Newsletter

The May 2026 Hydrology Section Newsletter is out!

Read it: HERE

This issue highlights opportunities and advances across our community, including a reminder to apply for the Bridges to the Future Program, which provides $2,000 grants to support students pursuing careers in hydrology (deadline: October 15).

This issue also features our Remote Sensing Technical Committee (Pages 9–10), including committee updates and an article written by our committee members “A New Era for Soil Moisture Remote Sensing with NISAR.” This article highlights the recent launch of the NASA–ISRO NISAR mission, which provides high-resolution, all-weather global soil moisture observations at unprecedented spatial scales, bridging a long-standing gap between field measurements, models, and satellite data.

Checkout the committee updates and NISAR article below! 

In this Issue:

• Awardee Speaks – Sam Zipper
• Student Spotlight – Uncertainty in Estimating Short-Duration Extreme Precipitation Frequency and Trend (Nischal Kafle)
• Early Career Spotlight – Benjamin Bass
• Science to Solutions – Management-scale groundwater solutions from space (Ryan Smith, Md Fahim Hasan, Rahel Pommerenke; Colorado State University)
• Early Career Spotlight – Fraser King
• Technical Committee (Remote Sensing) – Vinit Sehgal (Louisiana State University); Jasmeet Judge (University of Florida); Rowena Lohman (Cornell University), Alex Lewandowski (Alaska Satellite Facility DAAC); Andrew Feldman (NASA GSFC/University of Maryland), Huilin Gao, Kristen Whitney

Explore all archived newsletters HERE

Featured in the AGU Hydrology Section May 2026 Newsletter, available HERE

We are delighted to share the following updates:

• The RSTC currently has 24 active members across six subcommittees (e.g., newsletter, social media, awards).
  LinkedIn has been a key platform for connecting with the broader community, with over 1,500 members. In addition to announcements, research highlights from recent remote sensing of hydrology publications and news are posted regularly (approximately every two weeks).
• At AGU25, the RSTC organized 15 sessions and one workshop, and 10 students received the RSTC Best Student Presentation Award (detailed further down in this page). For AGU26, more than 10 sessions have been proposed.
• The community-driven Live Cheat Sheet on “Remote Sensing Products for Hydrology” continues to grow and has become a valuable resource for teaching and research. Community members can contribute to this living resource by suggesting new datasets through the Cheat Sheet Suggestion Form.

We invite all colleagues interested in remote sensing—particularly early-career researchers—to stay connected by following us on our LinkedIn, or by subscribing to our mailing list. We also welcome posts of events, opportunities, and other remote sensing hydrology content on our LinkedIn group.

Featured in the AGU Hydrology Section May 2026 Newsletter, available HERE

The recent launch of the NASA-Indian Space Research Organization (ISRO) Synthetic Aperture Radar (NISAR) mission has unlocked a long‑anticipated observing capability of global soil moisture at high spatial resolutions for the hydrology community. Designed as the first joint Earth-observing satellite between NASA and ISRO, NISAR is a science-driven mission that is a combination of dual-frequency imaging radars, large swath, and twice every 12-days coverage to study changes in Earth’s land surfaces at spatial resolutions of 5-80 m. In addition, because NISAR is an all-weather, day-night radar system, it provides consistent observations during extreme events such as floods, droughts, and rapidly evolving wetting episodes, while optical data depends upon solar illumination and is impeded by clouds. For users and enthusiasts interested in learning about NISAR’s vision, algorithms and datasets, the mission's Science Users’ Handbook and a summary article are great starting points.

At the center of the global soil moisture product is NISAR’s L‑band (24-cm wavelength) Synthetic Aperture Radar, which is capable of penetrating moderate vegetation and sensing surface soil moisture at spatial resolutions of 200 m or less with an uncertainty of 6% by volume. This is orders-of-magnitude finer than the current capabilities of microwave soil moisture products from the SMAP and SMOS missions, which typically operate at spatial scales of tens of kilometers. This uncertainty level is unprecedented at this spatial resolution. For hydrologists, the availability and quality of soil moisture at this scale bridges a long-standing gap between field observations, catchment-scale models, and satellite remote-sensing products

Early demonstrations and regional operational products further illustrate NISAR’s potential. For example, over India, ISRO has shown soil moisture retrievals at resolutions as fine as 100 m using combined S‑ (9.4-cm wavelength) and L‑band observations, enabling district/county-scale agricultural and hydrologic monitoring. These products capture field-scale irrigation signals, rainfall-driven wetting and drying cycles, and moisture stress across diverse agroclimatic regions, which have previously remained unresolved by existing resources. Such field-scale soil moisture will enable more rigorous testing of hydrologic and land-surface models, particularly in data-poor regions. NISAR has also opened new pathways for data assimilation, allowing models to ingest spatially explicit moisture information that represents real-world variability in terrestrial hydrology. Such a high-resolution capability is transformative for hydrology, where spatial heterogeneity in soil moisture strongly controls runoff generation, evapotranspiration, and land-atmosphere feedbacks. This scale is also key for improved land management on farms and ranches. Equally important is NISAR’s role in advancing hydrology beyond soil moisture as a standalone variable. When combined with complementary datasets, such as evapotranspiration, precipitation, and groundwater observations, NISAR soil moisture supports improved estimation of water and energy fluxes, drought intensification, and land-atmosphere coupling strength.

Samples of preliminary NISAR observations, including the 200 m soil moisture product, are available through the NASA Earthdata platform for selected sites across the globe for the scientific community. The first public release of the global Level-1 and -2 products are anticipated in early summer 2026, along with a beta version of the soil moisture product. The updated soil moisture retrievals will be available upon completion of product calibration and validation, about 6-9 months later. The mission’s free and open data policy, along with analysis-ready formats distributed through the NASA Earthdata and ISRO Bhoonidhi portals, further lowers barriers for broad scientific and operational use. Due to its large swath and high spatial resolution, NISAR will add upwards of 80 terabytes of data per day to the archive. Over the course of its 3-year mission, NISAR’s data volume (including products at all Levels) will surpass that of all other NASA Earth Observation datasets combined. Individual data products are often tens of gigabytes in size and delivered in the HDF5 file format. To support the user community, the Alaska Satellite Facility has published an executable NISAR Cookbook and NISAR Data User Guide as regularly updated, living documents. They serve as resources for those wishing to learn about NISAR data, view updates from the mission Project and Science Teams, and learn methods to efficiently access and work with the dataset both in Python and with GIS software.

In summary, the launch of NISAR marks a significant step forward for hydrologic sciences. Its high-resolution, globally consistent, and physically meaningful observations, enable cutting-edge science at previously inaccessible scales. The high-resolution soil moisture product from NISAR, along with complementary capabilities of current satellite missions such as NASA SMAP, ESA SMOS and Sentinel-1, will provide transformational advances in hydrologic sciences and applications. As adoption expands across the community, these datasets are expected to become foundational to next-generation hydrologic research and water-resource decision making.

Written by members of our AGU Remote Sensing Technical Committee
Vinit Sehgal (Louisiana State University); Jasmeet Judge (University of Florida); Rowena Lohman (Cornell University); Alex Lewandowski (Alaska Satellite Facility DAAC); Andrew Feldman (NASA GSFC/University of Maryland)

We are pleased to recognize the outstanding recipients of the Remote Sensing Student Award for their exceptional presentations during our AGU25 Remote Sensing Hydrology sessions. These students have demonstrated excellence in research, innovation, and communication in the field of remote sensing for hydrology.

AGU25 Remote Sensing Student Award winners:

RSTC feature in the April 2025 Hydrology Section Newsletter

Read it: HERE

This month’s theme, building bridges, highlights efforts that span disciplines, generations, and geographies—supporting students in honor of those who shaped our field, expanding access to tools and data, and applying remote sensing to water resource challenges.

This issue features an article from our Remote Sensing Technical Committee, "Easing the Learning Curve with a New Cheat Sheet for Remote Sensing of the Hydrological Cycle", which debuts our new Remote Sensing Hydrology Cheat Sheet, a curated guide to key remote sensing datasets. This effort was led by our early career researchers. Checkout the article and description of the cheat sheet below! 

The AGU Hydrology Section Executive committee is seeking contributions for Hydrology Horizons, a new section spotlighting emerging research and technologies—new data, methods, tools, or early insights. Nominate yourself or a colleague at: agu.hydro.news@gmail.com.

In this Issue:

• Bridges to the Future Program: Dr. John Selker
• Awardee Speaks: Kaidi Peng
• Technical Committee: Remote Sensing
• Fellow Speaks: Dr. Christina (Naomi) Tague
• Science to Solutions: WWAO
• Sister Organization: EGU
• Open Channel: Help shape the newsletter through the survey

Explore all archived newsletters HERE 

Featured in the AGU Hydrology Section April 2025 Newsletter, available HERE

Over the past few decades, Earth observations using satellite remote sensing have proven to be integral to scientific research and applications. This is especially true for hydrological systems, where nearly all components of the hydrological cycle are observable from space using freely accessible and globally available remote sensing products. The advancements in hydrology remote sensing contribute valuable data to support hydrological modeling, water resources management, disaster preparedness, and more. With near real-time global coverage and increasingly better temporal and spatial resolutions, remote sensing continues to improve our understanding of hydrological systems, particularly in regions of the world that lack in-situ ground observations.

As the quantity of remote sensing products continually increases, the ‘learning curve’ for using new datasets becomes steeper. Keeping track of remote sensing products and their characteristics can be complex and time consuming. Many users struggle with navigating extensive user guides, Algorithm Theoretical Basis Documents (ATBDs), multiple product versions, and numerous websites in their search for specific data. Even for well-versed researchers, navigating diverse file formats, repositories, tools, and dataset structures can be cumbersome. For new users, this learning curve can be discouraging and may even deter them from using these datasets at all.

Given the scientific potential of remote sensing for hydrological research and applications, as well as the substantial investment of time and resources to develop these technologies, there is a critical need to increase resources aimed to support new users. As a step towards easing this learning curve, the Remote Sensing Technical Committee (RSTC) has compiled a new (representative) Hydrology Remote Sensing Live Cheat Sheet. We envision this resource to be regularly maintained, updated, and available on the RSTC website. Please note that this directory is not comprehensive and only represents a subset of available datasets. We invite the AGU community to support development of this directory by submitting dataset recommendations to us for review and inclusion through this form. The Live Cheat Sheet will be updated every two months based on responses submitted through the form.

Together, we can lower the learning curve of hydrology remote sensing to continue increasing the scientific potential and reach of hydrology research and applications.

Remote Sensing Products for Hydrology

Sample cheat sheet. View the full Live Cheat Sheet HERE. Suggest a cheat HERE.

Disclaimer: This cheat sheet is a non-comprehensive, community-updated resource. It reflects a representative selection of datasets—not an exhaustive directory. Help us keep it inclusive and diverse by suggesting datasets through this form. 

Written by members of the AGU Remote Sensing Technical Committee
Gigi Pavur (US Army Corps of Engineers), Deep Shah (Texas A&M University), Laura Almendra (University of Florida), Leah Kocian (Texas A&M University), Debasish Mishra (Texas A&M University), Vinit Sehgal (Louisiana State University), Huilin Gao (Texas A&M University), Kristen Whitney (NASA GFSC; University of Maryland),  Hatim Geli (New Mexico State University), Andrew Feldman (NASA GSFC; University of Maryland) 

We are pleased to recognize the outstanding recipients of the Remote Sensing Student Award for their exceptional presentations during our AGU24 Remote Sensing Hydrology sessions. These students have demonstrated excellence in research, innovation, and communication in the field of remote sensing for hydrology.

Please join us in congratulating this year's winners on our LinkedIn post HERE!

For the fourth consecutive year, the student-led workshop on Large-Scale Geospatial Data Analysis and Visualization in R has now become a staple of AGU fall meeting. This year’s workshop included a full-day, hands-on training in R, covering a range of topics from foundational concepts to advanced techniques in large-scale geospatial analysis. The workshop explored practical aspects of remote sensing, working with satellite-based soil moisture and vegetation indices. It also introduced parallel computing for large-scale analysis. In the afternoon, a coding boot camp followed.

Debasish Mishra and Leah Kocian–both Ph.D. students at Texas A&M University–served as instructors alongside Dr. Vinit Sehgal, an Assistant Professor at Louisiana State University. About 40 attendees enthusiastically participated in the workshop, including graduate students, industry professionals, and researchers across various career stages.  Participants represented diverse geographical regions, including Asia (India, Thailand), Europe, Canada, and the United States, with expertise spanning hydrology, GIS, atmospheric sciences, groundwater hydrology, and ocean engineering.

The workshop codes and notes can be accessed at: https://vinit-sehgal.github.io/lgar/

Reference: Mishra, Debasish, Leah Kocian, and Vinit Sehgal. "Large-Scale Geospatial Data Analysis and Visualization in R." In AGU24. AGU, 2024.

Written by Dr. Vinit Sehgal (Louisiana State University)

Featured in the AGU Hydrology Section March 2024 Newsletter available HERE

Since the first use of hot-air balloons for military reconnaissance, remote sensing technology has come a long way in observing and recording datasets of Earth’s environment and ecosystems. Remote sensing has thus played an important role in advancing our understanding of key hydrological variables including precipitation, soil moisture and evapotranspiration (ET), with its ability of providing consistent, regional and long-term datasets and products. The needs and applications of these datasets govern the mission stakeholders, investors and end-users. For example, commercial products may address data gaps and solve business problems that are typically driven by stakeholders from the private sector to be used for revenue-driven applications. On the other hand, freely available andimpact-driven products contribute to saving, enhancing quality of life and reducing economic damage. Lastly, scientific, and research-driven products aim to advance Earth observation or its applications in specific domains. Collectively, these products can result from a mix of public and private investments, as well as philanthropic organizations, leading to a wide range of benefits. Specifically, all these types of products have been critical in addressing economic, social and environmental challenges. As technology advances, so does the quality of data, with spatial resolution emerging as a crucial focus, particularly in managing hydrological systems at different scales where the spatial variability of hydrological processes can be decisive.

Among these advances, precipitation monitoring has been enhanced by merging datasets from various sources. Currently, the Multi-Source Weighted-Ensemble Precipitation, version 2 -  MSWEP V2, with global coverage, achieves high spatial and temporal resolutions of 0.1 degrees every 3 hours. MSWEP V2 integrates gauges, satellites and reanalysis, incorporating river discharge observations for robustness. Another example is the Climate Hazards Group InfraRed Precipitation with Station Data version 2 -  CHIRPS, achieving 0.05-to-0.1-degree resolutions every 6 hours. CHIRPS integrates station measurements and satellite data with a novel blending procedure. While CHIRPS excels in spatial resolution, its reliance on station data limits coverage to land analysis between 50 degrees South and 50 degrees North. Fortunately, the Global Precipitation Measurement (GPM) can extend this coverage globally with its Integrated Multi-satellite Retrieval of GPM-IMERG product at a similar resolution.

Furthermore, the development of microwave sensor technology has been crucial for global monitoring of soil moisture. However, the size constraints of these instruments have historically limited their spatial resolution. Downscaling techniques emerged to overcome this limitation, with the most recent one derived from the Soil Moisture Active and Passive (SMAP) L-band radiometer and based on the thermal inertia theory. Combining the SMAP Enhanced L2 radiometer Half-Orbit 9 km EASE-Grid Soil Moisture product with land surface temperature from the Moderate Resolution Imaging Spectroradiometer (MODIS) has resulted in a global daily 1 km resolution surface soil moisture time series. Nevertheless, in April 2024, NISAR (NASA-ISRO SAR Mission) will launch and provide active microwave measurements and thus retrievals of soil moisture at <100m resolution. Concurrently, other recent technological advancements have enabled the integration of microwave sensors onto drone-mounted systems. The Soil Moisture Company, a collaborative effort between Black Swift Technologies, Weather Stream and the University of Colorado Center for Environmental Technology, has pioneered the development of L-band Differential Correlation Radiometer technology and a soil moisture retrieval algorithm. This technique offers high-resolution soil moisture data that can be adapted to various needs and specifications.

High-resolution insights into water-plant relationships have also been achieved, leading to a revolution in water management through initiatives like OpenET. It provides daily to annual ET estimates at 30 meters resolution using public satellite and weather data by combining inputs from Landsat, Sentinel-2, GOES and more. This precision empowers sustainable decision-making for user-defined areas, enhancing resource management efficiency. Another example takes place on the International Space Station, ECOSTRESS (ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station) that marks a breakthrough in how we monitor environmental and agricultural health. Through its multispectral thermal infrared radiometer, it captures the Earth's surface across five spectral bands at an impressive ~70 m resolution, identifying plant water stress and the onset of droughts with unparalleled accuracy. These data offer essential insights into how the terrestrial biosphere reacts to alterations in water availability, impacts on the global carbon cycle and enhances water conservation and agricultural resilience.

All these advancements in spatial resolution within remote sensing methods enable improved detection and monitoring of hydrological challenges, leading to better understanding and management of water resources, as well as more effective disaster response strategies. 

Written by members of the AGU Remote Sensing Technical Committee
Laura Almendra-Martin (University of Florida), Debasish Mishra (Texas A&M University), Deep Shah (Texas A&M University), Leah Kocian (Texas A&M University), Vinit Sehgal (Louisiana State University), Hatim Geli (New Mexico State University), Andrew Feldman (NASA GSFC), Huilin Gao (Texas A&M University), and Jasmeet Judge (University of Florida)

Email us at agu.rstc2024@gmail.com.