Despite the significant potential of remotely sensed earth observations, their application is still not full-fledged in water resources research, management and education. Inconsistent storage structures, data formats and spatial resolution among different platforms/sources of earth observations hinder the use of these data. Available web-services can help bulk data downloading and visualization, but they are not sufficiently tailored to meet the degree of interoperability required for direct application of earth observations in hydrologic modeling at user-defined spatio-temporal scales (e.g. Rajib et al., 2016a; Lin et al., 2017). Similarly, the least ambiguous way for educators and watershed managers is to instantaneously obtain a time-series at any watershed of interest without spending time and computational resources on data download and post-processing activities. To address this issue, an open access, online platform, named HydroGlobe, is developed that minimizes all these processing tasks and delivers ready-to-use data from different earth observation sources. HydroGlobe can provide spatially-averaged time series of earth observations by using the following inputs: (i) data source, (ii) temporal extent in the form of start/end date, and (iii) geographic units (e.g., grid cell or sub-basin boundary) and extent in the form of GIS shapefile. Currently, HydroGlobe handles multiple data sources including the surface and root zone soil moisture from SMAP (Soil Moisture Active Passive Mission), actual and potential evapotranspiration as well as Leaf Area Index from MODIS (Moderate Resolution Imaging Spectroradiometer), and precipitation from GPM (Global Precipitation Measurements). HydroGlobe is capable of cross-platform interoperability including those with SWATShare (Rajib et al., 2016b) and HydroShare.

Lin, P., A. Rajib, Z-L. Yang, M. Somos-Valenzuela, V. Merwade, D. Maidment, Y. Wang, L. Chen (2017), Spatio-temporal evaluation of simulated evapotranspiration and streamflow over Texas using the WRF-Hydro-RAPID modeling framework, Journal of the American Water Resources Association (in press)

Rajib, M.A., V. Merwade, and Z. Yu (2016a), Multi-objective calibration of a hydrologic model using spatially distributed remotely sensed/in-situ soil moisture, J. Hydrol., 536, 192-207.

Rajib, M.A., V. Merwade, I L. Kim, L. Zhao, C. Song, and S. Zhe (2016b), SWATShare – A web platform for collaborative research and education through online sharing, simulation and visualization of SWAT models, Environ. Model. Softw., 75, 498–512, doi:10.1016/j.envsoft.2015.10.032.

Rajib, A., V. Merwade, J. Shin, L. Zhao, J. Smith, C. Song (2017). HydroGlobe - A cyber-enabled platform for auto-extraction and processing of earth observations for hydrologic analysis. Accessible online at: Data tool accessible at https://mygeohub.org/tools/hydroglobetool

Researchers should cite this work as follows:

• Adnan Rajib; I Luk Kim; Jaewoo Shin; Venkatesh Merwade; Lan Zhao; Jack A Smith; Carol Song (2022), "Hydroglobe Tool," https://mygeohub.org/resources/hydroglobetool.

  BibTex | EndNote

1. HydroGlobe
2. tool:hydroglobetool