Earthquake source parameters of the 2009 M_W7.8 Fiordland （New Zealand） earthquake from L-band InSAR observations

The 2009 M W 7.8 Fiordland (New Zealand) earthquake is the largest to have occurred in New Zealand since the 1931 M W 7.8 Hawke’s Bay earthquake, 1 000 km to the northwest. In this paper two tracks of ALOS PALSAR interferograms (one ascending and one descending) are used to determine fault geometry and slip distribution of this large earthquake. Modeling the event as dislocation in an elastic half-space suggests that the earthquake resulted from slip on a SSW-NNE orientated thrust fault that is associated w...     

Development and application of a spatially‐distributed Arctic hydrological and thermal process model (ARHYTHM)

A process‐based, spatially distributed hydrological model was developed to quantitatively simulate the energy and mass transfer processes and their interactions within arctic regions (arctic hydrological and thermal model, ARHYTHM). The model first determines the flow direction in each element, the channel drainage network and the drainage area based upon the digital elevation data. Then it simulates various physical processes: including snow ablation, subsurface flow, overland flow and channel flow routing, soil thawing and evapotranspiration. The kinematic wave method is used for conducting overland flow and channel flow routing. The subsurface flow is simulated using the Darcian approach. The energy balance scheme was the primary approach used in energy‐related process simulations (snowmelt and evapotranspiration), although there are options to model snowmelt by the degree‐day method and evapotranspiration by the Priestley–Taylor equation. This hydrological model simulates the dynamic interactions of each of these processes and can predict spatially distributed snowmelt, soil moisture and evapotranspiration over a watershed at each time step as well as discharge in any specified channel(s). The model was applied to Imnavait watershed (about 2·2 km²) and the Upper Kuparuk River basin (about 146 km²) in northern Alaska. Simulated results of spatially distributed soil moisture content, discharge at gauging stations, snowpack ablations curves and other results yield reasonable agreement, both spatially and temporally, with available data sets such as SAR imagery‐generated soil moisture data and field measurements of snowpack ablation, and discharge data at selected points. The initial timing of simulated discharge does not compare well with the measured data during snowmelt periods mainly because the effect of snow damming on runoff was not considered in the model. Results from the application of this model demonstrate that spatially distributed models have the potential for improving our understanding of hydrology for certain settings. Finally, a critical component that led to the performance of this modelling is the coupling of the mass and energy processes. Copyright © 2000 John Wiley & Sons, Ltd.     

Variations of the geomagnetic field and the geomagnetic effects of three earthquakes ( M s>5.0) in Jiangsu Province, China

Since 1979 the repeated observations and experiments of geomagnetic total intensity and vertical component have been carried out for ten years in the geomagetic network which is located in Jiangsu Province, China. Three earthquakes aboveM _s 5.0 occurred during the decade, and some seismomagnetic effects were observed. The observation results show that the anomalies of the vertical geomagnetic component can’t be observed untill some months before the earthquake (M _s>5.0) in this area. In this paper it is suggested that a densely distributed network for continuous observation of geomagnetic vertical component may catch seismomagnetic anomalies and thus improve earthquake prediction in the light of the geomagnetic measurements of the mid — or — low latitude locations. The Chinese version of this paper appeared in the Chinese edition ofActa Seismologica Sinica,13, 80–87, 1991. This study is sponsored by the Chinese Joint Seismological Science Foundation.     

Integration of gauge and radar rainfall to enable best simulation of hydrological parameters

This study is about use of spatially distributed rain in physically based hydrological models. In recent years, spatially distributed radar rainfall data have become available. The distributed radar rain is used to precisely model hydrologic processes and it is more realistic than the past practice of distribution methods like Thiessen polygons. Radar provides a highly accurate spatial distribution of rainfall and greatly improves the basin average rainfall estimates. However, quantification of the exact amount of rainfall from radar observation is relatively difficult. Thus, the fundamental idea of this study is to apply hourly gauge and radar rainfall data in a distributed hydrological model to simulate hydrological parameters. Hence the comparison is made between the outcomes of the WetSpa model from radar rainfall distribution and gauge rainfall distributed by the Thiessen polygon technique. The comparative plots of the hydrograph and the results of hydrological components such as evapotranspiration, surface runoff, soil moisture, recharge and interflow, reflect the spatially distributed radar input performing well for model outflow simulation.

EDITOR D. Koutsoyiannis

ASSOCIATE EDITOR F. Pappenberger     

Development of a soil moisture‐based distributed hydrologic model for determining hydrologically based critical source areas

A simple grid cell‐based distributed hydrologic model was developed to provide spatial information on hydrologic components for determining hydrologically based critical source areas. The model represents the critical process (soil moisture variation) to run‐off generation accounting for both local and global water balance. In this way, it simulates both infiltration excess run‐off and saturation excess run‐off. The model was tested by multisite and multivariable evaluation on the 50‐km² Little River Experimental Watershed I in Georgia, U.S. and 2 smaller nested subwatersheds. Water balance, hydrograph, and soil moisture were simulated and compared to observed data. For streamflow calibration, the daily Nash‐Sutcliffe coefficient was 0.78 at the watershed outlet and 0.56 and 0.75 at the 2 nested subwatersheds. For the validation period, the Nash‐Sutcliffe coefficients were 0.79 at the watershed outlet and 0.85 and 0.83 at the 2 subwatersheds. The per cent bias was less than 15% for all sites. For soil moisture, the model also predicted the rising and declining trends at 4 of the 5 measurement sites. The spatial distribution of surface run‐off simulated by the model was mainly controlled by local characteristics (precipitation, soil properties, and land cover) on dry days and by global watershed characteristics (relative position within the watershed and hydrologic connectivity) on wet days when saturation excess run‐off was simulated. The spatial details of run‐off generation and travel time along flow paths provided by the model are helpful for watershed managers to further identify critical source areas of non‐point source pollution and develop best management practices.     

GOCE Gravity Field Processing Strategy

A processing strategy and the corresponding software architecture for the processing of GOCE (Gravity field and steady-state Ocean Circulation Explorer) observables is presented and described, with the major objective to compute a high-accuracy, high-resolution spherical harmonic model of the Earth's gravity field. The combination of two numerical solution strategies, i.e. the rigorous solution of the corresponding large normal equation systems applying parallel processing (on a PC cluster) as the core solver, and the fast semianalytic approach as a quick-look gravity field analysis (QL-GFA) tool, is proposed. Such a method fusion benefits from the advantages of the individual components: the rigorous inversion of the system providing also the full variance-covariance information, and the quickness enabling the consecutive production of intermediate gravity field solutions, for the purpose to analyse partial and incomplete data sets and to derive a diagnosis of the performance of the GOCE measurement system. The functionality and operability of the individual components are demonstrated in the framework of a closed loop simulation, which is based on a realistic mission scenario both in terms of the orbit configuration and the coloured measuring noise. Special concern is given to the accuracy of the recovered coefficients, the numerical behaviour, the required computing time, and the particular role of the individual modules within the processing chain. In the case of the core solver, it is demonstrated that the assembling and rigorous solution of large normal equation systems can be handled by using Beowulf clusters within a reasonable computing time. The application of the quick-look tool to partial data sets with short-term data gaps is demonstrated on the basis of several case studies. Additionally, the spectral analysis of the residuals of the adjustment is presented as a valuable tool for the verification of the noise characteristics of the GOCE gradiometer.     

Comparison of genetic algorithms and shuffled complex evolution approach for calibrating distributed rainfall–runoff model

Three methods, Shuffled Complex Evolution (SCE), Simple Genetic Algorithm (SGA) and Micro‐Genetic Algorithm (µGA), are applied in parameter calibration of a grid‐based distributed rainfall–runoff model (GBDM) and compared by their performances. Ten and four historical storm events in the Yan‐Shui Creek catchment, Taiwan, provide the database for model calibration and verification, respectively. The study reveals that the SCE, SGA and µGA have close calibration results, and none of them are superior with respect to all the performance measures, i.e. the errors of time to peak, peak discharge and the total runoff volume, etc. The performances of the GBDM for the verification events are slightly worse than those in the calibration events, but still quite satisfactory. Among the three methods, the SCE seems to be more robust than the other two approaches because of the smallest influence of different initial random number seeds on calibrated model parameters, and has the best performance of verification with a relatively small number of calibration events. Copyright © 2009 John Wiley & Sons, Ltd.     

Effects of land-use/cover change on hydrological processes using a GIS/RS-based integrated hydrological model: case study of the East River,China

Abstract

An integrated model, combining a surface energy balance system, an LAI-based interception model and a distributed monthly water balance model, was developed to predict hydrological impacts of land-use/land-cover change (LUCC) in the East River basin, China, with the aid of GIS/RS. The integrated model is a distributed model that not only accounts for spatial variations in basin terrain, rainfall and soil moisture, but also considers spatial and temporal variation of vegetation cover and evapotranspiration (ET), in particular, thus providing a powerful tool for investigating the hydrological impact of LUCC. The model was constructed using spatial data on topography, soil types and vegetation characteristics together with time series of precipitation from 170 stations in the basin. The model was calibrated and validated based on river discharge data from three stations in the basin for 21 years. The calibration and validation results suggested that the model is suitable for application in the basin. The results show that ET has a positive relationship with LAI (leaf area index), while runoff has a negative relationship with LAI in the same climatic zone that can be described by the surface energy balance and water balance equation. It was found that deforestation would cause an increase in annual runoff and a decrease in annual ET in southern China. Monthly runoff for different land-cover types was found to be inversely related to ET. Also, for most of the scenarios, and particularly for grassland and cropland, the most significant changes occurred in the rainy season, indicating that deforestation would cause a significant increase in monthly runoff in that season in the East River basin. These results are important for water resources management and environmental change monitoring.

Editor Z.W. Kundzewicz     

Application of singular spectrum analysis to identify the degrading structure using deteriorating distributed element model

Reinforced concrete structure may exhibit significant inelastic hysteretic behavior when subject to strong earthquake excitation. To investigate such an inelastic behavior, in this study, a new system identification technique is applied by using the deteriorating distributed element (DDE) model to simulate the hysteretic behavior of a degrading structure. Through the advanced signal processing technique, the multiple singular spectrum analysis (SSA) and the nonlinear SSA, the recorded inelastic restoring force of a deteriorating structure can be decomposed into several independent additive components in its sequentially degrading order and with decreasing weight. With each decomposed hysteresis loop, the model parameters of the DDE model are identified. The evolutionary properties of the progressive stiffness degradation behavior of reinforced concrete structure can be observed from the identified model parameters. Finally, comparison on the physical properties of the identified DDE model with respect to the seismic response data of the deteriorating structure is also discussed. The result shows that the proposed identification technique can have a good estimation on the seismic behavior of the degrading structure. Copyright © 2012 John Wiley & Sons, Ltd.     

Coupling of a simultaneous heat and water model with a distributed hydrological model and evaluation of the combined model in a cold region watershed

Snow and frozen soil prevail in cold regions worldwide, and the integration of these processes is crucial in hydrological models. In this study, a combined model was developed by fully coupling a simultaneous heat and water model with a geomorphologically based distributed hydrological model. The combined model simulates vertical and lateral water transfer as well as vertical heat fluxes and is capable of representing the effects of frozen soil and snowmelt on hydrological processes in cold regions. This model was evaluated by using in situ observations in the Binggou watershed, an experimental watershed for cold region hydrology of the Watershed Allied Telemetry Experimental Research Project. Results showed that the model was able to predict soil freezing and thawing, unfrozen soil water content, and snow depth reasonably well. The simulated hydrograph was in good agreement with the in situ observation. The Nash–Sutcliffe coefficient of daily discharge was 0.744 for the entire simulation period, 0.472 from April to June, and 0.711 from June to November. This model can improve our understanding of hydrological processes in cold regions and assess the impacts of global warming on hydrological cycles and water resources. Copyright © 2012 John Wiley & Sons, Ltd.