Detailed spatial analysis of the plausibility of surface runoff and sediment yields at HRU level in a mountainous watershed in China

Transcription

1 Christian-Albrechts-Universität zu Kiel Institut für Natur- und Ressourcenschutz Detailed spatial analysis of the plausibility of surface runoff and sediment yields at HRU level in a mountainous watershed in China K. Bieger, G. Hörmann & N. Fohrer 2013 International SWAT Conference, Toulouse, France July 19, 2013

2 Impacts of the Three Gorges Dam Construction of the Three Gorges Dam Higher risk of eutrophication Reduced flow velocities Land use change X. Jiang 2007 Increase in erosion and landslides Increasing diffuse inputs S. Schönbrodt 2010 D. Ehret 2010 Department of Hydrology and Water Resources Management Bieger et al. -2-

3 YANGTZE-GEO Land use change, erosion, mass movements and diffuse matter inputs in the Three Gorges Region Coordination: Research Centre Jülich Remote Sensing Potsdam Land use change Giessen Erosion Tübingen Landslides Erlangen Diffuse sediment and P inputs Kiel Assessment of mass movements using remote sensing techniques Classification of land use and assessment of vulnerability Assessment and analysis of soil erosion Assessment and analysis of landslides Analysis of sediment and phosphorus inputs to rivers using SWAT Aim: Analysis of land use change and vulnerability, risk assessment of mass movements, soil erosion and diffuse inputs to rivers Department of Hydrology and Water Resources Management Bieger et al. -3-

4 Study area: Xiangxi Catchment Catchment area: 3200 km 2 Length of Xiangxi River: 94 km Mean annual temperature: 16,9 C Mean annual precipitation: 1000 mm Mean discharge at gage: 36,4 m 3 /s Steep slopes: average 24, maximum 76 Department of Hydrology and Water Resources Management Bieger et al. -4-

5 Observed and simulated streamflow NSE: 0,69 R 2 : 0,70 PBIAS: -5,77 Department of Hydrology and Water Resources Management Bieger et al. -5-

6 Observed and simulated sediment loads NSE: 0,47 R 2 : 0,76 NSE: 0,08 R 2 : 0,15 Department of Hydrology and Water Resources Management Bieger et al. -6-

7 Analysis of output at HRU level More precise targeting of Best Management Practices Plausibility check for spatial variability of processes within the watershed based on expert knowledge Surface runoff and sediment yield forest < orange orchard < cropland Yellowbrown soil (sandy) < Limestone soil (clayey) slope class 1 (<15 ) < 2 (15-25 ) < 3 (25-35 ) < 4 (35-45 ) < 5 (>45 ) Department of Hydrology and Water Resources Management Bieger et al. -7-

8 Surface runoff at HRU level Average Correlation Small-scale annual of variation surface of runoff: slopes and hampers Limestone precipitation: spatial Forest: analysis soil 0.79 (clayey): mm Yellowbrown Orchard: soil (sandy): mm Arable land: 549 mm Department of Hydrology and Water Resources Management Bieger et al. -8-

9 Surface runoff and slope gradient Problems with steep slopes in SWAT 1. Modification of equations for calculating surface runoff and lateral flow (Modifications A and B) 2. Recalibration of slope length and daily curve number calculation method (Modifications C and D) Department of Hydrology and Water Resources Management Bieger et al. -9-

10 A: Slope adjustment of CN values Original equation: Modified equation: CN = CN CN 1 2 exp slp+cn s CN 3 CN slp CN 2s = CN 2 Department of Hydrology and Water Resources Management Bieger et al. -10-

11 B: Equation for lateral flow estimation Q v lat lat 2 SW = = K sat hill ly,excess d K L hill sat slp sin α slp ) tan( hill Department of Hydrology and Water Resources Management Bieger et al. -11-

12 C: Recalibration of average slope length Q lat = SW ly,excess d K L hill sat slp Increase in slp Increase in Q lat Decrease of soil moisture Decrease of Q surf Increase of L hill necessary Department of Hydrology and Water Resources Management Bieger et al. -12-

13 D: Daily variation of CN values Soil moisture method: S = S max 1 SW SW + exp w w 1 2 SW Plant ET method: S = S prev + ET cncoef S exp Smax prev R day + Q surf Strong impact on water balance, so appropriate method should be selected in an early stage of calibration! Department of Hydrology and Water Resources Management Bieger et al. -13-

14 Improved plausibility of surface runoff Department of Hydrology and Water Resources Management Bieger et al. -14-

15 Sediment yield at HRU level Plausible variation with land use, soils and precipitation Average sediment yield per slope class: Department of Hydrology and Water Resources Management Bieger et al. -15-

16 Sediment yield and slope gradient Modifications do not impove plausibility of variation of sediment yield with slope gradient Strong impact of HRU area (non-linear relationship) MUSLE: Department of Hydrology and Water Resources Management Bieger et al. -16-

17 Conclusions Detailed analysis of model output at HRU level is highly recommendable In mountainous watersheds, particular focus should be placed on the dependence of surface runoff and sediment yield on slope The plausibility of surface runoff can be improved by modifying key algorithms and recalibrating selected parameters Sediment yields are highly dependent on HRU area Department of Hydrology and Water Resources Management Bieger et al. -17-

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19 Impact of HRU area on sediment yield 1 HRU with an area of 100 ha: q peak sed 11.8 ( ) HRUs with an area of 10 ha each: q peak sed 10(11.8 ( ) ) Department of Hydrology and Water Resources Management Bieger et al. -19-

20 Comparison of spatial output Department of Hydrology and Water Resources Management Bieger et al. -20-

21 Sediment yield from different land use types Department of Hydrology and Water Resources Management Bieger et al. -21-

22 Comparison of variants Department of Hydrology and Water Resources Management Bieger et al. -22-