Hydrology and Regional Modeling

1. Hydrology and RegionalModeling Marcio Moraes and Cintia Bertacchi Lund University Water Resources Engineering

2. Impact of changes in the biosphere to local climate and hydrology - How biofuel plantations affect local atmospheric circulation and rivers The major scientific objective of this proposal is to create a model system able to simulate the effects caused by the biosphere on the local/regional atmosphere and hydrology. the final objective of the project is the assessment of the impacts of the expansion of the plantation of biofuel species, in substitution to the native vegetation or to the prior customary crops, to the local climate and hydrology Project Subject

3. (1) adaptation and adjusting of a hydrological model to a characteristic river basin where sugar-cane plantation has been expanding significantly. (2) Analyse the capacity of a regional atmospheric model to simulate local climate in the same region as in (1). (3) Develop a two-way coupling of the atmospheric and hydrological models. (4) Carry out experiments designed to analyse the impacts of the change in vegetation on the river basin and how these impacts will, on their hand, affect the local climate and, (5) finally, significantly improve the knowledge, and hopefully be able to quantify the impacts of the biofuel plantation on the local hydrology and climate The aim of this project

4. Atmospheric Brazilian Regional Atmospherical Model System – BRAMS Modified version of RAMS (Walko et al 2000) Large use in the Brazilian Forcast Institute – INPE/CPTEC Hydrological Large Basin Model – Hydraulic Research Institute (MGB-IPH) Applied in various brazilian basins The chosen Models

5. MGB-IPH Divide th basin in cells or mini-basins, about 10x10 Km. Daily time step or small one. Represents the variability in the cells. Developed to big basins, > 104 Km2

6. Process in the model Evapotranspiration Water storage in the soil Drainage in the cells Rivers and dams flow MGB-IPH

7. Input data Precipitation and flow Temperature, pressure, solar radiation, relative humidity and wind velocity Satelite images Soil types Digital Elevation Model Transversal section of the rivers MGB-IPH

8. BRAMS Braziliam Regional Atmospheric Model System – BRAMS Based on RAMS (Walko et al. 2000) – version 6 RAMS is a multipurpose, numerical prediction model designed to simulate atmospheric circulations spanning from hemispheric scales down to large eddy simulations (LES) of the planetary boundary layer (Walko et al., 2000, www.atmet.com) The model is equipped with a multiple grid nesting scheme which allows the model equations to be solved simultaneously on any number of interacting computational meshes of differing spatial resolution

9. The model has a complex set of packages to simulate processes such as radiative transfer, surface-air water, heat and momentum exchanges, turbulent planetary boundary layer transport, and cloud microphysics. The initial conditions can be defined from various observational data sets that can be combined and processed with a mesoscale isentropic data analysis package (Tremback, 1990). For the boundary conditions, the 4DDA schemes allow the atmospheric fields to be nudged towards the large-scale data. BRAMS features used in this system include an ensemble version of a deep and shallow cumulus scheme based on the mass flux approach (Grell and Devenyi, 2002) and soil moisture initialization data (Gevaerd and Freitas, 2006). BRAMS

10. parameterizations are used in the model: The horizontal diffusion coefficients are based on the Smagorinsky (1963) formulation. The vertical diffusion is parameterized according to the Mellor and Yamada (1974) scheme, which employs a prognostic of the turbulent kinetic energy. The surface-atmosphere water, momentum and energy exchanges are simulated by the Land Ecosystem Atmosphere Feedback model (LEAF-3), which represents the storage and vertical exchange of water and energy in multiple soil layers, including the effects of freezing and thawing soil, temporary surface water or snow cover, vegetation, and canopy air (Walko et al., 2000). The advection scheme is forward upstream of second-order (Tremback et al, (1987)). Bulk microphysics (Walko et al., 2000) Convective cumulus scheme for deep and shallow convection based on Grell and Devenyi (2002). The 4D Data Assimilation (4DDA), a nudging type scheme in which the model fields can be nudged toward assimilated observational data. BRAMS

11. LEAF-3 vertical levels and patches SINGLE ATMOSPHERIC COLUMN NZS = 3 NZG = 7 Canopy air Vegetation Snowcover Water Soil NPATCH=5: P1 P2 P3 P4 P5

12. A wav hav was has wca hca wca hca hvc hvc wvc wvc rvc rav C V V wvs hvs LEAF–3 fluxes C rsv wsc hsc rsa S2 S1 wss hss longwave radiation sensible heat water rga wgvc2 rgv wgc hgc G2 wgs hgs wgvc2 G2 wgvc1 wgvc1 wgg hgg wgg G1 hgg G1 PATCH 1 PATCH 2

13. Two way coupling of a conceptual hydrological model to a regional atmospheric model • The Coupling process • The region of study: • Rio Grande Basin: Brazil – South America

14. LEAF to hydrological scheme

16. Firts Results BRAMS MGB-BRAMS

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31. Tusen Takk