community centers).
Buffer Zone Demarcation and Fencing
Purpose: To physically protect critical wetland habitats and prevent encroachment or grazing in sensitive areas.
Details: Fencing or natural barriers like vegetation planting along designated riparian zones.
Construction of a Local Conservation and Data Hub
Purpose: To provide a space for community meetings, training sessions, citizen science coordination, and storing field equipment.
Location: Ideally within a local government or NGO compound near the lake.
Rehabilitation of Degraded Wetlands
Purpose: Restore areas where the lakebed or surrounding wetlands have been severely altered.
Methods: Planting of indigenous wetland vegetation, removal of invasive species, and controlled re-wetting.
Water Resource Management Infrastructure
Purpose: To improve the regulation and sustainable use of the lake's water.
Examples: Controlled inflow/outflow channels, community-led irrigation management systems, water pans for livestock to reduce direct lake access.
Signage and Protected Area Boundary Markers
Purpose: To raise awareness of Lake Ol’ Bolossat’s legal protection status and to visually communicate boundaries to land users.
Materials: Durable signs, educational posters, and protected area plaques.
Solar-Powered Connectivity Units (Optional but strategic)
Purpose: For uplinking field sensor data or enabling access to the online dashboard in remote locations.
Components: Solar panels, GSM routers, rugged tablets or data loggers.
Outline steps for a solution
Phase 1: Planning and Stakeholder Engagement – To do
The first phase involves defining the objectives of the monitoring system and identifying measurable success indicators aligned with conservation priorities and local needs. This is followed by engaging key stakeholders such as the National Environment Management Authority (NEMA), Kenya Wildlife Service (KWS), Water Resources Authority (WRA), Nyandarua County Government, and local community-based organizations. Stakeholder consultations are critical for gathering input on data needs, identifying decision-making gaps, and ensuring buy-in from both policy actors and community leaders. A situational analysis should be conducted to map existing infrastructure, technical capacity, internet access, and human resources available on the ground, helping to identify opportunities and constraints for implementation.
Phase 2: Data Collection and System Design – In progress
In this phase, a comprehensive monitoring framework is developed, specifying the key indicators to be tracked, such as seasonal water extent, land cover transitions, and flood-prone zones. Relevant Earth observation datasets are selected, including Sentinel-1 SAR for water extent, Sentinel-2 for habitat classification, JRC Global Surface Water for historical trends, and CHIRPS for rainfall data. A prototype dashboard is developed using Google Earth Engine, visualizing these datasets through maps, time series graphs, and interactive overlays. Simultaneously, field validation activities are conducted to ground-truth satellite-derived maps. This includes collecting GPS points, photos, and observations on vegetation, land use, and visible signs of degradation, ensuring the remote sensing outputs are accurate and contextually relevant.
Phase 3: System Testing and Expansion – To do
Once the prototype is ready, it is tested with stakeholders through pilot sessions and community workshops. These engagements are used to collect feedback on the dashboard’s usability, relevance, and user experience, particularly for non-technical audiences. Revisions are made to improve clarity, layer toggling, labelling, and interpretability. In parallel, basic physical interventions begin, such as the installation of simple water gauges, informational signboards, and boundary markers for conservation zones. These elements help translate digital insights into tangible tools for the community. Plans for expanding field infrastructure, such as creating buffer zones or establishing a local conservation hub, are also explored during this phase.
Phase 4: Deployment and Knowledge Sharing – In progress
Following successful pilot testing and system refinement, the full monitoring platform is deployed on a publicly accessible hosting environment, such as Firebase, Earth Engine Apps, or a custom-built website. The platform is shared with agencies and conservation partners, accompanied by a rollout plan that includes formal training sessions. These capacity-building workshops are designed to empower users, ranging from government officers to youth groups, with the skills to interpret dashboard outputs and use the data in planning and response. User guides, translated materials, and offline summaries are provided to support long-term usability and local ownership.
Phase 5: Monitoring, Maintenance, and Scaling – To do
The final phase focuses on monitoring the performance and real-world impact of the system. Regular evaluations are conducted to assess usage, data accuracy, stakeholder engagement, and improvements in environmental decision-making. Lessons learned are used to refine system features, add new datasets, and introduce functionalities such as alert notifications or mobile-friendly access. The success of the Lake Ol’ Bolossat solution creates a foundation for scaling to other endangered wetlands across Kenya, such as Lakes Baringo, Naivasha, or Kanyaboli. Finally, the project contributes to the broader Space4Water and open science communities by publishing methods, code, and findings on platforms like GitHub and Earth Engine’s asset repository, ensuring transparency, replicability, and collaboration.
Results
The Lake Ol’ Bolossat monitoring system, currently at prototype stage, holds significant potential to transform how freshwater ecosystems are managed at local and national levels. By integrating satellite-derived water and habitat data into an accessible dashboard, the system aims to bridge the gap between Earth observation science and on-the-ground conservation action. Once implemented with key stakeholders and end users, the following impacts are anticipated:
Support for Environmental Agencies and County Governments: The system could enhance the capacity of institutions such as the National Environment Management Authority (NEMA), Kenya Wildlife Service (KWS), Water Resources Authority (WRA), and the Nyandarua County Government by providing timely, location-specific data for decision-making on lake and wetland management.
Early Warning for Hydrological and Ecological Risks: The dashboard could enable stakeholders to detect abnormal patterns in water extent, such as persistent shrinkage or sudden expansion, triggering early intervention to prevent ecological degradation or disaster impacts on nearby communities.
Community Awareness and Engagement: By visualizing seasonal and long-term changes, the system can be used to build awareness among residents, farmers, and water users around Lake Ol’ Bolossat, empowering them to engage in sustainable practices and to advocate for the protection of the lake.
Policy-Relevant Monitoring Tool: The platform can serve as a long-term environmental monitoring tool to support the implementation of wetland protection policies, local water catchment strategies, and integrated land use planning frameworks.
Scalability to Other Freshwater Ecosystems: Once validated, the approach used at Lake Ol’ Bolossat can be adapted to other small inland water bodies across Kenya and East Africa, particularly those facing similar risks of drying, encroachment, or biodiversity loss.
Alignment with Global and National Development Goals: The system supports Kenya’s contributions to Sustainable Development Goals (SDGs), particularly:
SDG 6: Ensure availability and sustainable management of water and sanitation
SDG 13: Take urgent action to combat climate change and its impacts
SDG 15: Protect, restore and promote sustainable use of terrestrial ecosystems and halt biodiversity loss
This solution combines multi-source satellite remote sensing, ecohydrological modeling, and community science to address spring decline and water insecurity caused by afforestation and land-use changes in Nepal's Middle Hills. The integrated approach offers a pathway to scientifically informed, community-driven forest and water management.
Satellite Data Fusion: The first core strategy involves fusing multi-temporal and multi-sensor satellite data to assess vegetation trends, hydrological changes, and potential spring recharge zones.
Vegetation Monitoring: Time-series NDVI, EVI, and LAI are derived using Sentinel-2, Landsat, NOAA and MODIS. These indices help detect vegetation growth trends and assess forest types based on phenological signatures.
Cloud Mitigation: Nepal’s rugged terrain and monsoon conditions create persistent cloud cover challenges. While no perfect cloud-removal technique exists, we aim to apply machine learning and established algorithms like CLAY3 or Fmask to improve data quality for vegetation and land cover analysis.
Hydrological Metrics: ET using MODIS, Soil moisture is mapped using SMAP data, downscaled using terrain parameters such as slope and elevation. GRACE data informs groundwater trends. Satellite-based precipitation datasets are validated against DHM station data to compensate for missing or sparse in-situ observations.
RHESSys Ecohydrological Simulation: The RHESSys model simulates the complex interactions between vegetation, soil moisture, surface and subsurface water flow, and groundwater storage. The model is run in growth mode to evaluate how forest type changes influence spring discharge.
MODIS ET and Sentinel-1 soil moisture serve as validation inputs. The model provides spatial outputs including groundwater depth, lateral flow, and baseflow dynamics—critical for delineating micro-watersheds and assessing recharge efficiency.
Recharge Zone and Spring Hotspot Mapping: Topographic indices such as TWI (Topographic Wetness Index) and HAND (Height Above Nearest Drainage), derived from ASTER DEMs, are used to identify spring recharge zones.
These zones are further validated using RHESSys outputs, satellite data layers, and available field measurements.
Machine learning (e.g., Random Forest) and participatory mapping help cross-check locations of active and declining springs.
The resulting maps guide protection measures and afforestation policies targeting hydrologically sensitive areas.
Field Validation and Community Co-Design: Local participation through spring monitoring and mapping ensures the integration of indigenous knowledge with scientific analysis. Field measurements validate model predictions and support community-driven management strategies.
Requirements
Data
Remote sensing: NDVI, EVI, LAI, Evapotranspiration (MODIS), Soil Moisture (SMAP), satellite-based precipitation, terrestrial Groundwater storage (GRACE), Land Use Land Cover, DEM (ASTER).
In-situ: Precipitation and temperature data from DHM Nepal
Software
Google Earth Engine (cloud computing, satellite data analysis)
Cross-validation of spring locations and groundwater depth measurements through field visits.
Priority Support Areas: To realize objectives, we seek support in the following areas:
High-Resolution and Cloud-Free Satellite Data: Technical assistance in accessing and processing Sentinel-1 SAR, Sentinel-2, and Landsat data, and applying cloud-removal algorithms.
Downscaling Remote Sensing Products: Assistance in refining MODIS-based NDVI, EVI, LAI, and phenological indicators using auxiliary terrain and land cover datasets.
Integration of Hydrological and Remote Sensing Data: Guidance on synchronizing outputs from RHESSys with MODIS, SMAP, and GRACE datasets for robust cross-validation.
Mapping Recharge and Spring Zones: Technical support in combining terrain indices with RHESSys-derived metrics to map spring recharge zones and inform land-use planning.
Outline steps for a solution
Phase 1: Satellite Analysis and Vegetation Mapping (completed)
Use GEE to analyze NDVI, EVI, LAI, ET from NOAA, MODIS, Sentinel, and Landsat.
Define AOI, set date ranges, apply quality filters, visualize maps, and export CSV time series.
LULC maps are from Global Land Cover (Chinese Academy of Sciences).
Note: "The full code and comprehensive instructions for running the model are provided in this repository."
Results
Preliminary analysis shows increasing trends in both evapotranspiration and LAI, indicating higher water consumption by vegetation and less water available for downstream use.
Mapped recharge zones and high-risk spring areas.
Groundwater storage trends over time and identification of water-available zones suitable for settlement planning.
Spatial maps and hydrologic models to support forest and water governance.
Policy briefs on forest-water tradeoffs and spring recovery.
Community awareness on how certain forest types and species are accelerating water loss and increasing water stress for downstream communities, prompting migration.
Technical findings paired with management strategies offer actionable insights for land-use planning and ecosystem resilience.
Remote sensing can significantly aid in groundwater resource management. Further with the integration of Internet of Things (IoT), the information of groundwater storage and change in groundwater level can be shared through mobile technology to end users, policy makers and also to the government.
Here are a few key steps showing how it can be useful:
Mapping and monitoring land use/land cover: Remote sensing helps identify areas of vegetation, agriculture, urbanisation and water bodies, which influence groundwater recharge and extraction.
Identifying potential groundwater zones: Satellite imagery, combined with GIS, can analyse geological, hydrological and geomorphological features to locate promising groundwater zones.
Monitoring groundwater levels and storage: Missions like Gravity Recovery and Climate Experiment (GRACE) measure changes in Earth's gravity field, enabling estimation of groundwater storage changes over time.
Assessing drought and recharge conditions: Remote sensing provides data on precipitation, soil moisture and evapotranspiration, essential for evaluating recharge potential and drought impacts.
Supporting sustainable management: Continuous remote sensing data supports long-term planning, policy-making and sustainable groundwater resource development.
Integration of remote sensing with IoT: IoT modules can be developed for groundwater level; total groundwater storage; drought level etc and can be sent to end users using mobile technology.
Requirements
Data
GRACE & GRACE FO satellite data set
Central Groundwater Board, India
Water Resources Information System (WRIS) India
USGS data sets of remote sensing imagery
Software
QGIS
Visual MODFLOW flex
HEC-RAS (Hydrologic Engineering Center's River Analysis System)
MATLAB
R software
ERDAS IMAGINE
Physical
Workstation as servers lab for developing IoT for groundwater management
Outline steps to a solution
Worked on GRACE satellite data and used it in field condition to study groundwater anomalies of few cities of India (completed).
Developed spatio-temporal maps of Standardized Groundwater Index (SGI) (completed).
Water quality monitoring of water bodies using remote sensing (in progress).
Water spread mapping and its monitoring, of various water bodies using remote sensing and artificial intelligence (research is in progress).
Internet of Things (IoT) models which can link groundwater depletion/anomalies information with the end-users (in progress).
Steps to a solution
Study area and data acquisition
Study area has to be selected for groundwater monitoring and management.
The shapefile of the study area has to be downloaded from government websites or can be ordered on request basis. Gridded GRACE products (Level-3) can be used from the Jet propulsion Laboratory (JPL), the National Aeronautics and Space Administration (NASA) to get the monthly water equivalent thickness data.
Development of Standardized Groundwater Index (SGI) for understanding the severity of groundwater anomalies or draught
Standardized Groundwater Index (SGI) is a drought indicator which was developed by Bloomfield and Marchant (2013) to quantify groundwater drought. It is used for estimating groundwater level deficit at any time scale which reflects the extreme drought condition of any location. It is similar to the traditional drought index, Standardized Precipitation Index (SPI) and can be calculated on the same basis like SPI. In SGI, groundwater level data is used for measuring drought condition, instead of precipitation data which is used in SPI. Groundwater time series data obtained from ground observation can be appropriately normalized to evaluating the groundwater drought. SGI values can also be analysed by calculating groundwater deviation from the mean groundwater value (Halder et al., 2020). SGI can be given by following formula
where, K is groundwater level of the respective year; M is long term mean groundwater level of 18 years, σ is standard deviation
Gravity Recovery and Climate Experiment satellite for groundwater anomalies study
GRACE was launched by NASA on March 17, 2002. It was a joint mission of NASA and German Aerospace Centre (DLR). The two twin satellites of GRACE are monitored to observe the changes in the Earth's gravity field. GRACE satellite, a first remote sensing satellite which provides an efficient and cost-effective way to map Earth’s gravity field and measure the total groundwater storage changes (TWS) with unprecedented accuracy (Yirdaw et al, 2008). GRACE studies the variation in the gravity which are caused due to effects that include: changes due to deep currents in the ocean; runoff and ground water storage on land mass; exchanges between ice sheets or glaciers and the oceans, and variations of mass within the solid Earth. The distance between the twin satellite as they orbit the Earth help in measuring changes in the Earth's gravity field for each month. From these monthly gravity field, time series of regional mass anomalies can be derived using specially designed averaging function. GRACE mission provides an opportunity to directly measure the total groundwater storage changes and with the help of gravity field data of GRACE drought conditions can also be monitored over a region. GRACE satellite has coarse resolution of 300-400 km and provides data in an interval of 30 days. The distance between the two satellite is about 200 km at a starting altitude of about 500 km. The GRACE gridded TWS products (1˚×1˚) from spherical harmonics are provided by the Centre of Research (CSR) at the University of Texas, the Jet Propulsion Laboratory (JPL) and German Research Centre for Geoscience (GFZ). The gridded products estimate the changes in mass in unit of water equivalent thickness (WET).
Machine learning algorithms to model data from GRACE with observed data
Using machine learning (ML) for modelling GRACE satellite data alongside observation datasets (e.g., in-situ hydrological measurements, meteorological data) is a powerful approach to extract spatiotemporal patterns, downscale or predict terrestrial water storage (TWS) anomalies. Machine learning algorithms like artificial neural network, random forest, support vector machines etc can be used to model satellite data with observed data. For more details following journal articles can be studied:
IoT for groundwater monitoring and sending information to end users
Using IoT for groundwater level monitoring is an effective way to automate the collection, transmission and dissemination of real-time groundwater data to decision-makers, farmers or the public.
Results
Today, no remote sensors can directly monitor groundwater, a combination of surface features anomalies and gravity data obtained by various satellites, allows for optimal groundwater management. Example satellites for monitoring include: GRACE and its Follow-On mission (GRACE-FO) to study groundwater fluctuations, Landsat, Moderate Resolution Imaging Spectroradiometer (MODIS) etc, groundwater management can be done using space technology.
I developed a Standardized Groundwater Index (SGI) for Bihar state of India which proved to be very important to understand the severity of groundwater problems in that region. The spatio-temporal variation of SGI using geographical information systems (see figure 1) was published in the peer reviewed Journal of the Geological Society of India (Kumar and Kumari, 2024).
Note: this description is a work in progress developed by the collaborating entities in a workshop. If you would like to contribute reach out to office@space4water.org, or your trusted Space4Water point of contact.
The solution approach begins with identifying the region's main rivers and understanding their hydrology using mapping and geoprocessing tools. After understanding the hydrography of the area and mapping the surface water extent river course through the building a hydrographic dataset, multiple image sources are used to map the historical land use and land cover surrounding the river.
PostGIS Spatial Database System https://postgis.net/
PgHydro extension for PostgreSQL/PostGIS http://pghydro.org/
PgHydro Plugin for QGIS https://plugins.qgis.org/plugins/PghydroTools/
Data
Forest And Buildings removed Copernicus DEM
Publications
see reference in the bibliography below.
2. Steps to the solution & status
Overivew
Plot the Region of Interest (completed)
Identify the region's main rivers and understand their hydrology (completed);
Identify the region's potential flood areas using H.A.N.D.;
Build a hydrography dataset (completed);
Identify multiple image sources for land cover analysis (completed);
Map the historical land use and land cover surrounding the river (in progress);
Step-by-step
1. Plot the Region of Interest (completed)
Download and install QGIS to plot the KML files of the region of interest
Figure 1: Example KML plot of the strip of land of the Maori communtiy who submitted the challenge
2. Identify the region's main rivers and understand their hydrology (completed)
Download the FABDEM data for the Region of Interest.
FABDEM (Forest And Buildings removed Copernicus DEM) is a global elevation map that removes building and tree height biases from the Copernicus GLO 30 Digital Elevation Model (DEM) (https://data.bris.ac.uk/data/dataset/25wfy0f9ukoge2gs7a5mqpq2j7). Figure 2: A FEABDEM Digital Elevation Model of the Ngutunui region, New Zealand.
Download and Install TerraHidro 5 - Console applications (https://www.dpi.inpe.br/terrahidro/doku.php) to extract the hydrograph products derived from the FABDEM to understand the hydrography setup of the area (Flow direction, flow accumulation and drainage lines and areas, H.A.N.D.). Figure 3: Flow direction in the Ngutunui region, New ZealandFigure 4: Flow accumultation in the Ngutunui region, New ZealandFigure 5: Sintetic draingage lines and areas Ngutunui region, New Zealand
3. Identify the region's potential flood areas using H.A.N.D.
Building on Nobre et. al (2011) in which the HAND terrain model that "normalizes topography according to the local relative heights found along the drainage network, and in this way, presents the topology of the relative soil gravitational potentials, or local draining potentials" is introduced by the authors.
Figure 6: Height Above the Neaerest Drainage (HAND) in the Ngutunui region showng the areas for potential flooding in darker blue. In the current map this is in the bottom right quarter of the image.
4. Build a hydrography dataset (completed)
Download and instal PostgreSQL/PostGIS Spatial Database System (https://www.postgresql.org/) (https://postgis.net/), PgHydro extension for PostgreSQL/PostGIS (http://pghydro.org/) and PgHydro Plugin for QGIS;(https://plugins.qgis.org/plugins/PghydroTools/).
Build the Hydrograph Dataset;(https://www.youtube.com/channel/UCgkCUQ-i72bBY41a1bhVWyw) using the Drainage Lines and Drainage Areas extracted from FABDEM;
Information like drainage area, upstream area, drainage line length and distance to sea information are now available. Figure 7: Hydrography dataset of the Ngutunui region in New Zealand
5. Identify multiple image sources for landing cover analysis (completed);
To collect historic and high-resolution up-to-date imagery over the area, UNOOSA contacted the Land and Information New Zealand Data Service, which provided both historical aerial imagery and LIDAR data sources.
Historic data for the relevant land patch can be accessed via the Retrolens New Zealand Service (https://retrolens.co.nz/Map/#/1784971.9859981549/5783474.532151884/1786387.2653498782/5784857.564632303/2193/12).
Up-to-date aerial photos of the area can be accessed here at the New Zealand Data Service. Tile 503 and 603 are the ones of interest (https://data.linz.govt.nz/layer/112048-waikato-03m-rural-aerial-photos-index-tiles-2021-2023/history/).
Relevant Landsat data are available from 1989. For the study area, Landsat 7 data is available from 2 July 1999, and Landsat 4 from 2 February 1989;
Google Earth Engine Apps - Global Forest Change (https://google.earthengine.app/view/forest-change)
6. Map the historical land use and land cover surrounding the river (in progress);
