Search

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., (© 2024. The Author(s).)

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., Competing Interests: The authors declare no conflict of interest., (© 2023 The Author(s).)

The value of sediment for helping coastal habitats and infrastructure respond to sea level rise is widely recognized. Across the country, coastal managers are seeking ways to beneficially use sediment sourced from dredging and other projects to counter coastal erosion and protect coastal resources. However, these projects are difficult to permit and have been slow to actualize. This paper draws on interviews with sediment managers and regulators in California to explore the challenges and opportunities for habitat restoration and beach nourishment within the current permitting regime. We find that permits are costly, difficult to obtain, and sometimes stand as a barrier to more sustainable and adaptive sediment management. We next characterize streamlining approaches and describe entities and ongoing efforts within California that apply them. Finally, we conclude that to keep pace with coastal losses due to climate change impacts, efforts toward efficient permitting must be accelerated and approaches diversified to support coastal resilience practices state-wide, in a timeframe that will allow coastal managers to innovate and adapt., (© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Land surface depressions play a central role in the transformation of rainfall to ponding, infiltration and runoff, yet digital elevation models (DEMs) used by spatially distributed hydrologic models that resolve land surface processes rarely capture land surface depressions at spatial scales relevant to this transformation. Methods to generate DEMs through processing of remote sensing data, such as optical and light detection and ranging (LiDAR) have favored surfaces without depressions to avoid adverse slopes that are problematic for many hydrologic routing methods. Here we present a new topographic conditioning workflow, Depression-Preserved DEM Processing (D2P) algorithm, which is designed to preserve physically meaningful surface depressions for depression-integrated and efficient hydrologic modeling. D2P includes several features: (1) an adaptive screening interval for delineation of depressions, (2) the ability to filter out anthropogenic land surface features (e.g., bridges), (3) the ability to blend river smoothing (e.g., a general downslope profile) and depression resolving functionality. From a case study in the Goodwin Creek Experimental Watershed, D2P successfully resolved 86% of the ponds at a DEM resolution of 10 m. Topographic conditioning was achieved with minimum impact as D2P reduced the number of modified cells from the original DEM by 51% compared to a conventional algorithm. Furthermore, hydrologic simulation using a D2P processed DEM resulted in a more robust characterization on surface water dynamics based on higher surface water storage as well as an attenuated and delayed peak streamflow., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Recovery housing is an important resource for many in their recovery from alcohol and other drug use disorders. Yet providers of recovery housing face a number of challenges. Many of these challenges are rooted in stigma and bias about recovery housing. The ability to describe the service and purported mechanisms of action vis-a-vis an overarching framework, approach, or orientation could also go a long way in adding credence to recovery housing as a service delivery mechanism. Several aspects of social model recovery are often explicitly built or organically reflected in how recovery housing operates, yet describing recovery housing in these terms often does little to demystify key features of recovery housing. To more fully cement social model recovery as the organizing framework for recovery housing this article aims to: review the history, current status, and evidence base for social model recovery; comment on challenges to implementing the social model in recovery housing; and delineate steps to overcome these challenges and establish an evidence base for social model recovery housing.

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.

Sea level rise (SLR), a well-documented and urgent aspect of anthropogenic global warming, threatens population and assets located in low-lying coastal regions all around the world. Common flood hazard assessment practices typically account for one driver at a time (e.g., either fluvial flooding only or ocean flooding only), whereas coastal cities vulnerable to SLR are at risk for flooding from multiple drivers (e.g., extreme coastal high tide, storm surge, and river flow). Here, we propose a bivariate flood hazard assessment approach that accounts for compound flooding from river flow and coastal water level, and we show that a univariate approach may not appropriately characterize the flood hazard if there are compounding effects. Using copulas and bivariate dependence analysis, we also quantify the increases in failure probabilities for 2030 and 2050 caused by SLR under representative concentration pathways 4.5 and 8.5. Additionally, the increase in failure probability is shown to be strongly affected by compounding effects. The proposed failure probability method offers an innovative tool for assessing compounding flood hazards in a warming climate., Competing Interests: The authors declare no conflict of interest.

Catchment urbanization perturbs the water and sediment budgets of streams, degrades stream health and function, and causes a constellation of flow, water quality, and ecological symptoms collectively known as the urban stream syndrome. Low-impact development (LID) technologies address the hydrologic symptoms of the urban stream syndrome by mimicking natural flow paths and restoring a natural water balance. Over annual time scales, the volumes of stormwater that should be infiltrated and harvested can be estimated from a catchment-scale water-balance given local climate conditions and preurban land cover. For all but the wettest regions of the world, a much larger volume of stormwater runoff should be harvested than infiltrated to maintain stream hydrology in a preurban state. Efforts to prevent or reverse hydrologic symptoms associated with the urban stream syndrome will therefore require: (1) selecting the right mix of LID technologies that provide regionally tailored ratios of stormwater harvesting and infiltration; (2) integrating these LID technologies into next-generation drainage systems; (3) maximizing potential cobenefits including water supply augmentation, flood protection, improved water quality, and urban amenities; and (4) long-term hydrologic monitoring to evaluate the efficacy of LID interventions.

Enclosed beaches along urban coastlines are frequent hot spots of fecal indicator bacteria (FIB) pollution. In this paper we present field measurements and modeling studies aimed at evaluating the impact of small storm drains on FIB pollution at enclosed beaches in Newport Bay, the second largest tidal embayment in Southern California. Our results suggest that small drains have a disproportionate impact on enclosed beach water quality for five reasons: (1) dry weather surface flows (primarily from overirrigation of lawns and ornamental plants) harbor FIB at concentrations exceeding recreational water quality criteria; (2) small drains can trap dry weather runoff during high tide, and then release it in a bolus during the falling tide when drainpipe outlets are exposed; (3) nearshore turbulence is low (turbulent diffusivities approximately 10(-3) m(2) s(-1)), limiting dilution of FIB and other runoff-associated pollutants once they enter the bay; (4) once in the bay, runoff can form buoyant plumes that further limit vertical mixing and dilution; and (5) local winds can force buoyant runoff plumes back against the shoreline, where water depth is minimal and human contact likely. Outdoor water conservation and urban retrofits that minimize the volume of dry and wet weather runoff entering the local storm drain system may be the best option for improving beach water quality in Newport Bay and other urban-impacted enclosed beaches.

Humans create vast quantities of wastewater through inefficiencies and poor management of water systems. The wasting of water poses sustainability challenges, depletes energy reserves, and undermines human water security and ecosystem health. Here we review emerging approaches for reusing wastewater and minimizing its generation. These complementary options make the most of scarce freshwater resources, serve the varying water needs of both developed and developing countries, and confer a variety of environmental benefits. Their widespread adoption will require changing how freshwater is sourced, used, managed, and priced.

Nearshore waters in bays, harbors, and estuaries are frequently contaminated with human pathogens and fecal indicator bacteria. Tracking down and mitigating this contamination is complicated by the many point and nonpoint sources of fecal pollution that can degrade water quality along the shore. From a survey of the published literature, we propose a conceptual and mathematical framework, the "beach boundary layer model", for understanding and quantifying the relative impact of beach-side and bay-side sources of fecal pollution on nearshore water quality. In the model, bacterial concentration in ankle depth water C(ankle) [bacteria L(-3)] depends on the flux m'' [bacteria L(-2) T(-1)] of fecal bacteria from beach-side sources (bather shedding, bird and dog feces, tidal washing of sediments, decaying vegetation, runoff from small drains, and shallow groundwater discharge), a cross-shore mass transfer velocity k [L T(-1)] that accounts for the physics of nearshore transport and mixing, and a background concentration C(bay) [bacteria L(-3)] attributable to bay-side sources of pollution that impact water quality over large regions (sewage outfalls, creeks and rivers): C(ankle) = m''/k + C(bay). We demonstrate the utility of the model for identifying risk factors and pollution sources likely to impact shoreline water quality, and evaluate the model's underlying assumptions using computational fluid dynamic simulations of flow, turbulence, and mass transport in a trapezoidal channel.

The scientific literature presents conflicting assessments of whether tidal saltwater wetlands reduce or increase fecal indicator bacteria (FIB) impairment of marine bathing waters. In this paper we describe the use of a two end-member salinity-mixing model to calculate FIB treatment efficiencies for the Talbert Marsh, a tidal saltwater wetland in Orange County, California. The mixing model utilized FIB and salinity measurements (n = 10 716) collected during a three-year longitudinal study of the Talbert Marsh. Over the course of the study the marsh received progressively less dry weather surface water runoff from the surrounding urban landscape due to the implementation of a runoff interception and treatment program. As the volume of dry-weather runoff entering the marsh declined, the Talbert Marsh more efficiently removed one FIB group (total coliform) and became a significantly smaller source of two other FIB groups (Escherichia coli and enterococci bacteria). Hence, there may be a maximum volume of dry weather urban runoff (in this case < 1% of the average tidal prism of 2.35 x 10(5) m3/day) that a tidal saltwater wetland can receive, above which the wetland is a net source of FIB to coastal waters.

There are an increasing number of coastal ocean observing systems that deploy new technology for environmental sensing and stream these data in near-real-time to end-users (e.g., scientists and coastal managers) via the worldwide web. The temporal resolution, spatial coverage, and accessibility of these data open up new opportunities for better understanding and managing the coastal ocean, but they also present enormous challenges relative to data processing and data interpretation, particularly in cases where these data are to inform rapid management decision making. Here we demonstrate that changes in surf zone water quality at a popular beach in southern California are signaled by changes in the Fisher Information and Shannon Entropy of high frequency (1/4 min(-1)) measurements of salinity and temperature in the surf zone. These results support the hypothesis that the information content of environmental signals, such as salinity and temperature, can be used to identify changes in the water quality of the coastal ocean. More generally, the approach described here-of using information theory indices calculated from monitoring data as real-time indicators of environmental change-is quite general, and may therefore be applicable to other situations where rapid management decisions are based on high-frequency measurements of environmental parameters.

Recreational water quality at beaches in California and elsewhere is often poor near the outlets of rivers, estuaries, and lagoons. This condition has prompted interest in the role of wetlands in modulating surface water concentrations of fecal indicator bacteria (FIB), the basis of water quality standards internationally. A model was developed and applied to predict the dry-weather tidal cycling of FIB in Talbert Marsh, an estuarine, intertidal wetland in Huntington Beach, California, in response to loads from urban runoff, bird feces, and resuspended sediments. The model predicts the advection, dispersion and die-off of total coliform, Escherichia coli, and enterococci using a depth-integrated formulation. We find that urban runoff and resuspension of contaminated wetland sediments are responsible for surface water concentrations of FIB in the wetland. Model predictions show that urban runoff controls surface water concentrations at inland sites and sediment resuspension controls surface water concentrations near the mouth. Direct wash-off of bird feces into the surface water is not a significant contributor, although bird feces can contribute to the sediment bacteria load. The key parameters needed to accurately predict FIB concentrations, using a validated hydrodynamic model, are: the load due to urban runoff, sediment erodibility parameters, and sediment concentrations and surface water die-off rates of enteric bacteria. In the present study, literature values for sediment erodibility and water column die-off rates are used and average concentrations of FIB are predicted within 1/2 log unit of measurements. Total coliform are predicted more accurately than E. coli or enterococci, both in terms of magnitude and tidal variability. Since wetland-dependent animals are natural sources of FIB, and FIB survive for long periods of time and may multiply in wetland sediments, these results highlight limitations of FIB as indicators of human fecal pollution in and near wetlands.

This paper describes a series of field studies aimed at identifying the spatial distribution and flow forcing of fecal indicator bacteria in dry and wet weather runoff from the Talbert watershed, a highly urbanized coastal watershed in southern California. Runoff from this watershed drains through tidal channels to a popular public beach, Huntington State Beach, which has experienced chronic surf zone water quality problems over the past several years. During dry weather, concentrations of fecal indicator bacteria are highest in inland urban runoff, intermediate in tidal channels harboring variable mixtures of urban runoff and ocean water, and lowest in ocean water at the base of the watershed. This inland-to-coastal gradient is consistent with the hypothesis that urban runoff from the watershed contributes to coastal pollution. On a year round basis, the vast majority (>99%) of fecal indicator bacteria loading occurs during storm events when runoff diversions, the management approach of choice, are not operating. During storms, the load of fecal indicator bacteria in runoff follows a power law of the form L approximately Qn, where L is the loading rate (in units of fecal indicator bacteria per time), Q is the volumetric flow rate (in units of volume per time), and the exponent n ranges from 1 to 1.5. This power law and the observed range of exponent values are consistent with the predictions of a mathematical model that assumes fecal indicator bacteria in storm runoff originate from the erosion of contaminated sediments in drainage channels or storm sewers. The theoretical analysis, which is based on a conventional model for the shear-induced erosion of particles from land and channel-bed surfaces, predicts that the magnitude of the exponent n reflects the geometry of the stormwater conveyance system from which the pollution derives. This raises the possibility that the scaling properties of pollutants in stormwater runoff (i.e., the value of n) may harbor information about the origin of nonpoint source pollution.

The surf zone is the unique environment where ocean meets land and a place of critical ecological, economic, and recreational importance. In the United States, this natural resource is increasingly off-limits to the public due to elevated concentrations of fecal indicator bacteria and other contaminants, the sources of which are often unknown. In this paper, we describe an approach for calculating mass budgets of pollutants in the surf zone from shoreline monitoring data. The analysis reveals that fecal indicator bacteria pollution in the surf zone at several contiguous beaches in Orange County, California, originates from well-defined locations along the shore, including the tidal outlets of the Santa Ana River and Talbert Marsh. Fecal pollution flows into the ocean from the Santa Ana River and Talbert Marsh outlets during ebb tides and from there is transported parallel to the shoreline by wave-driven surf zone currents and/or offshore tidal currents, frequently contaminating >5 km of the surf zone. The methodology developed here for locating and quantifying sources of surf zone pollution should be applicable to a wide array of contaminants and coastal settings.

In this study, we evaluate the potential for internal tides to transport wastewater effluent from the Orange County Sanitation District (OCSD) ocean outfall toward Huntington Beach. Results of plume tracking studies show that OCSD effluent occasionally moves shoreward into water less than 20 m deep. Analyses of current and temperature observations indicate cold water is regularly advected cross-shelf, in to and out of the nearshore, at both semi-diurnal and diurnal frequencies. Isotherms typically associated with the waste field near the outfall are observed just outside the Huntington Beach surf zone, where the total depth is less than 6 m, highlighting the extent of the cross-shelf transport. This advection is attributed to a mode 1 internal motion, or internal tide. On the basis of the analyses presented here, the OCSD plume cannot be ruled out as a contributor to poor bathing-water quality at Huntington Beach.

Elevated levels of enterococci bacteria, an indicator of fecal pollution, are routinely detected in the surf zone at Huntington State and City Beaches in southern California. A multidisciplinary study was carried out to identify sources of enterococci bacteria landward of the coastline. We find that enterococci bacteria are present at high concentrations in urban runoff, bird feces, marsh sediments, and on marine vegetation. Surprisingly, urban runoff appears to have relatively little impact on surf zone water quality because of the long time required for this water to travel from its source to the ocean. On the other hand, enterococci bacteria generated in a tidal saltwater marsh located near the beach significantly impact surf zone water quality. This study identifies a potential tradeoff between restoring coastal wetlands and protecting beach water quality and calls into question the use of ocean bathing water standards based on enterococci at locations near coastal wetlands.