Response of Runoff to Meteorological Factors Based on Time-Varying Parameter Vector Autoregressive Model with Stochastic Volatility in Arid and Semi-Arid Area of Weihe River Basin

This study explores the response characteristics of runoff to variability meteorological factors. A modified vector autoregressive (VAR) model is proposed by combining time-varying parameters (TVP) and stochastic volatility (SV). Markov chain Monte Carlo (MCMC) used estimate parameters. The TVP-SV-VAR daily factors established applied series from Linjiacun hydrological station, Shaanxi Province, China. It found that posterior estimates four variables fluctuate significantly with time, variance fluctuations precipitation have strong synchronicity. simultaneous impact evaporation on pulse close 0. Runoff has a positive impulse precipitation, which decreases as lag time increases, negative temperature fluctuation. speed > temperature. avoids hypothesis homoscedasticity allows be randomly variable, improves analysis performance. provides theoretical support for water resource management under conditions climate change.