Storm Sewer Infrastructure Planning with Climate Change Risk: The City of Alexandria Virginia Case Study

2010 ◽  
Vol 5 (4) ◽  
Author(s):  
L. van der Tak ◽  
P. Pasteris ◽  
L. Traynham ◽  
C. Salas ◽  
T. Ajello ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Greenhouse Gas Emission ◽  
Design Criteria ◽  
Precipitation Frequency ◽  
Climate Change Risk ◽  
Design Storm ◽  
Current Design ◽  
The City ◽  
Storm Sewer

The City of Alexandria, Virginia, has experienced repeated and increasingly frequent flooding events attributable to old infrastructure, inconsistent design criteria, and perhaps climate change. The purpose of this project is to provide a program that, over a period of up to 5 years, will analyze storm sewer capacity issues, identify problem areas, develop and prioritize solutions, and provide support for public outreach and education. The purpose of the first task was to review and propose revisions to the City's stormwater design criteria, including benchmarking of design criteria from neighboring jurisdictions, updated precipitation frequency results, evaluation of climate change risk. This paper summarizes potential changes in intensity, duration, and frequency (IDF) values, as well as sea level rise values, that were determined based on the results of general climate models paired with a range (low to high) in greenhouse gas emission scenarios. In addition, modeling of stormwater capacity under current design storm and projected storm intensity for the year 2100 are presented.

scholarly journals Future Flood Hazard Assessment for the City of Pamplona (Spain) Using an Ensemble of Climate Change Projections

Water ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 792
Author(s):  
Marco Lompi ◽  
Luis Mediero ◽  
Enrica Caporali
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Greenhouse Gas Emission ◽  
Time Windows ◽  
Return Periods ◽  
Catchment Scale ◽  
Climate Change Projections ◽  
Rcp 8.5 ◽  
The City ◽  
Peak Discharges

Understanding how the design hyetographs and floods will change in the future is essential for decision making in flood management plans. This study provides a methodology to quantify the expected changes in future hydraulic risks at the catchment scale in the city of Pamplona. It considers climate change projections supplied by 12 climate models, 7 return periods, 2 emission scenarios (representative concentration pathway RCP 4.5 and RCP 8.5), and 3 time windows (2011–2040, 2041–2070, and 2070–2100). The Real-time Interactive Basin Simulator (RIBS) distributed hydrological model is used to simulate rainfall-runoff processes at the catchment scale. The results point to a decrease in design peak discharges for return periods smaller than 10 years and an increase for the 500- and 1000-year floods for both RCPs in the three time windows. The emission scenario RCP 8.5 usually provides the greatest increases in flood quantiles. The increase of design peak discharges is almost 10–30% higher in RCP 8.5 than in RCP 4.5. Change magnitudes for the most extreme events seem to be related to the greenhouse gas emission predictions in each RCP, as the greatest expected changes are found in 2040 for the RCP 4.5 and in 2100 for the RCP 8.5.

scholarly journals Impact of climate change on sediment yield in the Mekong River basin: a case study of the Nam Ou basin, Lao PDR

2013 ◽  
Vol 17 (1) ◽  
pp. 1-20 ◽  
Author(s):  
B. Shrestha ◽  
M. S. Babel ◽  
S. Maskey ◽  
A. van Griensven ◽  
S. Uhlenbrook ◽  
...  
Keyword(s):  
Climate Change ◽  
Sediment Yield ◽  
General Circulation ◽  
Climate Models ◽  
Greenhouse Gas Emission ◽  
Circulation Model ◽  
Sediment Flux ◽  
Seasonal Temperature ◽  
Impact Of Climate Change ◽  
The Impact

Abstract. This paper evaluates the impact of climate change on sediment yield in the Nam Ou basin located in northern Laos. Future climate (temperature and precipitation) from four general circulation models (GCMs) that are found to perform well in the Mekong region and a regional circulation model (PRECIS) are downscaled using a delta change approach. The Soil and Water Assessment Tool (SWAT) is used to assess future changes in sediment flux attributable to climate change. Results indicate up to 3.0 °C shift in seasonal temperature and 27% (decrease) to 41% (increase) in seasonal precipitation. The largest increase in temperature is observed in the dry season while the largest change in precipitation is observed in the wet season. In general, temperature shows increasing trends but changes in precipitation are not unidirectional and vary depending on the greenhouse gas emission scenarios (GHGES), climate models, prediction period and season. The simulation results show that the changes in annual stream discharges are likely to range from a 17% decrease to 66% increase in the future, which will lead to predicted changes in annual sediment yield ranging from a 27% decrease to about 160% increase. Changes in intra-annual (monthly) discharge as well as sediment yield are even greater (−62 to 105% in discharge and −88 to 243% in sediment yield). A higher discharge and sediment flux are expected during the wet seasons, although the highest relative changes are observed during the dry months. The results indicate high uncertainties in the direction and magnitude of changes of discharge as well as sediment yields due to climate change. As the projected climate change impact on sediment varies remarkably between the different climate models, the uncertainty should be taken into account in both sediment management and climate change adaptation.

scholarly journals Contrasting dynamics of hydrological processes in the Volta River basin under global warming

2021 ◽  
Author(s):  
Moctar Dembélé ◽  
Mathieu Vrac ◽  
Natalie Ceperley ◽  
Sander J. Zwart ◽  
Josh Larsen ◽  
...  
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
River Basin ◽  
General Circulation ◽  
Climate Models ◽  
Greenhouse Gas Emission ◽  
Local Population ◽  
Hydrologic Model ◽  
Mitigation Strategies ◽  
Low Flow

Abstract. A comprehensive evaluation of the impacts of climate change on water resources of the West Africa Volta River basin is conducted in this study, as the region is expected to be hardest hit by global warming. A large ensemble of twelve general circulation models (GCM) from CMIP5 that are dynamically downscaled by five regional climate models (RCM) from CORDEX-Africa is used. In total, 43 RCM-GCM combinations are considered under three representative concentration pathways (RCP2.6, RCP4.5 and RCP8.5). The reliability of each of the climate datasets is first evaluated with satellite and reanalysis reference datasets. Subsequently, the Rank Resampling for Distributions and Dependences (R2D2) multivariate bias correction method is applied to the climate datasets. The corrected simulations are then used as input to the fully distributed mesoscale Hydrologic Model (mHM) for hydrological projections over the twenty-first century (1991–2100). Results reveal contrasting changes in the seasonality of rainfall depending on the selected greenhouse gas emission scenarios and the future projection periods. Although air temperature and potential evaporation increase under all RCPs, an increase in the magnitude of all hydrological variables (actual evaporation, total runoff, groundwater recharge, soil moisture and terrestrial water storage) is only projected under RCP8.5. High and low flow analysis suggests an increased flood risk under RCP8.5, particularly in the Black Volta, while hydrological droughts would be recurrent under RCP2.6 and RCP4.5, particularly in the White Volta. Disparities are observed in the spatial patterns of hydroclimatic variables across climatic zones, with higher warming in the Sahelian zone. Therefore, climate change would have severe implications for future water availability with concerns for rain-fed agriculture, thereby weakening the water-energy-food security nexus and amplifying the vulnerability of the local population. The variability between climate models highlights uncertainties in the projections and indicates a need to better represent complex climate features in regional models. These findings could serve as a guideline for both the scientific community to improve climate change projections and for decision makers to elaborate adaptation and mitigation strategies to cope with the consequences of climate change and strengthen regional socio-economic development.

scholarly journals An Investigation of Parameter Sensitivity of Minimum Complexity Earth Simulator

Atmosphere ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 95
Author(s):  
Jiewei Chen ◽  
Huijuan Cui ◽  
Yangyang Xu ◽  
Quansheng Ge
Keyword(s):  
Climate Change ◽  
Sensitivity Analysis ◽  
Climate Models ◽  
Climate Model ◽  
Greenhouse Gas Emission ◽  
Parameter Sensitivity ◽  
Parameter Sensitivity Analysis ◽  
Output Measurement ◽  
Sensitivity Analysis Method ◽  
The Impact

Climate change, induced by human greenhouse gas emission, has already influenced the environment and society. To quantify the impact of human activity on climate change, scientists have developed numerical climate models to simulate the evolution of the climate system, which often contains many parameters. The choice of parameters is of great importance to the reliability of the simulation. Therefore, parameter sensitivity analysis is needed to optimize the parameters for the model so that the physical process of nature can be reasonably simulated. In this study, we analyzed the parameter sensitivity of a simple carbon-cycle energy balance climate model, called the Minimum Complexity Earth Simulator (MiCES), in different periods using a multi-parameter sensitivity analysis method and output measurement method. The results show that the seven parameters related to heat and carbon transferred are most sensitive among all 37 parameters. Then uncertainties of the above key parameters are further analyzed by changing the input emission and temperature, providing reference bounds of parameters with 95% confidence intervals. Furthermore, we found that ocean heat capacity will be more sensitive if the simulation time becomes longer, indicating that ocean influence on climate is stronger in the future.

Statistical evaluation on storm sewer design criteria under climate change in Seoul, South Korea

2013 ◽  
Vol 11 (5) ◽  
pp. 370-378 ◽  
Author(s):  
Jaena Ryu ◽  
Hakpyo Lee ◽  
Soonyu Yu ◽  
Kyoohong Park
Keyword(s):  
Climate Change ◽  
South Korea ◽  
Statistical Evaluation ◽  
Design Criteria ◽  
Storm Sewer

A Hybrid Dynamical–Statistical Downscaling Technique. Part II: End-of-Century Warming Projections Predict a New Climate State in the Los Angeles Region

2015 ◽  
Vol 28 (12) ◽  
pp. 4618-4636 ◽  
Author(s):  
Fengpeng Sun ◽  
Daniel B. Walton ◽  
Alex Hall
Keyword(s):  
Climate Change ◽  
Los Angeles ◽  
Climate Models ◽  
Greenhouse Gas Emission ◽  
Regional Scale ◽  
Global Climate Models ◽  
First Century ◽  
Climate Change Signal ◽  
Uncertainty Estimates ◽  
Twenty First Century

Abstract Using the hybrid downscaling technique developed in part I of this study, temperature changes relative to a baseline period (1981–2000) in the greater Los Angeles region are downscaled for two future time slices: midcentury (2041–60) and end of century (2081–2100). Two representative concentration pathways (RCPs) are considered, corresponding to greenhouse gas emission reductions over coming decades (RCP2.6) and to continued twenty-first-century emissions increases (RCP8.5). All available global climate models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) are downscaled to provide likelihood and uncertainty estimates. By the end of century under RCP8.5, a distinctly new regional climate state emerges: average temperatures will almost certainly be outside the interannual variability range seen in the baseline. Except for the highest elevations and a narrow swath very near the coast, land locations will likely see 60–90 additional extremely hot days per year, effectively adding a new season of extreme heat. In mountainous areas, a majority of the many baseline days with freezing nighttime temperatures will most likely not occur. According to a similarity metric that measures daily temperature variability and the climate change signal, the RCP8.5 end-of-century climate will most likely be only about 50% similar to the baseline. For midcentury under RCP2.6 and RCP8.5 and end of century under RCP2.6, these same measures also indicate a detectable though less significant climatic shift. Therefore, while measures reducing global emissions would not prevent climate change at this regional scale in the coming decades, their impact would be dramatic by the end of the twenty-first century.

scholarly journals Climate change and U.S. agriculture: Accounting for multidimensional slope heterogeneity in panel data

2020 ◽  
Vol 11 (4) ◽  
pp. 1391-1429 ◽  
Author(s):  
Michael Keane ◽  
Timothy Neal
Keyword(s):  
Climate Change ◽  
Panel Data ◽  
Climate Models ◽  
Crop Yields ◽  
Greenhouse Gas Emission ◽  
Weather Conditions ◽  
Weather Data ◽  
Future Climate Change ◽  
Spatial And Temporal Variation ◽  
Local Climate

We study potential impacts of future climate change on U.S. agricultural productivity using county‐level yield and weather data from 1950 to 2015. To account for adaptation of production to different weather conditions, it is crucial to allow for both spatial and temporal variation in the production process mapping weather to crop yields. We present a new panel data estimation technique, called mean observation OLS (MO‐OLS) that allows for spatial and temporal heterogeneity in all regression parameters (intercepts and slopes). Both forms of heterogeneity are important: We find strong evidence that production function parameters adapt to local climate, and also that sensitivity of yield to high temperature declined from 1950–89. We use our estimates to project corn yields to 2100 using 19 climate models and three greenhouse gas emission scenarios. We predict unmitigated climate change will greatly reduce yield. Our mean prediction (over climate models) is that adaptation alone can mitigate 36% of the damage, while emissions reductions consistent with the Paris targets would mitigate 76%.

scholarly journals Mitigation of CH4 emissions in sanitary landfills: An efficient technological arrangement to reduce Greenhouse gas emission.

2021 ◽  
Vol 43 ◽  
pp. e90
Author(s):  
Henrique Rossi Otto ◽  
José Carlos de Jesus Lopes
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Greenhouse Gas Emission ◽  
Ghg Emissions ◽  
Sanitary Landfill ◽  
Gas Emission ◽  
Ch4 Emissions ◽  
Sanitary Landfills ◽  
The City ◽  
Technological Model

Problems related to the solid waste have been shown a relevant subject, by contributing to global warming and climate change. The MSW is one of the main sources of Greenhouse Gases (GHG) emissions, especially the methane gas (CH4). Towards this concern, the general objective of this research is to estimate CH4 emissions produced at the Dom Antonio Barbosa II Sanitary Landfill, situated in the City of Campo Grande, state of MS. Its aim, specifically, is to verify the gravimetric composition of these residues, as well as measure the amount of the MSW already existing and also the volume placed in the mentioned sanitary landfill. The CH4 emissions were estimated in an accumulated total of 2,364,556.28 tCO2eq. It was obtained a total reduction of 1,479,693.87 tCO2eq by methane burning, transforming it into CO2, thus it was possible mitigating the emissions of 62.65% of CH4 generated in DAB II landfill. It is expected that the results from this research contribute to the attenuation of the problems related to the MSW impact on the environment, as well as reflect on the effectiveness of the current adopted technological model.

scholarly journals The Greenland Ice Sheet Response to Transient Climate Change

2011 ◽  
Vol 24 (13) ◽  
pp. 3469-3483 ◽  
Author(s):  
Diandong Ren ◽  
Rong Fu ◽  
Lance M. Leslie ◽  
Jianli Chen ◽  
Clark R. Wilson ◽  
...  
Keyword(s):  
Climate Change ◽  
High Resolution ◽  
Mass Loss ◽  
Climate Models ◽  
Greenhouse Gas Emission ◽  
Global Climate Model ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Surface Flow ◽  
Climate System Model

Abstract This study applies a multiphase, multiple-rheology, scalable, and extensible geofluid model to the Greenland Ice Sheet (GrIS). The model is driven by monthly atmospheric forcing from global climate model simulations. Novel features of the model, referred to as the scalable and extensible geofluid modeling system (SEGMENT-Ice), include using the full Navier–Stokes equations to account for nonlocal dynamic balance and its influence on ice flow, and a granular sliding layer between the bottom ice layer and the lithosphere layer to provide a mechanism for possible large-scale surges in a warmer future climate (granular basal layer is for certain specific regions, though). Monthly climate of SEGMENT-Ice allows an investigation of detailed features such as seasonal melt area extent (SME) over Greenland. The model reproduced reasonably well the annual maximum SME and total ice mass lost rate when compared observations from the Special Sensing Microwave Imager (SSM/I) and Gravity Recovery and Climate Experiment (GRACE) over the past few decades. The SEGMENT-Ice simulations are driven by projections from two relatively high-resolution climate models, the NCAR Community Climate System Model, version 3 (CCSM3) and the Model for Interdisciplinary Research on Climate 3.2, high-resolution version [MIROC3.2(hires)], under a realistic twenty-first-century greenhouse gas emission scenario. They suggest that the surface flow would be enhanced over the entire GrIS owing to a reduction of ice viscosity as the temperature increases, despite the small change in the ice surface topography over the interior of Greenland. With increased surface flow speed, strain heating induces more rapid heating in the ice at levels deeper than due to diffusion alone. Basal sliding, especially for granular sediments, provides an efficient mechanism for fast-glacier acceleration and enhanced mass loss. This mechanism, absent from other models, provides a rapid dynamic response to climate change. Net mass loss estimates from the new model should reach ~220 km3 yr−1 by 2100, significantly higher than estimates by the Intergovernmental Panel on Climate Change (IPCC) Assessment Report 4 (AR4) of ~50–100 km3 yr−1. By 2100, the perennial frozen surface area decreases up to ~60%, to ~7 × 105 km2, indicating a massive expansion of the ablation zone. Ice mass change patterns, particularly along the periphery, are very similar between the two climate models.

scholarly journals Impacts of Climate Change on Rainfall Indices Estimation in Some of Subbasins West of Iran

2017 ◽  
Author(s):  
Hadi Nazaripouya
Keyword(s):  
Climate Change ◽  
Heavy Rainfall ◽  
Climate Models ◽  
Greenhouse Gas Emission ◽  
Coupled Model ◽  
Impact Of Climate Change ◽  
Intensity Index ◽  
Hamedan Province ◽  
Relative Change ◽  
The Impact

Future projections from climate models and recent studies shows impact of climate change on rainfall indices estimation. This study assesses the simulations of rainfall indices based on the Coupled Model Intercomparison Project CMIP5 and CMIP3 in the some of subbasin Hamedan Province West of Iran. The analysis of the rainfall indices are: simple rainfall intensity, very heavy rainfall days, maximum one-day rainfall and rainfall frequency has been carried out in this study to evaluating the impact of climate change on rainfall indices events. Relative change in three rainfall indices is investigated by GCMs under various greenhouse gas emission scenarious A1B and B1 and RCP8.5, RCP8.5 scenarios for the future periods 2020–2045 and 2045-2065. The final results show that each of rainfall indices differs in stations under the three GCMs model (GIAOM, MIHR, MPEH5) and emission scenarios A1B and B1, and RCP2.5, RCP8.5 scenarios. Relative change of daily intensity index varies from -9.93% - 25%, very heavy rainfall days 20.71% - 25.9% and yearly rainfall depth -15.71% - 13% can be observed at study area in 50y for future periods (2046–2065). Rainfall indices of sum wet days, nday >1mm and maximum one-day rainfall are projected to decrease under the senariuos B1,A1B and sum wet days, simple daily intensity and heavy Rainfall days>10 projected to decrease under the RCP2.6.

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