EML BASED URBAN FIRE INCIDENT MODELING METHOD AND PROTOTYPE

Precipitation forecasting has potential uncertainty due to data and model uncertainties. Here, an integrated predictive uncertainty modeling framework is proposed by jointly considering data and model uncertainties through an uncertainty propagation theorem. The results indicate an effective predictive uncertainty estimation for precipitation forecasting, indicating the great potential for uncertainty quantification of numerous predictive applications.

The development of effective methods for high-accuracy precipitation estimates over complex terrain and on a daily scale is important for mountainous hydrological applications. This study offers a novel approach called WHU-SGCC by blending rain gauge and satellite data to estimate daily precipitation at 0.05° resolution over the Jinsha River basin, the complicated mountainous terrain with sparse rain gauge data, considering the spatial correlation and historical precipitation characteristics.