Our research analyzes the regional changes of extreme dry spell, represented by the annual maximum dry spell length (noted as AMDSL) during the rainy season in the Wei River Basin (WRB) of China for 1960–2014 using the L-moments method. The mean AMDSL values increase from the west to the east of the WRB, suggesting a high dry risk in the east compared to the west in the WRB. To investigate the regional frequency more reasonably, the WRB is clustered into four homogenous subregions via the K-means method and some subjective adjustments. The goodness-of-fit test shows that the GEV, PE3, and GLO distribution can be accepted as the “best-fit” model for subregions 1 and 4, subregion 2, and subregion 3, respectively. The quantiles of AMDSL under various return levels figure out a similar spatial distribution with mean AMDSL. We also find that the dry risk in subregion 2 and subregion 4 might be higher than that in subregion 1. The relationship between ENSO events and extreme dry spell events in the rainy season with cross wavelet analysis method proves that ENSO events play a critical role in triggering extreme dry events during rainy season in the WRB.