Search

Limited research has been directed toward coastal protection infrastructure compared to other types of infrastructure, despite the increasing global population in low-elevated coastal regions and the threats posed by climate change. This paper presents a risk-based asset management framework for coastal protection structures that improves accuracy with each inspection. The framework consists of five components: the Coastal Asset Inventory (CAI), Inspection and Condition Assessment (ICA) module, Backward Markovian Deterioration Model (BMDM), Forward Markovian Deterioration Model (FMDM), and Intervention Policy Engine (IPE). The framework addresses challenges in accurately predicting coastal structure deterioration due to uncertainties in wave loading conditions and the need for frequent inspections. It is applied to rubble-mound breakwaters in Alexandria, Egypt. The BMDM and FMDM models are developed based on inspection data, and the IPE optimizes interventions considering structural condition, risk thresholds, and budget constraints. Results showed that long-term deterioration estimates occur at an accelerated rate with an increase in inspection points, triggering earlier interventions. However, the framework proves reliable even with only two inspection points, allowing asset managing agencies to implement the model based on the structural condition at the year of construction and a minimum of two inspections. The proposed risk-based asset management framework provided a comprehensive approach to managing coastal protection infrastructure, reducing risks to life and property. By accurately predicting deterioration and optimizing intervention decisions, the framework can greatly assist in the effective management and maintenance of coastal assets. This is vital in ensuring the safety of coastal populations facing global climate change and demographic growth. Coastal protection structures are crucial for safeguarding coastal populations in the face of climate change and demographic growth. This research paper introduces a risk-based asset management framework for coastal protection structures, with practical applications for coastal management agencies and practitioners. The framework addresses the challenges of predicting coastal structure deterioration and optimizing intervention decisions. The framework consists of five components: the Coastal Asset Inventory (CAI), Inspection and Condition Assessment (ICA), Backward Markovian Deterioration Model (BMDM), Forward Markovian Deterioration Model (FMDM), and Intervention Policy Engine (IPE). It has been successfully applied to rubble-mound breakwaters in Alexandria, Egypt. The practical implications are significant: The framework enables asset managers to make informed decisions on coastal infrastructure maintenance and interventions, reducing risks to life and property. It provides a comprehensive approach to managing coastal protection infrastructure and ensuring the safety of coastal populations. By accurately predicting deterioration and optimizing interventions, the framework supports effective management and maintenance of coastal assets. Its reliability and flexibility make it a valuable tool for coastal management practitioners, promoting sustainable development and safeguarding coastal areas. With its potential for broader application, this risk-based asset management framework offers practical solutions for coastal protection worldwide. [ABSTRACT FROM AUTHOR]

Electric power systems face heightened risks from climate change, on top of existing challenges like aging infrastructure, regulatory shifts, and cybersecurity threats. This paper explores how advanced technologies, including smart grids, artificial intelligence (AI), and machine learning, (ML), enhance the resilience of power systems against climate-driven extreme weather events. Drawing insights from resilience theory, the paper presents a state-of-the-art review of the literature on power system resilience, highlighting the escalating vulnerabilities of energy systems to weather-related disruptions. Although utilities currently use technologies like automated meter reading and advanced metering infrastructure to collect vital grid performance data, the lack of strategic collaboration often impedes effective data governance and sharing, thus undermining efficient responses to climate threats. The paper underscores the significance of distributed energy resources, long-duration energy storage, microgrids, and demand-side management. It further illustrates how AI and ML optimize smart grids to support these strategies. Proactive integration of smart grids with advanced technologies could significantly reduce climate-related costs compared to non-adaptive methods. Such proactive grid resilience strategies not only climate-proof energy infrastructure against climatic changes but also herald a modern, placed-based industrial transformation. Climate change exacerbates challenges in our energy systems, from aging infrastructure and a constantly shifting regulatory environment to cybersecurity risks and diversifying energy portfolios. Addressing these issues requires strategic investment in modern infrastructure, particularly smart grids enhanced by advanced technologies like artificial intelligence (AI) and machine learning (ML). These technologies are vital for enhancing power system resilience against climate impacts. Automated systems such as automated meter infrastructure (AMI) and supervisory control and data acquisition (SCADA) provide real-time data crucial for managing extreme weather events. AI and ML contribute to predictive maintenance, preventing failures and blackouts. They also forecast grid loads during severe weather, facilitating proactive power distribution management to prevent blackouts. This comprehensive improvement in situational awareness promotes economic growth in the energy sector and supports sustainable, climate-resilient transformation. AI and ML not only improve energy distribution and efficiency but also promote conservation efforts and ensure reliable energy amidst a changing climate. Collaboration among utility managers, regulators, and governments is key, focusing on data access, verification, and adaptability. Strategies should be tailored to each utility's unique challenges. Moreover, establishing technical standards is critical for enhancing power grid resilience against climate-induced extreme weather events. [ABSTRACT FROM AUTHOR]

The global rise in urban energy demand poses severe environmental and economic health challenges. We need adaptive policies in urban planning to reduce the need for urban energy. This has become a prominent agenda in urban planning, encompassing social (education and innovation in consumption), economic (real pricing), and physical (urban morphology) aspects. This research aims to investigate the influential role of urban form, particularly the physical environment, on energy performance. The methodological approach is centered on conducting analytical-comparative research to examine how urban form influences theoretical energy requirements. Yazd City is selected as a case study because of its distinctive features and traditional approaches to urban sustainability, which have been largely overlooked in previous energy consumption investigations. In a broader comparative context, five tissue types (morphological units) have been selected from Rome, Barcelona, Madrid, and Venice and used as the analytical basis of the study. The research categorizes urban forms into three levels: macro (fabric), medium (block), and micro (building patterns). Heating, cooling, and total energy consumption were computed at each level. The findings indicate that, at the macroscale, the Barcelona fabric offers the highest potential for adaptation in the hot, dry climate of Yazd City. Moreover, the paper analyzes the most recurring morphological indices in the tissues and proposes guidelines for new developments tailored to Yazd City's unique climatic conditions. By focusing on urban form's impact on energy performance, this research contributes to the broader understanding of sustainable urban planning. It offers valuable insights for energy-sensitive urban development in other contexts facing similar climate challenges. [ABSTRACT FROM AUTHOR]

Building simulation tools can empower architects to evaluate and optimize the performance of their designs. Therefore, it is essential to integrate building performance simulation modeling from an early design stage. A critical part of the simulated environment is the weather file. It is a compilation of 20–30 years of historical weather and hourly data on temperature, solar radiation, wind speed, and wind direction. The accuracy and contextual relevance of said data are of utmost importance to the integrity of the analysis. Current energy modeling weather files are unlikely to include any indication of risk from potential climate change. Hence, there is a need to incorporate climate change projections in energy simulations and prepare architects to understand better the evolution of design strategies echoing such climate change in different climate zones. This paper describes the process of using the CCWorldWeatherGen tool to morph Energy Plus Weather files of 17 North American cities in key climate zones into three simulated scenarios representing 2020, 2050, and 2080, corresponding to a 1.5°C global temperature rise. By simulating the impact of the morphed weather files on five commercial building models, this paper outlines a database echoing the projected climate change impacts within the selected locations and highlights the critical impact of passive design strategies in facilitating indoor thermal comfort while limiting energy consumption. [ABSTRACT FROM AUTHOR]

A transportation system stress test is a set of one or more hypothetical scenarios designed to help determine if a transport system can continue to provide an acceptable level of service when subjected to one or more potentially disruptive events. Stress tests, if done well, enable policy makers, regulators, and network operators to assess the ability of transport systems to withstand and recover from potentially disruptive events, and modify the systems if necessary. Although work has been conducted on how to conduct high-level preliminary transportation stress tests, there has not yet been work conducted on how to conduct detailed quantitative simulation-based stress tests on transportation systems. This paper fills this gap by presenting both an approach to conduct simulation-based stress tests and example simulation-based stress tests for a transportation system subject to potentially disruptive hydrometeorological events. Three types of stress tests are conducted for the transportation system in the region of Chur, Switzerland, which is subject to heavy rainfalls that may result in floods and landslides. These include the stress caused by climate change leading to increasing the intensity of extreme rainfall events in the future, stress caused by uncertain future mobility behavior of people leading to excessive travel demand on the network, and stress caused by poor planning of the required resources for restoration interventions leading to having less resources for restoration than planned. It is argued that conducting such stress tests makes it clear to decision makers whether or not a transportation system is sufficiently resilient against various stressors, and if not, gives clear indications as to how it could be improved. [ABSTRACT FROM AUTHOR]

In light of the challenges posed by climate change and rural revitalization, high-quality construction in rural areas is facing significant obstacles from rainstorm flooding. This study adopts a regional disaster system analysis framework and examines the characteristics of rural rainstorm flooding disasters, including the instability of the breeding environment, the hazard characteristics, and the vulnerability of the exposure. Using this framework, we explore the various causes of rainstorm flooding in rural China, assess the effectiveness of responses to these disasters, and examine the differences between urban and rural responses. Our analysis reveals that the increase in rainstorm flooding in rural China is a complex result of multiple factors, including increased risk, instability, and vulnerability. While rural areas have made some progress in monitoring and responding to rainstorm flooding disasters, they remain weaker than cities in terms of governance and disaster management systems. To address these challenges, we recommend increased attention to rural flood control and disaster reduction, stronger preparation for disaster prevention and reduction plans, enhanced rural disaster infrastructure defense, increased financial support for water conservancy projects, and stronger professional emergency response teams, disaster relief equipment, and materials. Additionally, we recommend strengthening disaster prevention and reduction education and publicity among rural residents to promote the ability to self-rescue and mutual rescue. The disastrous impact of climate change and resulting extreme weather events on rural areas has become increasingly evident in recent years. China's vast rural areas have been particularly affected by frequent rainstorm flooding disasters. This paper identifies the increase in rainstorms, the instability of the disaster breeding environment in rural areas, and the increased vulnerability of exposures in these areas as the main reasons behind the intensification of rural rainstorm flooding. To mitigate the impact of these disasters, attention should be paid to natural disaster risk management, normalized flood control, and disaster reduction in rural areas. This requires overall coordination of rural disaster prevention and reduction planning, emphasis on improving the defense capacity of rural areas, increasing financial support for defensive water conservancy projects, promoting the construction of professional emergency rescue teams in rural areas, scientifically distributing flood prevention and disaster relief equipment and materials, strengthening publicity and education on disaster prevention and reduction, and enhancing rural disaster prevention awareness and self-rescue and mutual rescue capabilities. [ABSTRACT FROM AUTHOR]

Climate change (CC) is considered one of the most critical threats to human lives and activities due to dramatic increases in the frequency and severity of droughts and floods under global warming. To alleviate such impacts, many studies on CC adaptation strategies in water management have emerged. This review covers 131 relevant studies published over the past two decades. It aims to robustly synthesize the applied strategies/techniques and identify findings and gaps. In addition, a bibliometric analysis is performed to describe the co-citation network and statistical characteristics of the reviewed papers and identify the related research clusters. A typical procedure for CC adaptation studies is proposed based on previous studies. It is found that systems reoperation was preferred for CC adaptation in water resources management, specifically by updating the reservoir operation curves using optimization algorithms. However, low impact development (LID) measures were favored in storm drainage and flood mitigation systems. As for future relevant research, the main recommendations are integrating environmental, social, and economic aspects in evaluating CC adaptation strategies and incorporating land use and land cover (LULC) and water demand changes in CC adaptation studies. This state-of-the-art review represents essential information for improving CC adaptation strategies in water management. [ABSTRACT FROM AUTHOR]

With the ever-increasing emphasis on climate change and sustainability, there is growing interest in using environmentally friendly coastal structures. In addition to engineering and cost factors, the construction global warming potential (GWP) can and should be an influencing factor in the selection and design of the structures. Therefore, knowledge of construction GWP facilitates informed decision-making in coastal projects to achieve climate goals. Considering the number of Icelandic-type berm breakwater (IceBB) structures worldwide, this structure's design method is commonly accepted in coastal protection projects. In this paper, the construction process of an IceBB was assessed for its GWP and compared with concrete armor unit protection of a conventional rubble mound breakwater (ConRMB). The assessment and comparison were made for constructing a breakwater to protect the port of Thorlakshofn in southwest Iceland. The life cycle assessment (LCA) methodology was applied to calculate the construction carbon footprint of the structures using GaBi software, version 10.6.1. Using the International Union for Conservation of Nature (IUCN) criteria for nature-based solutions (NBS) and based on the existing literature, the characteristics of IceBB were briefly explored. The results showed that the construction of IceBB has a lower GWP than ConRMB, mainly due to using natural rock armor instead of concrete armor units. Furthermore, the results indicated that IceBB characteristics meet the IUCN criteria for NBS and thus can be granted as a (hard) NBS coastal structure. Acknowledging the advantages of IceBB, adopting this structure in coastal protection projects could meaningfully contribute to climate change mitigating policies. [ABSTRACT FROM AUTHOR]

Reducing carbon emissions in the construction sector is essential in a period of climate emergency. Disassembly and reuse of structural members are considered to reduce the carbon emissions from the construction and deconstruction of buildings. In this context, it is important to review the current state of the art to provide a framework for the development of future structural systems that can enable the easy disassembly and reuse of steel-framed buildings. This paper (1) presents a review of more than 100 documents to discuss the feasibility of disassembly and reuse of structural members; (2) develops detailed schematic illustrations to explain the design concepts and the underlying mechanics governing the behavior of demountable connections; (3) sheds lights on the technical and design challenges to implement disassembly and reuse of the structural members; and (4) defines future research needs to facilitate the disassembly and reuse of the structural members. [ABSTRACT FROM AUTHOR]

The effects of global climate change are already observed in coastal communities, and one of the key impacts of climate change is sea level rise (SLR). Such increases in sea level are expected to have large impacts on transportation infrastructure and result in region-wide commute disruption. Studies and adaptation strategies in coastal areas will allow decision-makers to take better actions against SLR. The present paper uses the San Francisco Bay Area as a case study. The study quantifies the interregional traffic delay of commuters due to the inundation of shoreline protection segments of the Bay Area. The approach is based on the marginal effect of protection within San Francisco Bay where individual stretches of coastline known as operational landscape units (OLUs) are protected one at a time. In the study, we integrate detailed shoreline scenarios, coastal inundation modeling, and traffic disruption modeling. Important insights from the analysis are obtained: the protection of an OLU (and specifically San Rafael OLU) will produce an average commute time reduction of up to 17% in the neighboring areas or the neighborhoods located across the bay. Five OLUs along with four bridges were identified as critical for minimizing disruptions to commute times. This methodology may be used by decision-makers when proposing adaptation and protection strategies that account for both local and regional areas. [ABSTRACT FROM AUTHOR]

From the Rocky Mountains in the US to the Sea of Cortez in Mexico, the Colorado River is one of the most managed and monitored rivers in the world. As decreasing river flows from drought and climate change continue to impact the Colorado River Basin, the US federal government, seven US states, and Mexico have signed agreements that would reduce deliveries, including a Drought Contingency Plan (DCP), an agreement among the US states and the Bureau of Reclamation, and Minute 323 (a treaty agreement between the US and Mexico). As part of the DCP, the US Bureau of Reclamation (Reclamation) committed to increasing conservation efforts to augment storage in Lake Mead. This paper presents an analysis of Reclamation's Decree Accounting Reports that record water deliveries and conservation savings from 1964 to 2019. Overall, this analysis illustrates that (1) the agency has implemented significant conservation actions over the last three decades, (2) the agency has responded to increased accounting needs as dictated by national and international management agreements, (3) some actions have resulted in environmental costs, and (4) future actions could be designed to avoid environmental harms while also augmenting Lake Mead levels. As climate change continues to constrain Colorado River water supply, detailed accounting may help reveal areas for potential efficiencies or demonstrate where the greatest levels of savings have been reached while ensuring that environmental and social benefits are preserved. Over the last 100 years, humans have changed the path and personality of the Colorado River by distributing water to cities, communities, and agricultural fields to support over 40 million people. Throughout the twentieth century, the US federal government, seven US, and Mexico signed agreements enabling development of Colorado River water. By the early 21st century, as it became evident that water demands and climate change were reducing available supplies, these same governments signed agreements to reduce pressure on the river. All these agreements have, in part, been tracked by the US federal agency that manages the river, the Bureau of Reclamation (Reclamation), through Decree Accounting Reports. Since 1964, these reports have recorded how water is or is not accounted for that might be important to the future of the river. This paper examines those reports and reveals four main findings: (1) Reclamation has implemented numerous water conservation projects, (2) they have responded to new management agreements, (3) some of their actions have impacted the environment, and (4) there are proactive ways they can reduce environmental impacts and bolster water supplies in the future. [ABSTRACT FROM AUTHOR]

Flood embankments are generally designed by assuming steady-state flow conditions and dry soil above the phreatic surface. However, steady-state conditions are rarely achieved and a significant portion of the embankment remains unsaturated upon a flood event. If transient water flow and partial saturation are considered, the flood embankment can be designed with steeper slopes on the landside, which may lead to significant savings in terms of earthfill material (i.e., embodied carbon) and footprint (i.e., habitat suppression and expropriation costs). This paper examines the case of flood embankments in the tidal area of the Elbe River in Germany. These embankments must be retrofitted by raising their crest from 5 to 7 m because of the new projection of extreme river levels due to climate change. In this paper, the conventional "prescriptive" design consisting of raising the embankment by maintaining the 1:3 inclination of the landside slope is compared with the "performance-based" design where the inclination of the slope on the landside could be potentially increased up to 1:1, which is shown to be sustainable if partial saturation and transient water flow are considered. Raising the flood embankment with 1:1 landside slope (rather than 1:3) could lead to expropriation cost savings on the order of €3.9 M/km. For the case of a newly built embankment of 7 m height, the saving would become €4.5 M/km. An approximate estimation of embodied carbon suggests that the carbon saving would be on the order of 3,100–4,200 tCO2e/km. [ABSTRACT FROM AUTHOR]

The Chinese government continues to contribute to tackling the global climate challenge and plans to continue lowering carbon emissions in the transportation infrastructure field. The comprehensive assessment of the impact of carbon emissions is mainly focused on high-speed railways (HSRs). This paper proposes a life-cycle cost considering carbon emissions (LCCCCE) model for HSR projects, which consists of a general life-cycle cost (GLCC) model and a quantified carbon emissions cost (CEC) model. The Beijing-Shanghai HSR is employed as a case study, in which the LCCCCE and sensitivity of carbon emission factors are analyzed using the proposed methodology. The results show that the LCCCCE of the Beijing-Shanghai HSR is 64.56 billion USD, and that its CEC is 1.04 billion USD, which contributes 1.61% to the LCCCCE. Thus, the LCCCCE analysis of HSRs or transportation infrastructure projects is an effective methodology to quantify the impacts of carbon emissions in China and around the world. [ABSTRACT FROM AUTHOR]

The US Gulf and Atlantic coasts are often struck by severe hurricanes that cause massive economic and life losses. Climate change and structural aging are expected to exacerbate the risk associated with hurricane hazards. Appropriate methodologies are needed to assess and mitigate these effects through improved design and retrofit solutions that rigorously account for the associated uncertainties, such as performance-based engineering methodologies. This paper extends the performance-based hurricane engineering (PBHE) framework to account for the hazard nonstationarity induced by climate change effects. The newly extended nonstationary PBHE framework was implemented by performing a loss analysis on a benchmark low-rise single-family house over a 50-year design service life, for which climate change effects were accounted for by using a recently developed predictive model for hurricane wind speed distributions. The effects of different modeling assumptions and solution approaches (including approximate estimates, time discretization, interpolation techniques, and models for annual discount rates), different locations, and different climate change scenarios on the means and standard deviations of the total losses were investigated. The performance comparison of different storm mitigation strategies was also performed as an application example. In general, the proposed methodology provides consistent results under different modeling assumptions; however, the modeling assumptions for the annual discount rates can affect significantly the results. Based on the analysis results and within the limitations of the present implementation of the nonstationary performance-based hurricane engineering framework, climate change effects are generally significant, with estimated increases contained between 13.2% and 38.1% for the total loss means, and between 2.5% and 12.4% for the standard deviations of the total losses for the benchmark structure at the reference location of Pinellas Park, Florida. The extended nonstationary PBHE framework was able to identify the optimal retrofit strategy in terms of costs and benefits for any given combination of structures, residential developments, locations, and climate scenarios. The proposed nonstationary PBHE framework represents an advancement in performance-based engineering because it provides a rigorous approach to account for climate change effects. This framework has immediate practical applications, such as those shown in this paper, and could be further extended to other natural and human-made hazards. [ABSTRACT FROM AUTHOR]

Climate change continues to cause frequent storms, droughts, floods, and other extreme weather events, and these events are affecting transport infrastructure assets around the world. Despite broad recognition that climate change is a significant threat to infrastructure, the traditional asset management process does not explicitly consider it. The upshot is that asset management decisions, at the current time, may not be helping to reduce the risk of climate change–related infrastructure failure. This paper describes a step-by-step framework to integrate the risk of infrastructure failure due to climate change into transportation asset management (TAM) practices. This framework incorporates methods for risk assessment, needs estimation, and climate change scenario analyses that one can apply to the management of infrastructure assets. The paper also presents an example to quantify the risk of climate change–related bridge failure. This example demonstrates the applicability of the framework to infrastructure management decision support at the network level. [ABSTRACT FROM AUTHOR]

This paper examines the life-cycle wind resistant performance of a constructed long-span suspension bridge in the coastal region of China, aiming to quantify the multisource time-variant effects and uncertainties and offering a reference for designs of long-span bridges in the future. Randomness from modal frequencies, damping ratios, and identification uncertainty of flutter derivatives (FDs) was considered; then, their effects on probability of flutter failure and probability of exceeding the predefined buffeting response root-mean square (RMS) are discussed. Firstly, results of full-track tropical cyclone (TC) simulation under various climate warming scenarios are reviewed; then, the time-variant probability density function (PDF) of annual extreme wind speed is discussed. Secondly, 6-year modal frequencies and damping ratios of a long-span suspension bridge with a center-slotted section were extracted by fast Bayesian FFT method with structural health monitoring (SHM) data, which were utilized to explore the deterioration rules of structural properties. Thirdly, FDs were modeled from a probabilistic perspective based on complex Wishart distribution, which were identified in the turbulent flow and the frequency domain by Bayesian inference. The posterior distributions of FDs, namely identification uncertainty, were quantified by Markov chain Monte Carlo (MCMC) sampling. This paper finds that for flutter resistant performance, the time-variant effects (i.e., modal frequencies and PDFs of extreme wind speed) will make the flutter failure probability seven times larger than the initial value; for the probability of exceeding the predefined buffeting response RMS, however, the time-variant effects will make a negligible difference. [ABSTRACT FROM AUTHOR]

This paper reviews the development of snow load research since the contemporary introduction and calibration of the ANSI A58-1982 provisions (and subsequent ASCE 7-88). The ASCE 77-88 ground snow loads were based on the data and methods available at the time and subsequently updated in 1995. The provided loads are based on 50-year mean recurrence intervals, with design loads for each category being obtained through a combination of partial safety and importance factors. Changes and improvements in snow load design over the last 40 year necessitate a reconsideration of the original calibration of these safety and importance factors. This paper discusses the need for a movement away from a uniform-hazard snow load design approach in combination with uniform load and importance factors, in favor of reliability-targeted design snow loads. This paper reviews the concept of reliability targeted loads as a means of meeting the ASCE 7 goal of uniform risk/reliability in the US. This paper further describes the incremental changes in both reliability and snow load research that will culminate in a change from uniform hazard (i.e. 50-year) loads to uniform-reliability loads. The purpose of this paper is to describe the motivation for, and historical context of E 7, the forthcoming changes to design ground snow loads in ASCE 7-22. Furthermore, the paper discusses the future of snow load prediction and its impact on the engineer and the code, particularly in regards to the implications of climate change for future snow load design. [ABSTRACT FROM AUTHOR]

Forum papers are thought-provoking opinion pieces or essays founded in fact, sometimes containing speculation, on a civil engineering topic of general interest and relevance to the readership of the journal. The views expressed in this Forum article do not necessarily reflect the views of ASCE or the Editorial Board of the journal. [ABSTRACT FROM AUTHOR]

Bridges play a crucial role in modern societies, regardless of their culture, geographical location, or economic development. The safest, most economical, and most resilient bridges are those that are well managed and maintained. Recently, climate change has been posed as one of the greatest concerns for the health of bridges. Although the uncertainty associated with the magnitude of the change is large, the fact that our climate is changing is unequivocal. As a result, making bridges resilient to climate change is a priority for the authorities. A well-planned early intervention may save lives and money. Until now, the focus of scientific research has mostly been on the climate science, but any practical plan for the adaptation of bridges has to be rooted in other disciplines, including physics, chemistry, engineering, economics, and finance. Therefore, the goal of this paper is to review the work already done from climate change to bridges and set a roadmap for an integrated assessment approach to the adaptation of bridges to climate change. This approach is grounded in a probabilistic- and physics-based framework able to prioritize bridge adaptation measures as a function of bridge location, climate scenario, impact, vulnerability, risk, and cost in order to assist the authorities in the decision-making process. Because adaptation to climate change is highly context-specific, this approach is mainly focused on concrete bridges. Structural health monitoring technology is proposed as a mechanism for assessing and continuously evaluating the structural condition of bridges and for triggering adaptation measures as a function of the predicted severity of climate change. [ABSTRACT FROM AUTHOR]

This paper provides an outlook on the effects of climate change and the severity and frequency of extreme weather events on the performance of flexible pavements across North America. Now more than ever, the climate is changing at a rapid pace, which will alter long-term environmental loading parameters and extreme weather events. Such alterations will pose implications for the design, maintenance, and rehabilitation of flexible pavements, especially in terms of their serviceability, safety, and functionality. In northern Canada, roads are founded on various terrain types, including thaw-sensitive ice-rich permafrost underlying terrains. Such roads have experienced signs of embankment and pavement damage, which are usually induced by the degradation of the underlying permafrost due to climate change. Therefore, the development and implementation of new permafrost thaw mitigation techniques for vulnerable roads are essential and will be discussed in this paper. Resilient flexible roads should be designed to withstand the conditions that are likely to occur during their design life, taking into account the impact of the climate change on pavement performance in response to daily and seasonal changes in heat, precipitation, freeze–thaw cycles, and extreme weather events. [ABSTRACT FROM AUTHOR]

Adapting reservoir operation to a changing climate is important to improve water system performance toward benefits including water security, and energy production. However, managers still need to know if and how reoperation can also assist long-term mitigation of climate change impacts on aquatic ecosystems, creating, for example, opportunities to revert fish migration and recruitment losses. This paper investigates the operational adaptive capacity of water systems to mitigate climate change impacts on both hydropower and aquatic ecosystems, with a detailed representation of fish species recruitment response to flow regime changes. The methodology framework combines hydroclimatic modeling, explicit stochastic reservoir operation modeling, and predictive modeling of migratory fish recruitment abundance, illustrated using the large-scale hydropower system of the Paraná River Basin in Brazil. Results identified that operating policies can be adapted to improve hydropower production under a changing climate with drier conditions by 2% to 8% compared with current operating policies. Although insufficient to eliminate all energy losses that climate change may cause, the optimized operation provided flexibility to adjust flow releases and reduce the likelihood of future severe multiyear deficits, which are very harmful to fish populations. Adapting operation to climate change sacrificed fish recruitment performance over a few years of the time horizon to maintain an overall higher storage, but it also improved the chances of producing flow releases in magnitude, timing, and duration during long drier periods that prevented more severe impacts of climate change on fish recruitment and population. This indicates that it might be possible to have synergies in adapting reservoir operation to not only prevent energy losses, but also to improve fish recruitment under climate change. The ecosystem resiliency under adapted operation increased up to 2 times compared with the isolated climate change effect. [ABSTRACT FROM AUTHOR]

There has been a rapid development of the nuclear industry on account of climatic change caused by global warming. The most favorable rocky sites for nuclear power plants are exhausted worldwide, and now nuclear facilities are proposed on soil sites. In a soil site, a combined piled raft foundation (CPRF) system can provide the desired level of performance for a nuclear structure under seismic loading conditions. The combined system of the nuclear structure with the CPRF involves complex dynamic interactions between the pile, soil, raft, and the superstructure. In the existing literature, the dynamic behavior of the CPRF system supporting massive and stiff structures is not well studied and investigated. Due to the highly nonlinear dynamic characteristic of the CPRF system supporting massive and stiff reactor buildings, this paper adopts interface nonlinearities (separation and sliding) through the master and slave concept, concrete and reinforcement material nonlinearities through the concrete damage plasticity model for piles and superstructures, and an equivalent linear approach considering soil degradation and damping with Mohr–Coulomb postyielding hardening behavior for the soil. After the successful validation of the modeling approach with the results of the experimental testing, the different aspects of the CPRF of reactor building are investigated, such as amplification, pile and raft behavior, pile–raft coefficient, separation and sliding, contact pressure, nonlinearity in the piles, and the response of the superstructure. This study indicates that the peripheral piles of the CPRF system could prevent the separation of the raft from the soil. The numerical result shows that damage in the CPRF system occurs near the top portion of the pile. The presented procedure to develop the combined model for the seismic analysis in the time domain could help to formulate guidelines for safety-related nuclear structures resting on the CPRF system. Several countries are planning and building new nuclear reactors to meet their increasing demand for clean electricity. The most favorable rocky sites to construct nuclear power plants are exhausted worldwide; therefore, some upcoming nuclear reactors are supported on a soil site. The seismic safety of nuclear power plants is paramount because their failure may cause disasters. Hence, the problem of soil–structure interaction becomes vital for nuclear power plants (NPPs) due to the building of nuclear structures under unfavorable ground conditions. The present study describes the methodology to assess piled raft–supported NPP behavior under extreme earthquake events. The presented approach will be helpful to consultants and designers working in the nuclear field. The present study will help to formulate guidelines for the seismic safety of NPPs that rest on soil sites. [ABSTRACT FROM AUTHOR]

One of the most important impacts of a future warmer climate is the projected increase in the frequency and intensity of extreme rainfall events. This increasing trend in extreme rainfall is seen in both the observational record and climate model projections. However, a thorough review of the recent scientific literature paints a complex picture in which the intensification of rainfall extremes depends on a multitude of factors. While some projected rainfall indices follow the Clausius-Clapeyron relationship scaling of an ∼7% increase in rainfall per 1°C of warming, there is substantial evidence that this scaling depends on rainfall extremes frequency, with longer return period events seeing larger increases, leading to super Clausius-Clapeyron scaling in some cases. The intensification of extreme rainfall events is now well documented at the daily scale but is less clear at the subdaily scale. In recent years, climate model simulations at a finer spatial and temporal resolution, including convection-permitting models, have provided more reliable projections of subdaily rainfall. Recent analyses indicate that rainfall scaling may also increase as a function of duration, such that shorter-duration, longer return period events will likely see the largest rainfall increases in a warmer climate. This has broad implications on the design and the use of rainfall intensity–duration–frequency (IDF) curves, for which both an overall increase in magnitude and a steepening can now be predicted. This paper also presents an overview of measures that have been adopted by various governing bodies to adapt IDF curves to the changing climate. Current measures vary from multiplying historical design rainfall by a simple constant percentage to modulating correction factors based on return periods and to scaling them to the Clausius-Clapeyron relationship based on projected temperature increases. All of these current measures fail to recognize a possible super Clausius-Clapeyron scaling of extreme rainfall and, perhaps more importantly, the increasing scaling toward shorter-duration rainfall and the most extreme rainfall events that will significantly impact stormwater runoff in cities and in small rural catchments. This paper discusses the remaining scientific gaps and offers technical recommendations for practitioners on how to adapt IDF curves to improve climate resilience. [ABSTRACT FROM AUTHOR]

Infrastructure systems are critical to the normal functioning of our modern communities, enabling access to essential resources and services and also providing a platform for social and economic growth. These systems are currently being subjected to a multitude of challenges and must, therefore, adapt to ensure the needs of society can continue to be met. Perhaps the most problematic of these challenges is climate change. The high level of uncertainty within long-term climate projections means that they cannot reliably be used as a basis for informed decisions to permanently alter existing assets or change the design of infrastructure assets (through alteration to design codes, for example). Therefore, we need new tools to ensure our infrastructure systems are resilient by using adaptable approaches, which do not require accurate long-term climate scenarios to inform decisions. This paper develops a modified location-allocation modeling approach, which can provide an adaptive solution that utilizes deployable resources to increase the resilience of infrastructure systems. Specifically, this approach can be applied to indicate the optimal location to store resources so as to ensure a baseline level of service to our communities, either through the protection of critical assets (e.g., mobile flood defenses and grit storage) or the provision of a temporary service (e.g., electricity generators). The approach we have developed is based upon a modified location-allocation analysis, which determines an optimal location for one or more resource sites to provide supplies to a given set of demand points (e.g., hospitals and community centers). The novel contribution of the work is to the development of a methodology to assign a weighting to assets with only qualitative attributes within the location-allocation methodology. We use ArcGIS to undertake the analysis and apply our methodology to a real-world infrastructure case study and natural hazard threat. [ABSTRACT FROM AUTHOR]

This paper evaluates several efficiency indexes of hydropower energy generation in Iran's Karkheh Basin water reservoir system (i.e., Seymareh and Karkheh Rivers) under climate change based on the system dynamics approach. The climate change effects are investigated with simulations of surface temperature and rainfall driven by downscaled climate projections from atmosphere–ocean circulation models in the current literature, and the models with the highest correlation and lowest error for rainfall and temperature in the 1976–2005 baseline period are identified. Rainfall and temperature are projected over two future periods, 2040–2069 and 2070–2099, and are downscaled to basin scale. Results project that the basin temperature over future periods will be higher than in the baseline period. Downscaled results under climate change indicate that rainfall will not follow a specific pattern. An artificial neural network applied to predict runoff indicates that the runoff and flood peak will decrease. Software is implemented to simulate the operation of hydropower reservoirs in baseline and future periods. Five reservoir operation states are considered, with simulation results of energy production showing that runoff and energy production have a complex pattern. Seven indexes of hydropower reservoir efficiency are also calculated for the five operation states corresponding to targets of energy production. [ABSTRACT FROM AUTHOR]

This paper presents an investigation of the role of climatic variability on interannual groundwater and streamflow variability in the southeast United States. For this purpose, streamflow and associated groundwater levels are analyzed for 20 basins that are minimally affected by reservoirs and groundwater pumping. Using the spatially averaged monthly precipitation time series obtained from the Precipitation-elevation Regressions on Independent Slopes Model (PRISM), this paper identifies the recharge and discharge periods that influence the groundwater levels during the winter [January, February, March (JFM)] and summer [July, August, September (JAS)] seasons. Recharge-discharge dependency analyses indicate that precipitation during the previous 3 months influences the groundwater level in a given month. Streamflow in any given month depends on the groundwater level during the previous 3 months. Principal component analysis (PCA) on the precipitation, temperature, streamflow, and groundwater data indicates that groundwater levels and streamflow are the two dominant variables influencing the basin hydroclimatology. Furthermore, relating the percentage variance explained from the PCA to baseflow index (BFI) clearly shows that basins with high BFI have higher eigenvalues, indicating that groundwater is a spatial integrator of hydroclimatic processes. Relating the groundwater levels with El Niño/ Southern Oscillation (ENSO) index, NINO3.4, shows that interannual variability in JFM groundwater levels could be partially explained by the ENSO conditions, but the relationship between JAS groundwater levels and JAS NINO3.4 is not statistically significant. Precipitation forecasts from the ECHAM4.5 general circulation model indicate that it is possible to quantify groundwater availability during the winter season on the basis of the forecasted precipitation and ENSO conditions. [ABSTRACT FROM AUTHOR]

The Tonle Sap Lake (TSL), located in southwestern Mekong Basin, is the largest freshwater lake in Southeast Asia. The water-level regime of the TSL has been changing over the last few decades due to the rapid development of water infrastructures and climate change in the Mekong Basin. This paper makes efforts to quantify the water-level regime alterations of the TSL by analyzing the pre- and post-1991 historical data of daily water levels from Kompong Luong Station. The method of modified indicators of hydrologic alteration was utilized, and the TSL's hydrological behavior was explored further by focusing on the redistribution of hydrology and unfavorable disturbances. The results reveal that the coefficients of variation of most indicators in recent years increase compared with the preimpact years from 1960 to 1990. This demonstrates that the Mekong Basin and TSL are experiencing an increasingly unstable and varied hydrological cycle, which is more susceptible to interference with increased frequency and degree. Moreover, the system may have suffered more unfavorable human interference in dry years and in the dry season. It is expected that the findings in this paper will contribute to the protective development and adaptive management of the Mekong Basin and the TSL in the future. [ABSTRACT FROM AUTHOR]

The article presents the descriptions and closures of authors related to the issues raised by the discusser in the paper "Determination of Irrigation Allocation Policy under Climate Change by Genetic Programming." Topics include the application of evolutionary algorithm-based methodology genetic programming (GP) to determine irrigation allocation policy in reservoir operation, impact of reservoir operation on climate change, and calculation of storage volume and spill volume of the reservoir.

To assess the impacts of climate change on water resources, hydrological models are the most commonly used to simulate future flows. Hydrological model calibration is typically based on historical hydrometeorological data, which may not be representative of the future climate. This paper evaluates various calibration strategies to minimize this issue. The impact of these calibration strategies is measured on 921 North American catchments using a lumped hydrological model. Five calibration strategies (warm, low rainfall, high rainfall, low-flow, and high-flow years) were investigated, each using a 5-year (noncontinuous) independent validation dataset maximizing all five studied climate anomalies. The remaining years were used as a pool of calibration years, using targeted subsets of years in multiples of five to assess the impact of the number of calibration years versus the climate anomaly of each calibration subset. Results showed large cross-catchment variability, indicating that no single calibration strategy and number of calibration years were optimal for all watersheds. However, the large number of catchments used in this study allows for some general conclusions to be drawn. For the warm-years calibration strategy, using a large number of years was the approach most likely to succeed, indicating that removing a small subset of cold years was preferable to keeping a small subset of warm years. For the other four calibration strategies, the approach most likely to succeed was the one in which about half of the years in the historical record were kept. For the warm year strategy, keeping a larger number of years for calibration ensures better model robustness to account for precipitation variability in the validation set. For the other four calibration strategies, which are mostly related to precipitation, a larger number of years had to be dropped to account for the much larger differences between wet and dry years. [ABSTRACT FROM AUTHOR]

Green building (GB) is gaining increased acceptance in the construction industry as a viable solution for meeting the growing demand for environmentally friendly or healthy buildings. However, the uptake of GB technologies is not as apparent as it should have been. This paper aims to examine the criticality of various barriers preventing the wider adoption of GB technologies. Results from statistical analyses of 104 questionnaire survey responses from GB experts around the world are presented. The results validated the criticality of 19 of the 26 barriers used for the survey. Respondents from different countries and with diverse backgrounds displayed broad consensus on the criticality levels of the barriers. Resistance of stakeholders to change and higher cost are identified as the most critical barriers to implementing GB technologies. Generally, the various groups of respondents shared similar views on the number of barriers affecting the industry; however, respondents with more than 15 years of experience in GB perceived fewer barriers. The factor analysis showed that the barriers to GB technologies adoption could be grouped into five main interrelated components, which suggest the need for holistic and integrated strategies to overcome the barriers. The findings of this paper could help policy makers identify specific problems in GB technologies adoption and develop suitable strategies for their wider uptake. From the perspective of international experts, this study contributes to the body of knowledge about GB barriers. [ABSTRACT FROM AUTHOR]

Climate change and an increase in the number of hazards and/or their intensities may increase the probability of failure associated with civil infrastructure systems. Understanding how natural hazards affect the life-cycle performance of highway bridges can lead to improved preparedness prior to extreme disasters and can ultimately benefit society. In this paper, a framework for time-variant loss and resilience assessment of highway bridges under time-dependent multiple hazards is presented. The effects of earthquakes and floods on bridges are both investigated. The life-cycle hazard losses with and without aging effects and climate change are computed. Additionally, the probabilistic changes in the hazard intensity and frequency resulting from climate change on the total life-cycle hazard loss are also investigated. The proposed framework is applied to a highway bridge located in California. [ABSTRACT FROM AUTHOR]

This paper shows how low-impact development (LID) practices affect the resilience of stormwater drainage system under climate change scenarios. A rainfall-runoff model was calibrated and evaluated a in a tropical watershed located in Midwestern Brazil. An ensemble of 17 general circulation model outputs forced by Representative Concentration Pathways (RCP 4.5 and RCP 8.5) was used to create future climate change scenarios up to 2095. The LID efficiency was evaluated based on the runoff peak reduction and the resilience of stormwater drainage by means of a resilience index. Overall, LID combinations showed a reduction in runoff peak higher than 20%, and the best LID combination had a reduction of as much as 46%. This represents a significant improvement in the resilience against flooding in the study area. Therefore, the findings can contribute to the increase in widespread adoption of LID and can encourage decisionmakers to provide such practices for urban flood management. [ABSTRACT FROM AUTHOR]

Human interventions and climate change have caused significant alterations in the hydrologic response of several highly managed basins in Iran. One of these alterations is a considerable reduction in streamflow quantity, resulting in severe water supply insecurity. This paper presents an integrated modeling approach combining remote sensing, water balance analysis, reservoir operations, and water allocation policy evaluations. The approach helps in understanding of the relative contribution of anthropogenic factors in places where a major challenge is the lack of measured data for the historical time series of water withdrawals for agricultural development and water lost from the system through actual evapotranspiration (AET). Calibrated moderate-resolution imaging spectroradiometer (MODIS) remote sensing data of monthly AET (MOD16), modified Thornthwaite-Mather (M-TWM) water balance model, annual MODIS Land Cover Type (MCD12Q1) products (MCQD12Q1), mass curve analyses, and periodic analysis of water balance parameters were used to evaluate the contribution of anthropogenic factors and the effect of climatic impacts on the inflow time series for the Talvar Reservoir. The procedure led to an estimation of the naturalized series of the streamflow free of anthropogenic impacts; based on this, more plausible estimates of the basin's future water availability were determined, which were then used in a water evaluation and planning (WEAP) model for Talvar Reservoir operations and water allocations. The study yielded four main results. First, it was seen that there were two abrupt change points in the analyzed mass curves, in the years 1998 and 2007, dividing the study period (1988–2012) into three periods. Periodic analysis of water balance parameters showed that while climate change caused streamflow changes in postimpact period A (1998–2007), intensified human activities brought about streamflow changes in postimpact period B (2008–2012). Secondly, it was found that the naturalized series of the Talvar streamflow had a better correlation coefficient with precipitation than the observed series for river flow. Thirdly, despite the proposed approach lacking the use of some water balance components such as soil moisture and snow water equivalent, the percentage of unaccounted water content was between 5% and 10%, indicating good accuracy of the proposed approach as a tool for sustainable water resources management. Fourth, the WEAP model simulation results demonstrated that the unfavorable condition of the aquifer can be ameliorated by applying proper management policies. The results also showed that to increase water supply security and facilitate sustainability, a certain amount of reduction in ground-water withdrawals and agricultural areas is inevitable. [ABSTRACT FROM AUTHOR]

Increasing global warming has led to the incremental retreat of glaciers, which in turn affects the water supply of the rivers dependent on glacier melts. This is further affected by the increases in flooding that is attributable to heavy rains during the snowmelt season. An accurate estimation of streamflow is important for water resources planning and management. Therefore, this paper focuses on improving the streamflow forecast for Kaidu River Basin, situated at the north fringe of Yanqi basin on the south slope of the Tianshan Mountains in Xinjiang, China. The interannual and decadal scale oceanic-atmospheric oscillations, i.e., Pacific decadal oscillation (PDO), North Atlantic oscillation (NAO), Atlantic multidecadal oscillation (AMO), and El Niño-southern oscillation (ENSO), are used to generate streamflow volumes for the peak season (April-October) and the water year, which is from October of the previous year to September of the current year for a period from 1955-2006. A data-driven model, least-square support vector machine (LSSVM), was developed that incorporated oceanic atmospheric oscillations to increase the streamflow lead time. Based on performance measures, predicted streamflow volumes are in agreement with the measured volumes. Sensitivity analyses, performed to evaluate the effect of individual and coupled oscillations, revealed a stronger presence of coupled PDO, NAO, and ENSO indices within the basin. The AMO index shows a pronounced effect when individually compared with the other oscillation modes. Additionally, model-forecasted streamflow is better than that for climatology. Overall, very good streamflow predictions are obtained using the SVM modeling approach. Furthermore, the LSSVM streamflow predictions outperform the predictions obtained from the most widely used feed-forward back-propagation models, artificial neural network, and multiple linear regression. The current paper contributes in improving the streamflow forecast lead time, and identified a coupled climate signal within the basin. The increased lead time can provide useful information to water managers in improving the planning and management of water resources within the Kaidu River Basin. [ABSTRACT FROM AUTHOR]

This paper focuses on the development of simplified mathematical models of the cryosphere which may be useful in further understanding possible global climate change impacts and in further assessing future impacts captured by global circulation models (GCMs). The mathematical models developed by leveraging the dominating effects of freezing and thawing within the cryosphere to simplify the relevant heat transport equations are tractable to direct solution or numerical modeling. In this paper, the heat forcing function is assumed to be a linear transformation of temperature (assumed to be represented by proxy realizations). The output from the governing mathematical model is total ice volume of the cryosphere. The basic mathematical model provides information as a systems modeling approach that includes sufficient detail to explain ice volume given the estimation of the heat forcing function. A comparison between modeling results in the estimation of ice volume versus ice volume estimates developed from use of proxy data are shown in the demonstration problems presented. [ABSTRACT FROM AUTHOR]

Increasing global warming has led to the incremental retreat of glaciers, which in turn affects the water supply of the rivers dependent on glacier melts. This is further affected by the increases in flooding that is attributable to heavy rains during the snowmelt season. An accurate estimation of streamflow is important for water resources planning and management. Therefore, this paper focuses on improving the streamflow forecast for Kaidu River Basin, situated at the north fringe of Yanqi basin on the south slope of the Tianshan Mountains in Xinjiang, China. The interannual and decadal scale oceanic-atmospheric oscillations, i.e., Pacific decadal oscillation (PDO), North Atlantic oscillation (NAO), Atlantic multidecadal oscillation (AMO), and El Niño-southern oscillation (ENSO), are used to generate streamflow volumes for the peak season (April-October) and the water year, which is from October of the previous year to September of the current year for a period from 1955-2006. A data-driven model, least-square support vector machine (LSSVM), was developed that incorporated oceanic atmospheric oscillations to increase the streamflow lead time. Based on performance measures, predicted streamflow volumes are in agreement with the measured volumes. Sensitivity analyses, performed to evaluate the effect of individual and coupled oscillations, revealed a stronger presence of coupled PDO, NAO, and ENSO indices within the basin. The AMO index shows a pronounced effect when individually compared with the other oscillation modes. Additionally, model-forecasted streamflow is better than that for climatology. Overall, very good streamflow predictions are obtained using the SVM modeling approach. Furthermore, the LSSVM streamflow predictions outperform the predictions obtained from the most widely used feed-forward back-propagation models, artificial neural network, and multiple linear regression. The current paper contributes in improving the streamflow forecast lead time, and identified a coupled climate signal within the basin. The increased lead time can provide useful information to water managers in improving the planning and management of water resources within the Kaidu River Basin. [ABSTRACT FROM AUTHOR]

Climate change has a different impact on each member of society. To reduce the damage caused by climate change, adaptation activities are being initiated, such as expanding the capacity of social infrastructures, and each stakeholder wants these adaptations to work in his or her favor. Therefore, a methodology is needed to determine adaptation measures that are most beneficial to all members of society. In this paper, a framework is proposed for producing an adaptation strategy that minimizes conflict between stakeholders. This framework casts the process of organizing climate change adaptations as a game and defines each community member as a stakeholder, each adaptation measure as a strategy, and the minimization of loss from future climate change as a payoff. In a case study involving sea level rise in Suncheon Bay, Korea, this framework is used to generate an optimal plan for minimizing conflicts while considering the losses of the central government, local governments, and local communities. The game theoretic results from the proposed framework enable a balanced distribution of responsibilities among stakeholders to achieve infrastructure adaptation to climate change. [ABSTRACT FROM AUTHOR]

Considerable research has been carried out on the optimization of water distribution systems (WDSs) over the last three decades. In previous research, attention has mainly focused on the minimization of cost, due to the high expenditure associated with the construction and maintenance of such systems. However, the impacts of WDSs on the environment usually have not been considered adequately. The recent increasing awareness of sustainability and climate change, especially global warming, has led to research where greenhouse gas (GHG) emissions are considered. In the study described in this paper a multiobjective genetic algorithm for WDS optimization has been used as an explorative tool to investigate the trade-offs between the traditional economic objective of minimizing costs and an additional environmental objective of minimizing GHG emissions. The impacts of minimizing GHG emissions on the results of WDS optimization have been explored for a case study in this paper. The results indicate that the inclusion of GHG emission minimization as one of the objectives results in significant trade-offs between the economic and environmental objectives. Furthermore, a sensitivity analysis has been conducted by using different discount rates in a present value analysis for computing both ongoing costs and GHG emissions. The results obtained show that the Pareto-optimal front is very sensitive to the discount rates used. As a result, the selection of discount rates has a significant impact on final decision making. [ABSTRACT FROM AUTHOR]

Increasing population and water use, rising pollution of water resources, and climate change affect the quantity and quality of water resources. Reservoir operation is an important tool for water supply that can be optimized by simulation-optimization considering the impact of climate change on water quality. This study presents a simulation-optimization approach linking the CE-QUAL-W2 hydrodynamic model with the firefly algorithm k -nearest neighbor (FA-KNN) model to obtain optimal reservoir discharges to achieve water quality objectives under climate change conditions. The developed algorithm overcomes the computational burden of CE-QUAL-W2. The FA-KNN hybrid algorithm is employed to optimize the total dissolved solids (TDS) while achieving computational efficiently beyond what could be achieved with CE-QUAL-W2 simulations alone. This paper's approach is evaluated with the Aidoghmoush Reservoir (East Azerbaijan, Iran). Overall, 36 simulation-optimization scenarios for dry and wet years under baseline and climate change conditions are evaluated by considering three initial water levels for the reservoir (minimum, average, and normal) and three thresholds for assessing the hybrid algorithm. The TDS released from the reservoir in wet years would be acceptable for agricultural use; in dry years, on average, the TDS would not be acceptable for 24 days per year under climate change. The reservoir in winter undergoes complete mixing; it becomes stratified in spring and summer, and it is close to complete mixing in the autumn. The highest TDS in the reservoir would occur during the summer in dry years under climate change, reaching TDS of approximately 2,645 g/m3. [ABSTRACT FROM AUTHOR]

This paper presents the results of a study on the impact of climate change on road infrastructure in South Africa. The approach used built on previous work associated with the UNU-WIDER Development under Climate Change (DUCC) effort, emphasizing understanding of the impact of climate change on roads. This paper illustrates how climate change effects on road infrastructure can be evaluated at a national and provincial level to produce quantitative estimates of climate change from multiple future scenarios. The results of the study indicate that the national-level climate change cost impact in South Africa will vary between US$116.8 million and US$228.7 million annually in the 2050 decade for the median and maximum climate scenarios if a no-adaptation policy action is taken. Conversely, if a proactive adaptation action is taken, these costs can be reduced to US$55.7 million. The savings in costs arising from climate change impacts based on this policy approach is equivalent to building more than 10,000 km of new, secondary paved road by 2050. The analysis focused on the advantage of a proactive policy approach: the upgrade of road infrastructure where climate impacts will exceed current design and maintenance standards. A stressor-response methodology created by the writers is briefly explained, including the application of 54 potential climate futures using general circulation models (GCMs) approved by the Intergovernmental Panel on Climate Change (IPCC). This paper focuses on provincial-level impacts of both a proactive and a reactive approach. Decadal and average annual costs are detailed through 2100. [ABSTRACT FROM AUTHOR]

Multiobjective water resources systems require long-term operational plans that consider vulnerability to failure under nonstationary conditions due to climate change. The paper presents a probabilistic decision-making framework under hydroclimatic nonstationary assumptions to evaluate the robustness of the preselected plans and identify the optimal plan using a genetic algorithm approach. The framework incorporates a new metric for maximum allowable time to apply the adaptations and maintaining operational targets without penalties. The framework has four stages for climate exposure identification, production of water supply scenarios, generation of water demand scenarios, and evaluation of system performance. Hydrologic variables considered include precipitation, temperature, and wind speed. The Diyala River Basin in Iraq was used as a case study to test the effectiveness of the framework. Three synthetic preselected plans were developed by reducing the demand ratios of the system. Results indicate that current operational rules are robust for flood protection but vulnerable in drought periods. Precipitation changes were dominant in flood and drought management, and temperature and wind speed change effects were significant during drought. Results demonstrated the framework's effectiveness to quantify detrimental climate change effects, provide long-term guides for operational planning, and identify the upper limit of application time of the adaptation strategies in the system to avert the climate change impact. Framework application suggests an optimal adaptation strategy, robustness examination of the presuggested plans, and identification of the maximum allowable time for the robust plans. [ABSTRACT FROM AUTHOR]

Heritage buildings are considered unique assets with a significant value for the country where they are situated that must be conserved or preserved for the coming generations. However, heritage sites, as any other site where a construction is present, experience tremendous risks that impact both the condition and the withstanding of the building or asset they include. Therefore, a risk management framework is essential for these sites and buildings, in particular to be able to decide how to respond and act upon foreseeable risks when they occur or even before experiencing them. This study starts with investigating the most dominant risks in the heritage buildings context with a focus on Yemeni sites, and consequently 38 Yemeni experts in the field of heritage building management were surveyed to examine the identified risks in three case study heritage sites in Yemen. The significance of the risks as well as their impact, likelihood, and detectability levels were measured using an analytic hierarchy process (AHP) basis that reduces the subjectivity of the expert opinions. After risks were analyzed, a suitable response action was therefore suggested to manage and minimize risk impacts as much as possible. In addition to the relative scoring for the priority of each identified risk, an overall risk proneness metric is presented in this paper that can be used to compare the vulnerability of different heritage buildings and/or sites for a strategic efficient budget allocation for the management and preservation of those areas. The preliminary results revealed that armed conflicts, climate change, and flooding are three of the most critical risk factors in Yemeni heritage buildings. This framework is expected to aid heritage building managers in identifying the correct course of actions to prevent or mitigate risks from disturbing the heritage sites and help preserve their value and significance. [ABSTRACT FROM AUTHOR]

In this paper, climate change impact on flood frequency has been investigated in Bagmati River Basin of Nepal using biascorrected global climate model (GCM) precipitation output. The research reported in this paper employed a high- resolution (approximately 20-km) daily GCM precipitation and temperature output of Meteorological Research Institute (MRI), Japan. Comparison of observation and GCM data pointed out that the MRI-GCM precipitation consists of significant biases in frequency and intensity values. Quantile-quantile mapping method of GCM bias correction was applied for minimizing the biases in precipitation frequencies and intensities. Concept of homogeneous precipitation regions was introduced to link the uneven observation data stations and GCM grid cells. Analyses of return period curves, shape, and scale factors at different observation stations enabled delineation of three homogeneous precipitation regions. Accordingly, regional quantile-quantile bias-correction technique was developed for minimizing biases in MRI-GCM precipitation output. A distributed rainfall-runoff model enabled generation of streamflow series using bias-corrected GCM output for 1979-2003 and 2075-2099 periods, as current and future scenarios, respectively. Finally, comparative flood frequency analyses were carried out for the simulated annual daily maximum streamflow series of current and future climates. The analyses revealed that the climate change will result more extreme precipitation events in monsoon months and less precipitation in other months. The analyses also revealed that flood events will be significantly increased in future. The range of change in 2-100 year return period floods was from 24-40%. [ABSTRACT FROM AUTHOR]

This paper presents a practical approach to adaptive management of dam risk based on robust decision-making strategies coupled with estimation of climate scenario probabilities. The proposed methodology, called multi-prior weighted scenarios ranking, consists of a series of steps from risk estimation for current and future situations through definition of the consensus sequence of risk reduction measures to be implemented. This represents a supporting tool for dam owners and safety practitioners in making decisions for managing dams or prioritizing long-term investments using a cost-benefit approach. This methodology is applied to the case study of a Spanish dam under the effects of climate change. Several risk reduction measures are proposed and their impacts are analyzed. The application of the methodology allows for identifying the optimal sequence of implementation measures that overcomes uncertainty from the diversity of available climate scenarios by prioritizing measures that reduce future accumulated risks at lower costs. This work proves that such a methodology helps address uncertainty that arises from multiple climate scenarios while adopting a cost-benefit approach that optimizes economic resources in dam risk management. [ABSTRACT FROM AUTHOR]

The increasingly frequent extreme weather disasters caused by global climate change have attracted more attention to adverse weather's effect on infrastructure systems. This paper aims to establish an integrated approach to assessing adverse weather's effect on urban rail transit facilities and to provide decision makers with a powerful tool to analyze potential risks and allocate limited sources for risk management. First, fault tree analysis is used to understand where the risks are, how the risks will occur, and what factors have the most significant effects by analyzing all possible basic events. All wind-, rain-, and snow-related adverse weather, along with human-related factors (construction leftover problems and design drawbacks), are found to potentially cause great risks. Adverse impact scenarios are summarized based on the fault tree analysis. Next, an analytic hierarchical process (AHP)-based fuzzy synthetic evaluation model is established to assess the risk level based on an evaluation index system. AHP is used to calculate the weights between the indices for each adverse weather factor. A fuzzy synthetic evaluation process is then carried out to identify the risk level of an evaluation target, an urban rail transit station, or line section. A case study on the Beijing URT Line 8 Olympic Center Station is conducted to illustrate the process of evaluation. The results show that the risk level is high and it becomes acceptable only after countermeasures are taken. Potential countermeasures regarding facility capacity, protection area management, and monitoring/inspection are then briefly discussed. [ABSTRACT FROM AUTHOR]

Adaptation to climate change requires careful evaluation of infrastructure performance under future climatic extremes. This study demonstrates how a multidisciplinary approach integrating geotechnical engineering, hydrology, and climate science can be employed to quantify site-specific impacts of climate change on geotechnical infrastructure. Specifically, this paper quantifies the effects of changes in future streamflow on the performance of an earthen levee in Sacramento, California, considering multiple modes of failure. The streamflows for historical (1950–2000) and projected (2049–2099) scenarios with different recurrence intervals were derived from routed hydrological simulations driven by bias-corrected global climate models. The historical and future flood levels were then applied in a set of transient coupled finite-element seepage and limit equilibrium slope stability analyses to simulate the levee subjected to extreme streamflow. Variability in hydraulic and mechanical properties of soils was addressed using a Monte Carlo sampling method to evaluate and compare the probability of failure of the levee under different historical and future climate scenarios. Three individual modes (underseepage, uplift, and slope stability) along with lower and upper bounds for the combined mode of failure were examined. The results showed that incorporating future floods into levee failure analysis led to considerable reductions in the mean factor of safety and increases in the levee's probability of failure, suggesting that risk assessment based on historical records can significantly underestimate the levee's failure probability in a warming climate. Despite inherent uncertainties in future projections and substantial variability across climate models, evaluating infrastructure against projected extremes offers insights into their likely performance for the future. [ABSTRACT FROM AUTHOR]

Global warming and climate change have increased the frequency of heavy precipitation. Heavy rainfall results in a large amount of water entering roadways within a short time period. Water remains in the pavement system for a certain time period, reduces strengths and moduli of granular bases and subgrades, and induces pavement distresses. Geotextiles are commonly used in roadways for drainage purposes, which require soil saturation. However, soil saturation does not always exist in roadways to enable gravity drainage of water by conventional geotextiles. Wicking geotextile, a new type of woven geotextile, was recently introduced to the market to remove moisture from unsaturated soils. The wicking geotextile includes special hydrophilic and hygroscopic 4 deep groove fibers with multichannel cross sections, which can induce high capillary force to wick water out of moist soil without saturation of soil. The ability and rate of this geotextile to remove water from moist soil depends on several factors, including temperature and relative humidity. In this study, a series of laboratory tests under controlled temperature and relative humidity were conducted to quantify the water removal rate of the wicking geotextile. A half length of the wicking geotextile was submerged in water tanks, and the other half was hung outside of the tanks. The water wicked from the tank into the geotextile evaporated into the air. Such tests were conducted under 12 different test conditions (i.e., different temperatures and relative humidities). Test results demonstrated that the wicking geotextile could remove water from the water tank at a certain rate. Three commonly used methods available in the literature were adopted to quantify the water removal rate of the wicking geotextile based on vapor pressure, temperature, and relative humidity. A new concept of equivalent water evaporation length of a wicking geotextile is proposed in this study. It should be pointed out that the tests presented in this paper aimed to determine the maximum water removal capacity of the geotextile given sufficient water supply. [ABSTRACT FROM AUTHOR]

Nexus thinking is critical to jointly address growing water, energy, and food security challenges. This paper evaluates the water, energy, and food nexus (WEFN) in the Indus River of Pakistan using the Indus Basin Model Revised—Multi Year, a hydro-agro-economic model extended with an agricultural energy use module. Impacts of a range of climate change scenarios on the WEFN in the Indus Basin were modeled and then the potential of different alternative water allocation mechanisms and water infrastructure developments to address growing water, energy and food security concerns in the country were assessed. Results show growing water and energy use under hotter and wetter climate conditions. While more flexible surface water allocation policies can mitigate negative climate change impacts on agricultural water and energy use allowing for larger crop and hydropower production, such policies might also increase the inter-annual variability of resource use. Moreover, a more flexible surface water allocation policy would increase surface water use in the basin, while groundwater and energy use would be lower. Study results can inform the WEFN in areas with similar hydro-climatic environments, such as California and Central Asia. Further integration of a groundwater model and an energy market model and explicitly addressing changes in food and energy demand as a result of demographic dynamics are three areas for future study. [ABSTRACT FROM AUTHOR]

The most comprehensive tools for producing climatic scenarios and consequently hydrological predictions are atmospheric-ocean general circulation models (AOGCMs). This paper evaluates the performance of those models. Possible scenarios of temperature and rainfall in the base period (1971-2000) for the Aidoghmoush basin located in East Azerbaijan are estimated with seven AOGCMs. A hydrological model is first calibrated for the basin and then monthly time series of temperature and rainfall resulting from AOGCMs in the base period are input to the hydrological model. The mean observed runoff (MOR) weighting method is employed to assess the effectiveness of each climate model to produce runoff. An appropriate probability distribution is chosen and relevant statistical parameters extracted and compared with observed runoff statistical parameters. Results show that the hybrid and Hadley Centre Coupled Model, version 3 (HadCM3) models with respective correlation coefficients of 97% [root mean square error (RMSE) = 2.09 m3/s, mean absolute error (MAE) =1.51 m3/s, and Nash Sutcliffe efficiency (NSE) = 0.89] for the hybrid model and 90% (RMSE = 3.22 m3/s, MAE = 2.58 m3/s, and NSE = 0.87) for the HadCM3 model can best simulate runoff. Comparison of the results of the probability distributions and the transition probability matrix from the AOGCM models with observed runoff shows that the hybrid and HadCM3 models with respective correlation coefficients of 91% (RMSE = 0.07 m3/s, MAE = 0.004 m3/s, and NSE = 0.80) and 86% (RMSE = 0.14 m3/s, MAE = 0.04 m3/s, and NSE = 0.78) yield reliable outputs. [ABSTRACT FROM AUTHOR]