TIGGE/S2S 기반 중장기 토양수분 예측 및 검증
Verification of Mid-/Long-term Forecasted Soil Moisture Dynamics Using TIGGE/S2S
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초록
Developing reliable soil moisture prediction techniques at agricultural regions is a pivotal issue for sustaining stable crop productions. In this study,a physically-based SWAP(Soil-Water-Atmosphere-Plant) model was suggested to estimate soil moisture dynamics at the study sites. ROSETTA was alsointegrated to derive the soil hydraulic properties( , , , , ) as the input variables to SWAP based on the soil information(Sand, Silt andClay-SSC, %). In order to predict the soil moisture dynamics in future, the mid-term TIGGIE(THORPEX Interactive Grand Global Ensemble) andlong-term S2S(Subseasonal to Seasonal) weather forecasts were used, respectively. Our proposed approach was tested at the six study sites ofRDA(Rural Development Administration). The estimated soil moisture values based on the SWAP model matched the measured data with the statisticsof Root Mean Square Error(RMSE: 0.034∼0.069) and Temporal Correlation Coefficient(TCC: 0.735∼0.869) for validation. When we predicted themid-/long-term soil moisture values using the TIGGE(0∼15 days)/S2S(16∼46 days) weather forecasts, the soil moisture estimates showed lessvariations during the TIGGE period while uncertainties were increased for the S2S period. Although uncertainties were relatively increased based onthe increased leading time of S2S compared to those of TIGGE, these results supported the potential use of TIGGE/S2S forecasts in evaluatingagricultural drought. Our proposed approach can be useful for efficient water resources management plans in hydrology, agriculture, etc.
Abstract
Developing reliable soil moisture prediction techniques at agricultural regions is a pivotal issue for sustaining stable crop productions. In this study,a physically-based SWAP(Soil-Water-Atmosphere-Plant) model was suggested to estimate soil moisture dynamics at the study sites. ROSETTA was alsointegrated to derive the soil hydraulic properties( , , , , ) as the input variables to SWAP based on the soil information(Sand, Silt andClay-SSC, %). In order to predict the soil moisture dynamics in future, the mid-term TIGGIE(THORPEX Interactive Grand Global Ensemble) andlong-term S2S(Subseasonal to Seasonal) weather forecasts were used, respectively. Our proposed approach was tested at the six study sites ofRDA(Rural Development Administration). The estimated soil moisture values based on the SWAP model matched the measured data with the statisticsof Root Mean Square Error(RMSE: 0.034∼0.069) and Temporal Correlation Coefficient(TCC: 0.735∼0.869) for validation. When we predicted themid-/long-term soil moisture values using the TIGGE(0∼15 days)/S2S(16∼46 days) weather forecasts, the soil moisture estimates showed lessvariations during the TIGGE period while uncertainties were increased for the S2S period. Although uncertainties were relatively increased based onthe increased leading time of S2S compared to those of TIGGE, these results supported the potential use of TIGGE/S2S forecasts in evaluatingagricultural drought. Our proposed approach can be useful for efficient water resources management plans in hydrology, agriculture, etc.
참고문헌 (18)
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