Figure 2. Trends in (a) QMAX, (b)
PMAX, (c) Psm.MAX and (d)
Peff.MAX across each of the 671 CAMELS catchments based
on the normalized Thiel-Sen slope (Tc ). Scatter
plots between Tc values of QMAXand Tc values of (f) PMAX, (g)
Psm.MAX, (h) Peff.MAX are also shown.
(d) Boxplot of the R2 between Tc values of annual floods and Tc values of annual precipitation extremes (see Figure S2 in the Supporting
Information for disaggregation of results across water resources
regions).
3.2 Co-occurrence probability of precipitation extremes and floods
across the CONUS
The low correlation between the spatial pattern of changes in
precipitation extremes and that of floods (discussed in Section 3.1) is
potentially attributable to a weak causal relationship, as there are
other mechanisms that could trigger floods [Blöschl et al. ,
2019; Merz and Blöschl , 2003]. To assess this hypothesis, we
assessed the co-occurrence probability between precipitation extremes
and floods over individual catchments and the results are shown in
Figure 3 (See Figure S3-S5 in the Supporting Information for
QDOYMAX, PDOYMAX,
Psm.DOYMAX, and Peff.DOYMAX across all
catchments). The averaged co-occurrence probability across all
catchments is 32%, 30%, and 37% for PDOYMAX,
Psm,DOYMAX, and Peff.DOYMAX extremes
respectively. This number is consistent with a previous investigation
[Ivancic and Shaw , 2015], indicating that annual
precipitation extremes are only responsible for about one-third of the
annual flood population.