Spatially distributed observations in constraining inundation modelling uncertainties

The performance of two modelling approaches for predicting floodplain inundation is tested using observed flood extent and 26 distributed floodplain level observations for the 1997 flood event in the town of Usti nad Orlici in the Czech Republic. Although the one‐dimensional hydrodynamic model and the integrated one‐ and two‐dimensional model are shown to perform comparably against the flood extent data, the latter shows better performance against the distributed level observations. Comparable performance in predicting the extent of inundation is found to be primarily as a result of the urban reach considered, with flood extent constrained by road and railway embankments. Uncertainty in the elevation model used in both approaches is shown to have little effect on the reliability in predicting flood extent, with a greater impact on the ability in predicting the distributed level observations. These results show that reliability of flood inundation modelling in urban reaches, where flood risk assessment is of more interest than in more rural reaches, can be improved greatly if distributed observations of levels in the floodplain are used in constraining model uncertainties. Copyright © 2005 John Wiley & Sons, Ltd.     

Modelling non-stationary water ages in a tropical rainforest: A preliminary spatially distributed assessment

Pristine tropical forests play a critical role in regional and global climate systems. For a better understanding of the eco-hydrology of tropical “evergreen” vegetation, it is essential to know the partitioning of water into transpiration and evaporation, runoff and associated water ages. For this purpose, we evaluated how topography and vegetation influence water flux and age dynamics at high temporal (hourly) and spatial (10 m) resolution using the Spatially Distributed Tracer-Aided Rainfall-Runoff model for the tropics (STARRtropics). The model was applied in a tropical rainforest catchment (3.2 km²) where data were collected biweekly to monthly and during intensive monitoring campaigns from January 2013 to July 2018. The STARRtropics model was further developed, incorporating an isotope mass balance for evapotranspiration partitioning into transpiration and evaporation. Results exhibited a rapid streamflow response to rainfall inputs (water and isotopes) with limited mixing and a largely time-invariant baseflow isotope composition. Simulated soil water storage showed a transient response to rainfall inputs with a seasonal component directly resembling the streamflow dynamics which was independently evaluated using soil water content measurements. High transpiration fluxes (max 7 mm/day) were linked to lower slope gradients, deeper soils and greater leaf area index. Overall water partitioning resulted in 65% of the actual evapotranspiration being driven by vegetation with high transpiration rates over the drier months compared to the wet season. Time scales of water age were highly variable, ranging from hours to a few years. Stream water ages were conceptualized as a mixture of younger soil water and slightly older, deeper soil water and shallow groundwater with a maximum age of roughly 2 years during drought conditions (722 days). The simulated soil water ages ranged from hours to 162 days and for shallow groundwater up to 1,200 days. Despite the model assumptions, experimental challenges and data limitation, this preliminary spatially distributed model study enhances knowledge about the water ages and overall young water dominance in a tropical rainforest with little influence of deeper and older groundwater.     

Multi-method global sensitivity analysis of flood inundation models

Global sensitivity analysis is a valuable tool in understanding flood inundation models and deriving decisions on strategies to reduce model uncertainty. In this paper, a sensitivity analysis of a one-dimensional flood inundation model (HEC-RAS) on the River Alzette, Luxembourg, is presented. It is impossible to define sensitivity in a unique way and different methods can lead to a difference in ranking of importance of model factors. In this paper five different methods (Sobol, Kullback–Leibler entropy, Morris, regionalised sensitivity analysis and regression) are applied and the outcomes on selected examples compared. It is demonstrated that the different methods lead to completely different ranking of importance of the parameter factors and that it is impossible to draw firm conclusions about the relative sensitivity of different factors. Moreover, the uncertainty inherent in the sensitivity methods is highlighted.     

Deaggregation of seismic loss of spatially distributed buildings

The catastrophic nature of seismic risk resides in the fact that a group of structures and infrastructure is simultaneously excited by spatially correlated seismic loads due to an earthquake. For this, both earthquake-to-earthquake (inter-event) and site-to-site (intra-event) correlations associated with ground motion prediction equations must be taken into account in assessing seismic hazard and risk at multiple sites. The consideration of spatial correlation of seismic demand affects aggregate seismic losses as well as identified scenario seismic events. To investigate such effects quantitatively, a simulation-based seismic risk model for spatially distributed structures is employed. Analysis results indicate that adequate treatment of spatial correlation of seismic demand is essential and the probability distribution of aggregate seismic loss can be significantly different from those based on the assumptions that seismic excitations are not correlated or fully correlated. Furthermore, the results suggest that identified scenario events by deaggregation in terms of magnitude and distance become more extreme if the spatial correlation is ignored.     

海啸危险性概率分析的不确定性研究

针对海啸危险性概率分析（PTHA）存在的较大不确定性问题,对不确定性产生来源进行了归纳和分类,提出了基于逻辑树与事件树方法合理量化不确定性的思路框架,并以马尼拉海啸潜源为研究对象,给出了量化震级上限、破裂面参数不确定的过程示例。数值模拟分析结果表明：海啸潜源震级上限的改变对危险性评估结果产生了显著影响,通过逻辑树方法可合理量化这种不确定性;地震破裂面的倾角、滑移角和破裂面积的随机不确定性对海啸危险性分析结果产生较为显著的影响,经事件树方法处理后的危险性结果保证率远高于20%,略低于80%,可基本满足工程抗海啸设计要求。     

Rock slope instability assessment using spatially distributed structural orientation data in Darjeeling Himalaya (India)

We discuss a geographic information system (GIS)‐based methodology for rock slope instability assessment based on geometrical relationships between topographic slopes and structural discontinuities in rocks. The methodology involves (a) regionalization of point observations of orientations (azimuth and dip) of structural discontinuities in rocks in order to generate a digital structural model (DStM), (b) testing the kinematical possibility of specific modes of rock slope failures by integrating DStMs and digital elevation model (DEM)‐derived slope and aspect data and (c) computation of stability scenarios with respect to identified rock slope failure modes. We tested the methodology in an area of 90 km² in Darjeeling Himalaya (India) and in a small portion (9 km²) within this area with higher density of field structural orientation data. The results of the study show better classification of rock slope instability in the smaller area with respect to known occurrences of deep‐seated rockslides than with respect to shallow translational rockslides, implying that structural control is more important for deep‐seated rockslides than for shallow translational rockslides. Results of scenario‐based analysis show that, in rock slopes classified to be unstable, stress‐induced rock slope instability tends to increase with increasing level of water saturation. The study demonstrates the usefulness of spatially distributed data of orientations of structural discontinuities in rocks for medium‐ to small‐scale classification of rock slope instability in mountainous terrains. Copyright © 2010 John Wiley & Sons, Ltd.     

ROC‐based calibration of flood inundation models

The use of spatial patterns of flood inundation (often obtained from remotely sensed imagery) to calibrate flood inundation models has been widespread over the last 15 years. Model calibration is most often achieved by employing one or even several performance measures derived from the well‐known confusion matrix based on a binary classification of flooding. However, relatively early on, it has been recognized that the use of commonly reported performance measures for calibrating flood inundation models (such as the F measure) is hampered because the calibration procedure commonly utilizes only one possible solution of a wet/dry classification of a remote sensing image [most often acquired by a synthetic aperture radar (SAR)] to calibrate or validate models and are biased towards either over‐prediction or under‐prediction of flooding. Despite the call in several studies for an alternative statistic, to this date, very few, if any, unbiased performance measure based on the confusion matrix has been proposed for flood model calibration/validation studies. In this paper, we employ a robust statistical measure that operates in the receiver operating characteristics (ROC) space and allows automated model calibration with high identifiability of the best model parameter set but without the need of a classification of the SAR image. The ROC‐based method for flood model calibration is demonstrated using two different flood event test cases with flood models of varying degree of complexity and boundary conditions with varying degree of accuracy. Verification of the calibration results and optional SAR classification is successfully performed with independent observations of the events. We believe that this proposed alternative approach to flood model calibration using spatial patterns of flood inundation should be employed instead of performance measures commonly used in conjunction with a binary flood map. © 2013 California Institute of Technology. Hydrological Processes © 2013 John Wiley & Sons, Ltd.     

Probabilistic seismic hazard analysis for spatially distributed infrastructure

Two key issues distinguish probabilistic seismic risk analysis of a lifeline or portfolio of structures from that of a single structure. Regional analysis must consider the correlation among lifeline components or structures in the portfolio, and the larger scope makes it much more computationally demanding. In this paper, we systematically identify and compare alternative methods for regional hazard analysis that can be used as the first part of a computationally efficient regional probabilistic seismic risk analysis that properly considers spatial correlation. Specifically, each method results in a set of probabilistic ground motion maps with associated hazard‐consistent annual occurrence probabilities that together represent the regional hazard. The methods are compared according to how replicable and computationally tractable they are and the extent to which the resulting maps are physically realistic, consistent with the regional hazard and regional spatial correlation, and few in number. On the basis of a conceptual comparison and an empirical comparison for Los Angeles, we recommend a combination of simulation and optimization approaches: (i) Monte Carlo simulation with importance sampling of the earthquake magnitudes to generate a set of probabilistic earthquake scenarios (defined by source and magnitude); (ii) the optimization‐based probabilistic scenario method, a mixed‐integer linear program, to reduce the size of that set; (iii) Monte Carlo simulation to generate a set of probabilistic ground motion maps, varying the number of maps sampled from each earthquake scenario so as to minimize the sampling variance; and (iv) the optimization‐based probabilistic scenario again to reduce the set of probabilistic ground motion maps. Copyright © 2012 John Wiley & Sons, Ltd.     

A spatially distributed model for the assessment of land use impacts on stream temperature in small urban watersheds

Stream temperatures in urban watersheds are influenced to a high degree by changes in landscape and climate, which can occur at small temporal and spatial scales. Here, we describe a modelling system that integrates the distributed hydrologic soil vegetation model with the semi‐Lagrangian stream temperature model RBM. It has the capability to simulate spatially distributed hydrology and water temperature over the entire network at high time and space resolutions, as well as to represent riparian shading effects on stream temperatures. We demonstrate the modelling system through application to the Mercer Creek watershed, a small urban catchment near Bellevue, Washington. The results suggest that the model was able to produce realistic streamflow and water temperature predictions that are consistent with observations. We use the modelling construct to characterize impacts of land use change and near‐stream vegetation change on stream temperatures and explore the sensitivity of stream temperature to changes in land use and riparian vegetation. The results suggest that, notwithstanding general warming as a result of climate change over the last century, there have been concurrent increases in low flows as a result of urbanization and deforestation, which more or less offset the effects of a warmer climate on stream temperatures. On the other hand, loss of riparian vegetation plays a more important role in modulating water temperatures, in particular, on annual maximum temperature (around 4 °C), which could be mostly reversed by restoring riparian vegetation in a fairly narrow corridor – a finding that has important implications for management of the riparian corridor. Copyright © 2014 John Wiley & Sons, Ltd.     

Fully probabilistic seismic displacement analysis of spatially distributed slopes using spatially correlated vector intensity measures

Earthquake‐induced slope displacement is an important parameter for safety evaluation and earthquake design of slope systems. Traditional probabilistic seismic hazard analysis usually focuses on evaluating slope displacement at a particular location, and it is not suitable for spatially distributed slopes over a large region. This study proposes a computationally efficient framework for fully probabilistic seismic displacement analysis of spatially distributed slope systems using spatially correlated vector intensity measures (IMs). First, a spatial cross‐correlation model for three key ground motion IMs, that is, peak ground acceleration (PGA), Arias intensity, and peak ground velocity, is developed using 2686 ground motion recordings from 11 recent earthquakes. To reduce the computational cost, Monte Carlo simulation and data reduction techniques are utilized to generate spatially correlated random fields for the vector IMs. The slope displacement hazards over the region are further quantified using empirical predictive equations. Finally, an illustrative example is presented to highlight the importance of the spatial correlation and the advantage of using spatially correlated vector IMs in seismic hazard analysis of spatially distributed slopes. Copyright © 2013 John Wiley & Sons, Ltd.     

Comparative assessment of two distributed watershed models with application to a small watershed

Distributed watershed models are beneficial tools for the assessment of management practices on runoff and water‐induced erosion. This paper evaluates, by application to an experimental watershed, two promising distributed watershed‐scale sediment models in detail: the Kinematic Runoff and Erosion (KINEROS‐2) model and the Gridded Surface Subsurface Hydrologic Analysis (GSSHA) model. The physics behind each model are to some extent similar, though they have different watershed conceptualizations. KINEROS‐2 was calibrated using three rainfall events and validated over four separate rainfall events. Parameters estimated by this calibration process were adapted to GSSHA. With these parameters, GSSHA generated larger and retarded flow hydrographs. A 30% reduction in both plane and channel roughness in GSSHA along with the assumption of Green‐Ampt conductivity K_G‐A = K_s, where K_s is the saturated conductivity, resulted in almost identical hydrographs. Sediment parameters not common in both models were calibrated independently of KINEROS‐2. A comparative discussion of simulation results is presented. Even though GSSHA's flow component slightly overperformed KINEROS‐2, the latter outperformed GSSHA in simulations for sediment transport. In spite of the fact that KINEROS‐2 is not geared toward continuous‐time simulations, simulations performed with both models over a 1 month period generated comparable results. Copyright © 2006 John Wiley & Sons, Ltd.     

Towards quantitative ecological risk assessment of elevated carbon dioxide levels in the marine environment

The environmental impact of elevated carbon dioxide (CO₂) levels has become of more interest in recent years. This, in relation to globally rising CO₂ levels and related considerations of geological CO₂ storage as a mitigating measure. In the present study effect data from literature were collected in order to conduct a marine ecological risk assessment of elevated CO₂ levels, using a Species Sensitivity Distribution (SSD). It became evident that information currently available from the literature is mostly insufficient for such a quantitative approach. Most studies focus on effects of expected future CO₂ levels, testing only one or two elevated concentrations. A full dose-response relationship, a uniform measure of exposure, and standardized test protocols are essential for conducting a proper quantitative risk assessment of elevated CO₂ levels. Improvements are proposed to make future tests more valuable and usable for quantitative risk assessment.     

A spatially distributed model for assessment of the effects of changing land use and climate on urban stream quality

While the effects of land use change in urban areas have been widely examined, the combined effects of climate and land use change on the quality of urban and urbanizing streams have received much less attention. We describe a modelling framework that is applicable to the evaluation of potential changes in urban water quality and associated hydrologic changes in response to ongoing climate and landscape alteration. The grid‐based spatially distributed model, Distributed Hydrology Soil Vegetation Model‐Water Quality (DHSVM‐WQ), is an outgrowth of DHSVM that incorporates modules for assessing hydrology and water quality in urbanized watersheds at a high‐spatial and high‐temporal resolution. DHSVM‐WQ simulates surface run‐off quality and in‐stream processes that control the transport of non‐point source pollutants into urban streams. We configure DHSVM‐WQ for three partially urbanized catchments in the Puget Sound region to evaluate the water quality responses to current conditions and projected changes in climate and/or land use over the next century. Here, we focus on total suspended solids (TSS) and total phosphorus (TP) from non‐point sources (run‐off), as well as stream temperature. The projection of future land use is characterized by a combination of densification in existing urban or partially urban areas and expansion of the urban footprint. The climate change scenarios consist of individual and concurrent changes in temperature and precipitation. Future precipitation is projected to increase in winter and decrease in summer, while future temperature is projected to increase throughout the year. Our results show that urbanization has a much greater effect than climate change on both the magnitude and seasonal variability of streamflow, TSS and TP loads largely because of substantially increased streamflow and particularly winter flow peaks. Water temperature is more sensitive to climate warming scenarios than to urbanization and precipitation changes. Future urbanization and climate change together are predicted to significantly increase annual mean streamflow (up to 55%), water temperature (up to 1.9 °C), TSS load (up to 182%) and TP load (up to 74%). Copyright © 2016 John Wiley & Sons, Ltd.     

Estimating tsunami inundation from hurricane storm surge predictions along the U.S. gulf coast

Gulf of Mexico (GOM) coasts have been included in the U.S. Tsunami Warning System since 2005. While the tsunami risk for the GOM is low, tsunamis generated by local submarine landslides pose the greatest potential threat, as evidenced by several large ancient submarine mass failures identified in the northern GOM basin. Given the lack of significant historical tsunami evidence in the GOM, the potential threat of landslide tsunamis in this region is assessed from a worst-case scenario perspective based on a set of events including the large ancient failures and most likely extreme events determined by a probabilistic approach. Since tsunamis are not well-understood along the Gulf Coast, we investigate tsunami inundation referenced to category-specific hurricane storm surge levels, which are relatively well established along the Gulf Coast, in order to provide information for assessing the potential threat of tsunamis which is more understandable and accessible to emergency managers. Based on tsunami inundation studies prepared for the communities of South Padre Island, TX, Galveston, TX, Mobile, AL, Panama City, FL, and Tampa, FL, we identify regional trends of tsunami inundation in terms of modeled storm surge inundation. The general trends indicate that tsunami inundation can well exceed the level of storm surge from major hurricanes in open beachfront and barrier island regions, while more interior areas are less threatened. Such information can be used to better prepare for tsunami events as well as provide a preliminary estimate of tsunami hazard in locations where detailed tsunami inundation studies have not been completed.     

Computing spatially distributed sediment delivery ratios: inferring functional sediment connectivity from repeat high‐resolution digital elevation models

High‐resolution digital elevation models (DEMs) from repeat LiDAR (light detection and ranging) or SfM (structure from motion) surveys have become an important tool in process geomorphology. The spatial pattern of negative and positive changes of surface elevation on raster DEMs of difference (DoD) can be interpreted in terms of geomorphic processes, and has been used for morphological budgeting. We show how the application of flow routing algorithms and flow accumulation opens new opportunities for the analysis of DoD. By accumulating the values of the DoD along downslope flowpaths delineated on a DEM, these algorithms lend themselves to computing the net balance, i.e. sediment yield (SY), for the contributing area of each cell. Doing the same for the negative subset of the DoD yields a minimum estimate of erosion (E) within the contributing area. The division of SY by E yields (a maximum estimate of) the sediment delivery ratio (SDR), that is the proportion of material eroded within the contributing area of each cell that has been exported from that area. The resulting SDR is a spatially distributed measure of functional sediment connectivity. In this letter, we develop the computationally simple approach by means of an example DoD from a lateral moraine section in the Upper Kaunertal Valley, Austrian Central Alps. We also discuss advantages, assumptions and limitations, and outline potential applications to connectivity research using field‐, laboratory‐, and model‐based DoD. Copyright © 2018 John Wiley & Sons, Ltd.     

Source models for the 1993 Hokkaido Nansei-Oki earthquake tsunami

A source model for the 1993 Hokkaido Nansei-Oki tsunami must satisfy certain conditions. Such conditions are presented in this paper, and two methods are used to determine the best source model for this event. A trial-and-error method selects DCRC-17a as the best among 24 different models. This model has three fault planes dipping westward. To reproduce well the tide gauge records at two locations, an inversion analysis is used to modify the dislocation of DCRC-17a.     

Correlation model for spatially distributed ground‐motion intensities

Risk assessment of spatially distributed building portfolios or infrastructure systems requires quantification of the joint occurrence of ground‐motion intensities at several sites, during the same earthquake. The ground‐motion models that are used for site‐specific hazard analysis do not provide information on the spatial correlation between ground‐motion intensities, which is required for the joint prediction of intensities at multiple sites. Moreover, researchers who have previously computed these correlations using observed ground‐motion recordings differ in their estimates of spatial correlation. In this paper, ground motions observed during seven past earthquakes are used to estimate correlations between spatially distributed spectral accelerations at various spectral periods. Geostatistical tools are used to quantify and express the observed correlations in a standard format. The estimated correlation model is also compared with previously published results, and apparent discrepancies among the previous results are explained. The analysis shows that the spatial correlation reduces with increasing separation between the sites of interest. The rate of decay of correlation typically decreases with increasing spectral acceleration period. At periods longer than 2 s, the correlations were similar for all the earthquake ground motions considered. At shorter periods, however, the correlations were found to be related to the local‐site conditions (as indicated by site V_s30 values) at the ground‐motion recording stations. The research work also investigates the assumption of isotropy used in developing the spatial correlation models. It is seen using the Northridge and Chi‐Chi earthquake time histories that the isotropy assumption is reasonable at both long and short periods. Based on the factors identified as influencing the spatial correlation, a model is developed that can be used to select appropriate correlation estimates for use in practical risk assessment problems. Copyright © 2009 John Wiley & Sons, Ltd.     

A test of TOPMODEL'a ability to predict spatially distributed groundwater levels

TOPMODEL was calibrated to a small catchment using precipitation and runoff data. Acceptable fits of simulated and observed runoff were obtained during both the calibration and validation periods. Predictions of groundwater levels using this calibration did not agree well with observations at the 37 points within the catchment where groundwater levels were measured, including three locations with continuous recordings. Groundwater level observations at one single point in time, however, sufficed to calibrate new topographic–soil indices that improved the prediction of the local groundwater levels at the observed tubes. This suggests that spatially distributed calibration data are necessary to exploit reliably TOPMODEL's ability to predict spatially distributed hydrology. The mean or recalibrated transmissivity values at these 37 points differed from the catchment mean as determined by the precipitation–runoff calibration. Thus, while groundwater information can help in predicting groundwater levels at specific locations, increasing the number of local groundwater level measurements is not sufficient to improve the spatially distributed representation of subsurface flow by TOPMODEL for the catchment as a whole, as long as the groundwater information is not integrated in the precipitation–runoff calibration. © 1997 John Wiley & Sons, Ltd.