Dr. Fadji Z. Maina, Associate Research Scientist, Hydrological Sciences Laboratory, NASA's Goddard Space Flight Center and the University of Maryland–Baltimore County
Research Interest: Hydrology.
Research Highlights: Of all the potential impacts associated with Earth's changing climate, shifts in the planet's hydrological cycle may be the most significant. For example, an atmosphere warmed by heat-trapping gasses will increase evaporation rates and raise the amount of moisture circulating throughout the troposphere (i.e., the lowest level of the atmosphere). This, in turn, would impact the development of clouds, change precipitation patterns, and increase the frequency of intense precipitation events. Further, warmer temperatures would result in more precipitation falling as rain rather than snow, which would affect patterns of terrestrial runoff and stream flow.
Yet, due to regional variations in topography and other geophysical characteristics, climate-induced changes to Earth’s hydrologic cycle would likely materialize differently in regions around the globe.
To find out how changes in the hydrologic cycle are impacting High Mountain Asia (HMA)—an area home to more than a billion people and that encompasses the Tibetan plateau and the nearby countries of China, Myanmar, Bhutan, Nepal, Bangladesh, India, Pakistan, Afghanistan, and Kyrgyzstan—NASA created a High Mountain Asia Team (HiMAT). Its goals are to assess and project changes in the region’s water, ice, snow, surface hazards, and related phenomena, and better understand how shifts in the region’s water resources are impacting its human and bio-geophysical systems.
Among the scientists involved in this is effort is Dr. Fadji Z. Maina, Associate Research Scientist in the Hydrological Sciences Laboratory at NASA's Goddard Space Flight Center in Greenbelt, Maryland, and at the University of Maryland, Baltimore County. As a member of HiMAT’s Water Budget Processes subgroup, Maina uses satellite data and hydrologic models to investigate changes in the HMA water budget over the past 20 years.
“We’re trying to reconstruct the hydrology of the region over the past two decades. But, in general, my focus is understanding the evolution of water resources in response to climate change,” said Maina. “The goal is to be able to do some forecasts later on and then corrections to see how these resources are going to change in the future, but right now we are trying to understand what is really driving the changes in water resources that we are observing.”
Although climate change is likely one of those drivers, it’s not the only one.
“If we think about High Mountain Asia, glaciers are melting and the entire hydrological cycle is changing, so [climate change] could be why we are seeing changes,” Maina said. “But the increased agricultural activities on the landscape and the consumption of water by humans could also be driving these changes. So, we need to understand what’s driving the changes in hydrology that we’re seeing.”
To zero-in on these drivers, Maina and her colleagues rely on NASA Earth science data from instruments aboard a range of satellites.
“All of our work is based on NASA products. That’s why we are targeting the past two decades, because it’s the satellite era,” she said. “We use Moderate Resolution Imaging Spectroradiometer (MODIS) data for [measurements of] Leaf Area Index, snow cover, land cover, and surface albedo. We use data from the Integrated Multi-satellitE Retrievals for GPM (IMERG) algorithm of the Global Precipitation Measurement (GPM) satellite constellation, data from the Gravity Recovery and Climate Experiment (GRACE) satellites, and, sometimes, data from the Soil Moisture Active Passive (SMAP) satellite mission for soil moisture.”
Given the HMA terrain, Maina’s reliance on satellite observations may not be a surprise. The size, topography, and harshness of the HMA environment make the use of ground-based sensors and other types of remotely-sensed data (i.e., airborne lidar) impractical, if not altogether impossible. Therefore, satellite data are the only option Maina and her fellow HiMAT team members have for observing HMA hydrological attributes and documenting how they have changed.
“With the exception of the ESA (European Space Agency) Climate Change Initiative (ESA-CCI) data product, which provides soil moisture data for a longer time [frame] than SMAP—which only goes back to 2015—the NASA products I cited are the only products that we can rely on to construct the hydrology in the region,” Maina said.
Maina and her colleagues get the data they need from several sources, including NASA’s National Snow and Ice Data Center Distributed Active Archive Center (NSIDC DAAC). Located in Boulder, Colorado, the NSIDC DAAC is part of the Cooperative Institute for Research in Environmental Sciences, a joint institute of University of Colorado Boulder and NOAA.
The NSIDC DAAC archives and distributes cryospheric and related geophysical data in NASA’s Earth Observing System Data and Information System (EOSDIS) that pertain to snow and ice processes, particularly in regard to interactions among snow, ice, the atmosphere, and the ocean. It also provides tools, resources, and support to data users around the globe.
In addition to serving as a member of the HiMAT team, Maina is also a member of the NSIDC DAAC’s User Working Group, which suggests specific data products and services to NASA and the NSIDC DAAC and represents the data user community in the development NSIDC DAAC products and services.
The utility of data available through the NSIDC DAAC for helping scientists like Maina better understand HMA hydrological changes is evident in studies like the one she and her colleagues published in the Nature journal Communications Earth & Environment in 2022. In this paper, Maina and her colleagues endeavored to explain the drivers of the increased HMA greening and its impact on the region’s water budget (the inputs, outputs, and changes in the storage of water within a system).
“High Mountain Asia exhibits one of the highest increases in vegetation greenness on Earth, subsequently influencing the exchange of water and energy between the land surface and the atmosphere,” the researchers write. “Given the strong interactions between the hydrosphere, the biosphere, and the cryosphere, understanding the drivers of greening in this highly complex region with significant land cover heterogeneity is essential to assess the changes in the regional water budget.”
To gain that understanding, Maina and her colleagues analyzed a variety of satellite observations from 2003 to 2020. They found that precipitation drives greening in mid and low elevations, decreased amounts of snow enhance greening in most of the hydrologic basins, and irrigation induces greening in irrigated lands.
“There are previous studies that have shown the region is experiencing this greening because of increases in carbon dioxide. But, when we looked over HMA using MODIS Leaf Area Index, along with IMERG and other products, we saw that it’s more complex,” Maina said. “In some areas we have increases in vegetation because we have increases in precipitation. In other areas it’s because we have warming in the Himalayas and, if we look downstream in India, we have greening [due to] irrigation. In fact, when you compare the rates of greening caused by warming versus that caused by precipitation and irrigation, the irrigation is leading to the highest rates of vegetation.”
These findings are significant, Maina said, as they point to the impact that human activity can have on the region’s water budget.
“The consequences of this are that irrigation can really change the water cycle, because when we have changes in vegetation, this is going to impact the land-atmosphere interactions and the energy balance,” she said. “So, the consequences of this might counter-balance the impacts of climate change or exacerbate them.”
In another 2022 paper published in Scientific Reports, Maina and her colleagues investigated how human- and climate-induced land surface changes, namely greening, irrigation, and decreases in snow cover, are impacting the HMA surface albedo.
Using a mathematical method for determining how information shared among a set of variables influences a particular outcome combined with remote sensing data to quantify the effects of the changes in LAI, soil moisture, and snow cover on surface albedo, Maina and her colleagues found that anthropogenic agricultural water use over irrigated lands caused the largest decreases in surface albedo. They also found that greening and decreased snow cover from warming drove changes in visible and near-infrared surface albedo in different HMA areas.
“We analyzed how the surface albedo, captured by MODIS, has changed and we showed that we have a significant decrease in surface albedo, which means that the environment is getting warmer,” Maina said. “We also showed that the causes of the decrease in surface albedo over the region and that these two main drivers—warming and irrigation—are significantly changing the surface albedo.”
These impacts to surface albedo are noteworthy as they could result in the overuse of water resources and negative impacts on the region’s population.
“Surface albedo decreases driven by irrigation are likely to have a positive feedback impact on water resource requirements,” Maina and her co-authors write in the paper’s discussion. “For example, the reduction in surface albedo due to irrigation could lead to more warming and high evaporative demand, which could subsequently lead to more irrigation demand and the overuse of water resources. Over the Ganges-Brahmaputra and Indus [areas] with large populations reliant on irrigated agriculture, these surface albedo decreases are a significant concern.”
In her most recent publication, which appeared in the American Geophysical Union journal Earth’s Future in early-2023, Maina and her Hydrological Sciences Laboratory colleague Dr. Sujay V. Kumar used MODIS and IMERG satellite data and the Noah-Multiparameterization Land Surface Model (Noah-MP LSM) to study the trends in rain-on-snow (ROS), a key contributor in influencing water availability and hazards such as HMA floods and landslides from 2001 to 2018.
Their results showed that changes in precipitation phase and rainfall are altering ROS. However, because of the strong HMA physical heterogeneity and atmospheric dynamics, ROS characteristics and trends are not uniform across the region.
“ROS occurs predominantly over the Indus, Ganges-Brahmaputra, and northwestern basins. In the Indus, ROS, representing ~5% of the annual precipitation and ~20% of the annual snowmelt, has an increasing trend,” Maina and Kumar write. “This is contrary to the Ganges-Brahmaputra characterized by decreasing ROS trends, where it represents ~11% of the annual precipitation and ~60% of the annual snowmelt.”
The results of this study are noteworthy, the researchers observe, as they provide new insights on ROS-driven changes in the HMA hydrological cycle. “Increasing trends in ROS over [the Indus basin] contribute to reducing the snowpack in late summer, with concerns of reduced water availability and increased groundwater exploitation," write Maina and Kumar. "Similarly, because of its high amount and contribution to snowmelt, the decreasing ROS trends in the Ganges-Brahmaputra [basin] will have consequences of decreased recharge from the headwaters and exacerbated use of groundwater unless increasing trends in rainfall compensate for the decreasing snowmelt.”
As the conclusions of these studies suggest, the use of satellite data by Maina and her colleagues to better understand the drivers of the HMA hydrological changes they’re observing are yielding valuable insights that will benefit the ongoing efforts to project how this region's water budget may evolve in the era of climate change. In addition, they also reveal the importance of how satellite data from NASA’s NSIDC and other DAACs can play a crucial role in providing scientists working in remote, data-scarce regions of the world with the data they need to conduct their research.
Representative Data Products Used or Created:
Available through NASA's NSIDC:
- MODIS Snow Cover
- NSIDC DAAC High Mountain Asia (HMA) Collection
- Soil Moisture Active Passive (SMAP)
Other data products used:
- MODIS Leaf Area Index
- Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) Precipitation
- ESA CCI Soil Moisture
- European Center for Medium-Range Weather Forecasts (ECMWF) Reanalysis v5 (ERA5) Climate Variables
- Gravity Recovery and Climate Experiment (GRACE)
- IMERG Precipitation
- Noah-Multiparameterization Land Surface Model (Noah-MP LSM)
Read about the Research:
Maina, F.Z. & Kumar, S.V. (2023). Diverging Trends in Rain-On-Snow Over High Mountain Asia. Earth's Future, 11(3), e2022EF003009. doi:10.1029/2022EF003009
Maina, F.Z., Kumar, S.V., Albergel, C., & Mahanama, S.P. (2022). Warming, increase in precipitation, and irrigation enhance greening in High Mountain Asia. Communications Earth & Environment, 3(43). doi:10.1038/s43247-022-00374-0
Maina, F.Z., Kumar, S.V., & Gangodagamage, C. (2022). Irrigation and warming drive the decreases in surface albedo over High Mountain Asia. Scientific Reports, 12, 16163. doi:10.1038/s41598-022-20564-2