Optimization of Hydrologic Response Units (HRUs) Using Gridded Meteorological Data and Spatially Varying Parameters
Abstract
:1. Introduction
2. Methodology
2.1. Area of the Study Case
2.2. Hydrologic Parameters and Meteorological Datasets
2.3. Clustering Processes and HRU Delineation
2.4. Hydrological Model Setup and Simulations
3. Results
3.1. PCA and Cluster Analysis
3.2. Hydrological Modeling and HRU Contribution
4. Discussion
4.1. Methodology and Data Uncertainties in the Dataset Preparation
4.2. Clustering Method and Results
4.3. Discharge Independence in the Hydrologic Modeling
5. Conclusions and Further Developments
Supplementary Materials
Author Contributions
Funding
Conflicts of Interest
References
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Dim.1 | Dim.2 | Dim.3 | Dim.4 | Dim.5 | |
---|---|---|---|---|---|
Explained Variance (%) | 50.7 | 16.1 | 11.9 | 5.9 | 5.0 |
Variables | Contribution to each dimension (%) | ||||
Temp | 28.2 | 0.1 | 0.7 | 0.2 | 5.1 |
Albedo | 11.5 | 1.1 | 5.6 | 1.6 | 10.0 |
Wind Speed | 10.8 | 1.3 | 0.6 | 0.0 | 8.5 |
Precipitation | 10.7 | 41.5 | 22.6 | 0.0 | 0.6 |
Evapotranspiration | 10.2 | 2.2 | 1.5 | 0.5 | 12.3 |
Net Radiation | 9.7 | 3.5 | 9.6 | 1.4 | 10.7 |
Relative Humidity | 9.5 | 5.6 | 1.4 | 1.0 | 0.0 |
Runoff Resistance Coefficient | 4.9 | 13.9 | 10.5 | 12.1 | 2.5 |
Soil Water Capacity | 4.1 | 20.3 | 6.4 | 4.4 | 9.7 |
Preferred Flow Direction | 0.3 | 4.7 | 32.1 | 0.4 | 35.6 |
Root Zone Hydraulic Conductivity | 0.0 | 5.7 | 9.0 | 78.3 | 5.0 |
Scenario | NSE | RMSE |
---|---|---|
HRU_01 | 0.58 | 4.1% |
HRU_02 | 0.71 | 4.3% |
HRU_03 | 0.72 | 3.6% |
HRU_04 | 0.77 | 3.5% |
HRU_05 | 0.78 | 3.2% |
HRU_06 | 0.79 | 3.1% |
HRU_07 | 0.78 | 3.1% |
HRU_08 | 0.77 | 3.1% |
HRU_09 | 0.76 | 3.2% |
HRU_10 | 0.74 | 3.2% |
Goal | 1.00 | 0.0% |
Cluster 1 | Cluster 2 | Cluster 3 | Cluster 4 | Cluster 5 | Cluster 6 | |
---|---|---|---|---|---|---|
Area (km2) | 34.0 | 22.1 | 125.2 | 121.7 | 10.9 | 41.5 |
% over total area | 9.6% | 6.2% | 35.2% | 34.2% | 3.1% | 11.7% |
Elevation (m.a.s.l.) | 1483 | 1460 | 2063 | 2080 | 2837 | 2951 |
Precipitation (mm) | 204 | 413 | 175 | 269 | 287 | 357 |
Evapotranspiration (mm) | 126 | 203 | 110 | 154 | 50 | 161 |
Evapotranspiration/Precipitation (–) | 0.62 | 0.49 | 0.63 | 0.57 | 0.17 | 0.45 |
Discharge | ||||||
Mean (m3/s) | 0.09 | 0.15 | 0.26 | 0.45 | 0.08 | 0.26 |
% over total discharge | 7% | 12% | 20% | 35% | 6% | 20% |
Standard deviation (m3/s) | 0.03 | 0.11 | 0.30 | 0.77 | 0.08 | 0.47 |
Coefficient of variation | 0.34 | 0.76 | 1.16 | 1.72 | 0.99 | 1.79 |
Hydrograph centroid (month index) | 9.65 | 9.85 | 9.79 | 10.57 | 10.35 | 11.49 |
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Poblete, D.; Arevalo, J.; Nicolis, O.; Figueroa, F. Optimization of Hydrologic Response Units (HRUs) Using Gridded Meteorological Data and Spatially Varying Parameters. Water 2020, 12, 3558. https://doi.org/10.3390/w12123558
Poblete D, Arevalo J, Nicolis O, Figueroa F. Optimization of Hydrologic Response Units (HRUs) Using Gridded Meteorological Data and Spatially Varying Parameters. Water. 2020; 12(12):3558. https://doi.org/10.3390/w12123558
Chicago/Turabian StylePoblete, David, Jorge Arevalo, Orietta Nicolis, and Felipe Figueroa. 2020. "Optimization of Hydrologic Response Units (HRUs) Using Gridded Meteorological Data and Spatially Varying Parameters" Water 12, no. 12: 3558. https://doi.org/10.3390/w12123558
APA StylePoblete, D., Arevalo, J., Nicolis, O., & Figueroa, F. (2020). Optimization of Hydrologic Response Units (HRUs) Using Gridded Meteorological Data and Spatially Varying Parameters. Water, 12(12), 3558. https://doi.org/10.3390/w12123558