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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Mechanisms of basin-scale nitrogen load reductions under intensified irrigated agriculture.

Irrigated agriculture can modify the cycling and transport of nitrogen (N), due to associated water diversions, water losses, and changes in transport flow-paths. We investigate dominant processes behind observed long-term changes in dissolved inorganic nitrogen (DIN) concentrations and loads of the extensive (465,000 km2) semi-arid Amu Darya River basin (ADRB) in Central Asia. We specifically considered a 40-year period (1960-2000) of large irrigation expansion, reduced river water flows, increased fertilizer application and net increase of N input into the soil-water system. Results showed that observed decreases in riverine DIN concentration near the Aral Sea outlet of ADRB primarily were due to increased recirculation of irrigation water, which extends the flow-path lengths and enhances N attenuation. The observed DIN concentrations matched a developed analytical relation between concentration attenuation and recirculation ratio, showing that a fourfold increase in basin-scale recirculation can increase DIN attenuation from 85 to 99%. Such effects have previously only been observed at small scales, in laboratory experiments and at individual agricultural plots. These results imply that increased recirculation can have contributed to observed increases in N attenuation in agriculturally dominated drainage basins in different parts of the world. Additionally, it can be important for basin scale attenuation of other pollutants, including phosphorous, metals and organic matter. A six-fold lower DIN export from ADRB during the period 1981-2000, compared to the period 1960-1980, was due to the combined result of drastic river flow reduction of almost 70%, and decreased DIN concentrations at the basin outlet. Several arid and semi-arid regions around the world are projected to undergo similar reductions in discharge as the ADRB due to climate change and agricultural intensification, and may therefore undergo comparable shifts in DIN export as shown here for the ADRB. For example, projected future increases of irrigation water withdrawals between 2005 and 2050 may decrease the DIN export from arid world regions by 40%.

Regime shifts under forcing of non-stationary attractors: Conceptual model and case studies in hydrologic systems.

We present here a conceptual model and analysis of complex systems using hypothetical cases of regime shifts resulting from temporal non-stationarity in attractor strengths, and then present selected published cases to illustrate such regime shifts in hydrologic systems (shallow aquatic ecosystems; water table shifts; soil salinization). Complex systems are dynamic and can exist in two or more stable states (or regimes). Temporal variations in state variables occur in response to fluctuations in external forcing, which are modulated by interactions among internal processes. Combined effects of external forcing and non-stationary strengths of alternative attractors can lead to shifts from original to alternate regimes. In systems with bi-stable states, when the strengths of two competing attractors are constant in time, or are non-stationary but change in a linear fashion, regime shifts are found to be temporally stationary and only controlled by the characteristics of the external forcing. However, when attractor strengths change in time non-linearly or vary stochastically, regime shifts in complex systems are characterized by non-stationary probability density functions (pdfs). We briefly discuss implications and challenges to prediction and management of hydrologic complex systems.

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).

Lessons in risk- versus resilience-based design and management.

The implications of recent catastrophic disasters, including the Fukushima Daiichi nuclear power plant accident, reach well beyond the immediate, direct environmental and human health risks. In a complex coupled system, disruptions from natural disasters and man-made accidents can quickly propagate through a complex chain of networks to cause unpredictable failures in other economic or social networks and other parts of the world. Recent disasters have revealed the inadequacy of a classical risk management approach. This study calls for a new resilience-based design and management paradigm that draws upon the ecological analogues of diversity and adaptation in response to low-probability and high-consequence disruptions.

A resilience perspective on biofuel production.

The recent investment boom and collapse of the corn ethanol industry calls into question the long-term sustainability of traditional approaches to biofuel technologies. Compared with petroleum-based transportation fuels, biofuel production systems are more closely connected to complex and variable natural systems. Especially as biofeedstock production itself becomes more independent of fossil fuel-based supports, stochasticity will become an increasingly important, inherent feature of biofuel feedstock production systems. Accordingly, a fundamental change in design philosophy is necessary to ensure the long-term viability of the biofuels industry. To respond effectively to unexpected disruptions, the new approach will require systems to be designed for resilience (indicated by diversity, efficiency, cohesion, and adaptability) rather than more narrowly defined measures of efficiency. This paper addresses important concepts in the design of coupled engineering-ecological systems (resistance, resilience, adaptability, and transformability) and examines biofuel conversion technologies from a resilience perspective. Conversion technologies that can accommodate multiple feedstocks and final products are suggested to enhance the diversity and flexibility of the entire industry.

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.

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.

Measurement of gas-accessible NAPL saturation in soil using gaseous tracers.

In this laboratory study, a new experimental method involving the use of a set of four gaseous tracers, was developed for measuring the NAPL saturation directly accessible to the mobile gas as well as the total NAPL saturation in unsaturated sand. One tracer with low water solubility (n-pentane) was used as the tracerthat partitions into NAPL directly accessible to the mobile gas, and another (chloroform)tracer with moderate water solubility and NAPL-partitioning, was selected for detecting total NAPL saturation. Helium and difluoromethane were used as the nonreactive and water-partitioning tracers, respectively. A saturated hydrocarbon, n-decane, was used as NAPL. Column experiments were conducted attwo water saturations (Sw = 0.68 and 0.16). The total NAPL saturation and NAPL saturation not directly accessible to the mobile gas were also successfully measured using the combined results of tracer experiments. At Sw = 0.68, only 28% of the total NAPL was detected by n-pentane, whereas 87% of the total NAPL was accessible to n-pentane at Sw = 0.16, implying more NAPL was accessible to the mobile gas phase at lower water saturation.

Inverse characterization of NAPL source zones.

This work presents a possible tool for inverse characterization of NAPL (nonaqueous phase liquid) source zones in terms of contaminant mass flux. A hybrid solution technique was applied that considers contaminant transport through a vertical flux plane. The hybrid solution technique takes advantage of the robust solution capabilities of simulated annealing (SA) and the uncertainty estimation capabilities of minimum relative entropy (MRE). The coupled technique (SA-MRE) provides probability density functions and confidence intervals that would not be available from an independent SA algorithm, and they are obtained more efficiently than if provided by an independent MRE algorithm. The SA-MRE method was used to characterize a NAPL source zone that was emplaced in a three-dimensional aquifer model. When dissolution experiments were complete, the aquifer model was excavated, and the distribution of NAPL zones was recorded using digital images of excavation grids. The excavation images were compiled into a three-dimensional representation of the source zone for comparison with and validation of modeling results.