An Integrated GIS-Hydro Modeling Methodology for Surface Runoff Exploitation via Small-Scale Reservoirs
Abstract
:1. Introduction
2. Material and Methods
2.1. Study Area
2.2. Methodological Framework
2.2.1. Overview and Data
2.2.2. Hydrological and Background Analysis—SWAT Simulation
- (a)
- filling of possible sinks and smoothing of possible excessive elevations lifts resolving thus possible water trapping or pseudo-changes in flow direction [55]
- (b)
- estimation of flow direction
- (c)
- estimation of flow accumulation
- (d)
- creation of streams and outlets of each catchment
2.2.3. SWAT Modeling Evaluation
2.2.4. Reservoir Simulation
3. Results
3.1. SWAT Modeling and Background Analysis
3.2. SWAT Modeling Evaluation Results
3.3. Reservoir Simulation
4. Discussion
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Type | Details | Source |
---|---|---|
DEM | Raster (28 × 28 m pixel size) | Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (Aster GDEM) |
Land cover | Vector (initial analog map scale 1:5000) | Greek Ministry of Agriculture |
Hydrolithology | Vector (initial analog map scale 1:50,000) | Institute of Geology and Mineral Exploration |
Meteorological data (rainfall, temperature, wind, solar radiation) | Tables | Hellenic National Meteorological Service |
First Site | Second Site | ||||||
---|---|---|---|---|---|---|---|
Level | Area | Volume (Between) | Total Volume | Level | Area | Volume (Between) | Total Volume |
(m a.s.l.) | (m2) | (m3) | (m3) | (m a.s.l.) | (m2) | (m3) | (m3) |
520 | 0 | 1352 | 0 | 420 | 0 | 2128 | 0 |
524 | 676 | 4988 | 1352 | 424 | 1064 | 7452 | 2128 |
528 | 1818 | 10,248 | 6340 | 428 | 2662 | 18,012 | 9580 |
532 | 3306 | 17,688 | 16,588 | 432 | 6344 | 34,528 | 27,592 |
536 | 5538 | 29,578 | 34,276 | 436 | 10,920 | 54,106 | 62,120 |
540 | 9251 | 63,854 | 440 | 16,133 | 116,226 |
UNIT | WATER | SED | |||||||
---|---|---|---|---|---|---|---|---|---|
TIME | PREC | SURQ | LATQ | GWQ | SW | ET | PET | YIELD | YIELD |
(month) | (mm) | (mm) | (mm) | (mm) | (mm) | (mm) | (mm) | (mm) | (t/ha) |
1 | 77.13 | 0 | 25.57 | 0 | 52.62 | 18 | 49.16 | 25.57 | 0 |
2 | 90.58 | 0.16 | 52.18 | 0.45 | 72.22 | 11.11 | 18.06 | 52.79 | 0.03 |
3 | 73.81 | 0 | 32.27 | 4.39 | 68.64 | 38.41 | 70.9 | 36.66 | 0 |
4 | 7.5 | 0 | 1.6 | 4.49 | 50.28 | 24.26 | 140.3 | 6.09 | 0 |
5 | 7.53 | 0 | 1.58 | 2.21 | 19.52 | 36.7 | 106.55 | 3.79 | 0 |
6 | 2.88 | 0 | 0 | 0.46 | 2.49 | 19.91 | 132.96 | 0.46 | 0 |
7 | 2.58 | 0 | 0 | 0.18 | 0.74 | 4.33 | 129.02 | 0.18 | 0 |
8 | 3.14 | 0 | 0.1 | 0.07 | 0.34 | 3.44 | 112.27 | 0.16 | 0 |
9 | 10.87 | 0 | 3.04 | 0.02 | 0.55 | 7.61 | 84.92 | 3.07 | 0 |
10 | 23.17 | 0 | 6.9 | 0.01 | 2.01 | 14.82 | 86.32 | 6.91 | 0 |
11 | 89.68 | 0 | 40.68 | 0 | 26.43 | 24.58 | 75.54 | 40.68 | 0 |
12 | 218.6 | 0.87 | 117.81 | 1.64 | 66.3 | 35.75 | 116.8 | 120.32 | 0.17 |
2020 | 607.46 | 1.03 | 281.72 | 13.92 | 66.3 | 238.94 | 122.81 | 296.66 | 0.2 |
UNIT | WATER | SED | |||||||
---|---|---|---|---|---|---|---|---|---|
TIME | PREC | SURQ | LATQ | GWQ | SW | ET | PET | YIELD | YIELD |
(month) | (mm) | (mm) | (mm) | (mm) | (mm) | (mm) | (mm) | (mm) | (t/ha) |
1 | 77.13 | 0.00 | 26.12 | 0.00 | 52.10 | 17.98 | 49.20 | 26.12 | 0.00 |
2 | 90.58 | 0.15 | 53.06 | 0.43 | 71.32 | 11.05 | 17.99 | 53.63 | 0.03 |
3 | 73.81 | 0.00 | 32.78 | 4.13 | 67.74 | 38.32 | 70.83 | 36.91 | 0.00 |
4 | 7.50 | 0.00 | 1.64 | 4.21 | 49.59 | 24.03 | 140.32 | 5.85 | 0.00 |
5 | 7.53 | 0.00 | 1.61 | 2.08 | 21.04 | 34.47 | 106.23 | 3.70 | 0.00 |
6 | 2.88 | 0.00 | 0.00 | 0.43 | 2.76 | 21.16 | 132.64 | 0.43 | 0.00 |
7 | 2.58 | 0.00 | 0.00 | 0.17 | 0.74 | 4.60 | 128.73 | 0.17 | 0.00 |
8 | 3.14 | 0.00 | 0.10 | 0.06 | 0.35 | 3.43 | 111.97 | 0.16 | 0.00 |
9 | 10.87 | 0.00 | 3.12 | 0.02 | 0.62 | 7.48 | 84.68 | 3.14 | 0.00 |
10 | 23.17 | 0.00 | 7.06 | 0.01 | 1.99 | 14.74 | 86.29 | 7.07 | 0.00 |
11 | 89.68 | 0.00 | 41.57 | 0.00 | 25.73 | 24.37 | 75.65 | 41.58 | 0.00 |
12 | 218.60 | 0.81 | 119.78 | 1.55 | 65.47 | 35.44 | 117.11 | 122.13 | 0.16 |
2020 | 607.46 | 0.95 | 286.84 | 13.09 | 65.47 | 237.071 | 121.64 | 300.87 | 0.19 |
Mean (mm) | Std (mm) | |
---|---|---|
Measurements | 245 | 75 |
Simulation | 238 * | 63 |
Nash–Sutcliffe coefficient | 0.79 | |
R2 | 0.85 |
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Kalogeropoulos, K.; Stathopoulos, N.; Psarogiannis, A.; Pissias, E.; Louka, P.; Petropoulos, G.P.; Chalkias, C. An Integrated GIS-Hydro Modeling Methodology for Surface Runoff Exploitation via Small-Scale Reservoirs. Water 2020, 12, 3182. https://doi.org/10.3390/w12113182
Kalogeropoulos K, Stathopoulos N, Psarogiannis A, Pissias E, Louka P, Petropoulos GP, Chalkias C. An Integrated GIS-Hydro Modeling Methodology for Surface Runoff Exploitation via Small-Scale Reservoirs. Water. 2020; 12(11):3182. https://doi.org/10.3390/w12113182
Chicago/Turabian StyleKalogeropoulos, Kleomenis, Nikolaos Stathopoulos, Athanasios Psarogiannis, Evangelos Pissias, Panagiota Louka, George P. Petropoulos, and Christos Chalkias. 2020. "An Integrated GIS-Hydro Modeling Methodology for Surface Runoff Exploitation via Small-Scale Reservoirs" Water 12, no. 11: 3182. https://doi.org/10.3390/w12113182