EGU2020-2766, updated on 12 Jun 2020
EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Application of hyper-resolution hydrological modeling for water resources decision making

Eric Wood1,2, Noemi Vergopolan1, Peirong Lin1, and Ming Pan1,2
Eric Wood et al.
  • 1Princeton University, Civil and Environmental Engineering, Princeton, NJ, United States of America (
  • 2Princeton Climate Analytics, 134 Nassau Street, Princeton, NJ, United States of America

Managing water resources and basin reclamation requires hydrological data across a set of scales.  Unfortunately, in many areas the in-situ data is sparse, or not made available to water managers.  With NASA, ESA and Chinese satellites, their data can potentially be merged with in-situ gauge data.  Doing so results in a number of research challenges: 1. Satellite data based on microwave sensors (e.g. L-band sensors from SMAP or SMOS) results in coarse resolution (~35-50 km) making the data difficult for management; (ii) Satellite data from instruments like LandSat (~90m) suffers from cloud contamination.  New satellites improve resolution but still suffer cloud contamination; (iii) Precipitation (along with radiation) falls between these two spectrums, and its fast dynamics can impact water management decision making; (iv) Topographic and soil characteristics, which govern the runoff from the land to rivers; and (v) river flows that are a water source for drought and a site for reservoirs.

In this talk I will present a new land surface model (HydroBlocks) that we run at a 30m resolution at regional to continental scales.  The water is transmitted to hyper-resolution streams for which we have extracted ~2,900,000 reaches.  Visualization of the models will offer the listener the impact of moving to these scales; and the data needed for water resources management of river basins.

How to cite: Wood, E., Vergopolan, N., Lin, P., and Pan, M.: Application of hyper-resolution hydrological modeling for water resources decision making, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2766,, 2020