Sciences and Exploration Directorate

Nishan Kumar Biswas

(Associate Scientist, Earth Sciences)

 n.biswas@nasa.gov

Org Code: 617

NASA/GSFC
Mail Code: 617
Greenbelt, MD 20771

Employer: UNIVERSITY OF MARYLAND BALTIMORE CO

Brief Bio


Hi, this is Nishan Kumar Biswas, a Bangladeshi by origin. I have been working with the Landslides Team and EIS Team in the Hydrological Research Laboratory of NASA Goddard Space Flight Center since February 2021. My research is focused on applying satellite remote sensing observations in water resources and hydro-climatic disaster management. I did my MS and PhD from the University of Washington (Seattle, WA, USA) and BSc from Bangladesh University of Engineering and Technology (Dhaka, Bangladesh). I am passionate about the overlapping areas of Machine learning, Cloud Computing, and Interactive and dynamic hydrologic application design and development.

Research Interests


Remote Sensing Application in water resources and hydroclimatic disaster management

Earth Science: Hydrology / Water Cycle

  • Hydrometeorological application of satellite remote sensing
  • Hydroclimatic disaster monitoring and forecasting
  • Cloud computing and data science application in hydrology


Cloud computing and geospatial analysis

Earth Science: Applications


Flood monitoring, forecasting assisted by satellite remote sensing and modelling efforts

Earth Science: Floods


Global/continental scale landslide modelling using AI?ML

Earth Science: Landslides

Current Projects


Landslide Hazard and Risk Assessment System in Lower Mekong Region

Applications

Leading the development of Google Cloud Platform based Landslide Hazard Assessment model for Situational Awareness (LHASA) for the Lower Mekong Region of South-East Asia. Providing training and building capacity of the stakeholder agencies on modern practices in landslide hazard monitoring and management using advanced information technology cloud computing. Working on migrating landslide hazard monitoring system to the advanced computational IT infrastructure (i.e. Google Earth Engine, Google Cloud Platform).


EIS Freshwater flooding impact quantification

Hydrology / Water Cycle

Team-member of NASA EIS open-science initiative, co-leading quantification of hydrological changes in coastal regions of the world due to climate change and human activities in Bengal Delta.


IDEAS Earth System Digital Twin

Hydrology / Water Cycle

Land Information System (LIS) team member of NASA Integrated Digital Earth Analysis System (IDEAS), an Earth System Digital Twin Architecture funded from Advanced Information Systems Technology program of NASA’s Earth Science Technology Office.

Positions/Employment


Associate Scientist

NASA GSFC/UMBC - Greenbelt, MD

February 2021 - Present

1) Lead developer of Machine Learning based Landslide Hazard Assessment model for Situational Awareness (LHASA) for the Lower Mekong Region of South-East Asia using Google Cloud Platform(GCP). Also, led the initiative to migrate landslide global hazard monitoring systems to the open-source cloud computing frameworks. Has been providing training to the Lower Mekong region agencies to enhance their understanding and capability to use NASA earth observation datasets and models for the decision support and policy analysis.

2) Team-member of NASA EIS open-science initiative, co-leading quantification of hydrological changes in coastal regions of the world due to climate change and human activities in Bengal Delta.

3) Land Information System (LIS) team member of NASA Integrated Digital Earth Analysis System (IDEAS), an Earth System Digital Twin Architecture funded from Advanced Information Systems Technology program of NASA’s Earth Science Technology Office. 


Graduate Research Assistant

University of Washington - Seattle, WA, USA

December 2015 - February 2021

  • A Global Reservoir Assessment Tool (RAT) was developed to monitor the operating pattern of 1600 reservoirs solely based on satellite observations, which showed an accuracy of more than 75%.
  • A Dynamic River Width based Altimeter Height Visualizer was developed to generate near-real-time river stages of 210 virtual stations over South and South-East Asia.
  • A skillful and computationally efficient flash flood forecasting system developed for the northeastern region of Bangladesh which has been used operationally to minimize flood risk and damage.
  • World’s first operational transboundary reservoir monitoring system was developed for Mekong and Red River Basins to monitor upstream dams using EO data with a promising accuracy.
  • A web analytics based real-time correction system was implemented for satellite based precipitation over the South and South-East Asia river basins which showed a significant improvement in prediction.
  • A scalable and operational web interface South Asian Surface Water Modelling System was developed which connects complex back-end models with user-friendly front-end.


Junior Engineer

Institute of Water Modelling - Dhaka, Bangladesh

August 2013 - December 2015

  • A vertically integrated and automated system were designed, developed and implemented for an operational flood prediction and inundation mapping for 160 million people of Bangladesh.
  • More than 6 hydrological-hydrodynamic models were developed, calibrated and validated using state of the art tools and software for river stage and flow prediction and water resources management.

Professional Societies


American Geophysics Union

Member

2021 - Present

Awards


NASA HBG Annual Peer Award for Science/Technical support, 2022

NASA SWOT Early Adopter Virtual Hackathon certificate of appreciation, 2020

Bangladesh Water Development Board appreciation award for flash flood forecasting, 2020

University of Washington student film contest on public messaging and engagement award, 2019

University of Washington Ivanhoe Fellowship, 2015; 2016

Publications


Refereed

Biswas, N. K., T. A. Stanley, D. B. Kirschbaum, et al. P. M. Amatya, C. Meechaiya, A. Poortinga, and P. Towashiraporn. 2022. A dynamic landslide hazard monitoring framework for the Lower Mekong Region Frontiers in Earth Science 10 [10.3389/feart.2022.1057796]

Getirana, A., N. K. Biswas, A. S. Qureshi, et al. A. Rajib, S. Kumar, M. Rahman, and R. K. Biswas. 2022. Avert Bangladesh’s looming water crisis through open science and better data Nature 610 (7933): 626-629 [10.1038/d41586-022-03373-5]

Biswas, N., and F. Hossain. 2022. A Multidecadal Analysis of Reservoir Storage Change in Developing Regions Journal of Hydrometeorology 23 (1): 71-85 [10.1175/JHM-D-21-0053.1]

Bose, I., S. Jayasinghe, C. Meechaiya, et al. S. K. Ahmad, N. Biswas, and F. Hossain. 2021. Developing a Baseline Characterization of River Bathymetry and Time-Varying Height for Chindwin River in Myanmar Using SRTM and Landsat Data Journal of Hydrologic Engineering 26 (11): 05021030 [10.1061/(asce)he.1943-5584.0002126]

Biswas, N. K., F. Hossain, M. Bonnema, H. Lee, and F. Chishtie. 2021. Towards a global Reservoir Assessment Tool for predicting hydrologic impacts and operating patterns of existing and planned reservoirs Environmental Modelling & Software 140 105043 [10.1016/j.envsoft.2021.105043]

Bose, I., F. Hossain, H. Eldardiry, et al. S. Ahmad, N. K. Biswas, A. Z. Bhatti, H. Lee, M. Aziz, and M. S. Kamal Khan. 2021. Integrating Gravimetry Data With Thermal Infra‐Red Data From Satellites to Improve Efficiency of Operational Irrigation Advisory in South Asia Water Resources Research 57 (4): [10.1029/2020wr028654]

Biswas, N. K., F. Hossain, M. Bonnema, et al. A. M. Aminul Haque, R. K. Biswas, A. Bhuyan, and A. Hossain. 2020. A computationally efficient flash flood early warning system for a mountainous and transboundary river basin in Bangladesh Journal of Hydroinformatics 22 (6): 1672-1692 [10.2166/hydro.2020.202]

Bhuiyan, M. A., F. Yang, N. K. Biswas, S. H. Rahat, and T. J. Neelam. 2020. Machine Learning-Based Error Modeling to Improve GPM IMERG Precipitation Product over the Brahmaputra River Basin Forecasting 2 (3): 248-266 [10.3390/forecast2030014]

Hossain, F., M. Bonnema, N. Biswas, et al. S. Ahmad, B. Duong, and N. Luong. 2019. When Floods Cross Borders, Satellite Data Can Help Eos 100 [10.1029/2019eo115775]

Biswas, N. K., F. Hossain, M. Bonnema, M. A. Okeowo, and H. Lee. 2019. An altimeter height extraction technique for dynamically changing rivers of South and South-East Asia Remote Sensing of Environment 221 24-37 [10.1016/j.rse.2018.10.033]

Biswas, N. K., and F. Hossain. 2017. A scalable open-source web-analytic framework to improve satellite-based operational water management in developing countries Journal of Hydroinformatics 20 (1): 49-68 [10.2166/hydro.2017.073]

Hossain, F., S. Sikder, N. Biswas, et al. M. Bonnema, H. Lee, N. Luong, N. Hiep, B. Du Duong, and D. Long. 2017. Predicting Water Availability of the Regulated Mekong River Basin Using Satellite Observations and a Physical Model Asian Journal of Water, Environment and Pollution 14 (3): 39-48 [10.3233/ajw-170024]

Talks, Presentations and Posters


Other

Understanding the stresses on freshwater resources in Ganges Delta due to climate change and human impact using satellite observations

February 6, 2023

Bangladesh, a developing country striving to become a food-sufficient nation, is dealing with the demands of a population of more than 160 million people. To ensure optimized food production, the country has expanded the agricultural land to a great extent and increased the cropping frequency in recent decades. When the cropping frequency increased, the dry season crops depend on groundwater resources for the irrigation due to surface water scarcity. In this study, we characterize the agricultural expansion and its impacts on water resources using satellite and in situ datasets. The expansion of the cropland was quantified using the NASA MODIS satellite provided annual land cover dataset. From the in-situ groundwater table data, the trend was analyzed to identify the region of the country with the most negative trend. MODIS satellite provided Leaf Area Index (LAI) data was used to see the increasing trend in agricultural activity and a match was found with the groundwater table data trend. Using the NASA MODIS satellite provided evapotranspiration data, an increasing trend found in the region with dry season agriculture, which can be explained by the flooding irrigation practices. The GRACE satellite provided terrestrial water storage (TWS) data, which was used to quantify the impact of groundwater depletion on the TWS availability. The decreasing trend in precipitation over the country was also seen from the NASA GPM satellite. It was found that the decreasing trend in precipitation with the depletion of groundwater has already put an enormous stress on the water resources in the region which has impact on the drinking water availability, groundwater contamination, and saltwater intrusion. This study sheds light on the understudied relationship between the different phenomena including season shifting, which will be useful in terms of identification of the water-stressed region, and future policy decisions.