Shallow subsurface storm ow in a forested headwater catchment: Observations and modeling using a modied TOPMODEL

The application of hydrological models in shallow landslides prediction 1 2010/11/41OutlineIntroductionReviewObjectiveMethodDataPreliminary results

2Introduction

Taiwan has been vulnerable to shallow landslide disasters caused by heavy rainfalls.Mitigate landslide disasters Evaluate the potential of slope failure events in space and time

Landslide susceptibility analysis in the Tachia Creek drainage basinLee at al., 2008

20043Introduction

Statistical approaches(Fuzzy Logic, Logistic Regression, and Neural Networks)Deterministic approachesPhysically-based models

(Iverson, 2000)Steady state modelSHALSTAB MODEL(Montgomery et al., 1994)SIMMAP (Pack et al., 1998)Transient modelTRIGRS (Baum et al., 2002)

BasicModelling of slope the hydrological responseTopography is considered ..

4ObjectiveTo establish a slope-instability analysis and a hydrological model for landslide prediction during heavy rainstorms.

Water tableSoilGround surfaceSliding surfaceFS5Application of hydrology modelReview MethodDataResultSHALSTAB (Dietrich and Montgomery, 1994)- Steady- state hydrological conditions- Fully saturated conditions- Homogeneous soil- Slop-parallel groundwater flow- Impermeable basal boundary

Hydrological modelInfinite slope

Critical Rainfall

Dietrich and Montgomery 1994; 1998 SHALSTAB(1)(2)(3)(4)(5)

6Application of hydrology modelReview MethodDataResultTRIGRS(Baum et al., 2002)- Transient hydrological conditions- Fully saturated conditions- Homogeneous soil- Slope-parallel watertable- Impermeable or infinite basal boundary

Infiltrate model

solution of Richards equation

Infinite slope model

USGS2002 TRIGRSTRIGRSIverson(2000)(1)(2)(3)(5)Richard equation + (*)=

7Application of hydrology modelReview MethodDataResult(Casadei., 2003)- Transient hydrological conditions- Unsaturated conditions- Slope-parallel watertable- Homogeneous soil- Impermeable boundaryCoupled hydrologicalslope stability modelInfinite slope model

Groundwater table above the slip surface

8Input dataFlow chartRainfallDataDEM DataGroundwater levelEstimation modelLandslide susceptibility MapInfinite Slope Stability ModelAreaDataSoil ParameterOutput dataHydrologic ParameterSafetyFactorGroundwaterHeight9

Upslope contributing area aStream lineContour lineHydrologic ModelReview MethodDataResult

TOPMODEL(TOPgraphy based hydrological MODEL)(Beven. et al., 1979)10

Topographic indexReview MethodDataResult

a Specific areatan slope

(contributing area)(saturation degree)(subsurface flow)

11

SrzSuzZwGroundwater tableqv TOPMODEL StructureReview MethodDataResultSrz Root zoneSuz Unsaturated zoneDSoil DepthZwWater table heightqv

TOPMODELSrzSuzZjqv=+

12

TOPMODEL Assumption

This equation can be solved for z:Saturated defict, zjSteady-statezjTOPMODEL(1)qj=rar[L/T]aj[L](2) tanBq=TtanB(3) z

2iZimT0rln(a/T0tanB)rmTOPMODELT0T0

Zi

13Hydrologic RoutingReview MethodDataResult

The recharge to the groundwater table

The baseflow from the saturated zone 14Hydrologic RoutingReview MethodDataResultThe recharge to the groundwater table

The baseflow from the saturated zone

15Infinite Slope MODELReview MethodDataResult

r

d

FS>1 StableFS 1.0, Set to 1.0Saturation < 0 , Set to 0

Zi26

Soil profile saturationReview MethodDataResult27 Rainfall ProcessReview MethodDataResult

T=3628 PredictionReview MethodDataResult

T=36Distribution map of slope failures of actual vs predicted by model 29 Classification Error Matrix Review MethodDataResultXX

XXXXXXXXXXXXXXXXX30 Classification Error Matrix Review MethodDataResultPredictUnstable(FS < 1)Stable(FS 1)ActualUnstableN1N2stableN3N4The results of both are quantitatively compared by using two following evaluation indexes.

AR= ( N1 ) / ( N1+ N2+ N3+ N4 ) (1)FAR= ( N3 ) / ( N1+ N2+ N3+ N4 ) (2)

Here, AR is accuracy rate (%), FAR is false alarm rate (%) and N1, N2, N3 and N4 (see Table ) N1, N2, N3, N4 : number of cell on each category 31 Classification Error Matrix Review MethodDataResultPredictUnstable(FS < 1)Stable(FS 1)ActualUnstable613451stable13402107343The results of both are quantitatively compared by using two following evaluation indexes.

N1, N2, N3, N4 : number of cell on each category AR= 57.61%32 classification error matrix 1(14015)(FS < 1)(FS 1)(1064)613451(120745)13402107343=57.61%=88.91%=88.62%Total=1218093334 Future WorkCalibration parameter

Model validation

Comparing the results 34Thank you for your attention35

Unit contour

length b

Contributing area A

Specific Catchment Area a = A/b