New Methodology to Develop Future Flood Frequency under the Changing Climate by Means of Physically-Based Numerical Atmospheric-Hydrologic Modeling

Trinh, T.; Kavvas, M. L.; Ishida, Kei; Fischer, Ida

doi:10.1061/9780784479872.071

Cited by 2 publications

(5 citation statements)

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“…Through a series of nested domains, MM5 is able to downscale coarse global atmospheric datasets down to finer resolutions, on the order of 10 km (Trinh et al, ). This study could be performed by any RCM although MM5 was selected due to its successful application over California as well as the study watershed, SDW (Chen & Dudhia, ; Grubišic, Vellore, & Huggins, ; Ishida et al, ; Jang & Kavvas, ; Kure, Jang, Ohara, Kavvas, & Chen, ; Ohara et al, ; Reeves, Lin, & Rotunno, ; Trinh et al, ).…”

Section: Numerical Coupled Regional Climate‐snow Modelling Descriptionmentioning

confidence: 99%

“…For each GCM, projections of possible emission scenarios under different initial conditions in time horizons of up to 100 years (Cubasch et al, 1992) are made. The first GCM is the CCSM3 in an ongoing series of coupled models developed through international community of students and scientists from universities TABLE 1 Special Report on Emission Scenarios (SRES) scenario descriptions (Trinh et al, 2016a) SRES scenario family Description A1 Rapid economic growth. Global population peaks mid-century at 9 billion in 2050), then declines.…”

Section: Future Climatic Datamentioning

confidence: 99%

“…Although GCMs might be one of the best tools for the estimation of future climate change, the use of GCMs' simulations introduces considerable uncertainty (Dosio & Paruolo, 2011;Teutschbein & FIGURE 7 Monthly climatology of snow water equivalent (SWE) at the eight station locations for three time windows (2011-2040, 2041-2070, and 2071-2100) Seibert, 2012; Trinh et al, 2016a). One recommendation is to use a bias correction method that employs a transformation process for adjusting RCM outputs as inputs to the snow modelling studies.…”

Section: Bias Correctionmentioning

confidence: 99%

“…Previously, most future climate-change impact studies using DD have considered only one or two scenarios in the future with downscaled data at grid resolutions that are normally equal to or larger than 20 km Trinh et al, 2016a). Such grid resolution may still be too coarse for the estimation of snowfall and snowmelt run-off, which usually appears in mountainous regions.…”

Section: Introductionmentioning

confidence: 99%

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Projected 21st century climate change on snow conditions over Shasta Dam watershed by means of dynamical downscaling

Trinh

Kavvas

Ishida

et al. 2017

Hydrological Processes

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Snow is an important component of the Earth's climate system and is particularly vulnerable to global warming. It has been suggested that warmer temperatures may cause significant declines in snow water content and snow cover duration. In this study, snowfall and snowmelt were projected by means of a regional climate model that was coupled to a physically based snow model over Shasta Dam watershed to assess changes in snow water content and snow cover duration during the 21st century. This physically based snow model requires both physical data and future climate projections. These physical data include topography, soils, vegetation, and land use/land cover, which were collected from associated organizations. The future climate projections were dynamically downscaled by means of the regional climate model under 4 emission scenarios simulated by 2 general circulation models (fifth‐generation of the ECHAM general circulation model and the third‐generation atmospheric general circulation model). The downscaled future projections were bias corrected before projecting snowfall and snowmelt processes over Shasta Dam watershed during 2010–2099. This study's results agree with those of previous studies that projected snow water equivalent is decreasing by 50–80% whereas the fraction of precipitation falling as snowfall is decreasing by 15% to 20%. The obtained projection results show that future snow water content will change in both time and space. Furthermore, the results confirm that physical data such as topography, land cover, and atmospheric–hydrologic data are instrumental in the studies on the impact of climate change on the water resources of a region.

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Section: Numerical Coupled Regional Climate‐snow Modelling Descriptionmentioning

confidence: 99%

Section: Future Climatic Datamentioning

confidence: 99%

Section: Bias Correctionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Projected 21st century climate change on snow conditions over Shasta Dam watershed by means of dynamical downscaling

Trinh

Kavvas

Ishida

et al. 2017

Hydrological Processes

View full text Add to dashboard Cite

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“…However, GCMs cannot resolve small scale circulation patterns that often lead to hydrological extremes (Maraun et al., 2010), that is, convective precipitation. Hence, strategies are needed to extract regional or local‐scale projected changes from GCMs, such as through the C‐C relationship (Martel et al., 2021; Schardong et al., 2018), or refining large‐scale information via dynamical (DeGaetano & Castellano, 2017; Giorgi, 2019; Lucas‐Picher et al., 2021; Trinh et al., 2016) or statistical (Cannon et al., 2015; Jeong et al., 2011; Maraun et al., 2010; Papalexiou et al., 2018) downscaling. Recent studies have incorporated future changes in precipitation into IDF curves by combining some of the aforementioned techniques based on simulations from phases 3 to five of the CMIP (Cheng et al., 2014; Cook et al., 2017; DeGaetano & Castellano, 2017; Martel et al., 2021; Ragno et al., 2018).…”

Section: Introductionmentioning

confidence: 99%

Potential Impacts of Future Extreme Precipitation Changes on Flood Engineering Design Across the Contiguous United States

Coelho

Ferreira

Johnston

et al. 2022

Water Resources Research

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The intensification of extreme precipitation in a warming climate is expected to increase flood risk. In order to support flood resilience efforts, it is important to anticipate and quantify potential changes in design standards under future climate conditions. This study assessed how extreme precipitation is expected to change over the 21st century in relation to current National Oceanic and Atmospheric Administration (NOAA) Atlas 14 design standards over the contiguous United States (CONUS). We used the Community Earth System Model Version 2 large ensemble (CESM2‐LE) simulations from the Coupled Model Intercomparison Project Phase 6 and incorporated future changes into flood engineering design standard with a spatially distributed quantile delta mapping method. Relative changes in extreme daily precipitation were computed for multiple average recurrence intervals (ARIs) up to 100‐year and different planning horizons (2020, 2040, 2060, 2080, and 2100). The results indicated an intensification of extreme precipitation by approximately 10%–40% in northern regions and 20%–80% in southern regions by 2100. The current 100‐year ARI with 24‐hr duration from NOAA Atlas 14 is projected to become the 50‐year ARI in the Northern Great Plains, less than the 25‐year ARI in Southwest areas, and approximately the 25‐year ARI in the other regions by 2100. While a nationwide consensus is still needed, this work presents a possible methodology for incorporating climate uncertainty in engineering design. A comparison across major metropolitan areas also illustrates regional variability in projected changes relative to NOAA Atlas 14, suggesting a need for varied local‐scale responses.

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New Methodology to Develop Future Flood Frequency under the Changing Climate by Means of Physically-Based Numerical Atmospheric-Hydrologic Modeling

Cited by 2 publications

References 0 publications

Projected 21st century climate change on snow conditions over Shasta Dam watershed by means of dynamical downscaling

Projected 21st century climate change on snow conditions over Shasta Dam watershed by means of dynamical downscaling

Potential Impacts of Future Extreme Precipitation Changes on Flood Engineering Design Across the Contiguous United States

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