How does your professional (and/or personal) experience relate to space technologies and water?
As we know, the 2030 Agenda for Sustainable Development, including 17 Sustainable Development Goals (SDGs), 169 targets, and 232 indicators, was adopted by all United Nations (UN) Member States in 2015. This agenda seeks to build on the Millennium Development Goals and complete what they did not achieve and aims at establishing principles of sustainable development in national policies. I have developed, and grown, at Chapman University, the Earth Systems Science Data Solutions (ESsDs) lab, which houses many PhD students who are doing cutting edge work under my supervision. In my laboratory, students are trained in the extensive possible usages of satellite earth observations; this training allows them to understand the utility of these observations on specific SDGs dealing with agriculture and food productivity, water resources, life under water, air quality, clean energy and climate action.
The ESsDs lab research interests’ ranges from dust storms monitoring and detecting their long range transport to their impacts on the human health, glaciers of the Sierra Nevada and Hurricanes formation and intensification. It also touches on climate change impact and marine habitats and coastal areas namely coral reefs in the pacific as well as mangroves in the Arabian Gulf and the Red Sea. Owed to the complexities embedded in the field of earth systems science, it is dramatically benefiting from combining the rapidly increasing data sources and associated computational power. Therefore, this research group employs Artificial Intelligence (AI) and Machine Learning (ML), and I take the lead in providing a good training environment for students in the lab in these two very active research areas. Since these two words (AI and ML) are sometimes used interchangeably, I will take a moment to describe in which ways they play a different role in my research agenda.
AI conceptualizes how machines can accomplish tasks in a way that we would consider “smart”, whereas ML deals with studying algorithms and statistical models (often built from known data) where machines rely on patterns and inference to independently carry out a specific task in an effective way with no need for explicit instructions.
Because of the complexities embedded in the field of earth systems science, the rapidly increasing data sources and the associated computational power allow increasing benefits when used appropriately. In recent years, we made use of the recent advances in AI and hence allow us to expand our deep understanding and knowledge of the Earth system driven from actual data and observations. The way we are applying and developing ML methodologies to geoscience and remote sensing problems, has the potential of becoming a universal approach in geoscientific classification, land use/land cover mapping, change- and anomaly-detection problems. As a testimony to his leading research and success in these areas, the Intergovernmental Panel on Climate Change (IPCC) has selected me as a contributing author to the Desertification Chapter of the IPCC special report that was published in August 2019.
While much of the research in earth systems and climate change focuses on global warming trends, I am interested in how the interaction between the earth’s spheres, namely atmosphere, hydrosphere, cryosphere, etc., leads to extreme climatic events. Over the last few years, we have seen the ever-increasing magnitude of extreme events like hurricanes, tsunamis, flooding, desertification and wildfires resulting from how the earth’s different compartments are communicating with one another.
Could you tell us about your current work, your latest project or your proudest professional moment?
Part of my work focuses on natural and anthropogenic (manmade) pollution and its influence on the environment. One major theme of my research is studying the impact and mixing of the multisource aerosols injected into the atmosphere by dust storms, manmade products, local emissions and biomass burning. I am particularly interested in the concept of “glocal” impact—how what’s happening globally in terms of climate affects us locally. For instance, sandstorms originating in Asia impact agriculture, air quality and water resources in North America. I have a wide range of collaborators and environmental experts across the globe on the practice of earth observations and modeling. I coauthored several scientific papers on the subject, such as “A Multi-Sensor Approach to Dust Storm Monitoring over the Nile Delta,” which appeared October 2003 as a cover article in the prestigious IEEE Transactions on Geoscience and Remote Sensing. In 2006, this work was awarded the Saudi Arabia Prize for best published article in environmental management trend hosted by Arab Administrative Development Organization (ARADO), affiliated with the League of Arab States for the best-published article in Environmental Management among 150 articles in 2006. Once again, as a testimony to the importance of the work of Professor El-Askary, I will simply point out that my research has been supported by extremely competitive agencies such as NSF, NASA, USDA and the EU.
What do you need to innovate?
Research and innovation are nowadays key transversal means to societal challenges that need to be addressed through an integrated approach. Ongoing global climate change, water scarcity, prolonged droughts, growing population, overexploitation of water resources, constructions on rivers, coastal and marine pollution, biodiversity decrease, development of blue economy and the intensification of economic activities are all pressing issues that affect water resources and cross different spatial and temporal scales. These water-related issues are becoming limiting factors for sustainable economic growth and require a collaborative and interdisciplinary approach to foster innovative solutions. The cross-area nature of this research and innovation theme is unique and important, hence should be utilized in current and future directives and policies to ensure better life for all and to achieve different sustainable development goals related to water resources.
I need to be aware of approaches that can help me to innovate in digital agriculture and in areas of big data/machine learning in water related issues. Innovation in predictive power of atmospheric phenomena as well evaluation and mitigation of impacts to climate change on water resources is important for me. Amongst the challenges I see that requires more innovation is bridging of water, energy and food ecosystems in support of interconnected polices and international agreements. My short-term innovation plan is to put effort on utilizing remote sensing, earth observations and modeling in coherency with other approaches and innovations to address the forth-mentioned challenges.
What do you think is poorly understood or unresolved within the area of sustainable water management and research? Why is this so? How do you believe space technologies add value?
I believe one of the biggest challenges in implementing the sustainable water management and research is the lack of data to monitor the progress of various studies. Incomplete and inconsistent data statistics and the lack of systems for observing the real situation of water resources are the main reasons for the lack of data and the low quality of existing data. It is also usually expensive and time consuming to obtain any data.
For example, in our recent study of Nile Watershed countries, we found that the local water measurements are outdated and limited. The latest records of stations in Global Runoff Data Centre date back to 1984. Meanwhile, the Food and Agriculture Organization of the United Nations (FAO) has been monitoring the parameters of water stress through its global water information system, AQUASTAT. The reference years (2007, 2012, 2017) are only reported at a five years period and sometimes varied between variables and countries. However, we found that the AQUASTAT dataset is also outdated and inconsistent. For example, Egypt, Sudan and South Sudan’s data before 2012 is not available. This results in uncertainties between the actual and estimated water stress situation.
Therefore, the space technologies such as Earth Observation (EO) play an important role to mitigate the shortage of in-situ data availability by providing reliable, updated and cost-effective data as solutions in a global or regional scale. Our research used multiple EO-based hydrological parameters related to water stress situation in the Nile Basin countries, especially highlighting the usage of EO to solve the spatial and temporal data shortage and inconsistency related to the renewable freshwater from both surface water and groundwater resources. We believe that the space technologies have great potential and values to the water management and research studies using freely accessible EO datasets, especially for the developing countries incapable of performing costly on-site data collections.
What do you see as the main conflicts (of analysis, priority, or value) among those who research water (and space technologies) or work with water (and space technologies)?
Conflicts in water research stem from differences in opinions, scientific ego, perception and most importantly the angle a scientist is coming from. Some researchers study water from a scientific perspective, others study it from a purely humanities or fundamental social sciences perspective. Some conflicts also stem from ignorance or not properly knowing that some tools or technologies exist, additionally from not being able to capitalize or contextualize on existing research. Whether the researcher did not perform a proper literature review or ignored the previous research and reinvented the wheel. The best, the trendiest and the most successful research is the one done with an interdisciplinary lens, keeping in mind all points of view and inviting researchers from different disciplines to collaborate. I am seeing the whole research community leaning towards this model and I am hoping scientists young and experience will continue to embrace it.
What is your favourite aggregate state of water?
As a scientist, I have to say I study all states of water. Solid, liquid and gas. I cannot favour one over the other. As a matter of fact, it is extremely important for a scientist to deeply understand all forms and how they affect our planet, environment and research. On a personal note, I love the water in its liquid form. I grew up in Alexandria, Egypt in an apartment building that overlooks the Mediterranean Sea. I enjoyed walking/running by the boardwalk almost every day. Now in my adult years, my favourite vacation is a vacation by the beach, a snorkel in the red sea where I can see the fascinating underwater creatures and plants or just a pleasant sun bath on the sand enjoying the breeze and the sound water. It is a magical moment.
If there is anything else you would like to share with an audience of professionals, with young professionals and other practitioners in the space and water domain, what would it be?
We live in a time of increasing strains on our global freshwater availability due to increasing population, warming climate, changes in precipitation, and extensive depletion of groundwater supplies. At the same time, we have seen enormous growth in capabilities to remotely sense the regional to global water cycle and model complex systems with physically based frameworks. The last decade has seen the implementation or soon-to-be launch of water cycle missions such as GRACE and GRACE-FO for groundwater, SMAP for soil moisture, GPM for precipitation, SWOT for terrestrial surface water, and the Airborne Snow Observatory for snowpack. With the advent of convection-resolving mesoscale climate and water cycle modeling (e.g. WRF, WRF-Hydro) and mesoscale models capable of quantitative assimilation of remotely sensed data (e.g. the JPL Western States Water Mission) we can now begin to test hypotheses on the nature and changes in the water cycle of the Western US from a physical standpoint. In turn, by fusing water cycle science, water management, and ecosystem management while addressing these hypotheses, this golden age of remote sensing and modeling can bring all fields into a markedly less uncertain state of present knowledge and decadal scale forecasts.
There is a lot of excitement nowadays and I call it the best time of Earth Observation for water studies.
I believe now is a golden age for young professionals and other practitioners in the space and water domain: satellites are providing us with an unprecedented wealth of data with the ongoing development of satellites observations, cloud computing, very high-resolution imagery, radar images and others.
Combine that with the new developments in data processing and storage, and in artificial intelligence for various applications, and you can see there is an order-of-magnitude change in capacity. There is so much to work with these days.
Therefore, I encourage the young generation of scientists to join this field in order to participate and witness how space technologies will change water studies and management.
