Title: Digital Elevation Model based Hydrologic Modeling
1Digital Elevation Model based Hydrologic Modeling
Outline
- Topography and Physical runoff generation
processes (TOPMODEL) - Raster calculation of wetness index
- Raster calculation of TOPMODEL runoff
- Extendability of ArcGIS using Visual Basic
Programming
2Physical Processes involved in Runoff Generation
- From http//snobear.colorado.edu/IntroHydro/geog_h
ydro.html
3Runoff generation processes
P
Infiltration excess overland flow aka Horton
overland flow
f
P
qo
P
f
Partial area infiltration excess overland flow
P
P
qo
P
f
P
Saturation excess overland flow
P
qo
P
qr
qs
4Map of saturated areas showing expansion during a
single rainstorm. The solid black shows the
saturated area at the beginning of the rain the
lightly shaded area is saturated by the end of
the storm and is the area over which the water
table had risen to the ground surface. from
Dunne and Leopold, 1978
Seasonal variation in pre-storm saturated area
from Dunne and Leopold, 1978
5Runoff generation at a point depends on
- Rainfall intensity or amount
- Antecedent conditions
- Soils and vegetation
- Depth to water table (topography)
- Time scale of interest
These vary spatially which suggests a spatial
geographic approach to runoff estimation
6TOPMODEL
- Beven, K., R. Lamb, P. Quinn, R. Romanowicz and
J. Freer, (1995), "TOPMODEL," Chapter 18 in
Computer Models of Watershed Hydrology, Edited by
V. P. Singh, Water Resources Publications,
Highlands Ranch, Colorado, p.627-668. - TOPMODEL is not a hydrological modeling package.
It is rather a set of conceptual tools that can
be used to reproduce the hydrological behaviour
of catchments in a distributed or
semi-distributed way, in particular the dynamics
of surface or subsurface contributing areas.
7TOPMODEL and GIS
- Surface saturation and soil moisture deficits
based on topography - Slope
- Specific Catchment Area
- Topographic Convergence
- Partial contributing area concept
- Saturation from below (Dunne) runoff generation
mechanism
8Saturation in zones of convergent topography
9Specific catchment area a is the upslope area per
unit contour length m2/m ? m
Numerical Evaluation with the D? Algorithm
Topographic Definition
Tarboton, D. G., (1997), "A New Method for the
Determination of Flow Directions and Contributing
Areas in Grid Digital Elevation Models," Water
Resources Research, 33(2) 309-319.)
(http//www.engineering.usu.edu/cee/faculty/dtarb/
dinf.pdf)
10Hydrological processes within a catchment are
complex, involving
- Macropores
- Heterogeneity
- Fingering flow
- Local pockets of saturation
The general tendency of water to flow downhill is
however subject to macroscale conceptualization
11TOPMODEL assumptions
- The dynamics of the saturated zone can be
approximated by successive steady state
representations. - The hydraulic gradient of the saturated zone can
be approximated by the local surface topographic
slope, tan?. - The distribution of downslope transmissivity with
depth is an exponential function of storage
deficit or depth to the water table
- To is lateral transmissivity m2/h
- S is local storage deficit m
- z is local water table depth m (S/ne)
- ne is effective porosity
- m is a storage-discharge sensitivity parameter
m - f ne/m is an alternative storage-discharge
sensitivity parameter m-1
12Topmodel - Assumptions
- The soil profile at each point has a finite
capacity to transport water laterally downslope.
e.g.
or
13Topmodel - Assumptions
Specific catchment area a m2/m ? m (per unit
contour length)
- The actual lateral discharge is proportional to
specific catchment area.
- R is
- Proportionality constant
- may be interpreted as steady state recharge
rate, or steady state per unit area
contribution to baseflow.
14Topmodel - Assumptions
Specific catchment area a m2/m ? m (per unit
coutour length)
- Relative wetness at a point and depth to water
table is determined by comparing qact and qcap
- Saturation when w gt 1.
- i.e.
15Topmodel
Specific catchment area a m2/m ? m (per unit
coutour length)
z
16Slope
Specific Catchment Area
Wetness Index ln(a/S) from Raster
Calculator. Average, l 6.91
17Numerical Example
- Given
- Ko10 m/hr
- f5 m-1
- Qb 0.8 m3/s
- A (from GIS)
- ne 0.2
- Compute
- R0.0002 m/h
- l6.90
- T2 m2/hr
Raster calculator -( ln(sca/S) - 6.90)/50.46
18Calculating Runoff from 25 mm Rainstorm
- Flat areas and z lt 0
- Area fraction (81 1246)/158938.3
- All rainfall ( 25 mm) is runoff
- 0 lt z ? rainfall/effective porosity 0.025/0.2
0.125 m - Area fraction 546/15893 3.4
- Runoff is P-z0.2
- (1 / Sat_during_rain ) (0.025 - (0.2 z))
- Mean runoff 0.0113 m 11.3 mm
- z gt 0.125 m
- Area fraction 14020/15893 88.2
- All rainfall infiltrates
- Area Average runoff
- 11.3 0.025 25 0.083 2.47 mm
- Volume 0.00247 15893 30 30 35410 m3
19Why Programming
20GIS estimation of hydrologic response function
- Amount of runoff generated
- Travel time to outlet
- Distance from each grid cell to outlet along flow
path (write program to do this) - Distance from each point on contributing area
- overlay grid to outlet distances with
contributing area.
21Steps for distance to outlet program
- Read the outlet coordinates
- Read the DEM flow direction grid. This is a set
of integer values 1 to 8 indicating flow
direction - Initialize a distance to outlet grid with a no
data value - Convert outlet to row and column references
- Start from the outlet point. Set the distance to
0. - Examine each neighboring grid cell and if it
drains to the current cell set its distance to
the outlet as the distance from it to the current
cell plus the distance from the current cell to
the outlet.
22Programming the calculation of distance to the
outlet
102.4
72.4
30
72.4
42.4
0
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24Visual Basic Programming in ArcMAP
- References
- ESRI, (1999), ArcObjects Developers Guide
ArcInfo 8, ESRI Press, Redlands, California. - Zeiler, M., (2001), Exploring ArcObjects. Vol 1.
Applications and Cartography. Vol 2. Geographic
Data Management, ESRI, Redlands, CA.
25Are there any questions ?