A New Generation of Hydrological Condition Simulator Employing Physical Models and Satellite-Based Meteorological Data

Abstract

Determining the distribution and dynamics of water on land at any given moment poses a significant challenge due to the constraints of observation. Consequently, as advancements in land surface models (LSMs) have been made, numerical simulation has emerged as an increasingly accurate and effective method for hydrological research. Nonetheless, systems that represent multiple land surface parameters in a near-real-time manner are scarce. In this study, we present an innovative land surface and river simulation system, termed Today's Earth (TE), which generates state and flux values for the near-surface environment with multiple outputs in near-real-time. There are currently three versions of TE, distinguished by the forcing data utilized: JRA-55 version, employing the Japanese 55-year Reanalysis (JRA-55, from 1958 to the present); GSMaP version, utilizing, the Global Satellite Mapping of Precipitation (GSMaP, from 2001 to the present), and MODIS version, utilizing the Moderate Resolution Imaging Spectroradiometer (MODIS, from 2003 to the present). These long-term forcing data set allow for outputs of the JRA-55 version from 1958, the GSMaP version from 2001, and the MODIS version from 2003. Aiming to provide water and energy values on a global scale in real-time, the TE system utilizes the LSM Minimal Advanced Treatments of Surface Interaction and Runoff (MATSIRO) (Takata et al., 2003, https://doi.org/10.1016/s0921-8181(03)00030-4; Yamazaki et al., 2011, https://doi.org/10.1029/2010wr009726) at a horizontal resolution of 0.5°, along with the river routing model CaMa-Flood (Yamazaki et al., 2011, https://doi.org/10.1029/2010wr009726) at a horizontal resolution of 0.25°. Both land surface and river products are available in 3-hourly, daily, and monthly intervals across all three versions. A notable feature of TE is its ability to release both state and flux parameters in near-real-time, offering convenience for various aspects of hydrological research. In addition to presenting the general features of TE-Global, this study examines the performance of snow depth, soil moisture, and river discharge data in daily intervals from 2003 to 2021, with validation spanning 2003 to 2016. When comparing snow depth results, the correlation coefficient ranged between 0.644 and 0.658, while for soil moisture it ranged between 0.471 and 0.494. These findings suggest that the LSM yields comparable results when utilizing JRA-55, MODIS, or GSMaP. Interestingly, river output from the three products exhibited distinct characteristics varying from GSMaP to JRA-55 and MODIS. For river discharge, the correlation coefficient ranged from 0.494 to 0.519, the root mean square error ranged from 3,730 m³/s to 6,330 m³/s, and the mean absolute error ranged from 3,000 m³/s to 5,160 m³/s among the different forcing versions. The overall bias in river discharge from GSMaP was 1,570 m³/s, in contrast to −589 m³/s for JRA-55 and −200 m³/s for MODIS. These metrics demonstrate that the TE system is capable of generating practical land surface and river products, highlighting differences arising from the use of various types of forcing data. This comprehensive system would be valuable for monitoring water-related movements, predicting disasters, and contributing to sophisticated water resource management. Regarding its application, the TE system has been included in the World Meteorological Organization as a Global Hydrological Modelling System. All TE-Global products can be freely accessed through File Transfer Protocol.