Estimation of the Monthly Dynamics of Surface Water in Wetlands from Satellite and Secondary Hydro-Climatological Data
Abstract
:1. Introduction
2. Study Area
3. Methodology and Data
3.1. Identification of the Surface Water from Satellite Data
- (a)
- Selection of the calibration area
- (b)
- Elimination of images with errors or clouds
- (c)
- Creation of a mask of possible surface water
- (d)
- Surface water mapping by applying a temporally variable threshold
3.2. Regression Models from Explanatory Variables
- (a)
- Main climatic variables: precipitation and temperature.
- (b)
- Those derived from the main climatic variables: potential evapotranspiration and effective precipitation.
- (c)
- Hydrological variables: aquifer discharge and surface water in the previous month.
3.3. Data
4. Results
4.1. Surface Water from Satellite Data
- -
- The number of pixels covered by clouds was less than 15,000 in the study domain (total of 895,275 pixels).
- -
- The reflectance threshold for water identification was smaller than 25 (considering surface reflectance from 0 to 255).
- -
- The number of pixels covered by water increased from 3000 to 7000.
4.2. Surface Water from Regression Models
5. Discussion
Limitations and Future Research
- (a)
- This study was focused on estimating the monthly dynamic, but in some applications daily information can be necessary. The proposed regression approach cannot be used for daily completion. It uses the surface water of the previous time step and there are no consecutive days with data for the case study. For daily dynamic characterisation other approaches should be explored.
- (b)
- The proposed approach to complete surface water by using hydro-climatological variables requires a good correlation between these variables and the surface water. However, in other cases studies this correlation may not exist or the information of secondary variables may not be available (especially for the aquifer discharge which requires the calibration of a groundwater model).
- (c)
- The studied area highlights a strong conflict between groundwater-dependent ecosystems such as wetlands, and groundwater pumping to supply demands (mainly irrigation). This problem might be exacerbated in the future due to the impact of climate change. In this area a reduction in precipitation from 1.0 to 2.7% and an increase in temperature from 14.1 to 14.5% are expected for the period 2016–2045 with respect the period 1974–2015 considering the RCP8.5 emission scenario [15]. These changes will also have an impact on the surface water of the wetland. The proposed methodology is useful to propagate the impact on the explanatory hydro-climatological variables to the surface water through the proposed regression ensemble. This approach could be explored in future research.
6. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Model | xi | xj | xl | xk | R² Calibration | RMSE (Pixels) Forecasting | RMSE (Pixels) Completion Forward | RMSE (Pixels) Completion Backward | RMSE (Pixels) Completion Forward–Backward |
---|---|---|---|---|---|---|---|---|---|
1.1 | (D) | (W) | (PE) | LOG(D) | 0.709 | 777.374 | 497.764 | 589.183 | 476.856 |
1.2 | (W) | LOG(D) | 1/(P) | (PE)2 | 0.707 | 777.878 | 501.515 | 586.689 | 477.398 |
1.3 | (D) | (W) | (PE) | SQRT(D) | 0.709 | 778.372 | 498.137 | 588.780 | 476.825 |
1.4 | (W) | (PE) | LOG(W) | 1/(D) | 0.709 | 778.419 | 498.782 | 588.137 | 476.714 |
1.5 | (D) | (W) | 1/(P) | (PE)2 | 0.707 | 778.557 | 501.822 | 587.120 | 477.638 |
1.6 | (W) | 1/(D) | 1/(PE) | (PE)2 | 0.709 | 778.733 | 498.290 | 587.081 | 476.276 |
2.1 | (W) | (PE) | 1/(D) | 1/(T) | 0.709 | 778.41 | 497.683 | 586.064 | 475.621 |
2.2 | (W) | (PE) | LOG(D) | 1/(T) | 0.709 | 779.114 | 497.983 | 586.479 | 475.854 |
2.3 | (W) | (PE) | 1/(D) | 1/(E) | 0.709 | 779.45 | 497.351 | 587.411 | 476.175 |
2.4 | (W) | (PE) | 1/(T) | SQRT(D) | 0.709 | 779.497 | 498.125 | 586.684 | 475.965 |
2.5 | (D) | (W) | (PE) | 1/(T) | 0.709 | 779.849 | 498.280 | 586.919 | 476.094 |
2.6 | (W) | (PE) | LOG(D) | 1/(E) | 0.709 | 780.244 | 497.652 | 587.810 | 476.400 |
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Collados-Lara, A.-J.; Pardo-Igúzquiza, E.; Pulido-Velazquez, D.; Baena-Ruiz, L. Estimation of the Monthly Dynamics of Surface Water in Wetlands from Satellite and Secondary Hydro-Climatological Data. Remote Sens. 2021, 13, 2380. https://doi.org/10.3390/rs13122380
Collados-Lara A-J, Pardo-Igúzquiza E, Pulido-Velazquez D, Baena-Ruiz L. Estimation of the Monthly Dynamics of Surface Water in Wetlands from Satellite and Secondary Hydro-Climatological Data. Remote Sensing. 2021; 13(12):2380. https://doi.org/10.3390/rs13122380
Chicago/Turabian StyleCollados-Lara, Antonio-Juan, Eulogio Pardo-Igúzquiza, David Pulido-Velazquez, and Leticia Baena-Ruiz. 2021. "Estimation of the Monthly Dynamics of Surface Water in Wetlands from Satellite and Secondary Hydro-Climatological Data" Remote Sensing 13, no. 12: 2380. https://doi.org/10.3390/rs13122380