connecting plot scale erosion experiments with...
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Connecting plot scale erosion experiments with small-catchment measurements –
sources of uncertainties
István SISÁKUnversity of Pannonia, Georgikon Faculty, Keszthely, Hungary
(Soil) Erosion Modelling Workshop20-22 March JRC, Ispra, Italy
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Frequency of the tributary monitoringDaily: 3 locationsWeekly: 2 locationsBiweekly: 24 locationsMonthly: 27 locations+ 3 monitored small-catchments
Water quality monitoring in the watershed of Lake Balaton
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Land use and other data on the three study catchments
Nagyhorváti Tagyon SomogybabodTotal area of the catchment km2 0.77 0.61 7.03North extent of the catchment º ′ ″ 46º42′48″N 46º54′19″N 46º40′44″NSouth extent of the catchment º ′ ″ 46º41′38″Ν 46º53′22″N 46º38′53″N West extent of the catchment º ′ ″ 17º4′43″E 17º39′41″E 17º43′42″EEast extent of the catchment º ′ ″ 17º5′44″E 17º40′40″E 17º46′15″E
Highest altitude within the catchment m 181 338.8 271Lowest altitude at the outlet m 129.5 157.3 155Average slope % 4.7 12.8 9.9
Land use Forest % 10.5 37.4 56.8Wood at stream and gullies % - - 3.2Arable land % 89.5 - 35.2Small plot viney. a. orch. % - 37.7 -Large field viney. a. orch. % - 27.9 4.8
Cipoletti weir Cipoletti weir Parshall flume
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Plot-scale experiments
Sites pHdw pHCaCl2 OM % CaCO3 % sand % silt % clay %
Nagyhorváti(1) 7.3 6.8 1.71 0.4 35.6 41.6 22.8
Somogybabod(2) 8.3 7.7 1.52 22 31.4 51.7 16.9
Tagyon(3) 7.6 7.2 1.81 4.3 41.3 29.5 29.2
Nikla(4) 5.8 5.4 1.20 0 82.1 13.7 4.2
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Sites Soil texture classes
Nikla (19 %) slightly silty sand Somogybabod (13 %) sandy loamy silt Nagyhorváti (7 %) slightly sandy loam Tagyon (6 %) sandy clay loam
*(Bodenkundliche Kartieranleitung)
Soil erodibility (USLE-K)* Slaking grade*
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Methodology developed in the DESPRAL project2x5 m plot size, 3-4 replicatesSeedbed condition in July-AugustGentle pre-wetting to field capacity60 mm/h simulated rainfall until equilibrium runoff rate reached3-4 consecutive simulations on the same plot with 2-3 day return time
1*3*0.5 m; 25 cm arable soil + 25 cm sand (subsoil)Uniform slope: 13 % (= SB field slope)+ field slope (TA 6%, NH 7%)
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NH-lab 13 %
NH-lab 13 % avg(X;Y)
SB-lab 13 %
SB-lab 13 % avg(X;Y)
TA-lab 13 %
TA-lab 13 % avg(X;Y)
GLM model is suitable to describe the core of the runoff-erosion relationships
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y = -3.8495x + 115.38R² = 0.8957
y = -0.4178x + 15.47R² = 0.8927
y = -1.0596x + 34.473R² = 0.6543
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equi
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equilibrium water conductivity at 60 mm/h simulated rainfall mm/h
Water conductivity and erosion rate in lab and plot measurements
Somogybabod
Tagyon
Nagyhorváti
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regr on ln(runoff) variance by 4 sites variance by 20 plots GLM (COV on ln(runoff)VAR by 4 sites)
GLM (COV on ln(runoff)VAR by 20 plots)
expl
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Explained variances in rainfall simulation experiments
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lg(E) vs. lg(Q)
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SBNHTASB: 1.92*X - 2.73; R2=0.94NH: 1.03*X + 0.38; R2=0.50TA: 1.99*X - 1.37; R2=0.82
Event based relationships between runoff an erosion for 3 small catchements
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Erosion Modelling Workshop, 20-22 March JRC, Ispra, Italy END OF PRESENTATION
Conclusions:
GLM analyses of lnQ – lnE relationsips provide reliable framework to integrate different scales
Lump estimates of average effects (USLE approach) is better than sole runoff based calculations
Hybrid models are needed: lump estimate of average effects +probability exploration of local variability
Thank you for your attention