publications

2025

1. Earth Space Sci.

   Multi-Satellite Tracking of Surface Water Storage Change in the Era of Surface Water and Ocean Topography (SWOT) Satellite Mission

   Pritam Das, and Faisal Hossain

   Earth and Space Science: Science from the Surface Water and Ocean Topography Mission, 2025 (in review)

   Abs

   The Surface Water and Ocean Topography (SWOT) satellite, launched in December 2022, represents a significant advancement in the remote sensing of global water bodies, providing simultaneous measurements of water surface elevation and extent in all-weather conditions. This study evaluates SWOT’s capability to estimate reservoir storage dynamics in comparison to pre-SWOT methods. SWOT demonstrates high accuracy in measuring water surface elevation, achieving a median R^2 close to 1 and root mean square errors (RMSE) nearly an order of magnitude lower compared to earlier non-SWOT approaches. SWOT offers substantial improvement over single-sensor and multi-sensor methods, due to spatial averaging of distributed elevation measurements, which was further validated by similar measurements of the ICESat-2 satellite. The key limiting factor in estimating storage from elevation measuring sensors was found to be the accuracy of Area-Elevation-Volume (AEV) curve. Furthermore, preliminary applications of machine learning to integrate SWOT with non-SWOT datasets show promise, although constrained by limited data availability of SWOT as of late 2024.

2. J. Hydrol. Eng. - ASCE

   Forecast-Informed Reservoir Operations within a Satellite-Based Framework for Mountainous and High-Precipitation Regions: Case of the 2018 Kerala Floods

   Pritam Das, Sarath Suresh, Faisal Hossain, and 7 more authors

   Journal of Hydrologic Engineering, Apr 2025

   Abs DOI PDF

   River regulation in mountainous and high-precipitation regions with hydropower dams often struggles to find the right balance between hydropower generation while ensuring flood protection for downstream inhabitants. The goal of hydropower generation is to keep reservoirs at the maximum pool as often as possible while for flood control, it is to maintain sufficient cushion in available storage to absorb an incoming flood wave. Using weather forecasts to proactively manage reservoir operations for such conflicting goals is now a well-known solution. However, this challenge of applying forecast-informed reservoir operations is magnified in developing regions where there is a paucity of ground data to track reservoir dynamics. In this study, we explore the utility of using publicly available precipitation forecasts from the Global Ensemble Forecasting System (GEFS) with a fully satellite-based reservoir tracking framework called reservoir assessment tool (RAT) to understand the potential of forecast-informed operations in highly mountainous and high-precipitation regions that are mostly ungauged. We apply our investigation to the case of damaging floods that took place in 2018 in the Southern Indian state of Kerala where river regulation is carried out with a fleet of hydropower dams. Our results show that the precipitation forecast from GEFS has sufficient skill, if focused on trends and bias adjustment, to predict reservoir inflow peaks up to a week ahead of time where the trend for the timing of the peak and rate of rise match well. Using our satellite-based RAT framework, we explore the range of actionable scenarios for dam operators that could potentially minimize downstream flood risk with this forecast-informed reservoir operations scheme.

2024

1. Environ. Model. Softw.

   ResORR: A Globally Scalable and Satellite Data-Driven Algorithm for River Flow Regulation Due to Reservoir Operations

   Pritam Das, Faisal Hossain, Sanchit Minocha, and 6 more authors

   Environmental Modelling & Software, May 2024

   Abs DOI PDF

   We propose a globally scalable algorithm, ResORR (Reservoir Operations driven River Regulation), to predict regulated river flow and tested it over the heavily regulated basin of the Cumberland River in the US. ResORR was found able to model regulated river flow due to upstream reservoir operations of the Cumberland River. Over a mountainous basin dominated by high rainfall, ResORR was effective in capturing extreme flooding modified by upstream hydropower dam operations. On average, ResORR improved regulated river flow simulation by more than 50% across all performance metrics when compared to a hydrologic model without a regulation module. ResORR is a timely software algorithm for understanding human regulation of surface water as satellite-estimated reservoir state is expected to improve globally with the recently launched Surface Water and Ocean Topography (SWOT) mission.

2. Earth’s Future

   Reconstruction of the Hydro-Thermal Behavior of Regulated River Networks of the Columbia River Basin Using Satellite Remote Sensing and Data-Driven Techniques

   G. K. Darkwah, Faisal Hossain, Victoria Tchervenski, and 7 more authors

   Earth’s Future, Oct 2024

   Abs DOI

   The use of satellite-based thermal infrared remote sensing has facilitated the assessment of surface water temperature on a large scale. However, the inherent limitations of this remote sensing technique make it difficult to assess rivers unless ambient conditions are cloud-free, devoid of steep terrain and the rivers are at least 60 m wide. To address these challenges that limit the spatiotemporal continuity of satellite-based hydro-thermal data, we harnessed the extensive coverage from the Landsat missions’ thermal infrared sensors and data-driven techniques to estimate surface water temperature of rivers. Out of the tested data-driven techniques, we selected the Random Forest Regressor as our prime non-linear approach for estimation of surface water temperature in rivers. Using the selected technique, proposed as THORR ( T hermal H istory of R egulated R ivers), we successfully reconstructed a multi-decadal, continuous spatiotemporal surface water temperature record for regulated rivers in the Columbia River Basin. Using 42 years of data, the surface water temperature could be predicted on average with 0.71^∘ C of absolute error regardless of the dam’s potential thermal influence in the downstream reaches. The reconstructed hydro-thermal behavior generated from THORR revealed a long-term downstream warming trend along the Columbia River. The open-source THORR tool can be extended to any river system around the world that is not gauged with in-situ temperature measurements for the reconstruction of hydro-thermal behavior. , Plain Language Summary Surface water temperature of rivers, which is an important ecological parameter for more robust water management, can be estimated in a cost-effective and globally scalable way from satellite thermal infrared (TIR) remote sensing. However, such a technique is limited to rivers of sufficient width and cloud-free conditions. In this study, data-driven techniques were explored to overcome this limitation and reconstruct surface water temperature of rivers in the continuum of space and time. By using a comprehensive record spanning 42 years of satellite remote sensing, we demonstrate that it is possible to recreate robust estimates of long spatiotemporal trends of river temperature to understand how surface waters are being altered thermally due to water management and climate change. , Key Points Thermal Infrared remote sensing from Landsat was used to estimate the surface water temperature of the highly regulated Columbia River Basin Using 42 years of data, the surface water temperature could be predicted on average with 0.7^∘C of absolute error regardless of the dam’s potential thermal influence The reconstructed hydro-thermal behavior indicated a long-term downstream warming trend along the Columbia River

3. Clim. Dyn.

   Remote Sensing of Snow Cover Dynamics and Climate Implications in the Indus, Ganga, and Brahmaputra River Basins

   Abhilasha Dixit, Ajanta Goswami, Sanjay K. Jain, and 1 more author

   Climate Dynamics, Aug 2024

   Abs DOI

   In the context of the Himalayan region, where glaciers and snow cover area (SCA) critically influence river runoff, monitoring SCA on a spatio-temporal basis is essential for the effective utilization of water resources. This study delves into the complex dynamics of snow cover within the Indus, Ganga, and Brahmaputra basins in the Hindu-Kush Himalayan region (HKH), leveraging the high temporal resolution of the Moderate Resolution Imaging Spectroradiometer (MODIS). The MODIS data, with its reduced cloud cover, offers an enhanced observation capability for these high-elevation regions. Our research focuses on evaluating the annual and seasonal variations in SCA across these basins from 2003 to 2021 and correlates these variations with critical climatic variables such as temperature and precipitation, using data from the fifth-generation European Centre for Medium-Range Weather Forecasts (ECMWF) Atmospheric Reanalysis of the global climate (ERA5). The study presents a comprehensive assessment of SCA, highlighting significant findings that include a range of mean annual SCA from 22.31 to 42.14%, with notable seasonal fluctuations. The data analysis reveals a clear correlation between SCA variability and climatic parameters, particularly temperature, indicating a high sensitivity of snow cover to temperature changes. Notably, the most significant temperature increases and their impacts on SCA were observed in the Ganga and Brahmaputra basins. Furthermore, the study examines how topographical attributes such as elevation, slope, and aspect contribute to the distribution of SCA, revealing the critical role these factors play in determining the varying elevations of the snow line across each basin. These findings underscore the profound influence of climate change on snow cover dynamics in this region. The study’s insights into the spatial and temporal variability of SCA, coupled with the observed climatic trends, emphasize the urgent need for adaptive water resource management strategies in these crucial river basins.

4. Remote Sens. Environ.

   Satellite-Based Tracking of Reservoir Operations for Flood Management during the 2018 Extreme Weather Event in Kerala, India

   Sarath Suresh, Faisal Hossain, Sanchit Minocha, and 5 more authors

   Remote Sensing of Environment, Jun 2024

   Abs DOI

   Uncoordinated management of hydropower dams during extreme and unexpected precipitation events in mountainous terrain can have disastrous consequences due to the competing nature of flood control and hydropower generation. Numerous cases of flooding events that have been exacerbated due to insufficient storage conditions in hydropower dams have been reported worldwide. There is a need for a scalable and publicly-accessible monitoring framework that is capable of providing reliable, near-real time, and transparent reservoir operations data. A fully satellite-based framework is the most viable solution to build such capability. The Reservoir Assessment Tool (RAT 3.0), which utilises high frequency remote sensing-based surface area and reservoir storage estimation alongside hydrological modelled inflow was applied here for the 2018 Kerala floods in India as a globally representative case for a mountainous river basin with high precipitation and hydropower dams. Application of satellite-based RAT 3.0 in monitoring the state of 19 reservoirs in Kerala during the flood event showed very promising results. In general, RAT 3.0, using satellite remote sensing, was found to be able to capture the temporal trend of the reservoir storage and pinpoint the sudden shift in filling or release decisions made by the dam operator. Inflow modelling in such regions was found to require careful calibration with identification of reservoirs that are heavily regulated being a critical aspect. The perennial high cloud cover in such regions necessitate and highlights the central role played by microwave and radar-based satellite sensors, such as the Surface Water and Ocean Topography (SWOT) mission, in tracking reservoir state. An operational version of RAT 3.0 for stakeholder agencies tailored for hydropower dams operating in high precipitation and mountainous environments is a real-world outcome of this study.

5. Environ. Chall.

   Assessing Snow Cover Patterns in the Indus-Ganga-Brahmaputra River Basins of the Hindu Kush Himalayas Using Snow Persistence and Snow Line as Metrics

   Abhilasha Dixit, Ajanta Goswami, Sanjay Jain, and 1 more author

   Environmental Challenges, Jan 2024

   Abs DOI

   This study investigates the utilization of snow persistence (SP) as a metric to assess snow cover patterns in the Upper Indus-Ganga-Brahmaputra (UIGB) river basins, an area notably susceptible to climate change. The objectives of the study are to establish seasonal snow persistence, calculate seasonal snow lines, and quantify the temporal trend of snow lines. It also underscores the importance of accounting for climate zones, elevation, and seasonal variations when investigating snow persistence. Furthermore, the study estimates the snow line elevation using the Regional Snow Line Elevation (RSLE) approach with remote sensing data. Over a span of 19 years (2003–2021), the analysis of SP% in UIGB basins indicates a notable reduction in the mean annual permanent snow zone area, decreasing by -2.61 %, -2.37 %, and -4.18 % from winter (DJF) to summer (JJA). The results uncover considerable fluctuations in snow cover across various climate zones and seasons. The impact of warming is clearly visible on snow cover, instigating a transition from permanent and seasonal snow zones towards intermittent and minimal or no snow zones. The seasonal analysis of the snow line from 2003 to 2021 illustrates fluctuation in the snow line for UIGB basins, from 2349 ± 117 m to 4802 ± 51.7 m, 3003 ± 286 m to 4871 ± 64.4 m, and 3238 ± 127 m to 5047 ± 73 m between winter and summer seasons, with the most significant fluctuation occurring in the Brahmaputra basin. A substantial increase in Snow Line Elevation (SLE) is observed for Ganga (6.67 m yr−1), and Brahmaputra (7.26 m yr−1) at the conclusion of the melting season. These findings offer invaluable insights for formulating targeted mitigation strategies in the snow accumulation regions of each river basin. They equip us with the ability to respond effectively to the spatiotemporal variability of snow cover caused by climate change.

6. Digital Water

   Reservoir Assessment Tool (RAT): A Python Package for Monitoring the Dynamic State of Reservoirs and Analyzing Dam Operations

   Sanchit Minocha,  Das, and Faisal Hossain

   Digital Water, 2024 (in review)

   Abs

   Advancements in satellite remote sensing has enabled the global tracking of reservoir operations, with the Reservoir Assessment Tool (RAT) emerging as a scalable modeling framework that captures the complete dynamic picture of a reservoir consisting of inflow, storage change, evaporation, surface area and outflow. To address the challenges regarding time-consuming installation and the lack of proper forum and documentation to update and test newer versions, we present RAT as a Python library, conveniently packaged with conda, and as a user-friendly command line utility. This simplifies installation, catering to both programming and non-programming users. Test cases and a Continuous Integration/Continuous Development (CI/CD) pipeline ensure robust code integration and community contributions. Thorough documentation is hosted at http://ratdocs.io. The transformation of RAT from a modeling framework into a self-reliant package enhances its usability, reliability, and collaborative nature, solidifying its position as a valuable tool at the nexus of remote sensing and hydrologic modeling.

2023

1. IEEE J. Apl. Earth Obs.

   Understanding Volume Estimation Uncertainty of Lakes and Wetlands Using Satellites and Citizen Science

   Shahzaib Khan, Faisal Hossain, Tamlin Pavelsky, and 21 more authors

   IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023

   Abs DOI

   We studied variations in the volume of water stored in small lakes and wetlands using satellite remote sensing and lake water height data contributed by citizen scientists. A total of 94 water bodies across the globe were studied using satellite data in the optical and microwave wavelengths from Landsat 8, Sentinel-1, and Sentinel-2. The uncertainty in volume estimation as a function of geography and geophysical factors, such as cloud cover, precipitation, and water surface temperature, was studied. The key finding that emerged from this global study is that uncertainty is highest in regions with a distinct precipitation season, such as in the monsoon dominated South Asia or the Pacific Northwestern region of the USA. This uncertainty is further compounded when small lakes and wetlands are seasonal with alternating land use as a water body and agricultural land, such as the wetlands of Northeastern Bangladesh. On an average, 45% of studied lakes could be estimated of their volume change with a statistical significant uncertainty that is less than the expected volume in South Asia. In North America, this statistically significant uncertainty in volume estimation was found to be around 50% in lakes eastward of the 108th meridian with lowest uncertainty found in lakes along the East coast of the USA. The article provides a baseline for understanding the current state of the art in estimating volumetric change of lakes and wetlands using citizen science in anticipation of the recently launched Surface Water and Ocean Topography Mission.

2022

1. Environ. Model. Softw.

   Reservoir Assessment Tool 2.0: Stakeholder Driven Improvements to Satellite Remote Sensing Based Reservoir Monitoring

   Pritam Das, Faisal Hossain, Shahzaib Khan, and 6 more authors

   Environmental Modelling & Software, Nov 2022

   Abs DOI PDF

   In light of the rapidly increasing regulation of rivers due to planned and constructed reservoirs, monitoring reservoir operations has become very crucial. The Reservoir Assessment Tool (RAT) framework was developed to monitor reservoir operations globally, using hydrological modeling and satellite observations. With feedback from stakeholders, improvements in the RAT framework are demonstrated in this study using the Mekong River Basin as an example. A novel multi-sensor reservoir area mapping technique was developed using comple mentary strengths of optical and SAR sensors at a 1 –5 day temporal resolution, allowing the quantification of sub-weekly reservoir operations. Additionally, the skill of radar altimeters in the RAT framework was tested using the Jason-3 altimeter. Using in-situ data from three Thai reservoirs in the Mekong Basin, consistent improvements were observed as compared to the original RAT framework. A functionality for visualizing forecasted outflow was also added using historically inferred reservoir operations or stakeholder-driven target storage expectations.

2. AGU Adv.

   Building User-Readiness for Satellite Earth Observing Missions: The Case of the Surface Water and Ocean Topography (SWOT) Mission

   Faisal Hossain, Pritam Das, Margaret Srinivasan, and 29 more authors

   AGU Advances, Nov 2022

   Abs DOI

   The goal in this commentary is to share the development of the NASA Applied Science pre-launch protocol called the Early Adopter Program (EAP) that is designed to build user-readiness of planned satellite Earth observing missions proactively and before the launch. Here we focus in particular on the Surface Water and Ocean Topography satellite mission EAP as an illustration of benefits of such a program of proactive and sustained user community engagement. Such a commentary will be of value to other satellite Earth observation missions that are currently in service, scheduled for launch or prioritized for development in the near future.

2019

1. Front. Earth Sci.

   Glacier-Surface Velocity Derived Ice Volume and Retreat Assessment in the Dhauliganga Basin, Central Himalaya – A Remote Sensing and Modeling Based Approach

   Ashim Sattar, Ajanta Goswami, Anil V. Kulkarni, and 1 more author

   Frontiers in Earth Science, May 2019

   Abs DOI

   Himalayan glaciers are a storehouse of fresh water and play a significant role in influencing the runoff through numerous perennial rivers flowing over the Indo-Gangetic plains, providing freshwater to the second largest populated country in the world. For suitable management of this water resource, measurement of glacier-ice volume is extremely important in the current scenario of climate change and water scarcity. To address this concern, the present study endeavors to find a suitable methodology to quantify glacier volume and retreat in the Central Himalaya. Herein, two methods were implemented to estimate the total glacier ice volume – conventional area-based scaling method and glacier-surface velocity based modeling technique. The availability of field data allowed a validation assessment to be carried out on two Himalayan glaciers (Chhota Shigri and Satopanth). Here, we propose a volume-area power law, appropriate for the application in the context of Himalayan glaciers. The ice volume of 15 glaciers larger than 1 km2 calculated using a spatially distributed ice thickness model is 3.78 × 109 m3 (f = 0.8), with an overall uncertainty of 18.4%. The total volume of the remaining glaciers in the basin, calculated using a tuned volume-area scaling relation is 2.71 × 109 m3. A sensitivity analysis is performed to evaluate the influence of input parameters on the model and volume-area scaling performance. The study also incorporates investigation of the glacier bed topography for discrete identification of the overdeepening sites in the glacier valley which are potential lake formation sites in the future. A total of 54 overdeepening sites covering an area of 2.85 km2 have been identified. In addition, the relative glacier area loss of the glaciers is investigated using historical CORONA and Landsat satellite imageries. Glaciers with a smaller area and those with lower mean ice thickness near the terminus shrank significantly more, as compared to the larger ones. The total area of the selected larger glaciers is estimated to be 68 km2 in 2015 and deglaciation of 4.7 km2 is observed over the period of 48 years that accounts for 6.9% of the total area in 1968.

2024

1. AGU24

   Toward Integrative Flood and Drought Management Services for Lower Mekong

   Hyongki Lee, Faisal Hossain, Pritam Das, and 7 more authors

   In AGU24, Dec 2024

   Abs

   Reliable forecasts of surface water resources are essential for informing polic...

2. AGU24

   Hidden Sediments, Lost Capacity: How Swiftly Are Global Reservoirs Depleting?

   Sanchit Minocha, Faisal Hossain, Joshua Zhao, and 2 more authors

   In AGU24, Dec 2024

   Abs

   Reservoir sedimentation is a growing concern that threatens water storage capac...

3. AMS24

   Interactive Visualization of the CESM-LENS2 Climate Dataset – Lessons Learned and Recommendations for Visualizing Gridded Datasets Using Open Science Tools

   Pritam Das, Negin Sobhani, Tammy Zhang, and 1 more author

   In 40th Conference on Environmental Information Processing Technologies, Jan 2024

   Presentation type: Talk
4. AMS24

   Interactive-Explanatory Geospatial Data Visualizations on the Web: A Review of Various Open Source Tools

   Tammy Zhang,  Cherukuru,  Das, and 2 more authors

   In 23rd Annual Student Conference, Jan 2024

2023

1. AGU23

   Monitoring and Predicting Reservoir Driven River Regulation from Space

   Pritam Das, Faisal Hossain, and Sanchit Minocha

   In AGU23, Dec 2023
2. AGU23

   Unlocking Climate Data Insights: A Comparative Study of Interactive Visualization Approaches

   Negin Sobhani, Pritam Das, Nihanth Cherukuru W., and 1 more author

   In AGU Fall Meeting 2023, Dec 2023

   Abs

   The increasing complexity and volume of climate datasets, such as the CESM LENS2 dataset, pose significant challenges for scientists seeking to identify crucial trends and effectively communicate findings to a broader audience. Recognizing the potential of interactive visualization as a solution, this project explores the development and comparative analysis of distinct interactive visualization approaches by creating different climate data dashboards for visualizing CESM LENS2 dataset. The CESM2 Large Ensemble Community Project (LENS2) dataset, spanning from 1850-2100, delivers comprehensive simulations of Earth system processes with a 1^∘x1^∘ spatial resolution. In this study, we have experimented with different approaches of creating interactive visualization dashboards. Each platform leverages the potential of interactive visualization, enabling users to manipulate visual representations and discern patterns that would be elusive with traditional visualization methods. These platforms permit users to visualize different variables spatially on a map and temporally for a specified location by clicking on the map. Users can also generate a plot for the regional average alongside the time-series of a specific location, enabling comparative analysis of local and regional trends. One platform is constructed upon the PyData and HoloViz ecosystem, capitalizing on tools that are already well-known to climate scientists for expedient interactive visualization development. The alternative platforms utilize unique server-client models created with FastAPI and D3.js to deliver a customized visualization experience. In this presentation, we aim to provide insights into these visualization methods’ respective advantages and potential drawbacks, providing guidelines for their application in scientific research. This exploration contributes to the evolving field of interactive data visualization, supporting the democratization of climate science understanding and fostering discovery within large-scale, intricate datasets.

3. AMS23

   Reservoir Assessment Tool 2.0: Stakeholder-driven Improvements to Satellite Remote Sensing-Based Monitoring of Reservoirs

   Faisal Hossain, and Pritam Das

   In American Meteorological Society Annual Meeting - Roger Pielke Symposium, Dec 2023

2022

1. AWRA22

   Monitoring Reservoir Operations of the Mekong River from Space – A Self-Correcting Multi-Sensor Approach

   Pritam Das, Faisal Hossain, Shahzaib Khan, and 6 more authors

   In AWRA Annual Water Resources Conference, Dec 2022

   Abs

   Even though dams and reservoirs have become a crucial part of most river networks across the world, understanding their effect on rivers is still difficult due to a lack of availability of reservoir operations data. Using freely available satellite remote sensing data reservoir operations can be quantified on a global scale, for both time-critical decision making and for multi-decadal hindcast studies. Unlike in-situ monitoring networks, satellite remote sensing-based reservoir state observations can have high uncertainties due to challenging conditions, such as cloud cover, atmospheric haze, or dendritic shorelines. In this study, we propose the Tiered Multi-Sensor - Optical and SAR (TMS-OS) algorithm to monitor the reservoir state with multiple tiers of filtering and corrections based on inputs from multiple satellite sensors. Using a combination of different satellite sensors, deficiencies of individual sensors are self-corrected – such as the poor performance of optical sensors during high cloud cover and the poor performance of SAR sensors in dendritic reservoirs. This algorithm can quantify reservoir operations (storage change) with an average Kling-Gupta Efficiency (KGE) of 0.24 and a correlation of 0.77 for three validation reservoirs in Thailand. Compared to previous systems that could monitor reservoirs at a monthly to fortnightly frequency, TMS-OS observes the reservoir state at an improved 1-5 day frequency, allowing for weekly to sub-weekly estimation of reservoir operations. This self-correcting algorithm can also be easily extended with additional sensors as new data becomes available, making it possible to robustly monitor reservoir operations using only publicly available satellite data.

2024

1. waterpower

   Reimagining Dams as Transit Hubs: Visualising Global Water Networks with DamNet.

   Sanchit Minocha, Pritam Das, and Faisal Hossain

   Dec 2024

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2023

1. waterpower

   A Satellite Remote Sensing Perspective on Water Resources.

   Faisal Hossain, Pritam Das, George Brencher, and 7 more authors

   May 2023

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2022

1. theconversation

   Satellites over the Amazon Capture the Choking of the ‘House of God’ by the Belo Monte Dam – They Can Help Find Solutions, Too

   Pritam Das, Faisal Hossain, Hordur B. Helgason, and 1 more author

   May 2022

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