MODELLING SURFACE RUNOFF
TO MITIGATE HARMFUL IMPACT
OF SOIL EROSION
Pavel KOVAR, Darina VASSOVA
Faculty of Environmental Sciences
Czech University of Life Sciences Prague
Research Grant NAZV QH 72085 (2010)
Simulation of Rain Erosivity and Soil Erodibility
Prague, January 2011
INTRODUCTION
Problems Caused by Water Erosion
– Loss of soil is an important issue worldwide, due to:
•
•
•
•
Increased frequency of hydrological extremes
Inexistent or insufficient erosion control measures
Improper land use
Improper agricultural/forest management
– First steps for solving problems related to water erosion :
• Empirical models:
– USLE/MUSLE (Modified/Universal Soil Loss Equation, Delivery Ratio)
• Simulation models:
– CN-based models (EPIC, CREAMS, AGNPS, ...)
– Surface Runoff and Erosion Processes (SMODERP, EROSION 2D, ...)
• Advanced simulation models:
– EUROSEM (European Erosion Model,
http://www.cranfield.ac.uk/eurosem/Eurosem.htm)
– WEPP (Water Erosion Prediction Project,
http://milford.nserl.purdue.edu/weppdocs/)
INTRODUCTION
CAN WATER EROSION BE PREDICTED USING A
MODIFIED HYDROLOGIC MODEL?
In this presentation we will try to determine the
common principles of surface runoff and soil erosion
analyses:
–
–
–
–
–
–
Physically-based models
Natural rainfall-runoff events data
Simulated rainfall-runoff data (using rain simulator)
Design rainfall data
Observed and computed rain erosivity data assessment
Soil loss analysis based on soil erodibility (rill and interrill
erosion assessment)
EXPERIMENTAL RUNOFF PLOTS
Area: TŘEBSÍN
EXPERIMENTAL SITES DESCRIPTION
Soil characteristics:
– Brown soil “Eutric Cambisol” on weathered eluvials and deluvials
– Field capacity (average): 33.5%
– Porosity (average): 48.3%
Plot parameters and crops
Plot No.
Length
(m)
Wide
(m)
Slope
(%)
Area
(m2)
Crop
2007
Crop
2008
Crop
2009
Crop
2010
9
37.7
6.6
11.2
248.8
sunflower
maize
maize
maize
6
37.8
6.7
12.8
253.3
sunflower
maize
maize
maize
4
37.4
6.8
14.3
254.3
sunflower
maize
maize
maize
Average
37.6
6.7
12.8
250.0
2

So
SF 
Soil hydraulic parameters
2K s
Plot No.
Satur. hydraulic conductivity
Ks (mm · min-1)
Sorptivity at FC
So (mm · min-0.5)
Storage suction factor
SF (mm)
9
0.214
1.06
2.63
6
0.177
1.20
4.07
4
4.360
4.64
2.47
RAIN SIMULATOR
RAIN SIMULATOR
SHEET FLOW
DISCHARGE/LOAD MEASUREMENT DEVICE
GRANULARITY CURVE
FOR EXPERIMENTAL RUNOFF AREAS AT TŘEBSÍN
100
1
2
3
4
5
6
7
8
9
percent (%)
80
60
Plot
No.
40
20
Grain
<0.002
Grain
<0.01
Grain
0.010.05
Grain
0.050.25
1
11.4
27.8
61.5
80.7
100.0
2
10.7
27.7
60.8
83.0
100.0
3
9.1
27.6
66.7
81.2
100.0
4
9.9
30.8
71.2
85.1
100.0
5
11.9
33.2
76.4
87.8
100.0
6
13.1
33.7
75.3
88.5
100.0
7
16.6
36.1
80.6
91.3
100.0
8
17.2
35.2
79.3
92.1
100.0
9
17.6
35.2
79.5
92.1
100.0
0
0.001
0.01
Grain
0.252.0
0.1
soil grain size
1
10
MODEL KINFIL – PRINCIPLES
EINFIL Part
– Infiltration computation:
• Green Ampt (and MorelSeytoux)
– Storage suction factor:
– Ponding time:
KINFIL Part
– Computation of flow on
slopes using kinematic
wave computation:
• (Lax-Wendroff numerical
scheme)
  s   i   H f
i  K s 1 

i tp

S f   s   i   H f
tp 




2

So

2K s
Sf
 i

i    1
 Ks 
y
y
 m ym 1  ie (t )
t
x
THE KINFIL PARAMETERS
ROOT
KS
SO
POR
FC
SMC
depth of root zone (m)
saturated hydraulic conductivity (m·s-1)
sorptivity at field capacity (m·s-0.5)
porosity (–)
field capacity (–)
(or API) soil moisture content (mm)
JJ
SLO
LEN
WID
NM
number of planes in cascade (–)
slope of plane (–)
length of plane (m)
width of plane (m)
Manning roughness
t
1

x m ym1
DS
D(i)
RO
mean soil particle diameter (mm)
soil particle category diameters (mm)
soil particle density (kg · m-3)
– cascade of planes
– cascade of segments
IMPACT OF PHYSIOGRAPHIC
CHARACTERISTICS ON SURFACE RUNOFF
Length of slope
Angle of slope
Slope angle vers. tim e to peak
(CN=88, length L=100m , Manning n=0,100)
1.5
Time to peak
(hrs)
1.5
1
0.5
1
0.5
0
0
0
50 100 150 200 250 300 350 400 450 500
0
0.02
0.04 0.06
Hydraulic roughness
Roughness vers. time to peak
(CN = 88, length L=100m, slope α=0,05 )
0.5
0.4
0.3
0.2
0.1
0
0.4
0.08
0.1
Slope angle α (-)
Slope length L (m )
Manning n
Specific discharge
q (l s -1 m -1)
Slope length vers. specific runoff
(CN=88, slope α = 0,05, Manning n=0,100)
0.6
0.8
1
Time to peak (hrs)
1.2
0.12
0.14 0.16
NATURAL RAINFALL-RUNOFF OBSERVATION
DT = 30 min, area 250 m2 (36.0 × 7.0 m), 10 August 2007
Rainfall-runoff events
Depths, velocity and shear velocity
Soil loss:
5330 kg · ha-1
Soil loss:
281 kg · ha-1
SIMULATED RAINFALL-RUNOFF EVENTS
TŘEBSÍN 9, DT = 1 min, area 30 m2 (3.0 × 10.0 m)
26 Aug. 2009 (DRY, SMCo=23.4%, Maize)
26 Aug. 2009 (DRY)
26 Aug. 2009 (WET, SMCo=39.3%, Maize)
Depths and Velocities
26 Aug. 2009 (WET)
DESIGN RAINFALLS
Rain gauge Benešov: Pt,N=P1d,N · a · t1-c
it,N=P1d,N · a · t-c
Design rainfall depths Pt,N (mm):
Rain depths Pt,N for duration td (10 to 300 min), N-years reccurance
Benešov
90
80
70
P (mm)
60
50
40
30
20
10
0
0
50
100
150
200
250
300
t (min)
2
5
10
20
50
100
years
DESIGN RAIN INTENSITIES
Design rain intensities it,N (mm · min-1):
Rain intensity it,N for duration td (10 to 300 min), N-years reccurence
Benešov
4.0
3.5
-1
i (mm · min )
3.0
2.5
2.0
1.5
1.0
0.5
0.0
0
50
100
150
200
250
t (min)
2
5
10
20
50
100 years
300
SURFACE RUNOFF FROM DESIGN RAINFALL
Locality: TŘEBSÍN 9, area 30 m2, Maize
DESIGN RUNOFF: DEPTH, VELOCITIES AND
SHEAR STRESS VALUES AT DIFFERENT TIME
Locality: TŘEBSÍN 9, area 30m2, N = 2 years, TD = 10 min
Tim e: 20 m in
2.50
0.05
2.00
0.04
1.50
0.03
1.00
0.02
0.50
Depth (m)
SHEAR STRESS (Pa)
VELOCITIES V (m.s-1)
Depth (m)
SHEAR STRESS (Pa)
2.00
0.06
0.06
0.05
0.04
1.50
0.03
1.00
0.02
0.50
0.01
0.01
Shear Stress
0.00
2
4
6
Length (m)
8
0
Velocity
10
0.00
2
Shear Velocity
Tim e: 30 m in
6
Length (m)
8
10
0.06
0.03
1.00
0.06
0.05
2.00
Depth (m)
SHEAR STRESS (Pa)
0.04
1.50
0.02
0.04
1.50
0.03
1.00
0.02
0.50
0.50
0.01
0.00
0.00
4
6
Length (m)
8
10
0.01
Velocity
Shear Velocity
Shear Stress
Depth
Shear Stress
Depth
2
Velocity
Shear Velocity
2.50
VELOCITIES V (m.s-1)
0.05
2.00
0
Depth
Tim e: 40 m in
2.50
Depth (m)
SHEAR STRESS (Pa)
4
VELOCITIES V (m.s-1)
0
Shear Stress
0.00
Depth
0.00
VELOCITIES V (m.s-1)
Tim e: 10 m in
2.50
0.00
0.00
0
2
4
6
Length (m)
8
10
Velocity
Shear Velocity
DESIGN RUNOFF: POTENTIAL SOIL LOSS
Locality: TŘEBSÍN 9, N = 2 years, TD = 10 min
Grain size categories and their critical shear stress:
Category (mm)
< 0.01
0.01–0.05 0.05–0.25 0.25–2.00
tc (Pa)
0.0076
0.0380
0.1900
1.6700
Effective medium grain size Ds = 0.030 mm, tc = 0.5 Pa
Experimental runoff area:
Potential soil loss (for Ds) at 20’
10’
30’
0.45
0.91
0.02
0.69
1.39
0.06
0.88
1.76
0.10
1.06
2.12
0.15
1.19
2.38
0.21
Pa
CONCLUSIONS
ADVANTAGES OF THE KINFIL MODEL
– provides results from the physically-based scheme.
– provides possibilities to calibrate model parameters for
natural rainfall-runoff event reconstructions.
– simulates surface runoff discharges, depths, velocities
and shear stress accurately enough to be compared with
measured discharges and soil losses measured by rain
simulator equipment.
– simulates also the change of land use and farming
management.
MODELLERS AIM
– to extend research in soil losses caused by rill erosion (t0
vers. tK for various granulometric spectra).
– to compare the KINFIL and WEPP models results.
Thank you for your attention