It is firmly established in the hydrologic literature that flooding depends on both antecedent watershed wetness and precipitation. One could phrase this relationship as "heavy precipitation does not necessarily lead to high stream discharge", but rarely do studies directly affirm this statement. We have observed several nonhydrologists mistake trends in heavy precipitation as a proxy for trends in riverine flooding. If the relationship between heavy precipitation and high discharge was more often explicitly presented, heavy precipitation may less often be misinterpreted as a proxy for discharge. In this paper, we undertake such an analysis for 390 watersheds across the contiguous U.S. We found that 99th percentile precipitation only results in 99th percentage discharge 36 % of the time. However, when conditioned on soil moisture from the Variable Infiltration Capacity model, 62 % of 99th percentile precipitation results in 99th percentile discharge during wet periods and only 13 % during dry periods. When relating trends in heavy precipitation to hydrologic response, precipitation data should, therefore, be segregated based on concurrent soil moisture. Taking this approach for climate predictions, we found that CMIP-5 atmosphere-ocean global circulation model (AOGCM) simulations for a RCP 6.0 forcing project increases in concurrence of greater than median soil wetness and extreme precipitation in the northern United States and a decrease in the south, suggesting northern regions could see an increase in very high discharges while southern regions could see decreases despite both regions having an increase in extreme precipitation. While the actual outcome is speculative given the uncertainties of the AOGCM's, such an analysis provides a more sophisticated framework from which to evaluate the output as well as historic climate data.
Numerous papers have shown links between >99th percentile hourly precipitation and daily temperature (P extreme versus T), often explained using the Clausius-Clapeyron (CC) relationship. The CC relationship predicts an approximately 7% increase in precipitation intensity per degree celsius. However, recent analyses indicate that the P extreme versus T rate can be larger than the CC prediction. In this work, we analyze the P extreme versus T rate with an automated method across the contiguous U.S. using station data aggregated on a 161 km grid. To evaluate controls on P extreme versus T, we isolate convective storms to evaluate whether greater than CC rates are due to the transition between storm types or are a feature of convective storms at high T. We repeat the analysis using dew point to assess whether T control on extreme P is indeed a matter of moisture availability. When evaluated using both T and dew point, the northeastern U.S. is most likely to exhibit a greater than predicted P extreme versus T rate (57% of the region when using T). At 56% of these points, the > CC rates appeared to occur entirely because of a transition between frontal and convective storms. At 30% of these sites, a greater than CC relationship appeared to occur entirely because of greater than CC scaling in convective intensity. At 11% of sites neither was found to be significant, and at 3% both were found to contribute significantly. This analysis suggests that > CC scaling is not prevalent everywhere in the contiguous U.S., and in regions where it does occur, it can be due to multiple causes.
Much of the work investigating sudden changes in streamflow in the U.S. has used only a small subset of all available gage data and has identified only a single change point in each gage's period of record. In this paper, we apply a change point detection and clustering algorithm that uses all U.S. Geological Survey flow gages with near‐continuous records, detects multiple change points in annual streamflow, and groups change points into geographic clusters which are not predefined by any political or hydrologic boundaries. We identify 17 spatially distinct change point clusters, 14 of which are related to concurrent changes in precipitation. Several geographic regions display multiple clusters, indicating multiple change points in time. The presence of abrupt changes in streamflow suggests that natural variability in the climate signal may be dominating observed streamflow variations in the last 60 years in many locations in the contiguous U.S.
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