Modelling Floodplain Vegetation Response to Groundwater Variability Using the ArcSWAT Hydrological Model, MODIS NDVI Data, and Machine Learning
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Methods
2.3. Hydrological Model Setup
2.3.1. Data Preparation
2.3.2. Study Period
2.3.3. DEM
2.3.4. Land Use/Land Cover Data
2.3.5. Soil Data
2.3.6. Climate Data
2.3.7. Sensitivity Analysis and Hydrological Model Calibration
2.3.8. Hydrological Model Performance Evaluation
2.3.9. Remote Sensing Data
2.3.10. Normalised Difference Vegetation Index (NDVI)
2.3.11. Machine Learning Algorithms for Data Analysis
3. Results
3.1. Hydrological Model Calibration and Validation
3.2. Relationships of Vegetation Responses and Groundwater
3.3. Vegetation Responses Considering Their Location within the Watershed
3.4. Seasonal Vegetation Responses
4. Discussion
4.1. Relationship between Vegetation Responses (NDVI) and ArcSWAT Model Simulated Soil Water Content (SWC) and Groundwater Flow (GW) Considering Vegetation Types and Their Locations
4.2. Seasonal Variability in Each Vegetation Type
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
Appendix A
References
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Data | Frequency | Description | Source |
---|---|---|---|
Precipitation | Daily | Station gauged, temporal | Bureau of Meteorology |
Temperature | Daily | Station gauged, temporal | Bureau of Meteorology |
Evapotranspiration Wind speed | Daily Hourly | Satellite-derived, 0.05 degree (approximately 5 × 5 km) Station gauged, temporal | Bureau of Meteorology Bureau of Meteorology |
Runoff | Daily | Satellite-derived, 0.05 degree (approximately 5 × 5 km) | Bureau of Meteorology |
Streamflow (discharge) | Daily | Station gauged, temporal | NSW Office of Water |
MODIS NDVI | 16-Day | 250 m spatial resolution | U.S. Geological Survey |
DEM | - | 30 m spatial resolution | U.S. Geological Survey |
Soil Map | - | 250 m spatial resolution | Digital Atlas of Australian Soil |
Land cover/land use map | - | 50 m spatial resolution | NSW Office of Environment and Heritage |
Parameter Definition | Value Range | Unit | Method | Par.inputfile | Ranking |
---|---|---|---|---|---|
Initial SCS runoff curve number for moisture condition | 35–89 | % | r | CN2 | 1 |
Effective hydraulic conductivity in the main channel alluvium | 0–500 | mm/h | v | CH_K2.rte | 13 |
Manning’s n value for the main channel | 0–0.3 | — | v | CH_N2.rte | 12 |
Base flow alpha factor | 0–1 | days | v | ALPHA_BF.gw | 5 |
Groundwater delay | 30–500 | days | v | GW_DELAY.gw | 10 |
Groundwater “revap” coefficient | 0.02–0.2 | — | v | GW_REVAP.gw | 11 |
Threshold depth of water in the shallow aquifer for return flow to occur | 0–5000 | mm H2O | v | GWQMN.gw | 3 |
Threshold depth of water in the shallow aquifer required for “revap” to occur | 0–1 | mm H2O | v | REVAPMN.gw | 8 |
Soil evaporation compensation factor | 0–0.65 | - | v | ESCO.bsn | 2 |
Average slope length | 10–150 | m | r | SLSUBBSN.hru | 9 |
Surface runoff lag coefficient | 0.05–24 | — | v | SURLAG.bsn | 15 |
Available water capacity of the soil layer | −0.5–0.5 | mmH2O/mm | r | SOL_AWC.sol | 4 |
Depth from the soil surface to layer bottom | −0.5–0.5 | mm | r | SOL_Z.sol | 6 |
Peak rate adjustment factor for sediment routing | 1–2 | - | r | ADJ_PKR.bsn | 14 |
Maximum canopy storage | 0–100 | mm H2O | v | CANMX.hru | 7 |
Scenario | NSE | R2 | PBIAS |
---|---|---|---|
Default | 0.25 | 0.36 | 73.2 |
Manual calibration | 0.51 | 0.72 | 54.2 |
SUFI-2 | 0.41 | 0.55 | 68.2 |
Variable | January | February | March | April | May | June | July | August | September | October | November | December |
---|---|---|---|---|---|---|---|---|---|---|---|---|
SWC | 86.28 | 98.54 | 93.18 | 96.25 | 112.64 | 130.79 | 131.11 | 129.71 | 122.23 | 106.23 | 100.48 | 78.14 |
GW | 6.07 | 3.72 | 5.10 | 4.59 | 4.60 | 9.13 | 21.15 | 29.00 | 28.73 | 24.57 | 15.01 | 10.96 |
Sub-Basin | GW | SWC | SWC and GW | |||||||
---|---|---|---|---|---|---|---|---|---|---|
# 28 | r | RMSE | RRSE | r | RMSE | RRSE | r | RMSE | RRSE | |
FOREST | SVM | 0.373 | 0.064 | 91% | 0.592 | 0.055 | 79% | 0.610 | 0.055 | 78% |
RF | 0.219 | 0.076 | 110.42% | 0.446 | 0.067 | 91% | 0.540 | 0.060 | 85% | |
SB_NDVI | SVM | 0.597 | 0.075 | 80% | 0.710 | 0.066 | 70% | 0.781 | 0.059 | 62% |
RF | 0.484 | 0.088 | 94% | 0.604 | 0.079 | 84% | 0.736 | 0.064 | 68% | |
TP_NDVI | SVM | 0.471 | 0.072 | 89% | 0.624 | 0.063 | 78% | 0.660 | 0.061 | 75% |
RF | 0.407 | 0.080 | 98% | 0.624 | 0.063 | 78% | 0.631 | 0.064 | 79% | |
BP_NDVI | SVM | 0.267 | 0.072 | 96% | 0.513 | 0.064 | 85% | 0.521 | 0.063 | 85% |
RF | 0.132 | 0.085 | 113% | 0.330 | 0.078 | 104% | 0.434 | 0.070 | 93% |
Sub-Basin | GW | SWC | SWC and GW | |||||||
---|---|---|---|---|---|---|---|---|---|---|
# 19 | r | RMSE | RRSE | r | RMSE | RRSE | r | RMSE | RRSE | |
SHRUB | SVM | 0.533 | 0.059 | 82% | 0.681 | 0.051 | 70% | 0.671 | 0.052 | 72% |
RF | 0.596 | 0.056 | 77.96% | 0.625 | 0.055 | 74% | 0.626 | 0.054 | 74% | |
SB_NDVI | SVM | 0.579 | 0.073 | 82% | 0.689 | 0.064 | 72% | 0.759 | 0.058 | 65% |
RF | 0.462 | 0.084 | 94% | 0.577 | 0.076 | 85% | 0.685 | 0.066 | 74% | |
TP_NDVI | SVM | 0.674 | 0.078 | 74% | 0.697 | 0.075 | 71% | 0.812 | 0.061 | 58% |
RF | 0.609 | 0.087 | 82% | 0.571 | 0.090 | 86% | 0.772 | 0.067 | 64% | |
BP_NDVI | SVM | 0.247 | 0.082 | 97% | 0.456 | 0.075 | 89% | 0.451 | 0.075 | 89% |
RF | 0.041 | 0.098 | 117% | 0.267 | 0.091 | 108% | 0.363 | 0.082 | 97% |
Sub-Basin | GW | SWC | SWC and GW | |||||||
---|---|---|---|---|---|---|---|---|---|---|
# 23 | r | RMSE | RRSE | r | RMSE | RRSE | r | RMSE | RRSE | |
GRASS | SVM | 0.4642 | 0.1116 | 84.57% | 0.5342 | 0.105 | 79.28% | 0.5629 | 0.1024 | 76.98% |
RF | 0.4876 | 0.1094 | 83.15% | 0.4607 | 0.112 | 82.75% | 0.4955 | 0.1088 | 80.10% | |
SB_NDVI | SVM | 0.6004 | 0.1071 | 80.63% | 0.649 | 0.1007 | 75.75% | 0.7431 | 0.0889 | 66.92% |
RF | 0.5369 | 0.1171 | 88.10% | 0.4353 | 0.1299 | 97.78% | 0.6522 | 0.1025 | 77.11% | |
TP_NDVI | SVM | 0.6528 | 0.1276 | 75.90% | 0.6729 | 0.1238 | 73.62% | 0.7883 | 0.1035 | 61.55% |
RF | 0.581 | 0.1422 | 84.62% | 0.4665 | 0.1605 | 95.47% | 0.7031 | 0.121 | 71.97% | |
BP_NDVI | SVM | −0.0069 | 0.1265 | 101.07% | 0.1134 | 0.1242 | 99.19% | 0.2045 | 0.1223 | 97.67% |
RF | −0.0646 | 0.1519 | 121.35% | 0.0884 | 0.1438 | 114.89% | 0.1552 | 0.1312 | 104.79% |
Sub-basin | GW | SWC | SWC and GW | |||||||
# 28 | r | RMSE | RRSE | r | RMSE | RRSE | r | RMSE | RRSE | |
FOREST | SVM | 0.527 | 0.053 | 0.837 | 0.481 | 0.056 | 0.871 | 0.594 | 0.051 | 0.792 |
RF | 0.581 | 0.053 | 0.828 | 0.317 | 0.068 | 1.074 | 0.560 | 0.054 | 0.844 | |
SB_NDVI | SVM | 0.730 | 0.058 | 0.674 | 0.570 | 0.071 | 0.815 | 0.782 | 0.054 | 0.625 |
RF | 0.702 | 0.062 | 0.716 | 0.434 | 0.084 | 0.974 | 0.750 | 0.058 | 0.666 | |
TP_NDVI | SVM | 0.564 | 0.068 | 0.817 | 0.539 | 0.070 | 0.840 | 0.649 | 0.063 | 0.753 |
RF | 0.592 | 0.069 | 0.826 | 0.379 | 0.085 | 1.017 | 0.637 | 0.065 | 0.777 | |
BP_NDVI | SVM | 0.362 | 0.061 | 0.921 | 0.368 | 0.061 | 0.917 | 0.403 | 0.060 | 0.901 |
RF | 0.420 | 0.063 | 0.944 | 0.254 | 0.073 | 1.099 | 0.403 | 0.062 | 0.935 | |
Sub-basin | GW | SWC | SWC and GW | |||||||
# 19 | r | RMSE | RRSE | r | RMSE | RRSE | r | RMSE | RRSE | |
SHRUB | SVM | 0.629 | 0.048 | 0.777 | 0.631 | 0.048 | 0.799 | 0.666 | 0.046 | 0.766 |
RF | 0.627 | 0.048 | .76.60% | 0.604 | 0.050 | 0.784 | 0.633 | 0.048 | 0.771 | |
SB_NDVI | SVM | 0.755 | 0.052 | 0.650 | 0.731 | 0.054 | 0.676 | 0.812 | 0.046 | 0.580 |
RF | 0.736 | 0.054 | 0.671 | 0.744 | 0.053 | 0.660 | 0.763 | 0.510 | 0.636 | |
TP_NDVI | SVM | 0.780 | 0.060 | 0.594 | 0.697 | 0.075 | 0.713 | 0.729 | 0.066 | 0.687 |
RF | 0.777 | 0.060 | 0.623 | 0.789 | 0.059 | 0.605 | 0.789 | 0.059 | 0.605 | |
BP_NDVI | SVM | 0.424 | 0.062 | 0.892 | 0.322 | 0.065 | 0.958 | 0.442 | 0.061 | 0.893 |
RF | 0.184 | 0.071 | 1.070 | 0.269 | 0.068 | 1.023 | 0.254 | 0.068 | 1.031 | |
Sub-basin | GW | SWC | SWC and GW | |||||||
# 23 | r | RMSE | RRSE | r | RMSE | RRSE | r | RMSE | RRSE | |
GRASS | SVM | 0.271 | 0.094 | 0.967 | 0.382 | 0.090 | 0.920 | 0.412 | 0.088 | 0.902 |
RF | 0.301 | 0.100 | 1.023 | 0.212 | 0.108 | 1.115 | 0.473 | 0.087 | 0.897 | |
SB_NDVI | SVM | 0.696 | 0.088 | 0.728 | 0.571 | 0.098 | 0.811 | 0.756 | 0.078 | 0.648 |
RF | 0.572 | 0.101 | 0.837 | 0.442 | 0.116 | 0.956 | 0.730 | 0.083 | 0.682 | |
TP_NDVI | SVM | 0.708 | 0.109 | 0.709 | 0.575 | 0.124 | 0.808 | 0.763 | 0.100 | 0.649 |
RF | 0.553 | 0.133 | 0.860 | 0.503 | 0.140 | 0.907 | 0.737 | 0.103 | 0.671 | |
BP_NDVI | SVM | −0.128 | 0.116 | 1.025 | −0.206 | 0.116 | 1.026 | 0.008 | 0.123 | 1.092 |
RF | −0.111 | 0.138 | 1.225 | −0.139 | 0.138 | 1.227 | −0.202 | 0.118 | 1.043 |
Sub-basin | GW | SWC | SWC and GW | |||||||
# 28 | r | RMSE | RRSE | r | RMSE | RRSE | r | RMSE | RRSE | |
FOREST | SVM | 0.163 | 0.050 | 98% | 0.372 | 0.047 | 93% | 0.356 | 0.048 | 0.934 |
RF | 0.230 | 0.055 | 107% | 0.182 | 0.058 | 114% | 0.242 | 0.053 | 1.035 | |
SB_NDVI | SVM | 0.501 | 0.060 | 86% | 0.623 | 0.054 | 78% | 0.710 | 0.049 | 0.699 |
RF | 0.530 | 0.066 | 94% | 0.458 | 0.067 | 96% | 0.640 | 0.055 | 0.785 | |
TP_NDVI | SVM | 0.246 | 0.057 | 96% | 0.371 | 0.054 | 92% | 0.358 | 0.055 | 0.927 |
RF | 0.361 | 0.058 | 99% | 0.060 | 0.071 | 121% | 0.092 | 0.076 | 1.288 | |
BP_NDVI | SVM | 0.089 | 0.058 | 99% | 0.245 | 0.057 | 97% | 0.203 | 0.057 | 0.981 |
RF | 0.159 | 0.063 | 108% | 0.028 | 0.071 | 121% | 0.048 | 0.066 | 1.120 | |
Sub-basin | GW | SWC | SWC and GW | |||||||
# 19 | r | RMSE | RRSE | r | RMSE | RRSE | r | RMSE | RRSE | |
SHRUB | SVM | 0.346 | 0.045 | 93% | 0.431 | 0.044 | 90% | 0.445 | 0.043 | 0.892 |
RF | 0.460 | 0.044 | 90.10% | 0.501 | 0.042 | 87% | 0.474 | 0.043 | 0.889 | |
SB_NDVI | SVM | 0.478 | 0.062 | 87% | 0.630 | 0.055 | 77% | 0.623 | 0.056 | 0.778 |
RF | 0.568 | 0.060 | 84% | 0.637 | 0.055 | 77% | 0.629 | 0.055 | 0.779 | |
TP_NDVI | SVM | 0.612 | 0.072 | 79% | 0.612 | 0.072 | 79% | 0.749 | 0.060 | 0.658 |
RF | 0.640 | 0.072 | 79% | 0.578 | 0.078 | 85% | 0.676 | 0.068 | 0.746 | |
BP_NDVI | SVM | −0.037 | 0.076 | 101% | 0.173 | 0.075 | 99% | 0.114 | 0.076 | 1.013 |
RF | −0.002 | 0.087 | 116% | 0.118 | 0.086 | 114% | 0.142 | 0.079 | 1.052 | |
Sub-basin | GW | SWC | SWC and GW | |||||||
# 23 | r | RMSE | RRSE | r | RMSE | RRSE | r | RMSE | RRSE | |
GRASS | SVM | 0.228 | 0.120 | 97% | 0.350 | 0.117 | 94% | 0.339 | 0.117 | 0.946 |
RF | 0.159 | 0.138 | 111% | 0.071 | 0.145 | 117% | 0.063 | 0.138 | 1.117 | |
SB_NDVI | SVM | 0.470 | 0.102 | 88% | 0.519 | 0.099 | 85% | 0.601 | 0.092 | 0.795 |
RF | 0.460 | 0.109 | 94% | 0.337 | 0.119 | 102% | 0.510 | 0.103 | 0.885 | |
TP_NDVI | SVM | 0.621 | 0.109 | 78% | 0.567 | 0.115 | 82% | 0.709 | 0.098 | 0.701 |
RF | 0.608 | 0.116 | 83% | 0.353 | 0.142 | 102% | 0.627 | 0.111 | 0.795 | |
BP_NDVI | SVM | 0.197 | 0.115 | 98% | −0.281 | 0.117 | 100% | 0.173 | 0.117 | 0.995 |
RF | −0.062 | 0.144 | 123% | −0.174 | 0.148 | 126% | −0.043 | 0.134 | 1.143 |
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Muhury, N.; Apan, A.A.; Marasani, T.N.; Ayele, G.T. Modelling Floodplain Vegetation Response to Groundwater Variability Using the ArcSWAT Hydrological Model, MODIS NDVI Data, and Machine Learning. Land 2022, 11, 2154. https://doi.org/10.3390/land11122154
Muhury N, Apan AA, Marasani TN, Ayele GT. Modelling Floodplain Vegetation Response to Groundwater Variability Using the ArcSWAT Hydrological Model, MODIS NDVI Data, and Machine Learning. Land. 2022; 11(12):2154. https://doi.org/10.3390/land11122154
Chicago/Turabian StyleMuhury, Newton, Armando A. Apan, Tek N. Marasani, and Gebiaw T. Ayele. 2022. "Modelling Floodplain Vegetation Response to Groundwater Variability Using the ArcSWAT Hydrological Model, MODIS NDVI Data, and Machine Learning" Land 11, no. 12: 2154. https://doi.org/10.3390/land11122154