Monitoring Eichhornia crassipes and Myriophyllum aquaticum in Irrigation Systems Using High-Resolution Satellite Imagery: Impacts on Water Quality and Management Strategies
Abstract
:1. Introduction
2. Materials and Methods
2.1. Site Description
2.2. Remote Sensing Data for Invasive Species Monitoring
2.3. Vegetation Indices, Classification, and Image Processing
2.4. Water Quality Assessment and Sampling Locations
3. Results
3.1. Temporal Variation of Vegetation Indices and Influencing Factors (2018–2020)
3.2. Class-Based Analysis of Vegetation Indices (2018–2020)
3.3. Seasonal NDVI Analysis and Vegetation Response
3.4. Water Quality Sampling and Analysis
4. Discussion
4.1. Influence of Edaphoclimatic Conditions on Vegetation, Invasive Species Monitoring with High-Resolution Remote Sensing, and Implications for Water Management Strategies
4.2. Impact of E. crassipes and M. aquaticum on Water Quality and Statistical Analysis
4.2.1. Effects of E. crassipes and M. aquaticum on Water Quality
4.2.2. Statistical Analysis of E. crassipes and M. aquaticum and Water Quality Parameters
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
Abbreviations
C | Conductivity |
DSC | Downstream sampling point |
EC | Electrical conductivity |
ETo | Reference evapotranspiration |
EVI | Enhanced Vegetation Index |
GCI | Green Chlorophyll Index |
GSR | Global solar radiation |
IAD | Image acquisition date |
LVID | Lis Valley Irrigation District |
NDVI | Normalized Difference Vegetation Index |
PF | Myriophyllum aquaticum/parrot’s feather |
PSC | Phenological stage code |
PSU | Practical Salinity Units |
R | Resistance to electrical flow |
RDO | Dissolved oxygen concentration |
Rf | Rainfall |
RH | Relative humidity |
RS | Remote sensing |
S | Salinity |
Sat DO | Dissolved Oxygen Saturation |
SS | Suspended solid concentration |
Temp | Temperature |
UAV | Unmanned Aerial Vehicle |
USP | Upstream sampling point |
WH | Eichhornia crassipes/water hyacinth |
WUA | Water User’s Association |
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2018 | 2019 | 2020 | ||||||
---|---|---|---|---|---|---|---|---|
IAD | PSC WH | PSC PF | IAD | PSC WH | PSC PF | IAD | PSC WH | PSC PF |
11 Jan | I | I | 09 Jan | I | I | 10 Jan | I | I |
23 Mar | II | II | 13 Feb | I | I | 19 Feb | I | I |
13 Apr | III | III | 26 Mar | II | II | 25 Mar | II | II |
17 May | IV | III | 12 Apr | III | III | 19 Apr | III | III |
19 Jun | IV | IV | 11 May | IV | III | 24 May | IV | III |
21 Jul | IV | IV | 11 Jun | IV | IV | 10 Jun | IV | IV |
08 Aug | IV | IV | 18 Jul | IV | IV | 16 Jul | IV | IV |
07 Sep | V | IV | 05 Aug | IV | IV | 13 Aug | IV | IV |
03 Oct | V | V | 12 Sep | V | IV | 10 Sep | V | IV |
22 Nov | V | V | 21 Oct | V | V | 12 Oct | V | V |
06 Dec | I | I | 23 Nov | V | V | 30 Nov | V | V |
17 Dec | I | I |
Index | Classification | Value Range |
---|---|---|
NDVI | Class 1 (Low Vegetation/Soil) | NDVI ≤ 0.2 |
Class 2 (Moderate Vegetation) | 0.2 < NDVI ≤ 0.4 | |
Class 3 (Dense Vegetation) | NDVI > 0.4 | |
EVI | Class 1 (Low Vegetation/Soil) | EVI ≤ 0.1 |
Class 2 (Moderate Vegetation) | 0.1 < EVI ≤ 0.3 | |
Class 3 (Dense Vegetation) | EVI > 0.3 | |
GCI | Class 1 (Low Chlorophyll Content) | GCI ≤ 0.2 |
Class 2 (Moderate Chlorophyll Content) | 0.2 < GCI ≤ 0.4 | |
Class 3 (High Chlorophyll Content) | GCI > 0.4 |
Year | Date | Vegetation Index | T 10D Average | RH 10D Average | GSR 10D Average | Rf 10D Sum | Eto 10d Sum | ||
---|---|---|---|---|---|---|---|---|---|
2018 | NDVI | EVI | GCI | (°C) | (%) | (%) | (mm) | (mm) | |
11 Jan | 0.28 | 0.25 | 0.97 | 10.2 | 93.5 | 3.9 | 30.0 | 6.4 | |
26 Mar | 0.53 | 0.29 | 2.88 | 10.3 | 83.1 | 13.5 | 67.6 | 18.4 | |
13 Apr | 0.27 | 0.19 | 1.27 | 11.0 | 90.8 | 10.6 | 114.2 | 18.2 | |
17 May | 0.41 | 0.27 | 1.78 | 15.6 | 77.3 | 20.1 | 1.0 | 32.1 | |
19 Jun | 0.40 | 0.21 | 1.89 | 18.2 | 85.5 | 19.6 | 16.4 | 33.3 | |
21 Jul | 0.55 | 0.35 | 2.93 | 21.1 | 81.4 | 19.5 | 0.0 | 34.8 | |
08 Aug | 0.61 | 0.38 | 4.26 | 22.5 | 73.0 | 21.5 | 0.0 | 41.0 | |
07 Sep | 0.44 | 0.34 | 1.87 | 20.9 | 78.1 | 18.7 | 1.2 | 33.8 | |
03 Oct | 0.42 | 0.22 | 2.19 | 21.6 | 71.9 | 17.0 | 0.0 | 30.4 | |
22 Nov | 0.25 | 0.07 | 1.01 | 13.3 | 87.5 | 8.5 | 34.7 | 9.5 | |
06 Dec | 0.31 | 0.14 | 1.32 | 11.3 | 90.1 | 8.0 | 21.0 | 8.4 | |
2019 | |||||||||
09 Jan | 0.49 | 0.21 | 2.46 | 7.6 | 79.6 | 10.0 | 0.6 | 8.7 | |
13 Feb | 0.53 | 0.28 | 2.61 | 9.2 | 84.2 | 12.2 | 5.2 | 13.2 | |
26 Mar | 0.41 | 0.23 | 1.69 | 13.3 | 63.1 | 20.7 | 0.4 | 29.6 | |
12 Apr | 0.54 | 0.28 | 3.26 | 12.1 | 84.9 | 16.3 | 62.2 | 23.5 | |
11 May | 0.62 | 0.37 | 3.95 | 17.1 | 78.5 | 22.2 | 20.4 | 35.0 | |
11 Jun | 0.38 | 0.21 | 1.94 | 15.4 | 75.5 | 27.9 | 10.0 | 42.3 | |
18 Jul | 0.45 | 0.27 | 2.11 | 20.1 | 83.0 | 19.9 | 3.2 | 36.4 | |
05 Aug | 0.62 | 0.38 | 3.49 | 18.8 | 84.3 | 23.5 | 6.6 | 40.0 | |
12 Sep | 0.58 | 0.32 | 3.71 | 17.7 | 74.4 | 21.1 | 0.0 | 38.0 | |
21 Oct | 0.32 | 0.14 | 1.38 | 15.8 | 87.1 | 9.3 | 55.6 | 17.2 | |
23 Nov | 0.39 | 0.20 | 1.51 | 12.1 | 90.2 | 6.6 | 106.6 | 10.3 | |
17 Dec | 0.52 | 0.26 | 2.18 | 11.7 | 94.7 | 5.7 | 49.0 | 6.9 | |
2020 | |||||||||
10 Jan | 0.54 | 0.22 | 2.7 | 7.2 | 92.1 | 8.0 | 2.6 | 7.6 | |
19 Feb | 0.64 | 0.36 | 3.2 | 12.7 | 90.5 | 9.8 | 5.6 | 9.3 | |
25 Mar | 0.56 | 0.35 | 2.5 | 11.9 | 16.4 | 5.7 | 13.4 | 21.6 | |
19 Apr | 0.53 | 0.25 | 2.4 | 14.8 | 16.9 | 6.3 | 43.0 | 25.7 | |
24 May | 0.48 | 0.28 | 2.2 | 16.7 | 26.5 | 6.4 | 3.2 | 38.6 | |
10 Jun | 0.47 | 0.30 | 1.9 | 17.8 | 24.2 | 7.2 | 0.6 | 38.6 | |
16 Jul | 0.56 | 0.30 | 4.2 | 19.4 | 27.4 | 6.7 | 0.0 | 48.1 | |
13 Aug | 0.57 | 0.34 | 4.4 | 19.4 | 21.0 | 7.3 | 0.8 | 33.0 | |
10 Sep | 0.53 | 0.29 | 3.8 | 18.5 | 21.3 | 5.7 | 0.0 | 39.6 | |
12 Oct | 0.41 | 0.21 | 1.7 | 15.5 | 15.3 | 5.9 | 10.2 | 20.4 | |
30 Nov | 0.45 | 0.23 | 2.3 | 10.3 | 8.3 | 4.5 | 53.8 | 10.7 |
Parameter | Location | 10 October 2018 | 30 October 2019 | 9 October 2020 |
---|---|---|---|---|
pH | Upstream | 7.23 | 7.13 | 7.03 |
Downstream | 7.03 | 7.44 | 7.56 | |
EC (µs/cm) | Upstream | 1153 | 1672 | 968 |
Downstream | 793 | 1905 | 914 | |
C (µs/cm) | Upstream | 987 | 1480 | 761 |
Downstream | 672 | 1705 | 815 | |
RDO (mg/L) | Upstream | 8.01 | 9.54 | 9.67 |
Downstream | 7.38 | 6.38 | 6.32 | |
Sat DO (%) | Upstream | 84.8 | 102.6 | 94.8 |
Downstream | 77.5 | 69.5 | 68.0 | |
Temp (°C) | Upstream | 17.5 | 19.1 | 19.0 |
Downstream | 17.1 | 19.7 | 19.4 | |
SS (ppm) | Upstream | 750 | 1090 | 480 |
Downstream | 516 | 1240 | 590 | |
S (PSU) | Upstream | 0.58 | 0.85 | 0.63 |
Downstream | 0.39 | 0.98 | 0.45 | |
R (Ω cm) | Upstream | 1013 | 676 | 1306 |
Downstream | 1484 | 585 | 1228 |
Parameter | Index | Multiple R | R2 | Standard Error | p-Value | Coef. X1 | F-Value | ANOVA p-Value |
---|---|---|---|---|---|---|---|---|
pH | NDVI | 0.852 | 0.726 | 0.129 | 0.031 | 6.540 | 10.610 | 0.031 |
EVI | 0.872 | 0.761 | 0.120 | 0.000 | 2.321 | 12.720 | 0.023 | |
GCI | 0.814 | 0.663 | 0.143 | 0.048 | 0.194 | 7.880 | 0.048 | |
EC | NDVI | 0.016 | 0.000 | 503.988 | 0.233 | 60.018 | 0.001 | 0.976 |
EVI | 0.071 | 0.005 | 502.788 | 0.894 | 385.659 | 0.020 | 0.894 | |
GCI | 0.089 | 0.008 | 502.053 | 0.867 | 43.376 | 0.032 | 0.867 | |
C | NDVI | 0.059 | 0.004 | 472.751 | 0.293 | 205.968 | 0.014 | 0.911 |
EVI | 0.107 | 0.011 | 470.866 | 0.840 | 547.205 | 0.046 | 0.840 | |
GCI | 0.136 | 0.018 | 469.196 | 0.798 | 62.168 | 0.075 | 0.798 | |
RDO | NDVI | 0.905 | 0.819 | 0.702 | 0.000 | −10.971 | 18.155 | 0.013 |
EVI | 0.813 | 0.661 | 0.961 | 0.001 | −14.505 | 7.803 | 0.049 | |
GCI | 0.942 | 0.886 | 0.556 | 0.005 | −1.503 | 31.232 | 0.005 | |
SAT DO | NDVI | 0.928 | 0.862 | 5.772 | 0.000 | −105.753 | 24.934 | 0.008 |
EVI | 0.831 | 0.690 | 8.644 | 0.001 | −139.290 | 8.902 | 0.041 | |
GCI | 0.941 | 0.886 | 5.247 | 0.005 | −14.124 | 31.021 | 0.005 | |
Temp | NDVI | 0.253 | 0.064 | 1.156 | 0.001 | 2.217 | 0.273 | 0.629 |
EVI | 0.297 | 0.088 | 1.141 | 0.000 | 3.831 | 0.386 | 0.568 | |
GCI | 0.159 | 0.025 | 1.180 | 0.763 | 0.184 | 0.104 | 0.763 | |
SS | NDVI | 0.073 | 0.005 | 354.138 | 0.316 | 190.936 | 0.022 | 0.890 |
EVI | 0.116 | 0.013 | 352.707 | 0.231 | 443.850 | 0.054 | 0.827 | |
GCI | 0.166 | 0.027 | 350.189 | 0.754 | 56.848 | 0.113 | 0.754 | |
S | NDVI | 0.066 | 0.004 | 0.255 | 0.182 | −0.123 | 0.017 | 0.902 |
EVI | 0.002 | 0.000 | 0.256 | 0.135 | 0.005 | 0.000 | 0.997 | |
GCI | 0.022 | 0.001 | 0.256 | 0.966 | −0.006 | 0.002 | 0.966 | |
R | NDVI | 0.050 | 0.002 | 400.450 | 0.178 | −146.556 | 0.010 | 0.925 |
EVI | 0.137 | 0.019 | 397.155 | 0.091 | −594.263 | 0.077 | 0.795 | |
GCI | 0.112 | 0.013 | 398.431 | 0.833 | −43.360 | 0.051 | 0.833 |
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Ferreira, S.; Sánchez, J.M.; Gonçalves, J.M.; Eugénio, R.; Damásio, H. Monitoring Eichhornia crassipes and Myriophyllum aquaticum in Irrigation Systems Using High-Resolution Satellite Imagery: Impacts on Water Quality and Management Strategies. AgriEngineering 2025, 7, 151. https://doi.org/10.3390/agriengineering7050151
Ferreira S, Sánchez JM, Gonçalves JM, Eugénio R, Damásio H. Monitoring Eichhornia crassipes and Myriophyllum aquaticum in Irrigation Systems Using High-Resolution Satellite Imagery: Impacts on Water Quality and Management Strategies. AgriEngineering. 2025; 7(5):151. https://doi.org/10.3390/agriengineering7050151
Chicago/Turabian StyleFerreira, Susana, Juan Manuel Sánchez, José Manuel Gonçalves, Rui Eugénio, and Henrique Damásio. 2025. "Monitoring Eichhornia crassipes and Myriophyllum aquaticum in Irrigation Systems Using High-Resolution Satellite Imagery: Impacts on Water Quality and Management Strategies" AgriEngineering 7, no. 5: 151. https://doi.org/10.3390/agriengineering7050151
APA StyleFerreira, S., Sánchez, J. M., Gonçalves, J. M., Eugénio, R., & Damásio, H. (2025). Monitoring Eichhornia crassipes and Myriophyllum aquaticum in Irrigation Systems Using High-Resolution Satellite Imagery: Impacts on Water Quality and Management Strategies. AgriEngineering, 7(5), 151. https://doi.org/10.3390/agriengineering7050151