Coupling Land Use Change Modeling with Climate Projections to Estimate Seasonal Variability in Runoff from an Urbanizing Catchment Near Cincinnati, Ohio
Abstract
:1. Introduction
2. Materials and Methods
2.1. Description of the Study Area
2.2. Conceptual Framework
2.3. CA-MARKOV Model of Land Cover Change
2.4. Assessment of the Impact of Climate Variability on Hydrologic Endpoints
Month | Hydrologic Endpoint Values Based on Historical Record 1969–2004 | ||||
---|---|---|---|---|---|
100-Year Flood (m3 s−1) | 7Q10 (m3 s−1) | Maximum (m3 s−1) | Mean (m3 s−1) | Minimum (m3 s−1) | |
January | 49.4 | 8.9 | 95.6 | 18.1 | 0.3 |
February | 88.8 | 10.4 | 59.6 | 18.1 | 1.1 |
March | 50.2 | 9.8 | 38.6 | 17.1 | 5.3 |
April | 105.7 | 8.2 | 60.0 | 19.2 | 7.4 |
May | 366.3 | 8.8 | 134.0 | 23.7 | 8.0 |
June | 351.6 | 9.8 | 131.3 | 25.0 | 7.4 |
July | 189.1 | 9.9 | 90.4 | 19.3 | 6.9 |
August | 42.8 | 6.0 | 90.5 | 17.1 | 5.4 |
September | 79.0 | 4.4 | 46.0 | 14.3 | 4.0 |
October | 64.1 | 4.9 | 38.4 | 14.2 | 4.3 |
November | 50.0 | 4.1 | 38.3 | 13.2 | 4.0 |
December | 60.3 | 3.9 | 40.9 | 15.4 | 3.8 |
Scenarios/ | Deltas from General Circulation Models Output for 2010–2039 | ||||||
---|---|---|---|---|---|---|---|
Timeseries | CCCM a | CCSR b | CSIR c | ECHM d | HDCM e | NCAR f | GDFL g |
A2 (mid-high) | Projected percent change in average precipitation over the base period 1971–2000 | ||||||
Annual | 0.04 | −0.03 | −0.02 | −0.02 | 0.03 | 0.04 | 0.02 |
Winter | 0.00 | 0.08 | 0.05 | −0.14 | 0.06 | 0.11 | −0.01 |
Spring | 0.08 | −0.01 | 0.04 | −0.05 | 0.05 | −0.01 | 0.02 |
Summer | −0.02 | −0.14 | 0.01 | 0.06 | 0.05 | 0.01 | 0.00 |
Fall | 0.16 | 0.03 | −0.20 | 0.00 | −0.19 | 0.21 | 0.14 |
B2 (mid-low) | Projected percent change in average precipitation over the base period 1971–2000 | ||||||
Annual | 0.08 | 0.07 | 0.04 | 0.06 | 0.03 | −0.01 | 0.01 |
Winter | −0.02 | 0.08 | 0.08 | 0.01 | 0.05 | 0.05 | −0.01 |
Spring | 0.06 | 0.05 | 0.00 | −0.01 | 0.02 | −0.03 | 0.02 |
Summer | 0.03 | 0.03 | 0.09 | 0.09 | 0.10 | −0.05 | −0.03 |
Fall | 0.33 | 0.12 | −0.02 | 0.13 | −0.09 | 0.07 | 0.12 |
2.5. Sensitivity Testing
3. Results and Discussion
3.1. Land Cover Change
OH-KY-IN MSA | 1992 | 2001 | Projected 2010 | Projected 2020 | Projected 2030 |
---|---|---|---|---|---|
Urban High Intensity | 361.38 | 377.71 | 538.97 | 700.70 | 860.72 |
Urban Low Intensity | 662.94 | 1831.12 | 2335.50 | 2706.92 | 3029.08 |
Woodland/Open space | 5440.65 | 5519.76 | 5942.51 | 6038.76 | 6098.52 |
Cropland | 7360.33 | 6138.60 | 5061.85 | 4429.27 | 3884.77 |
Water | 234.83 | 242.27 | 247.31 | 250.70 | 253.38 |
Wetlands | 71.43 | 25.97 | 27.29 | 28.17 | 29.10 |
Barren land | 18.10 | 14.22 | 12.95 | 11.88 | 10.92 |
EFLMR Watershed | 1992 | 2001 | 2010 | 2020 | 2030 |
Urban High Intensity | 10.35 | 14.74 | 29.19 | 29.21 | 85.37 |
Urban Low Intensity | 39.80 | 117.48 | 135.45 | 169.48 | 263.89 |
Woodland/ Open space | 328.17 | 417.42 | 420.31 | 420.38 | 397.01 |
Cropland | 885.59 | 713.77 | 678.21 | 644.09 | 517.37 |
Water | 12.79 | 12.80 | 12.75 | 12.75 | 13.00 |
Wetlands | 2.34 | 2.03 | 2.44 | 2.44 | 2.52 |
Barren land | 1.30 | 2.10 | 1.99 | 1.99 | 1.18 |
3.2. Incorporating Downscaled Climate Projections in BASINS-HSPF
3.3. Monte Carlo Simulation
Emissions Scenario | 100-Year Flood | 7Q10 | Mean | ||||
---|---|---|---|---|---|---|---|
Baseline (X) | (m3 s-1) | (m3 s-1) | (m3 s-1) | ||||
Winter | 66.2 | 7.7 | 17.2 | ||||
Spring | 174.1 | 8.9 | 20.0 | ||||
Summer | 194.5 | 8.6 | 20.4 | ||||
Fall | 64.4 | 4.5 | 13.9 | ||||
Mid-High (A2) IPCC Emissions Scenario: X1 | Probability of Exceeding Baseline Values | ||||||
Projected Change in Precipitation | P(X>X1) | P(X<X1) | P(X>X1) | ||||
Min (ECHM) | −0.14 | Max (NCAR) | 0.11 | Winter | 0.123 | 0.029 | 0.077 |
Min (ECHM) | −0.05 | Max (CCCM) | 0.08 | Spring | 0.045 | 0.013 | 0.022 |
Min (CCSR) | −0.14 | Max (ECHM) | 0.06 | Summer | 0.036 | 0.035 | 0.010 |
Min (CSIR) | −0.20 | Max (NCAR) | 0.21 | Fall | 0.177 | 0.009 | 0.085 |
Mid-Low (B2) IPCC Emissions Scenario: X2 | Probability of Exceeding Baseline Values | ||||||
Projected Change in Precipitation | P(X>X2) | P(X<X2) | P(X>X2) | ||||
Min (CCCM) | −0.01 | Max (CSIR, CCSR) | 0.08 | Winter | 0.097 | 0.016 | 0.026 |
Min (NCAR) | −0.03 | Max (CCCM) | 0.06 | Spring | 0.032 | 0.042 | 0.014 |
Min (NCAR) | −0.05 | Max (HDCM) | 0.10 | Summer | 0.021 | 0.044 | 0.028 |
Min (HDCM) | −0.09 | Max (CCCM) | 0.33 | Fall | 0.254 | 0.015 | 0.109 |
3.4. Sensitivity Analysis
Climate Change Scenario | Hot/Dry/Near Term | Warm Wet/Near Term | ||||||||
---|---|---|---|---|---|---|---|---|---|---|
Percent Impervious | 31.20% | 53.20% | 53.20% | 90.00% | 90.00% | 31.20% | 53.20% | 53.20% | 90.00% | 90.00% |
Wet Day Threshold (Inches) | 0.1 | 0.1 | 0.1 | 0.1 | 0.1 | 0.1 | 0.1 | 0.1 | 0.1 | 0.1 |
LID control: | % of impervious area treated/% of treated area used for LID | |||||||||
Disconnection | 10 | 10 | 10 | 0 | 10 | 10 | 10 | 10 | 0 | 10 |
Rain harvesting | 0 | 0 | 2 | 0 | 0 | 0 | 0 | 2 | 0 | 0 |
Rain gardens | 0 | 0 | 5 | 0 | 0 | 0 | 0 | 5 | 0 | 0 |
Street planters | 10 | 10 | 10 | 0 | 10 | 10 | 10 | 10 | 0 | 10 |
Infiltration basins | 0 | 0 | 10 | 0 | 0 | 0 | 0 | 10 | 0 | 0 |
Porous pavement | 5 | 5 | 5 | 0 | 5 | 5 | 5 | 5 | 0 | 5 |
Results: | Scenario 1 | Scenario 2 | Scenario 3 | Scenario 4 | Scenario 5 | Scenario 6 | Scenario 7 | Scenario 8 | Scenario 9 | Scenario 10 |
Average Annual Rainfall (in) | 45.8 | 42.48 | 42.48 | 42.48 | 42.48 | 46.92 | 46.92 | 46.92 | 46.92 | 46.92 |
Average Annual Runoff (in) | 18.27 | 19.1 | 13.06 | 32.89 | 27.1 | 15.97 | 15.1 | 15.01 | 36.96 | 30.82 |
Days per Year With Rainfall | 82.34 | 80.79 | 80.84 | 80.79 | 80.79 | 85.00 | 80.79 | 84.94 | 84.99 | 84.99 |
Days per Year with Runoff | 51.46 | 47.37 | 39.32 | 64.76 | 59.51 | 46.57 | 46.72 | 43.42 | 68.7 | 62.61 |
Percent of Wet Days Retained | 37.5 | 41.37 | 51.36 | 19.85 | 26.35 | 45.21 | 42.18 | 48.88 | 19.17 | 26.34 |
Smallest Rainfall w/Runoff (in) | 0.19 | 0.16 | 0.23 | 0.10 | 0.11 | 0.19 | 0.23 | 0.19 | 0.11 | 0.12 |
Largest Rainfall w/o Runoff (in) | 0.35 | 0.36 | 0.43 | 0.21 | 0.28 | 0.39 | 0.36 | 0.41 | 0.23 | 0.25 |
Max. Rainfall Retained (in) | 1.94 | 1.00 | 2.02 | 0.55 | 0.79 | 2.00 | 1.95 | 2.11 | 0.62 | 0.87 |
Infiltration (%) | 52 | 57 | 61 | 9 | 21 | 34 | 35 | 61 | 9 | 21 |
Evaporation (%) | 8 | 8 | 7 | 14 | 15 | 8 | 8 | 7 | 13 | 14 |
Runoff (%) | 40 | 35 | 32 | 77 | 63 | 58 | 57 | 32 | 78 | 65 |
4. Conclusions
Acknowledgments
Author Contributions
Conflicts of Interest
References
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Mitsova, D. Coupling Land Use Change Modeling with Climate Projections to Estimate Seasonal Variability in Runoff from an Urbanizing Catchment Near Cincinnati, Ohio. ISPRS Int. J. Geo-Inf. 2014, 3, 1256-1277. https://doi.org/10.3390/ijgi3041256
Mitsova D. Coupling Land Use Change Modeling with Climate Projections to Estimate Seasonal Variability in Runoff from an Urbanizing Catchment Near Cincinnati, Ohio. ISPRS International Journal of Geo-Information. 2014; 3(4):1256-1277. https://doi.org/10.3390/ijgi3041256
Chicago/Turabian StyleMitsova, Diana. 2014. "Coupling Land Use Change Modeling with Climate Projections to Estimate Seasonal Variability in Runoff from an Urbanizing Catchment Near Cincinnati, Ohio" ISPRS International Journal of Geo-Information 3, no. 4: 1256-1277. https://doi.org/10.3390/ijgi3041256
APA StyleMitsova, D. (2014). Coupling Land Use Change Modeling with Climate Projections to Estimate Seasonal Variability in Runoff from an Urbanizing Catchment Near Cincinnati, Ohio. ISPRS International Journal of Geo-Information, 3(4), 1256-1277. https://doi.org/10.3390/ijgi3041256