Search

Abstract Urbanization and climate change are contributing to severe flooding globally, damaging infrastructure, disrupting economies, and undermining human well-being. Approaches to make cities more resilient to floods are emerging, notably with the design of flood-resilient structures, but relatively little is known about the role of urban form and its complexity in the concentration of flooding. We leverage statistical mechanics to reduce the complexity of urban flooding and develop a mean-flow theory that relates flood hazards to urban form characterized by the ground slope, urban porosity, and the Mermin order parameter which measures symmetry in building arrangements. The mean-flow theory presents a dimensionless flood depth that scales linearly with the urban porosity and the order parameter, with different scaling for disordered square- and hexagon-like forms. A universal scaling is obtained by introducing an effective mean chord length representative of the unobstructed downslope travel distance for flood water, yielding an analytical model for neighborhood-scale flood hazards globally. The proposed mean-flow theory is applied to probe city-to-city variations in flood hazards, and shows promising results linking recorded flood losses to urban form and observed rainfall extremes.

This paper develops the concept of flood problem framing to understand decision-makers’ priorities in flood risk management in the Los Angeles Metropolitan Region in California (LA Metro). Problem frames shape an individual’s preferences for particular management strategies and their future behaviors. While flooding is a complex, multifaceted problem, with multiple causes and multiple impacts, a decision-maker is most likely to manage only those dimensions of flooding about which they are aware or concerned. To evaluate flood decision-makers’ primary concerns related to flood exposure, vulnerability, and management in the LA Metro, we draw on focus groups with flood control districts, city planners, nonprofit organizations, and other flood-related decision-makers. We identify numerous concerns, including concerns about specific types of floods (e.g., fluvial vs pluvial) and impacts to diverse infrastructure and communities. Our analyses demonstrate that flood concerns aggregate into three problem frames: one concerned with large fluvial floods exacerbated by climate change and their housing, economic, and infrastructure impacts; one concerned with pluvial nuisance flooding, pollution, and historic underinvestment in communities; and one concerned with coastal and fluvial flooding’s ecosystem impacts. While each individual typically articulated concerns that overlapped with only one problem frame, each problem frame was discussed by numerous organization types, suggesting low barriers to cross-organizational coordination in flood planning and response. This paper also advances our understanding of flood risk perception in a region that does not face frequent large floods.

Abstract Extreme flooding events are becoming more frequent and costly, and impacts have been concentrated in cities where exposure and vulnerability are both heightened. To manage risks, governments, the private sector, and households now rely on flood hazard data from national‐scale models that lack accuracy in urban areas due to unresolved drainage processes and infrastructure. Here we assess the uncertainties of First Street Foundation (FSF) flood hazard data, available across the U.S., using a new model (PRIMo‐Drain) that resolves drainage infrastructure and fine resolution drainage dynamics. Using the case of Los Angeles, California, we find that FSF and PRIMo‐Drain estimates of population and property value exposed to 1%‐ and 5%‐annual‐chance hazards diverge at finer scales of governance, for example, by 4‐ to 18‐fold at the municipal scale. FSF and PRIMo‐Drain data often predict opposite patterns of exposure inequality across social groups (e.g., Black, White, Disadvantaged). Further, at the county scale, we compute a Model Agreement Index of only 24%—a ∼1 in 4 chance of models agreeing upon which properties are at risk. Collectively, these differences point to limited capacity of FSF data to confidently assess which municipalities, social groups, and individual properties are at risk of flooding within urban areas. These results caution that national‐scale model data at present may misinform urban flood risk strategies and lead to maladaptation, underscoring the importance of refined and validated urban models.

Abstract In 2006 following several years of preliminary study, the American Society of Clinical Oncology (ASCO) launched the Quality Oncology Practice Initiative (QOPI). This cancer‐focused quality initiative evolved considerably over the next decade‐and‐a‐half and is expanding globally. QOPI is undoubtedly the leading standard‐bearer for quality cancer care and contemporary medical oncology practice. The program garners attention and respect among federal programs, private insurers, and medical oncology practices across the nation. The MaineHealth Cancer Care Network (MHCCN) has undergone expansive growth since 2017. The network provides cancer care to more than 70% of the cases in Maine in a largely rural health system in Northern New England. In fall 2020, the MHCCN QOPI project leadership, following collaborative discussions with the ASCO‐QOPI team, elected to proceed with a health system–cancer network‐wide QOPI certification. Key themes emerged over the course of our two‐year journey including: (1) Developing a highly interprofessional team committed to the project; (2) Capitalizing on a single electronic medical record for data transmission to CancerLinQ; (3) Prior experience, especially policy development, in other cancer‐focused accreditation programs across the network; and (4) Building consensus through quarterly stakeholder meetings and awarding Continuing Medical Education (CME) and American Board of Medical Specialists (ABMS) Maintenance of Certification (MOC) credits to oncologists. All participants demonstrated a genuine spirit to work together to achieve certification. We report our successful journey seeking ASCO‐QOPI certification across our network, which to our knowledge is the first‐of‐its‐kind endeavor.

Flood and debris hazards are heightened following wildfires, but are challenging to quantify due to interdependence between fire frequency and severity, runoff and sediment fluxes during storms, and sedimentation that reduces infrastructure capacity. Herein we present a stochastic simulation framework to estimate compound flood and debris hazards from sequences of wildfires and rainstorms and the accumulation of sediment within flood infrastructure. Application of the framework to a hypothetical watershed representative of southern California shows that the present-day compound hazard may be up to 6 times greater than the marginal hazard posed by peak flows in the absence of wildfire, and that future compound hazards could be up to 11 times greater than the marginal hazard based on future increases in wildfire frequency. Numerous sensitivities are investigated, including infrastructure design and maintenance, which are shown to be crucial for moderating future increases in post-fire flood hazards.

Background:. Carpal tunnel syndrome affects up to 6% of the general population, and surgical intervention is often required to ameliorate symptoms. Osteoarthritis (OA) is a common condition that often coexists with carpal tunnel syndrome. We hypothesized that patients with preexisting OA use more healthcare resources after carpal tunnel release (CTR) than patients without arthritis. Methods:. This was a retrospective cohort study at a single academic center between January 1, 2018 and November 1, 2021. Patients who underwent CTR were included. Preoperative carpal tunnel symptoms, diagnostic tests, medications, and concomitant OA were abstracted. Hand, wrist, and basal joint arthritis were specified. The primary outcome was healthcare utilization represented by duration and frequency of hand clinic and occupational therapy (OT) follow-up. In total, 312 hands were included. Multivariable analysis was performed. Results:. The average duration of hand clinic follow-up among patients without arthritis was 25.3 days compared with 87.1 days for patients with any arthritis (P = 0.0375) and 172 days for patients with wrist arthritis (P = 0.012). The average number of postoperative surgeon visits was increased in patients with hand arthritis, with an average of 2.3 visits versus 1.34 visits for patients without arthritis (P = 0.003). Both the number of OT visits and the duration of OT follow-up did not differ between cohorts. Conclusion:. After CTR, patients with preexisting OA use more healthcare resources than patients without OA.

Greenbug (Schizaphis graminum, Rondani) is a serious insect pest in many wheat growing regions and has been infesting cereal crops in the USA for over a century. Continuous occurrence of new greenbug biotypes makes it essential to explore all greenbug resistant sources available to manage this pest. Gb1, a recessive greenbug resistance gene in DS28A, confers resistance to several economically important greenbug biotypes and is the only gene found to be resistant to greenbug biotype F. A set of 174 F2:3 lines from the cross DS28A × Custer was evaluated for resistance to greenbug biotype F in 2020 and 2022. Selective genotyping of the corresponding F2 population using single nucleotide polymorphism (SNP) markers generated by genotyping-by-sequencing (GBS) led to the identification of a candidate genomic region for Gb1. Thus, SSR markers previously mapped in this region were used to genotype the entire F2 population, and kompetitive allele specific PCR (KASP) markers were also developed from SNPs in the target region. Gb1 was placed in the terminal region of the short arm of chromosome 1A, and its location was confirmed in a second population derived from the cross DS28A × PI 697274. The combined data analysis from the two mapping populations delimited Gb1 to a

Introduction: Climate change is a global phenomenon with far-reaching consequences, and its impact on human health is a growing concern. The intricate interplay of various factors makes it challenging to accurately predict and understand the implications of climate change on human well-being. Conventional methodologies have limitations in comprehensively addressing the complexity and nonlinearity inherent in the relationships between climate change and health outcomes. Objectives: The primary objective of this paper is to develop a robust theoretical framework that can effectively analyze and interpret the intricate web of variables influencing the human health impacts of climate change. By doing so, we aim to overcome the limitations of conventional approaches and provide a more nuanced understanding of the complex relationships involved. Furthermore, we seek to explore practical applications of this theoretical framework to enhance our ability to predict, mitigate, and adapt to the diverse health challenges posed by a changing climate. Methods: Addressing the challenges outlined in the objectives, this study introduces the Complex Adaptive Systems (CAS) framework, acknowledging its significance in capturing the nuanced dynamics of health effects linked to climate change. The research utilizes a blend of field observations, expert interviews, key informant interviews, and an extensive literature review to shape the development of the CAS framework. Results and discussion: The proposed CAS framework categorizes findings into six key sub-systems: ecological services, extreme weather, infectious diseases, food security, disaster risk management, and clinical public health. The study employs agent-based modeling, using causal loop diagrams (CLDs) tailored for each CAS sub-system. A set of identified variables is incorporated into predictive modeling to enhance the understanding of health outcomes within the CAS framework. Through a combination of theoretical development and practical application, this paper aspires to contribute valuable insights to the interdisciplinary field of climate change and health. Integrating agent-based modeling and CLDs enhances the predictive capabilities required for effective health outcome analysis in the context of climate change. Conclusion: This paper serves as a valuable resource for policymakers, researchers, and public health professionals by employing a CAS framework to understand and assess the complex network of health impacts associated with climate change. It offers insights into effective strategies for safeguarding human health amidst current and future climate challenges.

Larval source management has gained renewed interest as a malaria control strategy in Africa but the widespread and transient nature of larval breeding sites poses a challenge to its implementation. To address this problem, we propose combining an integrated high resolution (50 m) distributed hydrological model and remotely sensed data to simulate potential malaria vector aquatic habitats. The novelty of our approach lies in its consideration of irrigation practices and its ability to resolve complex ponding processes that contribute to potential larval habitats. The simulation was performed for the year of 2018 using ParFlow-Common Land Model (CLM) in a sugarcane plantation in the Oromia region, Ethiopia to examine the effects of rainfall and irrigation. The model was calibrated using field observations of larval habitats to successfully predict ponding at all surveyed locations from the validation dataset. Results show that without irrigation, at least half of the area inside the farms had a 40% probability of potential larval habitat occurrence. With irrigation, the probability increased to 56%. Irrigation dampened the seasonality of the potential larval habitats such that the peak larval habitat occurrence window during the rainy season was extended into the dry season. Furthermore, the stability of the habitats was prolonged, with a significant shift from semi-permanent to permanent habitats. Our study provides a hydrological perspective on the impact of environmental modification on malaria vector ecology, which can potentially inform malaria control strategies through better water management.

In the current era of rapid climate change, accurate characterization of climate-relevant gas dynamics-namely production, consumption, and net emissions-is required for all biomes, especially those ecosystems most susceptible to the impact of change. Marine environments include regions that act as net sources or sinks for numerous climateactive trace gases including methane (CH4) and nitrous oxide (N2O). The temporal and spatial distributions of CH4 and N2O are controlled by the interaction of complex biogeochemical and physical processes. To evaluate and quantify how these mechanisms affect marine CH4 and N2O cycling requires a combination of traditional scientific disciplines including oceanography, microbiology, and numerical modeling. Fundamental to these efforts is ensuring that the datasets produced by independent scientists are comparable and interoperable. Equally critical is transparent communication within the research community about the technical improvements required to increase our collective understanding of marine CH4 and N2O. A workshop sponsored by Ocean Carbon and Biogeochemistry (OCB) was organized to enhance dialogue and collaborations pertaining to marine CH4 and N2O. Here, we summarize the outcomes from the workshop to describe the challenges and opportunities for near-future CH4 and N2O research in the marine environment.

As urbanization and climate change alter sediment fluxes, relative sea level, and coastal erosion around the world, management of sediment as a resource is increasingly important. Sediment is needed to enhance marsh accretion rates, raise the grade elevation of development, and build up beaches and dunes. Beneficial reuse of sediment refers to the repurposing of local sources of sediment for these applications, material typically available from dredging or sediment capture infrastructure, and represents a more sustainable approach compared to the status-quo involving transport to and from distant locations. However, in many locations, beneficial reuse remains a concept or is constrained to small-scale applications. In this paper, we draw on interviews with coastal sediment managers and regulators in Southern California to identify barriers to beneficial reuse and opportunities to overcome them. Interviewees reported numerous regulatory, technical, psychological, financial, and interorganizational barriers in their watersheds and regions. By highlighting these barriers, we aim to identify systemic changes that would make beneficial reuse a realistic and accessible option for Southern California and elsewhere. Most prominently, a more flexible regulatory framework that allows sediment management practices to adapt over time, pilot studies to understand how beneficial reuse works in various settings, and educational programs for regulators and the public could make beneficial reuse a more widespread approach.

Existing needs to manage flood risk in the United States are underserved by available flood hazard information. This contributes to an alarming escalation of flood impacts amounting to hundreds of billions of dollars per year and countless disrupted lives and affected communities. Making information about flood hazards useful for the range of decisions that dictate the consequences of flooding poses many challenges. Here, we describe collaborative flood modeling, whereby researchers and end-users at two coastal sites co-develop fine-resolution flood hazard models and maps responsive to decision-making needs. We find, first of all, that resident perception and awareness of flooding are enhanced more by fine-resolution depth contour maps than Federal Emergency Management Agency (FEMA) flood hazard classification maps and that viewing fine-resolution depth contour maps helps to minimize differences in flood perception across subgroups within the community, generating a shared understanding. We also find that collaborative flood modeling supports the engagement of a wide range of end-users in contemplating the risks of flooding and provides strong evidence that the co-produced knowledge can be readily adopted and applied for Flood Risk Management (FRM). Overall, collaborative flood modeling advances FRM by providing multiple points of entry for diverse groups of end-users to contemplate the spatial extent, intensity, timing, chance, and consequences of flooding, thus enabling the web of decision-making related to flooding to be better informed with the best available science. This transdisciplinary approach emphasizes vulnerability reduction and is complementary to FEMA Flood Insurance Rate Maps used for flood insurance administration.

Pluvial flash flooding (PFF) is a growing hazard facing cities around the world as a result of rapid urbanization and more intense precipitation from global warming, particularly for low-resourced settings in developing countries. We present collaborative modeling (CM) as an iterative process to meet diverse decision-making needs related to PFF through the co-production of flood hazard models and maps. CM resulted in a set of flood hazard maps accessible through an online viewer that end-users found useful and useable for understanding PFF threats, including debris blockages and barriers to mobility and evacuation. End-users of information included individuals concerned with general flood awareness and preparedness, and involved in infrastructure and emergency management, planning, and policy. CM also showed that rain-on-grid hydrodynamic modeling is needed to depict PFF threats in ways that are intuitive to end-users. These outcomes evidence the importance and transferability of public health rationale for community-based research and principles used here including recognizing community as a unit of identity, building on strengths of the community, and integrating knowledge for the benefit of all partners.

A method to link bivariate statistical analysis and hydrodynamic modeling for flood hazard estimation in tidal channels and estuaries is presented and discussed for the general case where flood hazards are linked to upstream riverine discharge Q and downstream ocean level, H. Using a bivariate approach, there are many possible combinations of Q and H that jointly reflect a specific return period, T, raising questions about the best choice as boundary forcing in a hydrodynamic model. We show, first of all, how possible Q and H values depend on whether the definition of T corresponds to the probability of exceedance of “H OR Q” or “H AND Q”. We also show that flood hazards defined by “OR” return periods are more conservative than “AND” return periods. Finally, we introduce a new composite water surface profile to represent the spatially distributed hazard for return period T. The composite profile synthesizes hydrodynamic model results from the “AND” hazard scenario and two scenarios based on traditional univariate analysis, a “Marginal Q” scenario and a “Marginal H” scenario.

Understanding the impact of digital, interactive flood hazard maps and flood control systems on public flood risk perception could enhance risk communication and management. This study analyzed a survey of residents living near California’s Newport Bay Estuary and found that self-rated nonspatial perceptions of dread or concern over future flood impacts were positively associated with spatial awareness of flood-prone areas. Trust in flood control systems was associated with greater spatial flood hazard awareness but weaker nonspatial dread or concern, suggesting residents who witnessed and trust flood control systems developed a confident sense of flood-prone areas and that this confidence reduced the overall nonspatial sense of flood dread and concern. Viewing a flood hazard map eliminated differences in spatial hazard awareness between subgroups that existed prior to viewing a map, and viewing a map with estimated flood depth and greater spatial differentiation was associated with higher levels of postmap spatial awareness.

Microbial anaerobic oxidation of methane may not substantially mitigate projected warming-induced emissions of methane from marine hydrate-bearing sediments, according to a coupled hydraulic-thermodynamic-geomechanical hydrate model.

Abstract Background Many older Americans suffer from long-term upper limb dysfunction, decreased grip strength, and/or a reduced ability to hold objects due to injuries and a variety of age-related illnesses. The objective of this study was to design and build a five-fingered powered assistive exoskeleton for the human hand, and to validate its ability to augment the gripping and pinching efforts of the wearer and assist in performing ADLs. Methods The exoskeleton device was designed using CAD software and 3-D printed in ABS. Each finger’s movement efforts were individually monitored by a force sensing resistor at each fingertip, and proportionally augmented via the microcontroller-based control scheme, linear actuators, and rigid exoskeleton structure. The force production of the device and the force augmenting capability were assessed on ten healthy individuals with one 5-digit grasping test, three pinching tests, and two functional tests. Results Use of the device significantly decreased the forearm muscle activity necessary to maintain a grasping effort (67%, p

Cycles of wildfire and rainfall produce sediment‐laden floods that pose a hazard to development and may clog or overtop protective infrastructure, including debris basins and flood channels. The compound, post‐fire flood hazards associated with infrastructure overtopping and clogging are challenging to estimate due to the need to account for interactions between sequences of wildfire and storm events and their impact on flood control infrastructure over time. Here we present data sources and calibration methods to estimate infrastructure clogging and channel overtopping hazards on a catchment‐by‐catchment basis using the Post‐Fire Flood Hazard Model (PF2HazMo), a stochastic modeling approach that utilizes continuous simulation to resolve the effects of antecedent conditions and system memory. Publicly available data sources provide parameter ranges needed for stochastic modeling, and several performance measures are considered for model calibration. With application to three catchments in southern California, we show that PF2HazMo predicts the median of the simulated distribution of peak bulked flows within the 95% confidence interval of observed flows, with an order of magnitude range in bulked flow estimates depending on the performance measure used for calibration. Using infrastructure overtopping data from a post‐fire wet season, we show that PF2HazMo accurately predicts the number of flood channel exceedances. Model applications to individual watersheds reveal where infrastructure is undersized to contain present‐day and future overtopping hazards based on current design standards. Model limitations and sources of uncertainty are also discussed. Plain Language Summary: Communities at the foot of the mountains face an especially dangerous type of flooding called "sediment‐laden floods." Many such communities in the southwestern U.S. are protected from water floods by flood infrastructure designed to trap sediment at the mouth of mountain canyons and convey only water flows safely past developed areas to a downstream water body. Sediment‐laden floods, which are more forceful and typically larger than water floods, are more likely to happen during storms over burned mountain canyons soon after a wildfire occurs. However, estimating the likelihood that sediment‐laden floods fill and overtop flood infrastructure is challenging since existing sediment‐laden flood models do not explicitly consider the role of flood infrastructure. Here we present the Post‐Fire Flood Hazard Model (PF2HazMo), a model that can estimate the likelihood of post‐fire floods on a canyon‐by‐canyon basis accounting for flood infrastructure. Environmental data collected following a major wildfire is used to apply PF2HazMo to three mountain canyons in southern California, and we find that it predicts the number of floods accurately relative to observed post‐fire flood channel overtopping events. Further, the model is used to predict the frequency of floods due to infrastructure overtopping under both present‐day and future wildfire scenarios. Key Points: Flood risks are heightened by clogging of infrastructure with sediment, which can occur from sequences of storms especially after wildfiresA framework for calibration and validation of a post‐fire infrastructure clogging and flood hazard model is presentedModel applications reveal whether infrastructure is adequately sized to meet design levels of protection [ABSTRACT FROM AUTHOR]

Great uncertainty exists about household responses to intensifying sea-level rise and related flooding, especially about when residents may consider relocation. Understanding how preferences for in-situ adaptation versus climate mobility evolve through time across communities with varying capacities can help identify policy solutions suited to a range of community needs. We present an analysis of 40 interviews and 597 survey responses from residents of Miami-Dade County, FL, USA—an area of substantial and increasing flood-related risk where concerns related to climate mobilities are emerging. We integrate new flood hazard models depicting chronic inundation and 1%-annual-chance flooding with street-level detail under increasing sea-level rise, which when combined with the interview and survey data reveal the multiplicities of spatiotemporal risk. Overall, we find that up to 75% of all participating respondents have experienced precipitation-based flooding in recent years, and “new normal” experiences of inundation are already reshaping current decisions to move. However, up to 57% of survey respondents preferred in-situ adaptations over moving away, highlighting a need for society-wide commitments to long-term adaptation. Socioeconomic pressures dominated climate mobility considerations among interview and survey respondents, raising climate justice concerns over socially inequitable mobility outcomes. Examinations of differential climate mobility pressures and preferences for adaptation increase understanding of the transformations reshaping coastal communities today to guide more equitable societal adaptations in the future.