Local-scale Model Research Articles

Multi-scenario validation of CALMET-RIMPUFF for local-scale atmospheric dispersion modeling around a nuclear powerplant site with complex topography

The CALMET-RIMPUFF is composed of the California Meteorological Model and the Risø Mesoscale PUFF model, which provides refined atmospheric dispersion modeling for nuclear emergency response. Because the performance of an atmospheric dispersion model can be case-sensitive, a multi-scenario validation is important to understand a model's behavior and limits. In this study, a multi-scenario validation of CALMET-RIMPUFF was performed based on six wind tunnel experiments simulating a real China's nuclear powerplant site with complex topographies and dense buildings. The CALMET-RIMPUFF simulations were compared with the measurements of the vertical wind profiles, 2D ground wind and concentration fields, both qualitatively and quantitatively. The results demonstrate that the CALMET-RIMPUFF can simulate the ground-level wind with acceptable accuracies. For vertical wind profiles, the accuracies show high dependencies on the local topography and building layout. The simulated ground concentrations generally agree well with the measurements, though the plume axis showed slight discrepancies from the measurements in three cases. Because the CALMET-RIMPUFF lacks a building effect module, it shows noticeable discrepancies in the building area. However, such discrepancies do not propagate to the downwind mountainous and sea areas, which the accuracies are quite satisfactory. Thus, the CALMET-RIMPUFF is capable for local-scale modeling at this site.

Twenty-first century regional temperature response in Chile based on empirical-statistical downscaling

Local scale estimates of temperature change in the twenty-first century are necessary for informed decision making in both the public and private sector. In order to generate such estimates for Chile, weather station data of the Dirección Meteorológica de Chile are used to identify large-scale predictors for local-scale temperature changes and construct individual empirical-statistical models for each station. The geographical coverage of weather stations ranges from Arica in the North to Punta Arenas in the South. Each model is trained in a cross-validated stepwise linear multiple regression procedure based on (24) weather station records and predictor time series derived from ERA-Interim reanalysis data. The time period 1979–2000 is used for training, while independent data from 2001 to 2015 serves as a basis for assessing model performance. The resulting transfer functions for each station are then directly coupled to MPI-ESM simulations for future climate change under emission scenarios RCP2.6, RCP4.5 and RCP 8.5 to estimate the local temperature response until 2100 A.D. Our investigation into predictors for local scale temperature changes support established knowledge of the main drivers of Chilean climate, i.e. a strong influence of the El Niño Southern Oscillation in northern Chile and frontal system-governed climate in central and southern Chile. Temperature downscaling yields high prediction skill scores (ca. 0.8), with highest scores for the mid-latitudes. When forced with MPI-ESM simulations, the statistical models predict local temperature deviations from the 1979–2015 mean that range between − 0.5–2 K, 0.5–3 K and 2–7 K for RCP2.6, RCP4.5 and RCP8.5 respectively.

Simulation of primary and secondary particles in the streets of Paris using MUNICH.

High particle concentrations are observed in the streets. Regional-scale chemistry-transport models are not able to reproduce these high concentrations, because their spatial resolution is not fine enough. Local-scale models are usually employed to simulate the high concentrations in street networks, but they often adopt substantial simplifications to determine background concentrations and use simplified chemistry. This study presents the new version of the local-scale Model of Urban Network of Intersecting Canyons and Highways (MUNICH) that integrates background concentrations simulated by the regional-scale chemistry-transport model Polair3D, and uses the same complex chemistry module as Polair3D, SSH-aerosol, to represent secondary aerosol formation. Gas and aerosol concentrations in Paris streets are simulated with MUNICH, considering a street-network with more than 3800 street segments, between 3 May and 30 June. Comparisons with PM10 and PM2.5 measurements at several locations of Paris show that the high PM10 and PM2.5 concentrations are well represented. Furthermore, the simulated chemical composition of fine particles corresponds well to a yearly measured composition. To understand the influence of the secondary pollutant formation, several sensitivity simulations are conducted. Simulations with and without gas-phase chemistry show that the influence of gas-phase chemistry on the formation of NO2 is large (37% on average over May and across all modelled streets), but the influence on condensables is lower (less than 2% to 3% on average at noon for inorganics and organics), but may reach more than 20% depending on the street. The assumption used to compute gas/particle mass transfer by condensation/evaporation is important for inorganic and organic compounds of particles, as using the thermodynamic equilibrium assumption leads to an overestimation of the organic concentrations by 4.7% on average (up to 31% at noon depending on the streets). Ammonia emissions from traffic lead to an increase in inorganic concentrations by 3% on average, reaching 26% depending on the street segments. Not taking into account gas-phase chemistry and aerosol dynamics in the modelling leads to an underestimation of organic concentrations by about 11% on average over the streets and time, but this underestimation may reach 51% depending on the streets and the time of the day.

Evaluation of the CALPUFF model performance for the estimation of the urban ecosystem CO2 flux

Land-use and land-cover changes due to urban expansion is recognized as one of the crucial factors affecting carbon dioxide emissions. In this study, the land conversion effects on soil CO2 fluxes associated with temperate re-established grasslands within the Forest Botanical Garden found on an anthropogenic landform were investigated. The present work analyses the capabilities and requirements of the CALPUFF Lagrangian puff air quality modelling system to simulate the spatial distribution of ecosystem respired CO2 in the urban domain. The results are validated against the available observations of CO2 fluxes in the urban environment using the closed-chamber method with the measurements of the stable carbon isotope ratio (δ13C) of daytime soil-respired CO2. The isotope mass balance partitioning approach was applied to distinguish biogenic portions of CO2 from the admixture of atmospheric air.The spatial and temporal amplitude of the simulated CO2 concentrations from the CALPUFF model showed considerable agreement with the tracer measurements of the biogenic CO2 component in the near-ground air (0.25 m). In most cases, however, the CALPUFF predictions of ecosystem-derived CO2 showed a general tendency toward considerable underestimation of real concentration levels. Such discrepancies are related to the difficulties associated with the optimization of biospheric CO2 flux and uptake from ecosystems by means of local-scale modelling. The modelled results implied that the CALPUFF performance in the dispersion simulation of CO2 concentrations within the urban ecosystems is very sensitive to the initial meteorological conditions, grid resolution, measurement timescale, and the calculated gas flux rate from soils. A significant negative correlation was found between hourly values of the average modelled CO2 and observed wind speed during the entire study campaign (r = −0.58 and ρ = −0.82 for Pearson and Spearman statistics, respectively, p < 0.05). Moreover, analysis of the impact of the deposition parameters on changes in the atmospheric concentration of carbon dioxide indicated significant dependency of the temporal CO2 distribution patterns on the precipitation-based events. According to the obtained estimates, the wet deposition rate during rain events was approximately two orders higher than the average dry deposition flux.Overall, the present case study indicates that the CALPUFF model has a rather acceptable predictive ability. A better agreement of model predictions and all field measurements, however, require further studies of CO2 exchange between the ecosystem and atmosphere and understanding where they need to be improved.

Flood mapping employing local, regional and global scale modeling methods for the Uruguay river

The delimitation of flooded areas is important information for natural disaster management, environmental impact prediction and for territorial planning. Flooding occurs when water levels overflow the limits of a river’s channel and seep into the floodplains. When they affect people, they are considered a natural disaster. The delimitation of a flooded area, in the occurrence of an extreme event, can be performed by using field techniques, such as mapping, surveying through the afflicted area or by taking aerial photographs. However, field survey is not a trivial task and not always does it allow for the attainment of the necessary data for a given project. For that purpose, there are various techniques that can be used to assess flood-spots. Some techniques are simpler, being based only on a Digital Elevation Model (DEM), and such is the case of the HAND model (Height Above Nearest Drainage), which has garnered plenty of fame recently in the process of applying delimitations to possibly flooded areas. Other techniques are more complex, like the use of hydrodynamic modeling. There are large-scale hydrologic-hydrodynamic models that simulate runoff generation and water transportation processes in the river basin from rainfall, basin, and meteorological data. This is the case of the large-scale distributed hydrological model called MGB (Modelo de Grandes Bacias), which has been developed and employed in these types of cases. However, there are no studies in the literature that compare the results produced by these multiple approaches using differing degrees of complexity and spatial scales. It was precisely to fill this gap in scientific literature that this work was developed. Featured here, for the first time, is the validation of the MGB model’s performance in two versions, one of regional scale and another of continental scale (MGB AS), in delimiting the flooded areas, compared to a satellite image of the inundation; and with two versions of the HAND model, one generated by a local study and the other by a global reference. The case study used in this validation was a major flood that occurred in the Uruguay River, near the town of Itaqui (Rio Grande do Sul), which borders Brazil and Argentina, in October 1997. The results show that the MGB model, both in the regional and the continental scales, could delimit the flooded area, with a few overestimations in the northern portion of the image. The HAND method at the local scale also allowed a mapping of the flooded area, with overestimates for more springhead-like areas in small tributaries. The HAND method at the global scale, on the other hand, proved to be inadequate for the purpose of delimiting flooded areas in this region. The leading cause is believed to be the small drainage area threshold linked to the utilized global HAND product. From the calculation of performance metrics, like hit rate, false alarm ratio and criticality index, Regional MGB was the one that most adequately expressed the extent of the flood observed in the Landsat 5 image when compared to the others, followed by MGB AS.

Multiscale consensus habitat modeling for landscape level conservation prioritization

Globally, wide-ranging carnivore populations are imperiled due to human-caused habitat fragmentation. Where populations are fragmented, habitat quantification is often the first step in conservation. Presence-only species distribution models can provide robust results when proper scales and data are considered. We aimed to identify habitat for a fragmented carnivore population at two scales and aid conservation prioritization by identifying potential future habitat fragmentation. We used location data and environmental variables to develop a consensus model using Maxent and Mahalanobis distance to identify black bear (Ursus americanus floridanus) habitat across Florida, USA. We compared areas of habitat to areas of predicted sea level rise, development, and protected areas. Local-scale models performed better than state-scale models. We identified 23,798 km2 of habitat at the local-scale and 45,703 km2 at the state-scale. Approximately 10% of state- and 14% of local-scale habitat may be inundated by 2100, 16% of state- and 7% of local-scale habitat may be developed, and 54% of state- and 15% of local-scale habitat is unprotected. Results suggest habitat is at risk of fragmentation. Lack of focused conservation and connectivity among bear subpopulations could further fragmentation, and ultimately threaten population stability as seen in other fragmented carnivore populations globally.

Multiscale Modeling of Patient Movement to Determine Effects of Surveillance on Healthcare-Associated Infections

Background: The transmission of pathogenic organisms in healthcare settings is a major cause of healthcare-associated infections (HAIs). In recent years, infections with carbapenem-resistant Enterobacteriaceae (CRE) have become a significant public health threat, in part because many patients are arriving at the hospital already colonized, and colonization is a major risk factor for infection. Reducing transmission requires understanding how patient movement drives the spread of CRE; however, analysis of this issue has mostly been modeled at a hospital-level without much consideration for the population dynamics that occur outside of the hospital setting and how patients move between healthcare settings. Patients move between hospitals, other healthcare settings, such as long-term care facilities (LTCFs), and the community, all of which pose different colonization risks. Thus, studying each environment in isolation fails to realistically address the consequences of large-scale policy interventions. One such intervention is a statewide electronic registry to track patients who are known to be colonized or have had a CRE infection. Understanding the potential for reducing CRE morbidity and mortality requires consideration of small- and large-scale effects on patients’ movement and transmission. Methods: We developed a multiscale, metapopulation model for hospitals, communities, and LTCFs in the state of Maryland. In our computational simulation, we included a regional- as well as a local-scale model that were informed by the patient-mix data from the Maryland Health Service Cost Review Commission. We examined the impact of implementing a registry compared to less coordinated scenarios. Results: The most effective policy was the implementation of an electronic registry which resulted in 9.6% median reduction in CRE HAIs in Maryland for simulated outcomes (Fig. 1). Other interventions included colonization screening at various or all hospitals and using a predictive algorithm to determine at-risk patients that need to be screened. These interventions only resulted in ~1%–3% reductions in HAIs. We also observed that coupling other interventions with an electronic registry does not aid in reducing more HAIs.Funding: NoneDisclosures: NoneBoxplot of simulated outcomes of all scenarios compared to the baseline scenario. The scenarios include (1) complete screening with no electronic registry, (2) selective screening with no electronic registry, (3) predictive screening with no electronic registry, (4) baseline with an electronic registry, (5) complete screening with an electronic registry, (6) selective screening with an electronic registry, and (7) predictive screening with an electronic registry. Scenarios 5-7 include the same interventions as 1–3 coupled with an electronic registry.

Large eddy simulations of airflow and particle deposition in pulsating bi-directional nasal drug delivery

Chronic rhinosinusitis is a common disease worldwide, and the frequently prescribed nasal sprays do not sufficiently deliver the topical medications to the target sites so that the final treatment in severe cases is surgery. Therefore, there is a huge demand to improve drug delivery devices that could target the maxillary sinuses more effectively. In the present study, different particle diameters and device pulsation flow rates, mainly used in pulsating aerosol delivery devices such as the PARI SINUS®, are considered to evaluate optimal maxillary sinus deposition efficiency (DE). Numerical simulations of the particle-laden flow using a large eddy simulation with a local dynamic k-equation sub-grid scale model are performed in a patient-specific nasal cavity. By increasing the pulsation flow rate from 4 l/min to 15 l/min, nasal DE increases from 37% to 68%. Similarly, by increasing the particle size from 1 µm to 5 µm, nasal DE increases from 34% to 43% for a pulsation flow rate of 4 l/min. Moreover, normalized velocity, vorticities, and particle deposition pattern in different regions of the main nasal cavity and maxillary sinuses are visualized and quantified. Due to the nosepiece placement in the right nostril, more particles penetrate into the right maxillary sinus than into the left maxillary sinus despite the maxillary ostium being larger in the left cavity. Lower pulsation flow rates such as 4 l/min improve the DE in the left maxillary sinus. The use of 3 µm particles enhances the DE in the right maxillary sinus as well as the overall total maxillary drug delivery.

A Digital Twin Approach to a Quantitative Microstructure-Property Study of Carbon Fibers through HRTEM Characterization and Multiscale FEA.

Microstructures of typical carbon fibers (CFs) from polyacrylonitrile (PAN) and pitch-based precursors were studied using a novel digital twin approach with individual carbon fibers for a local crystal scale model. The transmission electron microscopy (TEM) samples were prepared using a focused-ion beam (FIB) for both longitudinal and transverse directions of carbon fibers. Measurements of the crystal size and orientation were estimated from X-ray scattering. TEM imaging of graphitic packing facilitated further comprehension of associations between processing and final material properties, which could enable customization of microstructures for property targets. Then the detailed microstructural information and their X-ray scattering properties were incorporated into the simulation model of an individual carbon fiber. Assuming that graphene properties are the same among different forms of carbon fiber, a reasonable physics-based explanation for such a drastic decrease in strength is the dislocations between the graphitic units. The model reveals critical defects and uncertainty of carbon fiber microstructures, including skin/core alignment differences and propagating fracture before ultimate failure. The models are the first to quantify microstructures at the crystal scale with micromechanics and to estimate tensile and compressive mechanical properties of carbon fiber materials, as well as potentially develop new fundamental understandings for tailoring carbon fiber and composites properties.

The relationship between black carbon and polycyclic aromatic hydrocarbon exposures and mortality in Allegheny County, Pennsylvania

Black carbon (BC) and polycyclic aromatic hydrocarbons (PAHs) are components of fine particulate matter associated with adverse health outcomes. However, limited work has examined the effects of PM constituents on mortality risk. Our multiple regression analysis evaluated the association of estimated neighborhood-level average fine particulate matter (PM2.5), BC, and PAH concentrations for 2013 obtained from local-scale land use regression models with 2007–2011 census tract-level age-adjusted non-accidental, cardiovascular, pulmonary, cancer, and other mortality rates in Allegheny County, PA. Models were further adjusted for census tract-level race, education, and health insurance status. In our adjusted models, estimated pollutant concentrations were not consistently associated with mortality. Only one model’s effect estimate did not include the null value, although the relationship was opposite of our original hypothesis. An interquartile range (0.25 μg/m3) increase in BC concentration was associated with a 5.9% (95% CI − 11.07, − 0.36%) decrease in log-transformed cancer mortality. However, in all mortality categories, education and health insurance covariates had a robust association with outcomes. We did not find a consistent relationship between pollutant exposures and age-adjusted mortality rates in Allegheny County, PA. However, having health insurance and having greater than a high school diploma were associated with lower mortality risk.

Nonstationary modeling of NO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt;, NO and NO&amp;lt;sub&amp;gt;&amp;lt;i&amp;gt;x&amp;lt;/i&amp;gt;&amp;lt;/sub&amp;gt; in Paris using the Street-in-Grid model: coupling local and regional scales with a two-way dynamic approach

Abstract. Regional-scale chemistry-transport models have coarse spatial resolution (coarser than 1 km ×1 km) and can thus only simulate background concentrations. They fail to simulate the high concentrations observed close to roads and in streets, where a large part of the urban population lives. Local-scale models may be used to simulate concentrations in streets. They often assume that background concentrations are constant and/or use simplified chemistry. Recently developed, the multi-scale model Street-in-Grid (SinG) estimates gaseous pollutant concentrations simultaneously at local and regional scales by coupling them dynamically. This coupling combines the regional-scale chemistry-transport model Polair3D and a street-network model, the Model of Urban Network of Intersecting Canyons and Highway (MUNICH), with a two-way feedback. MUNICH explicitly models street canyons and intersections, and it is coupled to the first vertical level of the chemical-transport model, enabling the transfer of pollutant mass between the street-canyon roof and the atmosphere. The original versions of SinG and MUNICH adopt a stationary hypothesis to estimate pollutant concentrations in streets. Although the computation of the NOx concentration is numerically stable with the stationary approach, the partitioning between NO and NO2 is highly dependent on the time step of coupling between transport and chemistry processes. In this study, a new nonstationary approach is presented with a fine coupling between transport and chemistry, leading to numerically stable partitioning between NO and NO2. Simulations of NO, NO2 and NOx concentrations over Paris with SinG, MUNICH and Polair3D are compared to observations at traffic and urban stations to estimate the added value of multi-scale modeling with a two-way dynamical coupling between the regional and local scales. As expected, the regional chemical-transport model underestimates NO and NO2 concentrations in the streets. However, there is good agreement between the measurements and the concentrations simulated with MUNICH and SinG. The two-way dynamic coupling between the local and regional scales tends to be important for streets with an intermediate aspect ratio and with high traffic emissions.

The impact of ship emissions on air quality and human health in the Gothenburg area – Part 1: 2012 emissions

Abstract. Ship emissions in and around ports are of interest for urban air quality management in many harbour cities. We investigated the impact of regional and local ship emissions on urban air quality for 2012 conditions in the city of Gothenburg, Sweden, the largest cargo port in Scandinavia. In order to assess the effects of ship emissions, a coupled regional- and local-scale model system has been set up using ship emissions in the Baltic Sea and the North Sea as well as in and around the port of Gothenburg. Ship emissions were calculated with the Ship Traffic Emission Assessment Model (STEAM), taking into account individual vessel characteristics and vessel activity data. The calculated contributions from local and regional shipping to local air pollution in Gothenburg were found to be substantial, especially in areas around the city ports. The relative contribution from local shipping to annual mean NO2 concentrations was 14 % as the model domain average, while the relative contribution from regional shipping in the North Sea and the Baltic Sea was 26 %. In an area close to the city terminals, the contribution of NO2 from local shipping (33 %) was higher than that of road traffic (28 %), which indicates the importance of controlling local shipping emissions. Local shipping emissions of NOx led to a decrease in the summer mean O3 levels in the city by 0.5 ppb (∼2 %) on average. Regional shipping led to a slight increase in O3 concentrations; however, the overall effect of regional and the local shipping together was a small decrease in the summer mean O3 concentrations in the city. In addition, volatile organic compound (VOC) emissions from local shipping compensate up to 4 ppb of the decrease in summer O3 concentrations due to the NO titration effect. For particulate matter with a median aerodynamic diameter less than or equal to 2.5 µm (PM2.5), local ship emissions contributed only 3 % to the annual mean in the model domain, while regional shipping under 2012 conditions was a larger contributor, with an annual mean contribution of 11 % of the city domain average. Based on the modelled local and regional shipping contributions, the health effects of PM2.5, NO2 and ozone were assessed using the ALPHA-RiskPoll (ARP) model. An effect of the shipping-associated PM2.5 exposure in the modelled area was a mean decrease in the life expectancy by 0.015 years per person. The relative contribution of local shipping to the impact of total PM2.5 was 2.2 %, which can be compared to the 5.3 % contribution from local road traffic. The relative contribution of the regional shipping was 10.3 %. The mortalities due to the exposure to NO2 associated with shipping were calculated to be 2.6 premature deaths yr−1. The relative contribution of local and regional shipping to the total exposure to NO2 in the reference simulation was 14 % and 21 %, respectively. The shipping-related ozone exposures were due to the NO titration effect leading to a negative number of premature deaths. Our study shows that overall health impacts of regional shipping can be more significant than those of local shipping, emphasizing that abatement policy options on city-scale air pollution require close cooperation across governance levels. Our findings indicate that the strengthened Sulphur Emission Control Areas (SECAs) fuel sulphur limit from 1 % to 0.1 % in 2015, leading to a strong decrease in the formation of secondary particulate matter on a regional scale was an important step in improving the air quality in the city.

An integrated modelling approach for assessing the effect of multiscale complexity on groundwater source yields

A new multi-scale groundwater modelling methodology is presented to simulate pumped water levels in abstraction boreholes within regional groundwater models, providing a robust tool for assessing the sustainable yield of supply boreholes and improving our understanding of groundwater availability during drought. A 3D borehole-scale model, which solves the Darcy-Forchheimer equation in cylindrical co-ordinates to simulate both linear and non-linear radial flow to a borehole in a heterogeneous aquifer, is embedded within a Cartesian grid, using a hybrid radial-Cartesian finite difference method. The local-scale model is coupled to a regional groundwater model, ZOOMQ3D, using the OpenMI model linkage software, providing a flexible and efficient tool for assessing the behaviour of a groundwater source within its regional hydrogeological context during historic droughts and under climate change. The advantages of the new method are demonstrated through application to a Chalk supply borehole in the UK.

Evaluation of Global Water Resources Reanalysis Data for Estimating Flood Events in the Brahmaputra River Basin

Bangladesh and India are in a long-standing conflict with regard to the sharing of hydro-meteorological information of the Brahamaputra River. Consequently, it limits flood risk management in Bangladesh (the downstream country). Recently developed water resources reanalysis data appear as a promising alternative in providing this information. Further evaluation of these global datasets is needed to understand their capabilities to improve flood events estimation. In this study, the potential of the global water resources reanalysis (WRR) developed within the EU-FP7 project eartH2Observe is critically assessed for detecting and estimating flood events in the Brahmaputra River basin for 1980 to 2012 period. The discharge time series of five large-scale models available in the WRR dataset and two multi-model combinations are evaluated at different temporal resolutions and their performance is compared with a local-scale hydrological model. In situ data and reported damaging flood events compiled from two global disaster databases are used as benchmarks in flood events evaluation. Results show that the WRR data have reasonable skill in detecting flood events, though a significant underestimation of magnitude is found. This study also reveals that the individual large-scale models simulate peak flows similarly or even better than the local-scale model, capturing the hydrological behaviour in the basin and identifying the occurrence and severity of both observed and reported damaging flood events. In conclusion, this study gives insights in the applicability of global hydrological models and datasets for estimating flood events at a local-scale for transboundary rivers in water-sharing countries.

An Assessment of the Influence of Uncertainty in Temporally Evolving Streamflow Forecasts on Riverine Inundation Modeling

Continental-scale river forecasting platforms forecast streamflow at reaches that can be used as boundary conditions to drive a local-scale flood inundation model. Uncertainty accumulated during this process stems not only from any part of the forecasting chain but can also be caused by the daily variations in weather forcing that keeps evolving as the event advances. This work aims to examine the influence of the evolving forecast streamflow on predicting the maximum inundation for extreme floods. A diagnostic case study was made on the basis of a hindcast of Hurricane Matthew striking the eastern U.S. in 2016. The U.S. National Water Model was one-way coupled to a hydrodynamic inundation model through a developed automated workflow. Although the river forcing has significantly mismatched hydrographs versus observations, the simulated peak water surface elevations and maximum extents were validated to be comparable with the observations, which indicates that the inundation model may not be sensitive to the inherited uncertainty from the weather forcing. Moreover, the uncertainty of the forecast streamflow time series caused only one order of magnitude fewer variations in inundation prediction; this dampening effect may become clearer for extreme events with large areas inundated. In addition, the forecast total volume of stream discharge appears to be an important metric for assessing the performance of river forcing for inundation mapping, as a linear correlation between the total volume and the accuracy of the predicted peak water surface elevation and maximum extent was found, with the coefficients of determination all above 0.8. Extra best-practice experience of running similar operational tasks demonstrated the tradeoff between the cost and accuracy gain.

Mapping legal authority for terrestrial conservation corridors along streams.

Wildlife corridors aim to promote species’ persistence by connecting habitat patches across fragmented landscapes. Their implementation is limited by patterns of land ownership and complicated by differences in the jurisdictional and regulatory authorities under which lands are managed. Terrestrial corridor conservation requires coordination across jurisdictions and sectors subject to site‐specific overlapping sources of legal authority. Mapping spatial patterns of legal authority concurrent with habitat condition can illustrate opportunities to build or leverage capacity for connectivity conservation. Streamside areas provide pragmatic opportunities to leverage existing policy mechanisms for riverine and terrestrial habitat connectivity across boundaries. Conservation planners and practitioners can make use of these opportunities by harmonizing actions for multiple conservation outcomes. We formulated an integrative, data‐driven method for mapping multiple sources of legal authority weighted by capacity for coordinating terrestrial habitat conservation along streams. We generated a map of capacity to coordinate streamside corridor protections across a wildlife habitat gap to demonstrate this approach. We combined values representing coordination capacity and naturalness to generate an integrated legal‐ecological resistance map for connectivity modeling. We then computed least‐cost corridors across the integrated map, masking the terrestrial landscape to focus on streamside areas. Streamside least‐cost corridors in the integrated, local‐scale model diverged (∼25 km) from national‐scale least‐cost corridors based on naturalness. Spatial categories comparing legal‐ and naturalness‐based resistance values by stream reach highlighted potential locations for building or leveraging existing capacity through spatial coordination of policy mechanisms or restoration actions. Agencies or nongovernmental organizations intending to restore or maintain habitat connectivity across fragmented landscapes can use this approach to inform spatial prioritization and build coordination capacity. Article impact statement: Combined mapping of legal authority and habitat condition reveals capacity to coordinate actions along streams for clean water and wildlife.

Local decadal prediction according to statistical/dynamical approaches.

Dynamical climate models present an initialization problem due to the poor availability of deep oceanic data, which is required for the model assimilation process. In this sense, teleconnection indices, defined from spatial and temporal patterns of climatic variables, are conceived as useful tools to complement them. In this work, the near‐term climate predictability of 35 temperature and 36 precipitation time series of three cities (Barcelona, Bristol and Lisbon) was analysed using two approaches: (a) a statistical–dynamical combination of self‐predictable teleconnection indices and long‐term climate projections on a local scale and (b) dynamical model outputs obtained from drift‐corrected decadal experiments. Fourier and wavelet analyses were used to assess the predictability of seven teleconnection indices thanks to a cross‐validation process (with differentiated training and validation periods). The standardized absolute error of teleconnection‐based prediction was compared with that obtained from a (9) multi‐model ensemble based on the Coupled Model Intercomparison Project Phase 5. Results showed that decadal predictions at horizons between 20 and 30 years are adequate for temperature and precipitation if a teleconnection‐based approach is used, while temperature is better predicted from a 5‐year horizon using drift‐corrected dynamical outputs.

Inter-aquifer connectivity between Australia’s Great Artesian Basin and the overlying Condamine Alluvium: an assessment and its implications for the basin’s groundwater management

Coal seam gas (CSG), or coal bed methane, developments in sedimentary basins such as the Great Artesian Basin (GAB) in Australia, have the potential to impact on aquifers overlying and underlying the target coal formations. The extent to which this may occur depends upon the degree of hydrogeological connectivity between the coal formations and the surrounding aquifers or aquifer systems, with general implications for groundwater management. In southeast Australia, one such aquifer system, the Condamine Alluvium (CA), overlies the Walloon Coal Measures (WCM), which is a formation of the GAB and also a target for CSG production. To investigate the connectivity between the two systems, multiple lines of investigation were employed involving field investigations, data gathering and analysis (including reinterpretation of geology, multivariate hydrochemistry analysis, regional water-level mapping, drilling and coring across the contact zone, multiple piezometer installations, long-term pumping tests, groundwater-level monitoring and local-scale modelling). The study found a low level of connectivity between the GAB and the overlying CA. A layer of undifferentiated basement clay (referred to as the ‘transition zone’)—a mixture of alluvial clay and weathered basement—provides an effective impediment to flow across the CA and the underlying GAB formations. Results from the study potentially have wider application across the GAB and sedimentary basins where younger alluvial sediments associated with river systems frequently overlie the erosional surface.

Neighbourhood scale nitrogen dioxide land use regression modelling with regression kriging in an urban transportation corridor

Land use regression models (LUR) associate observed air pollution concentrations with surrounding land use characteristics for air pollution modelling. This technique is common in urban landscapes focused at a city-wide spatial scale. Our study tested the applicability of LUR modelling at a local scale, defined as multiple air monitors within a neighbourhood. The study area was 15.4 km of an urban transportation corridor in Mississauga, Canada. Nitrogen dioxide (NO2) was sampled at 112 sites during the summer in 2018 and observations ranged from 5.8 ppb to 19.65 ppb. A linear regression LUR model explained 69% of the variation in NO2 concentrations at this local scale, with estimated prediction errors less than 1.61 ppb, which were calculated by three cross-validation methods. Traffic volume, major and minor road lengths were key determinants among the predictor variables, and park area and distance to the nearest major intersection were the only variables with negative coefficients in the local-scale model. Extending the linear model approach with regression kriging improved the model's explanatory ability with a coefficient of determination at 0.91; however, smaller improvements were observed during cross-validation. Leave-one-out cross-validation for the linear model LUR model (RMSE = 1.44 ppb and a R2 = 0.64) and the regression kriging LUR model (RMSE = 1.34 ppb and a R2 = 0.69) were similar. Model performance remained stable when 10-fold cross-validation was performed with the regression kriging LUR model (regression kriging, R2 = 0.68 and RMSE = 1.36 ppb). The predicted air pollution levels ranged from 4.5 ppb to 25.6 ppb. This study demonstrates the ability of LUR modelling to perform well for local scale modelling in transportation dominated local urban environments.

Computational modelling of morphodynamic response of a macro-tidal beach to future climate variabilities

Global climate variabilities have the potential to impact many coastlines around the world, and can have detrimental effects on the stability of coastlines and their function as natural coastal defenses. This paper investigates the impacts of future extreme storms and sea level rise on morphodynamics of the macro-tidal Sefton Coast, UK, taking a process-based model as a tool to simulate a snap-shot of future beach change during storms. Sefton Coast represents one of the largest dune systems in the UK, where frontal dunes function as a natural barrier against extreme conditions. Future storm conditions were determined from global predictions of future waves at the end of the twenty first century. Future sea levels were determined based on climate change allowances set by the UK Environment Agency (EA), while future surge conditions were determined based on the guidelines also provided by EA.A nested numerical modelling approach, that combined a regional scale model with a local scale model with high resolution, is used. The modelling suite was first validated against measured waves, water levels and beach change, before using it to simulate morphodynamic change from numerous statistically significant ‘future’ storm conditions. Future storm-induced morphodynamic change of the Sefton coast was then compared with that from the present storms. The results reveal that this beach will experience significant climate change driven impacts where dune retreat during storms will be considerably higher in future. The results also reveal that due to the shape of the beach and its orientation to predominant wave approach direction, there will be a strong longshore variability of morphodynamic response to storms. It was also found that the water level in front of the dune (and hence surge and future sea level rise) is the most critical factor that determines beach erosion during a storm.