Toward data-driven, dynamical complex systems approaches to disaster resilience.

With rapid urbanization and increasing climate risks, enhancing the resilience of urban systems has never been more important. Despite the availability of massive datasets of human behavior (e.g., mobile phone data, satellite imagery), studies on disaster resilience have been limited to using static measures as proxies for resilience. However, static metrics have significant drawbacks such as their inability to capture the effects of compounding and accumulating disaster shocks; dynamic interdependencies of social, economic, and infrastructure systems; and critical transitions and regime shifts, which are essential components of the complex disaster resilience process. In this article, we argue that the disaster resilience literature needs to take the opportunities of big data and move toward a different research direction, which is to develop data-driven, dynamical complex systems models of disaster resilience. Data-driven complex systems modeling approaches could overcome the drawbacks of static measures and allow us to quantitatively model the dynamic recovery trajectories and intrinsic resilience characteristics of communities in a generic manner by leveraging large-scale and granular observations. This approach brings a paradigm shift in modeling the disaster resilience process and its linkage with the recovery process, paving the way to answering important questions for policy applications via counterfactual analysis and simulations.

Toward General Principles for Resilience Engineering.

Maintaining the performance of infrastructure-dependent systems in the face of surprises and unknowable risks is a grand challenge. Addressing this issue requires a better understanding of enabling conditions or principles that promote system resilience in a universal way. In this study, a set of such principles is interpreted as a group of interrelated conditions or organizational qualities that, taken together, engender system resilience. The field of resilience engineering identifies basic system or organizational qualities (e.g., abilities for learning) that are associated with enhanced general resilience and has packaged them into a set of principles that should be fostered. However, supporting conditions that give rise to such first-order system qualities remain elusive in the field. An integrative understanding of how such conditions co-occur and fit together to bring about resilience, therefore, has been less clear. This article contributes to addressing this gap by identifying a potentially more comprehensive set of principles for building general resilience in infrastructure-dependent systems. In approaching this aim, we organize scattered notions from across the literature. To reflect the partly self-organizing nature of infrastructure-dependent systems, we compare and synthesize two lines of research on resilience: resilience engineering and social-ecological system resilience. Although some of the principles discussed within the two fields overlap, there are some nuanced differences. By comparing and synthesizing the knowledge developed in them, we recommend an updated set of resilience-enhancing principles for infrastructure-dependent systems. In addition to proposing an expanded list of principles, we illustrate how these principles can co-occur and their interdependencies.

Characterizing long-term land use/cover change in the United States from 1850 to 2000 using a nonlinear bi-analytical model.

We relate the historical (1850-2000) spatial and temporal changes in cropland cover in the conterminous United States to several socio-economic and biophysical determinants using an eco-region based spatial framework. Results show population density as a major determinant during the nineteenth century, and biophysical suitability as the major determinant during the twentieth century. We further examine the role of technological innovations, socio-economic and socio-ecological feedbacks that have either sustained or altered the cropland trajectories in different eco-regions. The cropland trajectories for each of the 84 level-III eco-regions were analyzed using a nonlinear bi-analytical model. In the Eastern United States, low biophysically suitable eco-regions, e.g., New England, have shown continual decline in the cropland after reaching peak levels. The cropland trajectories in high biophysically suitable regions, e.g., Corn Belt, have stabilized after reaching peak levels. In the Western United States, low-intensity crop cover (<10 %) is sustained with irrigation support. A slower rate of land conversion was found in the industrial period. Significant effect of Conservation Reserve Program on planted crop area is found in last two decades (1990-2010).

Spatial structure of city population growth.

We show here that population growth, resolved at the county level, is spatially heterogeneous both among and within the U.S. metropolitan statistical areas. Our analysis of data for over 3,100 U.S. counties reveals that annual population flows, resulting from domestic migration during the 2015-2019 period, are much larger than natural demographic growth, and are primarily responsible for this heterogeneous growth. More precisely, we show that intra-city flows are generally along a negative population density gradient, while inter-city flows are concentrated in high-density core areas. Intra-city flows are anisotropic and generally directed towards external counties of cities, driving asymmetrical urban sprawl. Such domestic migration dynamics are also responsible for tempering local population shocks by redistributing inflows within a given city. This spill-over effect leads to a smoother population dynamics at the county level, in contrast to that observed at the city level. Understanding the spatial structure of domestic migration flows is a key ingredient for analyzing their drivers and consequences, thus representing a crucial knowledge for urban policy makers and planners.

Emergent spatial patterns of competing benthic and pelagic algae in a river network: A parsimonious basin-scale modeling analysis.

Algae, as primary producers in riverine ecosystems, are found in two distinct habitats: benthic and pelagic algae typically prevalent in shallow/small and deep/large streams, respectively. Over an entire river continuum, spatiotemporal patterns of the two algal communities reflect specificity in habitat preference determined by geomorphic structure, hydroclimatic controls, and spatiotemporal heterogeneity in nutrient loads from point- and diffuse-sources. By representing these complex interactions between geomorphic, hydrologic, geochemical, and ecological processes, we present here a new river-network-scale dynamic model (CnANDY) for pelagic (A) and benthic (B) algae competing for energy and one limiting nutrient (phosphorus, P). We used the urbanized Weser River Basin in Germany (7th-order; ~8.4 million population; ~46 K km2) as a case study and analyzed simulations for equilibrium mass and concentrations under steady median river discharge. We also examined P, A, and B spatial patterns in four sub-basins. We found an emerging pattern characterized by scaling of P and A concentrations over stream-order ω, whereas B concentration was described by three distinct phases. Furthermore, an abrupt algal regime shift occurred in intermediate streams from B dominance in ω≤3 to exclusive A presence in ω≥6. Modeled and long-term basin-scale monitored dissolved P concentrations matched well for ω>4, and with overlapping ranges in ω<3. Power-spectral analyses for the equilibrium P, A, and B mass distributions along hydrological flow paths showed stronger clustering compared to geomorphological attributes, and longer spatial autocorrelation distance for A compared to B. We discuss the implications of our findings for advancing hydro-ecological concepts, guiding monitoring, informing management of water quality, restoring aquatic habitat, and extending CnANDY model to other river basins.

Emergent self-similarity and scaling properties of fractal intra-urban heat islets for diverse global cities.

Urban areas experience elevated temperatures due to the urban heat island (UHI) effect. However, temperatures within cities vary considerably and their spatial heterogeneity is not well characterized. Here, we use land surface temperature (LST) of 78 global cities to show that the surface UHI (SUHI) is fractal. We use percentile-based thermal thresholds to identify heat clusters emerging within SUHI and refer to them collectively as intra-urban heat islets. The islets display properties analogous to that of a percolating system as we vary the thermal thresholds. At percolation threshold, the size distribution of these islets in all cities follows a power law, with a scaling exponent (ß) of 1.88 (±0.23,95%CI) and an aggregated perimeter fractal dimension (D) of 1.33 (±0.064,95%CI). This commonality indicates that despite the diversity in urban form and function across the world, the urban temperature patterns are different realizations with the same aggregated statistical properties. Furthermore, we observe the convergence of these scaling exponents as the city sizes increase. Therefore, while the effect of diverse urban morphologies is evident in smaller cities, in the mean, the larger cities are alike. Lastly, we calculate the mean islet intensities, i.e., the difference between mean islet temperature and thermal threshold, and show that it follows an exponential distribution, with rate parameter λ, for all cities. λ varied widely across the cities and can be used to quantify the spatial heterogeneity within SUHIs. In conclusion, we present a basis for a unified characterization of urban heat from the spatial scales of an urban block to a megalopolis.

Paradoxical impact of sprawling intra-Urban Heat Islets: Reducing mean surface temperatures while enhancing local extremes.

Extreme heat is one of the deadliest health hazards that is projected to increase in intensity and persistence in the near future. Here, we tackle the problem of spatially heterogeneous heat distribution within urban areas. We develop a novel multi-scale metric of identifying emerging heat clusters at various percentile-based thermal thresholds and refer to them collectively as intra-Urban Heat Islets. Using remotely sensed Land Surface Temperatures, we first quantify the spatial organization of heat islets in cities at various degrees of sprawl and densification. We then condense the size, spacing, and intensity information about heterogeneous clusters into probability distributions that can be described using single scaling exponents (denoted by ß, [Formula: see text], and λ, respectively). This allows for a seamless comparison of the heat islet characteristics across cities at varying spatial scales and improves on the traditional Surface Urban Heat Island (SUHI) Intensity as a bulk metric. Analysis of Heat Islet Size distributions demonstrates the emergence of two classes where the dense cities follow a Pareto distribution, and the sprawling cities show an exponential tempering of Pareto tail. This indicates a significantly reduced probability of encountering large heat islets for sprawling cities. In contrast, analysis of Heat Islet Intensity distributions indicates that while a sprawling configuration is favorable for reducing the mean SUHI Intensity of a city, for the same mean, it also results in higher local thermal extremes. This poses a paradox for urban designers in adopting expansion or densification as a growth trajectory to mitigate the UHI.

Publisher's Note: Generic patterns in the evolution of urban water networks: Evidence from a large Asian city [Phys. Rev. E 95, 032312 (2017)].

This corrects the article DOI: 10.1103/PhysRevE.95.032312.

Stochastic dynamics of wetlandscapes: Ecohydrological implications of shifts in hydro-climatic forcing and landscape configuration.

Wetlands are embedded in landscapes in fractal spatial patterns, and are characterized by highly dynamic, interlinked hydrological, biogeochemical, and ecological functions. We propose here a stochastic approach to evaluate and predict the spatiotemporal hydrologic variability of wetlands at landscape scale (100 km2). Stochastic hydro-climatic forcing (daily rainfall and evapotranspiration) and the landscape topographic setting (spatial structure of wetlands within the landscape) are key drivers of wetland eco-hydrologic functionality. The novelty of our approach lies in the quantification of the hydrological dynamics for all wetlands distributed in a given landscape, and in linking stochasticity of hydroclimatic forcing and ecologically meaningful wetland network metrics. We applied the modeling framework to investigate daily hydrologic dynamics in six landscapes across the U.S. that span gradients of hydroclimate and abundance of wetlands. We assess landscape-scale patterns using four key wetland hydrological attributes that have significance in terms of aquatic habitat suitability and dispersal: (1) Abundance (2) Diversity (3) Persistence, and (4) Accessibility. We observe that the hydrologic responses of each of the six landscapes are driven by the interactions between regional stochastic hydro-climatic forcing and landscape topographic setting. Despite differences in these features, similar scaling relations define diversity (area distributions) and accessibility (separation-distance distributions). Persistence of hydrologic regimes, defined by duration of inundation above thresholds, was least in more-arid settings, and higher in humid settings, consistent with intuitive understanding. These results can support assessments of the spatiotemporal variability of ecohydrological attributes in diverse wetlandscapes, including aquatic species dispersal and habitat suitability for unique flora and fauna.

Real-time forecasting of pesticide concentrations in soil.

Forecasting pesticide residues in soils in real time is essential for agronomic purposes, to manage phytotoxic effects, and in catchments to manage surface and ground water quality. This has not been possible in the past due to both modelling and measurement constraints. Here, the analytical transient probability distribution (pdf) of pesticide concentrations is derived. The pdf results from the random ways in which rain events occur after pesticide application. First-order degradation kinetics and linear equilibrium sorption are assumed. The analytical pdfs allow understanding of the relative contributions that climate (mean storm depth and mean rainfall event frequency) and chemical (sorption and degradation) properties have on the variability of soil concentrations into the future. We demonstrated the two uncertain reaction parameters can be constrained using Bayesian methods. An approach to a Bayesian informed forecast is then presented. With the use of new rapid tests capable of providing quantitative measurements of soil concentrations in the field, real-time forecasting of future pesticide concentrations now looks possible for the first time. Such an approach offers new means to manage crops, soils and water quality, and may be extended to other classes of pesticides for ecological risk assessment purposes.

Bioavailable DDT residues in sediments: laboratory assessment of ageing effects using semi-permeable membrane devices.

We describe the reduction in bioavailability of DDT in contaminated soil after it was incubated as sediment for 365 d. Bioavailability was assessed using semi-permeable membranes. Contaminated soils from three cattle dip sites, one spiked paired uncontaminated site, and one spiked OECD standard soil were studied. Sandy soil with residues of 1880 mg/kg summation operator DDT incurred since 1962, initially had 4.6% of summation operator DDT available, reducing to 0.6% following 365 d. Clay soil (1108 mg summation operator DDT/kg) had 4.1% initially available, reducing to 0.3% after 365 d. Freshly spiked soils had a greater amount of DDT initially available (10.9%), but this reduced to 1.5% by the end of the incubation. Of the DDT congeners, both o,p'-DDD and p,p'-DDD were most bioavailable in the soils, but also had the most significant decrease following incubation.

Changes in contaminant mass discharge from DNAPL source mass depletion: evaluation at two field sites.

Changes in contaminant fluxes resulting from aggressive remediation of dense nonaqueous phase liquid (DNAPL) source zone were investigated at two sites, one at Hill Air Force Base (AFB), Utah, and the other at Ft. Lewis Military Reservation, Washington. Passive Flux Meters (PFM) and a variation of the Integral Pumping Test (IPT) were used to measure fluxes in ten wells installed along a transect down-gradient of the trichloroethylene (TCE) source zone, and perpendicular to the mean groundwater flow direction. At both sites, groundwater and contaminant fluxes were measured before and after the source-zone treatment. The measured contaminant fluxes (J; ML(-2)T(-1)) were integrated across the well transect to estimate contaminant mass discharge (M(D); MT(-1)) from the source zone. Estimated M(D) before source treatment, based on both PFM and IPT methods, were approximately 76 g/day for TCE at the Hill AFB site; and approximately 640 g/day for TCE, and approximately 206 g/day for cis-dichloroethylene (DCE) at the Ft. Lewis site. TCE flux measurements made 1 year after source treatment at the Hill AFB site decreased to approximately 5 g/day. On the other hand, increased fluxes of DCE, a degradation byproduct of TCE, in tests subsequent to remediation at the Hill AFB site suggest enhanced microbial degradation after surfactant flooding. At the Ft. Lewis site, TCE mass discharge rates subsequent to remediation decreased to approximately 3 g/day for TCE and approximately 3 g/day for DCE approximately 1.8 years after remediation. At both field sites, PFM and IPT approaches provided comparable results for contaminant mass discharge rates, and show significant reductions (>90%) in TCE mass discharge as a result of DNAPL mass depletion from the source zone.

Dynamics of functional failures and recovery in complex road networks.

We propose a new framework for modeling the evolution of functional failures and recoveries in complex networks, with traffic congestion on road networks as the case study. Differently from conventional approaches, we transform the evolution of functional states into an equivalent dynamic structural process: dual-vertex splitting and coalescing embedded within the original network structure. The proposed model successfully explains traffic congestion and recovery patterns at the city scale based on high-resolution data from two megacities. Numerical analysis shows that certain network structural attributes can amplify or suppress cascading functional failures. Our approach represents a new general framework to model functional failures and recoveries in flow-based networks and allows understanding of the interplay between structure and function for flow-induced failure propagation and recovery.

Generic patterns in the evolution of urban water networks: Evidence from a large Asian city.

We examine high-resolution urban infrastructure data using every pipe for the water distribution network (WDN) and sanitary sewer network (SSN) in a large Asian city (≈4 million residents) to explore the structure as well as the spatial and temporal evolution of these infrastructure networks. Network data were spatially disaggregated into multiple subnets to examine intracity topological differences for functional zones of the WDN and SSN, and time-stamped SSN data were examined to understand network evolution over several decades as the city expanded. Graphs were generated using a dual-mapping technique (Hierarchical Intersection Continuity Negotiation), which emphasizes the functional attributes of these networks. Network graphs for WDNs and SSNs are characterized by several network topological metrics, and a double Pareto (power-law) model approximates the node-degree distributions of both water infrastructure networks (WDN and SSN), across spatial and hierarchical scales relevant to urban settings, and throughout their temporal evolution over several decades. These results indicate that generic mechanisms govern the networks' evolution, similar to those of scale-free networks found in nature. Deviations from the general topological patterns are indicative of (1) incomplete establishment of network hierarchies and functional network evolution, (2) capacity for growth (expansion) or densification (e.g., in-fill), and (3) likely network vulnerabilities. We discuss the implications of our findings for the (re-)design of urban infrastructure networks to enhance their resilience to external and internal threats.

Enhanced Fenton's destruction of non-aqueous phase perchloroethylene in soil systems.

The Fenton's system is applied to the destruction of perchloroethylene (PCE) present as a dense non-aqueous phase liquid (DNAPL) in soil slurry systems; the initial concentration of PCE was 45 times higher than its aqueous solubility. Studies were conducted in two matrices: Ottawa sand and soil from Warsaw, IN. In Ottawa sand, a 60-62% decrease in PCE concentration was observed, and Cl(-) recovery was 47-58%, whereas in Warsaw soil, a 44-49% decrease in PCE concentration and a Cl(-) recovery of 40-42% were observed after the addition of 600 mM H(2)O(2) and 10 mM dissolved iron. Significantly enhanced destruction resulted during application of N-(2-hydroxyethyl) iminodiacetic acid (HEIDA) to Warsaw soil. For example, in the absence of HEIDA in Warsaw soil, 36% PCE loss and 33% Cl(-) release were observed at 600 mM H(2)O(2) and 5 mM Fe(III), while 74% PCE loss and 63% Cl(-) release were achieved at 600 mM H(2)O(2) and 5 mM Fe(III)-HEIDA. For both soils, the catalytic activities of Fe(II) and Fe(III) were nearly equivalent. These findings clearly demonstrate that system design can be optimized with regard to process variables in Fenton's treatment of DNAPL in soils.

Laboratory studies to characterize the efficacy of sand capping a coal tar-contaminated sediment.

Placement of a microbial active sand cap on a coal tar-contaminated river sediment has been suggested as a cost effective remediation strategy. This approach assumes that the flux of contaminants from the sediment is sufficiently balanced by oxygen and nutrient fluxes into the sand layer such that microbial activity will reduce contaminant concentrations within the new benthic zone and reduce the contaminant flux to the water column. The dynamics of such a system were evaluated using batch and column studies with microbial communities from tar-contaminated sediment under different aeration and nutrient inputs. In a 30-d batch degradation study on aqueous extracts of coal tar sediment, oxygen and nutrient concentrations were found to be key parameters controlling the degradation rates of polycyclic aromatic hydrocarbons (PAHs). For the five PAHs monitored (naphthalene, fluorene, phenanthrene, anthracene, and pyrene), degradation rates were inversely proportional to molecular size. For the column studies, where three columns were packed with a 20-cm sand layer on the top of a 5 cm of sediment layer, flow was established to sand layers with (1) aerated water, (2) N(2) sparged water, or (3) HgCl(2)-sterilized N(2) sparged water. After steady-state conditions, PAH concentrations in effluents were the lowest in the aerated column, except for pyrene, whose concentration was invariant with all effluents. These laboratory scale studies support that if sufficient aeration can be achieved in the field through either active and passive means, the resulting microbially active sand layer can improve the water quality of the benthic zone and reduce the flux of many, but not all, PAHs to the water column.

Partitioning of mono- and polycyclic aromatic hydrocarbons in a river sediment adjacent to a former manufactured gas plant site.

The equilibrium distributions, between water and coal-tar contaminated sediment, of 16 monocyclic and polycyclic aromatic hydrocarbons were measured and evaluated for consistency with a Raoult's Law-based quantitative relationship. The quantitative relationship calculates the pore water concentration as the product of the aqueous solubility (or for compounds that are solid at room temperature, the aqueous super-cooled liquid solubility) and the mole fraction concentration of the compound within the liquid coal tar. Sediment was collected at five locations at two depths within a 120 m stretch of a river adjacent to a former manufactured gas plant, and all samples contained non-aqueous phase liquid (NAPL) coal tar. Although the amount of coal tar varied between samples by over an order of magnitude, the Raoult's Law-based NAPL-water partition coefficients for each monocyclic or 2- or 3-ring polycyclic aromatic hydrocarbon measured in this study generally varied within a factor of 2 over all sediments.

Cosolvent-enhanced chemical oxidation of perchloroethylene by potassium permanganate.

A laboratory study was conducted to examine cosolvent-enhanced in-situ chemical oxidation (ISCO) of perchloroethylene (PCE) using potassium permanganate (KMnO4). The conceptual basis for this new technique is to enhance permanganate oxidation of dense non-aqueous phase liquids (DNAPLs) with the addition of a cosolvent, thereby increasing DNAPL solubility while avoiding mobilization. Among 17 cosolvent candidates screened, tertiary butyl alcohol (TBA) and acetone were the most stable in the presence of KMnO4, both of which increased PCE aqueous solubility significantly, and therefore are suitable to be used as cosolvent in this study. Batch experiments indicated that the second-order rate constant for PCE oxidation by potassium permanganate was 0.043+/-0.002 M(-1) s(-1) in the purely aqueous (no cosolvent) solution. In the presence of 20% cosolvent (volume fraction=fc=0.2), the rate constant decreased to 0.036+/-0.003 M(-1) s(-1) with TBA and to 0.031+/-0.002 M(-1) s(-1) with acetone. However, in the presence of free-phase PCE, chloride ion concentration from PCE oxidation in acetone/water solutions (fc=0.2) was about twice that in aqueous solutions, indicating that the increase in PCE solubility more than compensated for the decrease in reaction rate constant, such that the oxidation efficiency of PCE was increased with cosolvent. A complete chlorine mass balance was observed in the aqueous system, whereas approximately 70% was obtained in TBA/water or acetone/water (fc=0.2). In soil columns containing residual DNAPL and subjected to isocratic flushing with step-wise increases in f(c) cosolvent, TBA at fc=0.2 resulted in PCE mobilization, whereas acetone at fc

Field demonstration of surfactant-enhanced solubilization of DNAPL at Dover Air Force Base, Delaware.

This study reports on a surfactant-based flood for tetrachloroethylene (PCE) removal from a control test cell at the Dover National Test Site. The surfactant formulation (sodium dihexyl sulfosuccinate (Aerosol-MA or AMA), isopropanol and calcium chloride) was able to achieve a high concentration of PCE in swollen micelles (supersolubilization) without vertical PCE migration. The hydraulic system included eight screened wells that were operated in both vertical circulation and line drive configurations. After 10 pore volumes of flushing, the overall PCE removal was 68% (65% of which corresponded to the surfactant flooding alone). In addition, the residual PCE saturation was reduced from 0.7% to 0.2%, and the concentration of PCE in the groundwater was reduced from 37-190 mg/L before the flushing to 7.3 mg/L after flooding. Recycling the surfactant solution reduced the required surfactant mass (and thus cost, and waste) by 90%. Close to 80% of the total PCE removal was obtained during the first five pore volumes which were operated in an upward vertical circulation flow scheme. No free oil phase was observed during the test. Further analysis of multilevel sampler data suggests that most of the trapped oil remaining in the cell was likely localized in secluded regions of the aquifer, which helps explain the lower PCE groundwater concentration after remedial activities. In summary, this field study demonstrated the feasibility of surfactant-enhanced remediation to reduce the mass in the source zone and significantly reduce the PCE aqueous concentration and therefore the risk associated with the contaminant plume.

Oxygenated fuel induced cosolvent effects on the dissolution of polynuclear aromatic hydrocarbons from contaminated soil.

The cosolvent-induced dissolution of polynuclear aromatic hydrocarbons (PAHs) from contaminated soil caused by oxygenated fuel spills was studied. Oxygenated fuel induces a solvent flushing effect on the contaminated soil due to the high content of oxygenated compounds (i.e., methanol, ethanol, and methyl tert butyl ether (MTBE)). The miscible displacement techniques were applied to evaluate the increased potential for secondary contamination in an impacted site. Significant solubility enhancement of the 18 PAHs monitored during fuel spill simulation and cosolvent flushing is clearly evident when compared to normal water dissolution. The breakthrough concentration profile for each PAH constituent was integrated over the cumulative effluent volume (i.e., the zeroth moment) to determine the total PAH mass removed during the experiment. The removal efficiency of PAHs ranges from 46.6% to 99.9% in three oxygenated fuels (i.e., M85, E85, and oxygenated gasoline) during the fuel spill. Several factors including hydrophobicity of compounds, nonequilibrium dissolution due to nonuniform coal tar distribution, and heterogeneous media properties affect the oxygenated compound-induced dissolution process. This study provides a basis to predict the facilitated transport of hydrophobic organic compounds from subsurface environment due to the cosolvent effects of oxygenated fuels.