From catchment to global scale; towards hyperresolution modeling?
In this Post we want to share with the hydrological and meteorological community, the brilliant Keynote of Professor Eric F. Wood (Department of Civil and Environmental Engineering, Princeton University. Princeton NJ 08544 USA) that performed in the International Symposium on Distributed Hydrological Modelling. University of Bologna To mark the 70th birthday of Prof. Ezio Todini (5-7 June 2013).
This presentation was very important to us for the discussion of ideas and the subsequent foundation of the Non Profit Project: GH2MF2 – Association for a Participated Global Hydrological Monitoring and Flood Forecasting System. From here we want to thank Prof. Wood for his Keynote:
KEYNOTE Session IV: From catchment to global scale; towards hyperresolution modeling?
Continental-scale ‘hyper-resolution’ land surface modelling: Challenges and initial results.
By Eric F Wood (firstname.lastname@example.org)
Land surface models have their roots in numerical weather prediction and global circulation models. As a result, they emphasize simulating the land surface water and energy fluxes while oversimplifying the hydrology. This limits their usefulness for fine scale processes related to water management, floods, water quality, land-use effects, among others. Advances in data availability and computation have led the community to pose the grand challenge of creating global scale land surface models that can better capture high resolution hydrologic and landscape processes so as to improve their predictive ability at landscape scales (Wood et al. 2011).
In this presentation, we will discuss three challenges that need to be addressed in reaching this goal.
1. Computation: Future models must be highly parallelizable, allow for nested gridding, and take advantage of object-oriented programming. These would best be implemented with open source collaboration.
2. Data: To harness current and future high-resolution input data sets, data assimilation and ensemble frameworks should be used to account for uncertainties in the model parameters and input data.
3. Physics: Many underlying, local scale physical processes are still poorly understood and require improved parameterizations. This includes preferential flow paths, urban hydrology, landscape heterogeneity, and land-atmosphere interactions.
A convergence of broad research results is needed to bring the developments together into new parameterizations.Finally, we will illustrate the capabilities of current high-resolution hydrologic models by running the updated TOPLATS model (Pauwels and Wood, 2009; over the continental United States at a 15 arc sec (~500m) spatial resolution.The model is run with a suite of state of the art high resolution meteorological and land surface data sets. The results will be compared to coarser scale simulations using the VIC model to assess the potential for improved fine scale and up-scaled monitoring of the global hydrologic cycle. We will discuss the feasibility and steps necessary to apply this framework globally
- Famiglietti, J.S. and E.F. Wood, (1994) Multi-Scale Modeling of Spatially- Variable Water and Energy Balance Processes, Water Resources Research, 30 (11), 3061-3078.
- Pauwels, V.R.N., and E.F. Wood, (1999) A soil-vegetation-atmosphere transfer scheme for the modeling of water and energy balance processes in high latitudes. 1. Model improvements, J Geophysical Research, 104(D22) 27811-27822.
- Wood, E. F., and Coauthors, (2011) Hyperresolution global land surface modeling: Meeting a grand challenge for monitoring Earth’s terrestrialwater. Water Resources Research, 47, W05301.