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The relationship between cities and wetland cover varies across the globe, with some cities converting wetlands to low‐ and high‐density urban cover and others preserving, conserving, or restoring wetlands, or constructing new ones. However, the scientific literature lacks studies relating changes in systemic flood risk in an urban stormwater management systems to changes in wetland cover. Furthermore, whether and how such relationships are affected by changing storm intensity under climate change is unknown. We present a case study on the effects of changes in urban wetland extent and storm intensity on flooding in an urban drainage system in Valdivia, Chile, under several co‐produced future scenarios and historical trends of development. We used data derived from stakeholder workshops and historical landcover to determine four plausible scenarios of urban development, plus one business‐as‐usual scenario, in Valdivia through the year 2080. Additionally, we used historical precipitation data and downscaled climate data to estimate event rainfall from extreme storms in the year 2080. We found that system flood volume and time the system was flooded increased with increasing wetland loss and rainfall volume. Mean rate and hour of peak discharge were unaffected by wetland loss. Infiltration's relative role in reducing flooding diminished as wetland loss increased. Cities may still experience dangerous and/or unacceptable flooding even with extensive wetland coverage and will likely need to pair conservation with additional improvements in their stormwater management systems and contributing watersheds.
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This content will become publicly available on June 1, 2026
Amplified Mesoscale and Submesoscale Variability and Increased Concentration of Precipitation under Global Warming over Western North America
Abstract Cold-season precipitation statistics in simulations from the storm-resolving WRF Model at 6-km and 1-h resolution over western North America are analyzed. Pseudo–global warming future simulations for the 2041–80 period, constrained by GCMs under the RCP8.5 scenario, are compared to the 1981–2020 historical simulation. The analysis focuses on the dynamical properties of precipitation time series at subdaily scales and on the morphology of storms. The statistical distribution of precipitation intensities in each pixel of the simulation domain is characterized through nonparametric statistical indicators: frequency of wet hours, mean wet-hour precipitation intensity, and Gini coefficient as a measure of the temporal concentration of the precipitation volume. Additionally, the temporal and spatial Fourier power spectra of precipitation time series and precipitation fields are analyzed. The half-power period (HPP) and half-power wavelength (HPW) are defined as spectral measures of the characteristic scales of precipitation’s temporal and spatial patterns. The results show statistically significant increases in the mean wet-hour precipitation intensity and in the Gini coefficient in 99% of the pixels, indicating that the seasonal precipitation volume becomes more concentrated within a smaller number of hours with higher precipitation intensity. The statistics of change in the frequency of wet hours are more contrasted across the simulation domain. The changes are also reflected in the power spectra, which show the spatial and temporal variability increasing proportionally more with finer spatial and temporal scales and the HPW and HPP decreasing. These projected changes are expected to have consequences, not only in terms of hydrologic impacts but also in terms of the predictability of precipitation patterns. Significance StatementThe precipitation characteristics of winter storms over the western United States and southwestern Canada are analyzed in future climate simulations for the 2041–80 period. As compared to present-day climate, the most intense parts of the storms are projected to produce a higher rainfall volume, with increased concentration over smaller areas and shorter time intervals. The propensity of rainfall intensity to vary rapidly over time will be enhanced in the future according to the simulations. These model predictions imply an increased risk of rapid flooding in small basins. They also suggest that predicting several hours ahead the time and location at which a storm will produce maximum rainfall may become more challenging in the future.
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- Award ID(s):
- 2324008
- PAR ID:
- 10617972
- Publisher / Repository:
- American Meteorological Society
- Date Published:
- Journal Name:
- Journal of Climate
- Volume:
- 38
- Issue:
- 11
- ISSN:
- 0894-8755
- Page Range / eLocation ID:
- 2525 to 2542
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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