Effect of Spatial Variability on a Distributed Hydrologic Model May 6, 2015 Huidae Cho Water Resources Engineer, Dewberry Consultants Part-Time Assistant.

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Presentation transcript:

Effect of Spatial Variability on a Distributed Hydrologic Model May 6, 2015 Huidae Cho Water Resources Engineer, Dewberry Consultants Part-Time Assistant Professor, Kennesaw State University

2 Research Questions Is any model able to predict what happens within its time resolution? Does the spatial distribution of land use and soil type maps really matter when all rain drops drain within one time step? How significant is the impact of multiple rainfall gauges on small watersheds?

3 Spatial Variability in Small Watersheds Small watersheds have time of concentration shorter than the computational time step of the model. Spatial variability includes among others:  the spatial distribution of land uses and soil types,  distributed precipitation data from multiple rainfall gauges.

4 SWAT Soil and Water Assessment Tool (SWAT) operates on a daily basis (i.e., the time resolution is one day). The NRCS curve number method is used to estimate the surface runoff. The variable storage routing method is used to route stream flow to the outlet.

5 Study Area East Fork San Jacinto River watershed Area: 1,002 km 2 Rainfall: 1,320±241 mm/yr Daily stream flow: 9.5±33.5 m 3 /s Number of subbasins: 20

6 Study Area (cont.) Barton Creek watershed Area: 279 km 2 Rainfall: 926±290 mm/yr Daily stream flow: 1.5±5.7 m 3 /s Number of subbasins: 16

7 Study Area (cont.) Onion Creek watershed Area: 837 km 2 Rainfall: 937±295 mm/yr Daily stream flow: 2.3±16.7 m 3 /s Number of subbasins: 61 Edwards aquifer

8 East Fork San Jacinto River Watershed Land Use: NLCD 1992/Randomized/Uniform 2% Urban 1% Agriculture 72% Forest 23% Rangeland 2% Water

9 Barton Creek Watershed Land Use: NLCD 1992/Randomized/Uniform 6% Urban 1% Agriculture 51% Forest 41% Rangeland 1% Water

10 Onion Creek Watershed Land Use: NLCD 1992/Randomized/Uniform 9% Urban 3% Agriculture 45% Forest 42% Rangeland 1% Water

11 East Fork San Jacinto River Watershed Soil Type: STATSGO/Randomized/Uniform 16% Clay 22% Silt 62% Sand

12 Barton Creek Watershed Soil Type: STATSGO/Randomized/Uniform 28% Clay 38% Silt 34% Sand

13 Onion Creek Watershed Soil Type: STATSGO/Randomized/Uniform 36% Clay 35% Silt 29% Sand

14 Precipitation: Multiple/Single Gauge 26% 55% 14% 5% 83% 17% 58% 10% 26% 6%

15 Calibration

16 Calibration (cont.) Parameter change function p l ¡ 1 : 0 1 : 0 p new = p 0 + ® ( p b ¡ p 0 ) w h erep b = ( p u i f ® > 0 p l o t h erw i se p u p 0 p new ®

17 Simulation Periods Calibration period  2 years of stabilization: January 1, 1989 to December 31, 1990  4 years of simulation: January 1, 1991 to December 1994 Validation period  2 years of stabilization: January 1, 1995 to December 31, 1996  4 years of simulation: January 1, 1997 to December 31, 2000

18 Flow Routing Can we see the effect of flow routing at the outlet?

19 Calibration Results Calibration Multiple rain gaugesSingle rain gauge Soil type: Original Soil type: Single Soil type: Random Soil type: Original Soil type: Single Soil type: Random East Fork San Jacinto River Land use: Original Land use: Single Land use: Random Barton Creek Land use: Original Land use: Single Land use: Random Onion Creek Land use: Original Land use: Single Land use: Random NS=0.71

20 Spatial Validation Results Spatial validation Multiple rain gaugesSingle rain gauge Soil type: Original Soil type: Single Soil type: Random Soil type: Original Soil type: Single Soil type: Random East Fork San Jacinto River Land use: Original Land use: Single Land use: Random Barton Creek Land use: Original Land use: Single Land use: Random Onion Creek Land use: Original Land use: Single Land use: Random

21 Temporal Validation Results Temporal validation Multiple rain gaugesSingle rain gauge Soil type: Original Soil type: Single Soil type: Random Soil type: Original Soil type: Single Soil type: Random East Fork San Jacinto River Land use: Original Land use: Single Land use: Random Barton Creek Land use: Original Land use: Single Land use: Random Onion Creek Land use: Original Land use: Single Land use: Random NS=0.51

22 Spatio-temporal Validation Results Spatio-temporal validation Multiple rain gaugesSingle rain gauge Soil type: Original Soil type: Single Soil type: Random Soil type: Original Soil type: Single Soil type: Random East Fork San Jacinto River Land use: Original Land use: Single Land use: Random Barton Creek Land use: Original Land use: Single Land use: Random Onion Creek Land use: Original Land use: Single Land use: Random WatershedCorrelations between NCDC rainfall gauges East Fork San Jacinto River (55%) (26%) (14%) (5%) / / / 0.69 Barton Creek (83%) (17%) / 0.31 Onion Creek (58%) (26%) (10%) (6%) / / / 0.50

23 Conclusions There was not much degradation in performance when the virtual land use and soil type maps were used. Model parameters are adjusted to the system by calibration and becomes a part of the model. The spatial distribution of land use and soil type maps did not significantly affect the model performance in small watersheds.

24 Conclusions (cont.) The multiple-rain-gauge models showed better performance in validation than the single-rain-gauge models. In small watersheds, it is essential that peak rainfalls correspond to peak flows in the same day due to short response time.