Distribution of erosion across bedrock channels

Lateral erosion in bedrock rivers is an important control on the shape of channel cross‐sections, and the coupling of channels and hillslopes. Recent observations link lateral erosion to the variability of flow. We propose two mechanisms to explain this. One is based on changing shear stress distributions within the channel with varying flood level, the other on the competition between cover and tool effects in fluvial bedrock erosion. We assess these processes for the Liwu River, Taiwan, and conclude that cover and tool effects dominate the partitioning of lateral and vertical erosion in this case. Copyright © 2007 John Wiley & Sons, Ltd.     

红外高光谱观测值反演云参数

最小局部比辐射率变化MLEV算法根据在红外长波10～15 μm 区, 云的吸收、发射和散射具有相对有限的局部谱变化的特征, 利用对云敏感的长波红外辐射观测值来同时反演单层云的云顶高度和有效云比辐射率谱。先给定一些假想的云高初始猜测, 最佳的云高和比辐射率谱解使得用这些不同云高计算得到的比辐射率谱的局部变化最小, 该算法适用于高光谱(光谱分辨率从0.25～1 cm-1) 的大气红外探测器。通过用两种不同方案的内部比较及与激光雷达观测和MODIS业务云高产品的对比验证, 说明对卫星红外高光谱观测资料采用MLEV算法同时反演单层云的云顶高度和云有效比辐射率谱是非常有效的, 尤其是对中高云。     

Particulate carbohydrates and uronic acids in the northern East China Sea

Carbohydrate species, such as uronic acids, play an important role in oceanic carbon cycling, coagulation and adsorption processes. Concentrations of particulate carbohydrates (PCHO) and uronic acids (PURA) were measured in the northern East China Sea (ECS) during June and November, 2006. In June, maximum concentrations of PCHO and PURA were observed in the surface layer of coastal waters. Their concentrations rapidly decreased with depth, suggesting that they are both bio-reactive. Moreover, phytoplankton abundance and bacterial biomass seem to be associated with observed PCHO and PURA concentrations in the ECS during June, suggesting that production of carbohydrate species in the ECS is regulated by phytoplankton assemblages, bacterial assimilation or degradation. In November, however, PCHO and PURA concentrations were homogenous within the water column due to strong vertical mixing. No strong correlations were observed between carbohydrate species (PCHO and PURA) and phytoplankton or bacterial biomass, suggesting that production of these compounds in November might be caused by the physiological difference between nutrient limited and non-nutrient limited phytoplankton. Furthermore, strong negative correlations between nutrients and PCHO species suggest that nutrient levels may be one of the driving forces behind the production of these compounds in the ECS.     

Microbial dynamics in an oligotrophic bay of the western subtropical Pacific: Impact of short-term heavy freshwater runoff and upwelling

This two-year study investigates the possible factors that determine spatial and temporal dynamics of picoplankton (heterotrophic bacteria, autotrophic picoplankton—Synechococcus spp., Prochlorococcus, and picoeukaryotes) and nanoflagellate abundance in the subtropical Ilan Bay, Taiwan, where the inner bay is affected by freshwater run-off from the Lanyang River and the eastern outer bay by the Kuroshio Current. In the inner bay, there was more rain and freshwater discharge in 2005 than in 2004 during the warm season (>24° C, June–September). The abundance of bacteria, Synechococcus spp., Prochlorococcus, and picoeukaryotes and the percentage contributions of pigmented nanoflagellate (PNF %) were two- to eight-fold greater during this period (July in 2005) than for other sampling periods. Relatively low abundance of heterotrophic nanoflagellates (HNF) in the presence of abundant picoplankton prey suggests that top-down control determined HNF abundance in the Ilan Bay, Taiwan.     

Developing fragility curves for a pile-supported wharf

This study proposes a procedure for developing seismic fragility curves for a pile-supported wharf. A typical pile-supported wharf, as commonly used in the ports of Taiwan, is chosen for demonstration. For a structural model of the wharf, the deck is modeled by shell elements and the Winkler model is used for the pile–soil system, in which the piles and soils are represented by beam elements and springs, respectively. A pushover analysis with lateral loads distributed according to the fundamental modal shape of the wharf structure is conducted to deduce the capacity curve of the wharf. The procedure for developing fragility curves can be explicitly performed using the spreadsheet platform in Microsoft EXCEL. First, quantitative criteria for damage states are established from the sequence of development of plastic zones. Then a nonlinear static procedure called the Spectrum Capacity Method (CSM) is used to efficiently construct a response matrix of the wharf to 24 earthquake events with differing levels of peak ground acceleration (PGA). Based on the damage criteria and the response matrix, the fragility curves of the wharf can be thus constructed through simple statistical analysis. Shifted lognormal cumulative distribution functions are also employed to better approximate the fragility curves for practical applications.     

Gamma random field simulation by a covariance matrix transformation method

In studies involving environmental risk assessment, Gaussian random field generators are often used to yield realizations of a Gaussian random field, and then realizations of the non-Gaussian target random field are obtained by an inverse-normal transformation. Such simulation process requires a set of observed data for estimation of the empirical cumulative distribution function (ECDF) and covariance function of the random field under investigation. However, if realizations of a non-Gaussian random field with specific probability density and covariance function are needed, such observed-data-based simulation process will not work when no observed data are available. In this paper we present details of a gamma random field simulation approach which does not require a set of observed data. A key element of the approach lies on the theoretical relationship between the covariance functions of a gamma random field and its corresponding standard normal random field. Through a set of devised simulation scenarios, the proposed technique is shown to be capable of generating realizations of the given gamma random fields.     

An integrated flood risk assessment model for property insurance industry in Taiwan

Taiwan is located in an area affected by Northwest Pacific typhoons, which are also one of the most important sources of rainfall to the island. Unfortunately, the abundant rainfall brought by typhoons frequently produces hazards. In recent years, typhoons and floods have caused serious damage, especially Typhoon Morakot in 2009. In this study, a probabilistic model is developed based on historical events which can be used to assess flood risk in Taiwan. There are 4 separate modules in this model, including a rainfall event module, a hydraulic module, a vulnerability module, and a financial loss module. Local data obtained from the Taiwan government are used to construct this model. Historical rainfall data for typhoon and flood events that have occurred since 1960, obtained from the Central Weather Bureau, are used for computing the maximum daily rainfall for each basin. In addition, the latest flood maps from the Water Resources Agency are collected to assess the probable inundation depth. A case study using the local data is carried out. Assessment is made to predict possible economic loss from different financial perspectives such as the total loss, insured loss, and loss exceeding probabilities. The assessment results can be used as a reference for making effective flood risk management strategies in Taiwan.     

Conjunction effect of stream water level and groundwater flow for riverbank stability analysis

Variations in pore-water pressure determined by the groundwater table within a riverbank have been investigated and recognized as an essential factor in determining riverbank stability with respect to mass failure. However, the effect of pore-water pressure is taken into account for most of the existing riverbank stability models under some simplified assumptions, and the limitations of predicting ability may arise. To avoid the unrealistic estimation of pore-water pressure distribution, the new approach proposed here is to couple riverbank stability with groundwater flow modeling, and apply this to tackle the conjunction effect between river stage and groundwater table. Moreover, riverbank material characteristics and the influence of infiltration can be taken into consideration via groundwater flow modeling. Two hypothetical examples, stage rising and stage falling, are used to investigate the capabilities of the present study and two representative methods. The simulated results show that riverbank failure is triggered particularly during the falling stage, which has been pointed out by other researchers as well. Furthermore, the riverbank material characteristics predominantly control the occurrence of failure and should be considered regarding assessment of riverbank stability. Additionally, the effects of parameters indicate that riverbanks with soil properties of low permeability or high specific yield with great infiltration intensity during the falling stage have a tendency to riverbank failure.     

A recurrent support vector regression model in rainfall forecasting

To minimize potential loss of life and property caused by rainfall during typhoon seasons, precise rainfall forecasts have been one of the key subjects in hydrological research. However, rainfall forecast is made difficult by some very complicated and unforeseen physical factors associated with rainfall. Recently, support vector regression (SVR) models and recurrent SVR (RSVR) models have been successfully employed to solve time‐series problems in some fields. Nevertheless, the use of RSVR models in rainfall forecasting has not been investigated widely. This study attempts to improve the forecasting accuracy of rainfall by taking advantage of the unique strength of the SVR model, genetic algorithms, and the recurrent network architecture. The performance of genetic algorithms with different mutation rates and crossover rates in SVR parameter selection is examined. Simulation results identify the RSVR with genetic algorithms model as being an effective means of forecasting rainfall amount. Copyright © 2006 John Wiley & Sons, Ltd.     

Long‐term runoff forecasting by combining hydrological models and meteorological records

Reservoir operation is generally based on the inflows of the upstream catchment of the reservoir. If the arriving inflows can be forecasted, that can benefit reservoir operation and management. This study attempts to construct a long‐term inflow‐forecasting model by combining a continuous rainfall–runoff model with the long‐term weather outlook from the Central Weather Bureau of Taiwan. The analytical results demonstrate that the continuous rainfall–runoff model has good inflow simulation performance by using 10‐day meteorological and inflow records over a 33‐year period for model calibration and verification. The long‐term inflow forecasting during the dry season was further conducted by combining the continuous rainfall–runoff model and the long‐term weather outlook, which was found to have good performance. Copyright © 2005 John Wiley & Sons, Ltd.