Weather and seasonal climate prediction for flood planning in the Yangtze River Basin

This paper describes the use of numerical weather and climate models for predicting severe rainfall anomalies over the Yangtze River Basin (YRB) from several days to several months in advance. Such predictions are extremely valuable, allowing time for proactive flood protection measures to be taken. Specifically, the dynamical climate prediction system (IAP DCP-II), developed by the Institute of Atmospheric Physics, Chinese Academy of Sciences (IAP), is applied to YRB rainfall prediction and flood planning. IAP DCP-II employs ensemble prediction with dynamically conditioned perturbations to reduce the uncertainty associated with seasonal climate prediction. IAP DCP-II was shown to successfully predict seasonal YRB summer flooding events based on a 15-year (1980–1994) hindcast experiment and the real-time prediction of two summer flooding events (1999 and 2001). Finally, challenges and opportunities for applying seasonal dynamical forecasting to flood management problems in the YRB are discussed.     

Precipitation forecasts for rainfall runoff predictions. A case study in poorly gauged Ribb and Gumara catchments,upper Blue Nile,Ethiopia

Flow forecasting in poorly gauged, flood-prone Ribb and Gumara sub-catchments of the Blue Nile was studied with the aim of testing the performance of Quantitative Precipitation Forecasts (QPFs). Four types of QPFs namely MM5 forecasts with a spatial resolution of 2 km; the Maximum, Mean and Minimum members (MaxEPS, MeanEPS and MinEPS where EPS stands for Ensemble Prediction System) of the fixed, low resolution (2.5 by 2.5 degrees) National Oceanic and Atmospheric Administration Global Forecast System (NOAA GFS) ensemble forecasts were used. Both the MM5 and the EPS were not calibrated (bias correction, downscaling (for EPS), etc.). In addition, zero forecasts assuming no rainfall in the coming days, and monthly average forecasts assuming average monthly rainfall in the coming days, were used. These rainfall forecasts were then used to drive the Hydrologic Engineering Center’s–Hydrologic Modeling System, HEC–HMS, hydrologic model for flow predictions. The results show that flow predictions using MaxEPS and MM5 precipitation forecasts over-predicted the peak flow for most of the seven events analyzed, whereas under-predicted peak flow was found using zero- and monthly average rainfall. The comparison of observed and predicted flow hydrographs shows that MM5, MaxEPS and MeanEPS precipitation forecasts were able to capture the rainfall signal that caused peak flows. Flow predictions based on MaxEPS and MeanEPS gave results that were quantitatively close to the observed flow for most events, whereas flow predictions based on MM5 resulted in large overestimations for some events. In follow-up research for this particular case study, calibration of the MM5 model will be performed. The overall analysis shows that freely available atmospheric forecasting products can provide additional information on upcoming rainfall and peak flow events in areas where only base-line forecasts such as no-rainfall or climatology are available.     

Comparison of methods for predicting discharge in compound open channels

The relative accuracies of four conventional stage-discharge prediction methods, for flow in compound channels, were compared in a laboratory study. Discharge measurements in a physical model comprising a deep central channel flanked by wide shallow berms (flood plains), as well as similar observations by others, provided the basis for comparison.System discharge was either undertestimated (‘single-channel’ method) or overestimated (various ‘separate channels’ methods) when depth on the flood plain zones was small, i.e. when the velocity differential between the deep and shallow zones was large. These discrepancies can be attributed to questionable assumptions made in the different methods tested regarding the nature of flow in compound channels.A new method is proposed which accounts for momentum transfer between adjacent deep and shallow zones of compound sections. This transfer mechanism and its effect on system conveyance are usually ignored in conventional methods. The new method gives satisfactory results for the conditions examined. Its accuracy can be further improved with the development of more accurate friction factor relationships for compound channels.     

A note on distribution of uncorrected peak ground accelerations during the Northridge, California, earthquake of 17 January 1994

This paper presents a summary of uncorrected peak ground accelerations recorded during the Northridge, California, earthquake of 17 January 1994 and a preliminary analysis of these data. The presented contours of recorded accelerations agree well with observed patterns of damage. The paper also addresses the issue of how ‘unusual’ and ‘unexpected’ the recorded accelerations are relative to earlier predictions.     

Hydrological data assimilation with the Ensemble Square-Root-Filter: Use of streamflow observations to update model states for real-time flash flood forecasting

The objective of the study is to evaluate the potential of a data assimilation system for real-time flash flood forecasting over small watersheds by updating model states. To this end, the Ensemble Square-Root-Filter (EnSRF) based on the Ensemble Kalman Filter (EnKF) technique was coupled to a widely used conceptual rainfall-runoff model called HyMOD. Two small watersheds susceptible to flash flooding from America and China were selected in this study. The modeling and observational errors were considered in the framework of data assimilation, followed by an ensemble size sensitivity experiment. Once the appropriate model error and ensemble size was determined, a simulation study focused on the performance of a data assimilation system, based on the correlation between streamflow observation and model states, was conducted. The EnSRF method was implemented within HyMOD and results for flash flood forecasting were analyzed, where the calibrated streamflow simulation without state updating was treated as the benchmark or nature run. Results for twenty-four flash-flood events in total from the two watersheds indicated that the data assimilation approach effectively improved the predictions of peak flows and the hydrographs in general. This study demonstrated the benefit and efficiency of implementing data assimilation into a hydrological model to improve flash flood forecasting over small, instrumented basins with potential application to real-time alert systems.     

Controls on event runoff coefficients in the eastern Italian Alps

Analyses of event runoff coefficients provide essential insight on catchment response, particularly if a range of catchments and a range of events are compared by a single indicator. In this study we examine the effect of climate, geology, land use, flood types and initial soil moisture conditions on the distribution functions of the event runoff coefficients for a set of 14 mountainous catchments located in the eastern Italian Alps, ranging in size from 7.3 to 608.4 km². Runoff coefficients were computed from hourly precipitation, runoff data and estimates of snowmelt. A total of 535 events were analysed over the period 1989–2004. We classified each basin using a “permeability index” which was inferred from a geologic map and ranged from “low” to “high permeability”. A continuous soil moisture accounting model was applied to each catchment to classify ‘wet’ and ‘dry’ initial soil moisture conditions. The results indicate that the spatial distribution of runoff coefficients is highly correlated with mean annual precipitation, with the mean runoff coefficient increasing with mean annual precipitation. Geology, through the ‘permeability index’, is another important control on runoff coefficients for catchments with mean annual precipitation less than 1200 mm. Land use, as indexed by the SCS curve number, influences runoff coefficient distribution to a lesser degree. An analysis of the runoff coefficients by flood type indicates that runoff coefficients increase with event snowmelt. Results show that there exists an intermediate region of subsurface water storage capacity, as indexed by a flow–duration curve-based index, which maximises the impact of initial wetness conditions on the runoff coefficient. This means that the difference between runoff coefficients characterised by wet and dry initial conditions is negligible both for basins with very large storage capacity and for basins with small storage capacity. For basins with intermediate storage capacities, the impact of the initial wetness conditions may be relatively large.     

Horizontal to vertical spectral ratio and geological conditions: an analysis of strong motion data from Greece and Taiwan (SMART-1)

Nowadays, several research efforts have been directed towards the evaluation of the horizontal to vertical, (h/v), spectral ratio technique, following the pioneering work of Nakamura originally proposed for microtremor measurements. In the present study, an extension of this technique based on Greek and Taiwanese (SMART-1) strong motion data is attempted. Whenever possible comparisons with results obtained by the standard spectral ratio technique for the same sites are made. Regarding the Greek data it is concluded that (h/v) spectral ratio clearly distinguishes the range of resonant peaks between ‘rock’ and ‘alluvium’ sites. On the other hand, nonlinear effects that take place beneath SMART-1 array most probably obscure the expected consistency between (h/v) and standard spectral ratio technique.     

Nonlinear soil response as a natural passive isolation mechanism. Paper II. The 1933, Long Beach, California earthquake

The areas that experienced large strains and differential motions in the soil (indicated by breaks in the water and gas pipe distribution systems) and the areas with severely damaged buildings showed remarkable separation during the March 10, 1933, Long Beach, California earthquake. With analogous results for the 1994 Northridge, California earthquake [Soil Dynam. Earthquake Engng. 17 (1998) 41], the observations summarized in this paper show the fallacy of simplistic and popular interpretations, such as those that hold that in the near field the damage to buildings is caused by ‘soft’ or ‘bad ground’ conditions. In fact, significant reduction in the potential damage to buildings may be expected in the areas where the soil experiences ‘moderate to large’ strains.     

PAI-OFF: A new proposal for online flood forecasting in flash flood prone catchments

The Process Modelling and Artificial Intelligence for Online Flood Forecasting (PAI-OFF) methodology combines the reliability of physically based, hydrologic/hydraulic modelling with the operational advantages of artificial intelligence. These operational advantages are extremely low computation times and straightforward operation. The basic principle of the methodology is to portray process models by means of ANN. We propose to train ANN flood forecasting models with synthetic data that reflects the possible range of storm events. To this end, establishing PAI-OFF requires first setting up a physically based hydrologic model of the considered catchment and – optionally, if backwater effects have a significant impact on the flow regime – a hydrodynamic flood routing model of the river reach in question. Both models are subsequently used for simulating all meaningful and flood relevant storm scenarios which are obtained from a catchment specific meteorological data analysis. This provides a database of corresponding input/output vectors which is then completed by generally available hydrological and meteorological data for characterizing the catchment state prior to each storm event. This database subsequently serves for training both a polynomial neural network (PoNN) – portraying the rainfall–runoff process – and a multilayer neural network (MLFN), which mirrors the hydrodynamic flood wave propagation in the river. These two ANN models replace the hydrological and hydrodynamic model in the operational mode. After presenting the theory, we apply PAI-OFF – essentially consisting of the coupled “hydrologic” PoNN and “hydrodynamic” MLFN – to the Freiberger Mulde catchment in the Erzgebirge (Ore-mountains) in East Germany (3000 km²). Both the demonstrated computational efficiency and the prediction reliability underline the potential of the new PAI-OFF methodology for online flood forecasting.     

1971 San Fernando and 1994 Northridge, California, earthquakes: did the zones with severely damaged buildings reoccur?

This paper compares the distribution of damage from the San Fernando, 1971, and Northridge, 1994, earthquakes. Both events had similar size, occurred on blind thrust faults beneath the densely populated San Fernando Valley of the Los Angeles metropolitan area, and hence offer a rare opportunity to compare the effects of the two earthquakes. In a previous study of the distribution of red-tagged (‘unsafe’) buildings and of breaks in the water distribution system caused by the Northridge earthquake, the authors discovered that buildings were damaged less where the soil response was not linear (as indicated by the breaks in the water pipes), except in localized areas of very severe shaking (peak ground velocity exceeding 150 cm/s). The study in this paper shows that the same applies to the damage caused by the San Fernando earthquake, and that the areas with severely damaged buildings (so called ‘gray zones’) for both earthquakes overlapped. This reoccurrence of damage within the same area is interpreted to result from some specific properties of local soil and geology. These properties are not fully understood at present, but should be explored to provide a basis for a new tool for forecasting microzonation maps, and reducing future seismic hazard.     

Evaluating the utility of the ensemble transform Kalman filter for adaptive sampling when updating a hydrodynamic model

This paper compares two Monte Carlo sequential data assimilation methods based on the Kalman filter, for estimating the effect of measurements on simulations of state error variance made by a one-dimensional hydrodynamic model. The first method used an ensemble Kalman filter (EnKF) to update state estimates, which were then used as initial conditions for further simulations. The second method used an ensemble transform Kalman filter (ETKF) to quickly estimate the effect of measurement error covariance on forecast error covariance without the need to re-run the simulation model. The ETKF gave an unbiased estimate of EnKF analysed error variance, although differences in the treatment of measurement errors meant the results were not identical. Estimates of forecast error variance could also be made, but their accuracy deteriorated as the time from measurements increased due in part to model non-linearity and the decreasing signal variance. The motivation behind the study was to assess the ability of the ETKF to target possible measurements, as part of an adaptive sampling framework, before they are assimilated by an EnKF-based forecasting model on the River Crouch, Essex, UK. The ETKF was found to be a useful tool for quickly estimating the error covariance expected after assimilating measurements into the hydrodynamic model. It, thus, provided a means of quantifying the ‘usefulness’ (in terms of error variance) of possible sampling schemes.     

Experimental evidence for the exsolution of cratonic peridotite from high-temperature harzburgite

Phase equilibrium experiments were performed on typical ‘oceanic’ and ‘cratonic’ peridotite compositions and a Ca, Al-rich orthopyroxene composition, to test the proposal that garnet lherzolites exsolved from high-temperature harzburgites, and to further our understanding of the origin of ancient cratonic lithospheres. ‘Oceanic’ peridotites crystallize a garnet harzburgite assemblage at pressures above 5 GPa in the temperature range 1450–1600°C, but at 5 GPa and temperatures less than 1450°C, crystallize clinopyroxene to become true lherzolites. ‘Cratonic’ peridotites crystallize a garnet harzburgite assemblage at pressures above 5 GPa in the temperature range 1300–1600°C. Garnet-free harzburgite crystallizes from both ‘cratonic’ and ‘oceanic’ peridotite at temperatures above 1450°C and pressures below 4.5–5 GPa. Phase relations for the high Ca, Al-rich orthopyroxene composition essentially mirror those for ‘oceanic’ peridotite.The complete solution of garnet and clinopyroxene into orthopyroxene observed in all three starting compositions at temperatures near or above the mantle solidus at pressures less than 6 GPa supports the hypothesis that garnet lherzolite could have exsolved from harzburgite. The inferred cooling path for the original high-temperature harzburgite protoliths of garnet lherzolites differs depending on bulk composition. The precursor harzburgite protoliths of garnet lherzolites and harzburgites with ‘cratonic’ bulk compositions apparently experienced simple isobaric cooling from formation temperatures near the peridotite solidus to those at which most of these peridotites were sampled in the mantle (< 1200°C). The cooling histories for harzburgite protoliths of sheared garnet lherzolites with ‘oceanic’ compositional affinity are speculated to have involved convective circulation of mantle material to depths deeper than those at which it was originally formed.Phase equilibria and compositional relationships for orthopyroxenes produced in phase equilibrium experiments on peridotite and komatiite are consistent with an origin for ‘cratonic’ peridotite as a residue of Archean komatiite extraction, which has since cooled and exsolved clinopyroxene and garnet to become the common low-temperature, coarse-grained peridotite thought to comprise the bulk of the mantle lithosphere beneath the Archean Kaapvaal craton.     

Magma mingling in an andesite pyroclastic flow of the Pourahu Member, Ruapehu volcano, New Zealand

We describe a magma mingling episode from Ruapehu volcano between two andesite magmas, one very much minor in volume relative to the other. The event acted to trigger eruption of the andesitic Pourahu pyroclastic flow which is preserved in a thick sequence of tephras and laharic deposits in the southeastern ring plain of the volcano. The predominant andesite is pale brown coloured and porphyritic containing phenocrysts of plagioclase-clinopyroxene-orthopyroxene-Fe-Ti oxides. Rare clasts of a darker andesite are different texturally, less vesicular, and contain distinctive microphenocrysts of plagioclase and quench olivine. Equally rare clasts, of streaky pumice consisting of interbanded ‘dark’ and ‘light’ andesite attest to mingling between these two andesite components.Chemical analyses of discrete clasts demonstrate that the Pourahu pyroclastic flow andesites span much of the compositional spectrum of Ruapehu andesites. This observation demonstrates heterogeneity in the products of a relatively small eruption. The darker clast analyses and those from associated distal fall deposits lie within the fields defined by the dominant light coloured clasts. Phenocryst and microphenocryst geothermometry suggest slightly higher temperatures in the dark component. However, glasses from groundmass and phenocryst inclusions in the same specimen may differ considerably, leading us to conclude that many phenocrysts are in fact xenocrystic and were incorporated in the melts as they migrated towards the surface.We prefer a model in which a small volume of hot andesite magma injects a vent-feeding magma chamber, triggering vesiculation and eruption. We infer that the process of magma withdrawal extended downward into the magma body causing the dark component to intermingle with the lighter (dominant) component, ‘sucking’ more dark magma into the chamber. Our observations are entirely consistent with the existence of a plexus of small, possibly interlinked magma chambers beneath Ruapehu.     

Toxicity of antifouling biocides to the intertidal harpacticoid copepod Tigriopus japonicus (Crustacea, Copepoda): Effects of temperature and salinity

Intertidal harpacticoid copepods are commonly used in eco-toxicity tests worldwide. They predominately live in mid-high shore rock pools and often experience a wide range of temperature and salinity fluctuation. Most eco-toxicity tests are conducted at fixed temperature and salinity and thus the influence of these environmental factors on chemical toxicity is largely unknown. This study investigated the combined effect of temperature and salinity on the acute toxicity of the copepod Tigriopus japonicus against two common biocides, copper (Cu) and tributyltin (TBT) using a 2 × 3 × 4 factorial design (i.e. two temperatures: 25 and 35 °C; three salinities: 15.0‰, 34.5‰ and 45.0‰; three levels of the biocide plus a control). Copper sulphate and tributyltin chloride were used as the test chemicals while distilled water and acetone were utilised as solvents for Cu and TBT respectively. 96h-LC50s of Cu and TBT were 1024 and 0.149 μg l⁻¹ respectively (at 25 °C; 34.5‰) and, based on these results, nominal biocide concentrations of LC0 (i.e. control), LC30, LC50 and LC70 were employed. Analysis of Covariance using ‘concentration’ as the covariate and both ‘temperature’ and ‘salinity’ as fixed factors, showed a significant interaction between temperature and salinity effects for Cu, mortality increasing with temperature but decreasing with elevated salinity. A similar result was revealed for TBT. Both temperature and salinity are, therefore, important factors affecting the results of acute eco-toxicity tests using these marine copepods. We recommend that such eco-toxicity tests should be conducted at a range of environmentally realistic temperature/salinity regimes, as this will enhance the sensitivity of the test and improve the safety margin in line with the precautionary principle.     

Comparison between VELACS numerical ‘class A’ predictions and centrifuge experimental soil test results

The numerical ‘class A’ predictions performed within the framework of the VELACS Project are compared to the experimental results recorded in the centrifuge experiments. The comparisons are made in terms of: (1) the root mean square error of the predictions with respect to the mean of the experimental results; and (2) the size of a confidence interval centered at the predicted value which contains the estimated true value of the experimental results with a 75% probability. An assessment of the capability of various groups of constitutive soil models to predict excess pore pressures induced by dynamic loading is also presented.     

Internal waves and temperature fronts on slopes

Time series measurements from an array of temperature miniloggers in a line at constant depth along the sloping boundary of a lake are used to describe the ‘internal surf zone” where internal waves interact with the sloping boundary. More small positive temperature time derivatives are recorded than negative, but there are more large negative values than positive, giving the overall distribution of temperature time derivatives a small negative skewness. This is consistent with the internal wave dynamics; fronts form during the up-slope phase of the motion, bringing cold water up the slope, and the return flow may become unstable, leading to small advecting billows and weak warm fronts. The data are analysed to detect ‘events’, periods in which the temperature derivatives exceed a set threshold. The speed and distance travelled by ‘events’ are described. The motion along the slope may be a consequence of (a) instabilities advected by the flow (b) internal waves propagating along-slope or (c) internal waves approaching the slope from oblique directions. The propagation of several of the observed ‘events’ can only be explained by (c), evidence that the internal surf zone has some, but possibly not all, the characteristics of the conventional ‘surface wave’ surf zone, with waves steepening as they approach the slope at oblique angles.     

Fuzzy neural network models for liquefaction prediction

Integrated fuzzy neural network models are developed for the assessment of liquefaction potential of a site. The models are trained with large databases of liquefaction case histories. A two-stage training algorithm is used to develop a fuzzy neural network model. In the preliminary training stage, the training case histories are used to determine initial network parameters. In the final training stage, the training case histories are processed one by one to develop membership functions for the network parameters. During the testing phase, input variables are described in linguistic terms such as ‘high’ and ‘low’. The prediction is made in terms of a liquefaction index representing the degree of liquefaction described in fuzzy terms such as ‘highly likely’, ‘likely’, or ‘unlikely’. The results from the model are compared with actual field observations and misclassified cases are identified. The models are found to have good predictive ability and are expected to be very useful for a preliminary evaluation of liquefaction potential of a site for which the input parameters are not well defined.     

BMA集合预报在淮河流域应用及参数规律初探

以淮河流域吴家渡水文站作为试验站点,采用基于贝叶斯平均法(BMA)的集合预报模型处理来源于马斯京根法、一维水动力学方法、BPNN(Back Propagation Neural Network)的预报流量序列,通过分析BMA的参数以及其预报结果,对各方法在淮河典型站点流量预报中的适用性进行验证与分析.经2003—2016年19场洪水模拟检验可知,BMA模型能够有效避免模型选择带来的洪水预报误差放大效应,可以提供高精度、鲁棒性强的洪水预报结果.通过进一步比较各模型统计最优的频率与BMA权重值之间的相关性,发现权重值不适用于对单场洪水预报精度评定,而适用于描述多场洪水预报中,模型为最优的统计频率;基于大量先验信息,提前获取BMA的权重等参数,将是指导模型选择、降低洪水预报不确定性、改进洪水预报技术的有效手段.     

3-D Non-linear Travel-time Tomography: Imaging High Contrast Velocity Anomalies

In this paper we present an approach for 3-D travel-time tomography, which works well in reconstructing high contrast velocity anomalies in both location and strength. It uses a revised ‘irregular’ approach to the shortest-path method as the ray tracer and a damped minimum norm, and constrained least-squares CG approach as the inversion solver. In ray tracing, the advantages of the revised ‘irregular’ over the ‘regular’ approach are that the secondary nodes introduced on the cell surfaces significantly improve accuracy of computed travel times, without dramatically increasing the total number of cells and nodes; the tri-linear velocity function defined across the cell guarantees accurate ray tracing in a high velocity contrast medium; and the capacity to calculate a relatively large 3-D model, due to the fast run speed (at least one order of magnitude over the ‘regular’ approach) and less number of total nodes. The introduction of ‘soft’ and ‘hard’ bounds into the inversion process changes the conditioning and makes the solution meaningful in a physical sense. Thus the artifacts caused by noise and high velocity contrasts are substantially suppressed and the image quality is considerably improved, making the solution realistic with noisy or inconsistent travel-time data. Several numerical tests indicate that we can obtain good quality images even for high velocity contrast anomalies (say more than 20%) in the target region. This means the inversion algorithm is an efficient and effective procedure. Meanwhile, the inversion procedure is not very sensitive to the quality of the travel-time data, which is promising for practical usage.     

Developing a Web-based flood forecasting system for reservoirs with J2EE / Développement sur Internet avec J2EE d’un système de prévision de crue pour barrages

Abstract

Abstract A flood forecasting system is a crucial component in flood mitigation. For certain important large-scale reservoirs, cooperation and communication among federal, state, and local stakeholders are required when heavy flood events are encountered. The Web-based environment is emerging as a very important development and delivery platform for real-time flood forecasting systems. In this paper, the findings of a case study are presented of the development of a Web-based flood forecasting system for reservoirs using Java 2 platform Enterprise Edition (J2EE). J2EE of Sun Microsystems is chosen as the development solution for the Web-based flood forecasting system, Weblogic 6.0 of BEA as the container provider, and JBuilder 7.0 of Borland as the development tool. One of the key objectives in this project is to establish a collaborative platform for flood forecasting via Web technology in order to render hydrological models and data available to stakeholders and experts involved and thus offer an efficient medium for transferring and sharing information, knowledge and experiences among them. Compared with general Web-based query systems and traditional flood forecasting systems, the Web-based flood forecasting system is more focused on the on-line analysis of model-based forecasting of floods and provides opportunities for improving the transfer of information and knowledge from the hydrological scientists and managers to decision makers. Finally, a prototype system is used to demonstrate the system application.