UFPE

1. Modelling the hydrological processes and impacts of climate and land use changes on water resources in a northern Brazilian catchmentSuzana MontenegroFederal University of Pernambuco (UFPE), Brazil UFPE

2. Objectives • (1) to calibrate and validate the DiCaSM distributed model using stream flow measurements for a Brazilian tropical catchment; • (2) to further test the performance of the model against observed soil moisture data; • (3) to simulate the catchment hydrologic responses to different climate change scenarios; and • (4) to simulate the impact of land use change in the catchment on the water balance components.

3. SUMMARY • Model description 2. Area description and data 3. Calibration and validation 4. Climate change impacts 5. Land use change impacts

4. IHMS The Integrated Hydrological Modeling System (R. Ragab) The IHMS was designed for catchment scale to answer the following questions: • How Land use changes affect the hydrological cycle (evaporation, runoff, Stream flows, drainage flow, groundwater recharge, soil moisture,….etc. • How the possible future climate change will affect the hydrological cycle and land use. • How the sea water intrusion will be affected by changes in land use, ground water abstraction and climate in coastal regions. • How the possible future climate change will affect the land use, future balance between supply & demand and the length of crop growth season (sowing and harvest dates)

5. Click here to run DiCaSM Click here to run MODFLOW Click here to run SWI

6. The New Integrated Hydrological modeling System, IHMS • The System comprises three packages: DiCaSM, MODFLOW and SWI models. The Distributed Catchment scale model DiCaSM, produces the different components of the water balance.

7. 1- The DiCaSM model DiCaSM (Distributed Catchment Scale Model) has been developed to estimate water balance parameters and to account for the impact of possible future climate and land use changes on water flows.

8. The“DiCaSM”model characteristics • Physically based • Distributed approach • Variable spatial scale (default is 1km grid squares = REA) • Temporal scale: daily (one day time step) • Addresses the heterogeneity of input parameters at grid square level: • Above-surface plant parameters scheme (for evaporation) • Sub-surface plant parameters scheme ( for water uptake) • Sub-surface soil parameters scheme

9. Equations incorporated in DiCaSM model • Rainfall interception by Trees (Gash model, Gash,1995) and by • grass and crops (Aston, 1979; Von Hoyningen – Huene, 1981). • Infiltration by Philip equation (1957) and Green – Ampt • equation (1911). • Overland flow and channel flow routing by Yu and Jeng (1997). • Soil hydraulic properties by Rawls and Brakensiek (1989) • Evapotranspiration by Raupach (1995)

10. DiCaSM model Input data

11. DiCaSM model grid data

12. DiCaSM model data –climate change scenarios

13. DiCaSM model data –parameters

14. DiCaSM model possible outputs

15. DiCaSM model calibration /optimization for stream flow

16. Land use DiCaSM supports up to 20 different land covers per grid square

17. DiCaSM output

18. DiCaSM calculates the stream location and the flows: The Pang Catchment, UK

19. DiCaSM calculates the stream flow: The Pang Catchment, UK

20. Study site –Tapacura catchmentNortheast Brazil AREA=470.5 km2

21. Experimental basin- Brazilian semi- arid network EXPERIMENTAL BASINS: Serra Negra- UFRN Gameleira- UFPE Cariri- UFCG Jatobá- UFRPE Guaraíra- UFPB Jacuípe- UFBA Aiuaba- UFC

23. 1 km2 cells DEM LAND USE

25. Results of DiCaSM for Tapacura catchment CALIBRATION

26. VALIDATION

27. Table 7 . Performance criteria for DiCaSM model calibration and validation in Tapacurá catchment on stream flow. Period Simulation Nash - Determination Maximum observed daily 3 - 1 process Sutcliffe coefficient stream flow (m .sec ) 2 E ff iciency (R ) F actor 18/07 - 24/07 Calibration 93.99 0.9 7 203 (1970) 09/08 - 14/08 Validation 9 3.50 0.9 5 124 (1970) 20/06 - 30/06 Validation 64.58 0.9 0 144 (2000) 24/06 - 30/06 Validation 79.82 0. 83 30.93 (2004) 20/08 - 01/09 Validation 86.84 0.8 0 74 (2005) 01/01 - 31/12 Calibration 87.89 0. 88 203 (1970) 01/01 - 30/11 (1970) Validation 84.76 0. 87 350 SS2 01/01 - 31/10 Validation 54.73 0. 62 211 (2000) 01/01 - 31/12 * Validation 62.56 0. 64 132.8 (2005) R2=0.77 R2=0.67

28. SENSITIVITY ANALYSIS VARIATION IN THE CALIBRATION PARAMETERS: -60%, -40%, -20%, +20%, +40%, +60%

29. IMPACT OF FUTURE CLIMATE CHANGE Variation in temperature (T 0C) and rainfall (P %) for the simulations of climate change scenarios (CEH, 2008). 18 GCM 3 EMISSION SCENARIOS

30. BASELINE PERIOD: 2004-2007 CSMK3 B1 EMISSION SCENARIO (low emission) % 2010-2039 2040-2069 2070-2099

31. MPEH5 A2 EMISSION SCENARIO (high emission) 2010-2039 2040-2069 2070-2099

32. IMPACT OF FUTURE LAND USE CHANGE LUC1: ARABLE LAND FORESTLAND (reforestation) (increase 840 ha) LUC2: VEGETABLESSUGAR CANE (ETHANOL production) From 6,500 ha to 25,400 ha

33. FUTURE INVESTIGATIONS • Reforestation of part of the catchment area, by replacing current use, would produce decrease in both recharge and stream flow. Increasing sugar cane area by replacing current crops would not result in decrease of stream water availability, although groundwater recharge is decreased. FURTHER ANALYSIS IS NEEDED. • Simulate other scenarios of land use change and possible mitigation strategies • Investigate the uncertainty in climate change scenarios and models propose adaptation strategies

34. THANK YOU suzanam@ufpe.br Acknowledgements The first author would like to acknowledge the support of the Centre for Ecology and Hydrology, CEH-Wallingford, UK as a host for her Post Doctoral Research work and CNPq (Brazil) for the Post Doctoral Research grant.