Prediction of Water Carbon Fluxes and Emission Causes in Rice Paddies Using Two Tree-Based Ensemble Algorithms
Abstract
:1. Introduction
2. Materials and Methods
2.1. Site Data
2.2. Extreme Gradient Boosting (XGBoost)
2.3. Random Forest (RF)
2.4. Statistical Evaluation
3. Results
3.1. Models Performance and Driving Factors of ET Prediction
3.2. Models Performance and Driving Factors of NEE Prediction
3.3. Models Performance and Driving Factors of FCH4 Prediction
4. Discussion
4.1. Analysis of Influencing Factors of Evapotranspiration in Rice Paddies
4.2. Analysis of Influencing Factors of Net Ecosystem Carbon Exchange in Rice Paddies
4.3. Analysis of Influencing Factors of Methane Flux in Rice Paddies
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Sites | Latitude (°) | Longitude (°) | Start Year (Year) | End Year (Year) | Mean ET (mm hr−1) | Mean NEE (gC m−2 d−1) | Mean FCH4 (nmol m−2 s−1) |
---|---|---|---|---|---|---|---|
IT-Cas | 45.07 | 8.72 | 2009 | 2010 | 0.06 | −10.50 | 94.66 |
JP-Mse | 36.05 | 140.03 | 2012 | 2012 | 0.11 | −15.39 | 61.17 |
KR-CRK | 38.20 | 127.25 | 2015 | 2018 | 0.06 | −7.72 | 119.32 |
PH-RiF | 14.14 | 121.27 | 2012 | 2014 | 0.08 | −12.49 | 40.88 |
US-HRA | 34.59 | −91.75 | 2017 | 2017 | 0.07 | −32.60 | 63.80 |
US-HRC | 34.59 | −91.75 | 2017 | 2017 | 0.09 | −28.57 | 106.62 |
US-Twt | 38.11 | −121.65 | 2009 | 2017 | 0.10 | −8.60 | 43.57 |
Factors/Sites | IT-Cas | JP-Mse | KR-CRK | PH-RiF | US-HRA | US-HRC | US-Twt |
---|---|---|---|---|---|---|---|
TA | 15.9 | 21.1 | 13.3 | 27.0 | 24.0 | 23.9 | 18.9 |
SW_IN | 265.0 | 342.2 | 282.7 | 219.5 | 211.2 | 283.5 | 358.4 |
VPD | 14.0 | 8.4 | 6.2 | 9.7 | 5.4 | 7.6 | 12.3 |
PA | 100.4 | 101.0 | 99.2 | 100.5 | 100.9 | 100.8 | 101.3 |
WS | 1.1 | 2.4 | 2.2 | 1.9 | 1.5 | 2.0 | 4.3 |
NDVI | 0.5 | 0.5 | 0.4 | 0.6 | 0.7 | 0.6 | 0.5 |
SWC | 58.9 | 42.5 | 38.7 | 63.5 | 42.3 | 47.7 | |
DeltaTA | −0.5 | −0.6 | −0.4 | −0.1 | 0.1 | 0.0 | −0.5 |
Number | 15,497 | 4952 | 31,067 | 21,010 | 2149 | 2144 | 66,455 |
Factors/Sites | IT-Cas | JP-Mse | KR-CRK | PH-RiF | US-HRA | US-HRC | US-Twt |
---|---|---|---|---|---|---|---|
TA | 13.5 | 21.2 | 14.1 | 27.3 | 26.5 | 26.6 | 18.9 |
SW_IN | 221.1 | 364.1 | 239.5 | 267.7 | 353.7 | 370.4 | 348.9 |
LW_OUT | 431.6 | 391.6 | 468.8 | 464.1 | 463.5 | ||
VPD | 12.9 | 8.5 | 5.7 | 10.7 | 7.7 | 9.7 | 12.4 |
PA | 100.3 | 101.0 | 99.2 | 100.6 | 100.8 | 100.8 | 101.3 |
WS | 1.1 | 2.4 | 2.2 | 2.1 | 2.5 | 2.5 | 4.4 |
WD | 173.6 | 167.9 | 212.4 | 165.8 | 179.3 | 190.4 | 268.2 |
SWC | 60.4 | 42.6 | 40.7 | 62.1 | 41.7 | 47.8 | 0.4 |
USTAR | 0.1 | 0.2 | 0.2 | 0.2 | 0.2 | 0.2 | |
NETRAD | 125.8 | 141.9 | 188.6 | 232.0 | 249.3 | 187.1 | |
TS | 12.9 | 19.5 | 14.3 | 28.5 | 18.6 | ||
NDVI | 0.5 | 0.5 | 0.4 | 0.6 | 0.6 | 0.6 | 0.6 |
DeltaTA | −0.4 | −0.6 | −0.3 | −0.2 | −0.3 | −0.4 | −0.4 |
Number | 10,917 | 4207 | 23,594 | 13,844 | 1562 | 1813 | 55,854 |
Factors/Sites | IT-Cas | JP-Mse | KR-CRK | PH-RiF | US-HRA | US-HRC | US-Twt |
---|---|---|---|---|---|---|---|
TA | 18.7 | 22.0 | 15.7 | 27.4 | 26.8 | 26.6 | 19.1 |
SW_IN | 314.9 | 380.8 | 313.0 | 273.1 | 373.1 | 375.5 | 356.1 |
LW_OUT | 436.1 | 401.8 | 469.8 | 465.8 | 464.0 | ||
VPD | 15.7 | 8.9 | 7.4 | 11.1 | 8.1 | 10.0 | 12.7 |
PA | 100.5 | 101.0 | 99.1 | 100.6 | 100.8 | 100.8 | 101.3 |
WS | 1.2 | 2.3 | 2.4 | 2.1 | 2.5 | 2.5 | 4.3 |
WD | 184.9 | 163.3 | 216.5 | 164.0 | 180.7 | 191.2 | 268.6 |
SWC | 59.1 | 43.4 | 40.0 | 62.3 | 42.1 | 47.7 | |
USTAR | 0.2 | 0.2 | 0.2 | 0.2 | 0.2 | 0.2 | 0.4 |
NETRAD | 192.8 | 195.4 | 195.1 | 246.6 | 253.6 | 191.4 | |
RECO | 4.3 | 3.1 | 3.7 | 4.0 | 5.4 | 5.2 | 4.4 |
H | 25.8 | 20.2 | 23.6 | 23.0 | 9.2 | ||
GPP | 9.1 | 7.9 | 6.6 | 7.5 | 14.5 | 13.3 | 7.1 |
G | −21.7 | 4.9 | 10.9 | 20.6 | 23.7 | 6.7 | |
TS | 17.7 | 20.3 | 14.8 | 28.6 | 18.7 | ||
NDVI | 0.6 | 0.5 | 0.4 | 0.6 | 0.6 | 0.6 | 0.6 |
LE | 101.5 | 163.4 | 101.7 | 120.8 | 154.9 | 148.8 | 148.4 |
NEE | −4.5 | −4.7 | −2.6 | −3.4 | −9.0 | −7.8 | −2.5 |
DeltaTA | −0.6 | −0.6 | −0.4 | −0.2 | −0.3 | −0.4 | −0.4 |
Number | 8258 | 3594 | 18,366 | 9720 | 1326 | 1634 | 49,401 |
Models | RMSE | R2 | MAE | MBE | GRI |
---|---|---|---|---|---|
(mm hr−1) | (mm hr−1) | (mm hr−1) | |||
IT-Cas | |||||
RF | 0.0207 | 0.9240 | 0.0121 | 0.0002 | 3.0000 |
XGBoost | 0.0187 | 0.9377 | 0.0110 | 0.0000 | −1.0000 |
JP-Mse | |||||
RF | 0.0262 | 0.9128 | 0.0163 | 0.0002 | 3.0000 |
XGBoost | 0.0255 | 0.9175 | 0.0157 | 0.0000 | −1.0000 |
KR-CRK | |||||
RF | 0.0250 | 0.8816 | 0.0147 | 0.0004 | 3.0000 |
XGBoost | 0.0248 | 0.8841 | 0.0145 | 0.0000 | −1.0000 |
PH-RiF | |||||
RF | 0.0268 | 0.8906 | 0.0171 | 0.0006 | 3.0000 |
XGBoost | 0.0243 | 0.9098 | 0.0156 | 0.0000 | −1.0000 |
US-HRA | |||||
RF | 0.0269 | 0.9025 | 0.0151 | 0.0003 | 3.0000 |
XGBoost | 0.0255 | 0.9127 | 0.0142 | 0.0000 | −1.0000 |
US-HRC | |||||
RF | 0.0325 | 0.8583 | 0.0174 | −0.0001 | 1.5783 |
XGBoost | 0.0314 | 0.8671 | 0.0169 | −0.0003 | 0.0000 |
US-Twt | |||||
RF | 0.0297 | 0.8980 | 0.0198 | 0.0005 | 3.0000 |
XGBoost | 0.0246 | 0.9301 | 0.0160 | 0.0001 | −1.0000 |
Models | RMSE | R2 | MAE | MBE | GRI |
---|---|---|---|---|---|
(gC m−2 d−1) | (gC m−2 d−1) | (gC m−2 d−1) | |||
IT-Cas | |||||
RF | 9.2419 | 0.9341 | 4.6274 | 0.0623 | 2.0000 |
XGBoost | 9.1589 | 0.9355 | 4.6318 | 0.0429 | 0.0000 |
JP-Mse | |||||
RF | 6.5770 | 0.9581 | 4.2104 | −0.1047 | −0.3422 |
XGBoost | 6.4059 | 0.9603 | 4.1446 | −0.0420 | −1.0000 |
KR-CRK | |||||
RF | 17.4811 | 0.7548 | 8.9706 | 0.0292 | 0.0000 |
XGBoost | 17.5608 | 0.7525 | 9.1083 | 0.0103 | 2.0000 |
PH-RiF | |||||
RF | 10.7097 | 0.9096 | 7.1376 | −0.1542 | 0.4636 |
XGBoost | 9.6703 | 0.9254 | 6.6271 | −0.0326 | −1.0000 |
US-HRA | |||||
RF | 17.6100 | 0.9173 | 8.8268 | 0.3322 | 3.0000 |
XGBoost | 16.7583 | 0.9250 | 8.7333 | 0.2344 | −1.0000 |
US-HRC | |||||
RF | 24.3017 | 0.8196 | 8.3080 | 0.0480 | 1.0000 |
XGBoost | 23.4708 | 0.8286 | 8.8489 | −0.1704 | 1.0000 |
US-Twt | |||||
RF | 7.7431 | 0.9579 | 4.9390 | −0.0023 | −1.0596 |
XGBoost | 6.8748 | 0.9668 | 4.4939 | −0.0012 | −3.0596 |
Models | RMSE | R2 | MAE | MBE | GRI |
---|---|---|---|---|---|
(nmol m−2 s−1) | (nmol m−2 s−1) | (nmol m−2 s−1) | |||
IT-Cas | |||||
RF | 63.3657 | 0.7641 | 29.4863 | 0.7413 | 0.0000 |
XGBoost | 63.5845 | 0.7623 | 30.3872 | −0.4892 | 2.0000 |
JP-Mse | |||||
RF | 36.8322 | 0.8979 | 14.2688 | 0.2430 | 2.0000 |
XGBoost | 30.1109 | 0.9293 | 13.4638 | −0.2704 | 0.0000 |
KR-CRK | |||||
RF | 84.6257 | 0.7677 | 40.3356 | 0.9057 | 3.0000 |
XGBoost | 80.4056 | 0.7893 | 37.5336 | 0.1151 | −1.0000 |
PH-RiF | |||||
RF | 43.9581 | 0.6421 | 18.6736 | 0.6135 | 2.0000 |
XGBoost | 42.2099 | 0.6641 | 18.9505 | −0.0848 | 0.0000 |
US-HRA | |||||
RF | 37.0595 | 0.8292 | 15.0479 | 0.1860 | 1.0000 |
XGBoost | 35.8628 | 0.8408 | 15.0570 | −0.5114 | 1.0000 |
US-HRC | |||||
RF | 28.7857 | 0.9444 | 13.7692 | 0.3039 | 2.0000 |
XGBoost | 28.0140 | 0.9475 | 15.4187 | 0.1520 | 0.0000 |
US-Twt | |||||
RF | 29.5718 | 0.8293 | 14.4098 | 0.2981 | 2.0000 |
XGBoost | 28.9092 | 0.8355 | 14.8292 | 0.0876 | 0.0000 |
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Gu, X.; Yao, L.; Wu, L. Prediction of Water Carbon Fluxes and Emission Causes in Rice Paddies Using Two Tree-Based Ensemble Algorithms. Sustainability 2023, 15, 12333. https://doi.org/10.3390/su151612333
Gu X, Yao L, Wu L. Prediction of Water Carbon Fluxes and Emission Causes in Rice Paddies Using Two Tree-Based Ensemble Algorithms. Sustainability. 2023; 15(16):12333. https://doi.org/10.3390/su151612333
Chicago/Turabian StyleGu, Xinqin, Li Yao, and Lifeng Wu. 2023. "Prediction of Water Carbon Fluxes and Emission Causes in Rice Paddies Using Two Tree-Based Ensemble Algorithms" Sustainability 15, no. 16: 12333. https://doi.org/10.3390/su151612333