ABSTRACT:

HydroMET-EO (Hydrologic Model Evaluation Tool - Earth Observation) is the first-of-its-type desktop-based semi-automatic software designed for Soil and Water Assessment Tool (SWAT) hydrologic model. In its current version, HydroMET-EO harmonizes EO datasets of evapotranspiration, Leaf Area Index, and Soil Moisture from varying sources and resolutions to SWAT’s structure and time-step, enabling subbasin-level evaluation of model outputs. Guided by a user-friendly graphical interface with reproducible workflows, statistical metrics, and visual aids, HydroMET-EO streamlines EO integration and thus advances how we typically evaluate the accuracy and physical consistency of hydrologic models and watershed management decisions. Our case studies highlight the tool’s effectiveness, demonstrating that models calibrated solely on streamflow data, despite excellent performance, may fail to capture other critical hydrologic processes.

Here we provide HydroMET-EO software executable, a user guide, and an example SWAT project with pre-processed EO data.

Developed by Linji Wang, Purdue University.

ABSTRACT:

Advances in data availability, Earth observation technologies, and geospatial sciences have transformed our ability to map Global Surface Water Extents (GSWE). However, traditional GSWE mapping has been limited to static estimates, with more recent efforts focusing on annual averages and temporal attributes like frequency and occurrence of long-term variations. We harnessed remotely sensed Sentinel-2 based near real-time Dynamic World land cover product to produce the first public, routinely available 10-meter resolution global surface water datasets. Our key contribution is an Open Science operational framework to rapidly extract the latest available Dynamic World products every 2-5 days, run geospatial analytics, and create actionable water information for educators, researchers, and stakeholders at any scale of practical interest.

This dataset has been developed by the Hydrology & Hydroinformatics Innovation Lab at the University of Texas at Arlington, United States.

ABSTRACT:

Here we present the first-available global dataset that quantifies human alterations in 15 million sq km floodplains along the world’s 520 major river basins. We developed these data using a comprehensive 27-year (1992-2019) analysis of remotely sensed land use change at 250-m resolution. This new dataset reveals that the world has lost ~600,000 sq km floodplains in 27 years (1992-2019), moving from natural forest, grassland, and wetland conditions to 460,000 sq km of new agricultural and 140,000 sq km of new developed areas.

To ensure the maximum reuse of this dataset, we also developed three web-based semi-automatic programming tools partly supported with data-driven tutorials and step-by-step audiovisual instructions.

(1) Floodplain Mapping Tool
- Web-based Python code that runs in any internet browser using Google's high performance computing resource: https://colab.research.google.com/drive/1xQlARZXKPexmDInYV-EMoJ-HZxmFL-eW?usp=sharing
- A tutorial developed and published through an online data-driven geoscience education platform: https://serc.carleton.edu/hydromodules/steps/246320.html
- A YouTube video with step-by-step instructions: https://youtu.be/TgMbkJdALig

(2) Land Use Change Tool
- Web-based Python code that runs in any internet browser using Google's high performance computing resource: https://colab.research.google.com/drive/1vmIaUCkL66CoTv4rNRIWpJXYXp4TlAKd?usp=sharing
- A tutorial developed and published through an online data-driven geoscience education platform: https://serc.carleton.edu/hydromodules/steps/241489.html
- A YouTube video with step-by-step instructions: https://youtu.be/wH0gif_y15A

(3) Human Alteration Tool
- Web-based Python code that runs in any internet browser using Google's high performance computing resource: https://colab.research.google.com/drive/1r2zNJNpd3aWSuDV2Kc792qSEjvDbFtBy?usp=sharing

Note, the floodplain dataset used in this analysis (GFPLAIN250m; Nardi et al., 2019) does not cover deserts and ice-covered regions. Hence, places like northern Africa, Persian Gulf, Tibetan plateau, and the region above 60 degrees north latitude are not included in this analysis.

This global floodplain alteration dataset is built off our recent work published in the Nature Scientific Data: Rajib et al. (2021). The changing face of floodplains in the Mississippi River Basin detected by a 60-year land use change dataset. https://doi.org/10.1038/s41597-021-01048-w

ABSTRACT:

This work has been published in the Nature Scientific Data. Suggested citation:
Rajib et al. The changing face of floodplains in the Mississippi River Basin detected by a 60-year land use change dataset. Nature Scientific Data 8, 271 (2021). https://doi.org/10.1038/s41597-021-01048-w

Here, we present the first-available dataset that quantifies land use change along the floodplains of the Mississippi River Basin (MRB) covering 60 years (1941-2000) at 250-m resolution. The MRB is the fourth largest river basin in the world (3.3 million sq km) comprising 41% of the United States and draining into the Gulf of Mexico, an area with an annually expanding and contracting hypoxic zone resulting from basin-wide over-enrichment of nutrients. The basin represents one of the most engineered systems in the world, and includes complex web of dams, levees, floodplains, and dikes. This new dataset reveals the heterogenous spatial extent of land use transformations in MRB floodplains. The domination transition of floodplains has been from natural ecosystems (e.g. wetlands or forests) to agricultural use. A steady increase in developed land use within the MRB floodplains was also evident.

To maximize the reuse of this dataset, our contributions also include four unique products:
(i) a Google Earth Engine interactive map visualization interface: https://gishub.org/mrb-floodplain
(ii) a Google-based Python code that runs in any internet browser: https://colab.research.google.com/drive/1vmIaUCkL66CoTv4rNRIWpJXYXp4TlAKd?usp=sharing
(iii) an online tutorial with visualizations facilitating classroom application of the code: https://serc.carleton.edu/hydromodules/steps/241489.html
(iv) an instructional video showing how to run the code and partially reproduce the floodplain land use change dataset: https://youtu.be/wH0gif_y15A