Suitability of North American Regional Reanalysis (NARR) output for hydrologic modelling and analysis in mountainous terrain

Meteorological observations at high elevations in mountainous regions are often lacking. One opportunity to fill this data gap is through the use of downscaled output from weather reanalysis models. In this study, we tested the accuracy of downscaled output from the North American Regional Reanalysis (NARR) against high‐elevation surface observations at four ridgetop locations in the southern Coast Mountains of British Columbia, Canada. NARR model output was downscaled to the surface observation locations through three‐dimensional interpolation for air temperature, vapour pressure and wind speed and two‐dimensional interpolation for radiation variables. Accuracy was tested at both the 3‐hourly and daily time scales. Air temperature displayed a high level of agreement, especially at the daily scale, with root mean square error (RMSE) values ranging from 0.98 to 1.21 °C across all sites. Vapour pressure downscaling accuracy was also quite high (RMSE of 0.06 to 0.11 hPa) but displayed some site specific bias. Although NARR overestimated wind speed, there were moderate to strong linear relations (r² from 0.38 to 0.84 for daily means), suggesting that the NARR output could be used as an index and bias‐corrected. NARR output reproduced the seasonal cycle for incoming short‐wave radiation, with Nash–Sutcliffe model efficiencies ranging from 0.78 to 0.87, but accuracy suffered on days with cloud cover, resulting in a positive bias and RMSE ranged from 42 to 46 Wm^{? 2}. Although fewer data were available, incoming long‐wave radiation from NARR had an RMSE of 19 Wm^{? 2} and outperformed common methods for estimating incoming long‐wave radiation. NARR air temperature showed potential to assist in hydrologic analysis and modelling during an atmospheric river storm event, which are characterized by warm and wet air masses with atypical vertical temperature gradients. The incorporation of a synthetic NARR air temperature station to better represent the higher freezing levels resulted in increased predicted peak flows, which better match the observed run‐off during the event. Copyright © 2016 John Wiley & Sons, Ltd.     

How does DEM resolution affect microtopographic characteristics,hydrologic connectivity,and modelling of hydrologic processes?

The resolution of a digital elevation model (DEM) is a crucial factor in watershed hydrologic and environmental modelling. DEM resolution can cause significant variability in the representation of surface topography, which further affects quantification of hydrologic connectivity and simulation of hydrologic processes. The objective of this study is to examine the effects of DEM resolution on (1) surface microtopographic characteristics, (2) hydrologic connectivity, and (3) the spatial and temporal variations of hydrologic processes. A puddle‐to‐puddle modelling system was utilized for surface delineation and modelling of the puddle‐to‐puddle overland flow dynamics, surface runoff, infiltration, and unsaturated flow for nine DEM resolution scenarios of a field plot surface. Comparisons of the nine modelling scenarios demonstrated that coarser DEM resolutions tended to eliminate topographic features, reduce surface depression storage, and strengthen hydrologic connectivity and surface runoff. We found that reduction in maximum depression storage and maximum ponding area was as high as 97.56% and 76.36%, respectively, as the DEM grid size increased from 2 to 80 cm. The paired t‐test and fractal analysis demonstrated the existence of a threshold DEM resolution (10 cm for the field plot), within which the DEM‐based hydrologic modelling was effective and acceptable. The effects of DEM resolution were further evaluated for a larger surface in the Prairie Pothole Region subjected to observed rainfall events. It was found that simulations based on coarser resolution DEMs (>10 m) tended to overestimate ponded areas and underestimate runoff discharge peaks. The simulated peak discharge from the Prairie Pothole Region surface reduced by approximately 50% as the DEM resolution changed from 2 to 90 m. Fractal analysis results elucidated scale dependency of hydrologic and topographic processes. In particular, scale analysis highlighted a unique constant–threshold–power relationship between DEM scale and topographic and hydrologic parameters/variables. Not only does this finding allow one to identify threshold DEM but also further develop functional relationships for scaling to achieve valid topographic characterization as well as effective and efficient hydrologic modelling. Copyright © 2016 John Wiley & Sons, Ltd.     

Quantifying the effects of climate variability and human activities on runoff from the Laohahe basin in northern China using three different methods

Much attention has recently been focused on the effects that climate variability and human activities have had on runoff. In this study, these effects are quantified using three methods, namely, multi‐regression, hydrologic sensitivity analysis, and hydrologic model simulation. A conceptual framework is defined to separate the effects. As an example, the change in annual runoff from the semiarid Laohahe basin (18 112 km²) in northern China was investigated. Non‐parametric Mann‐Kendall test, Pettitt test, and precipitation‐runoff double cumulative curve method were adopted to identify the trends and change‐points in the annual runoff from 1964 to 2008 by first dividing the long‐term runoff series into a natural period (1964–1979) and a human‐induced period (1980–2008). Then the three quantifying methods were calibrated and calculated, and they provided consistent estimates of the percentage change in mean annual runoff for the human‐induced period. In 1980–2008, human activities were the main factors that reduced runoff with contributions of 89–93%, while the reduction percentages due to changes in precipitation and potential evapotranspiration only ranged from 7 to 11%. For the various effects at different durations, human activities were the main reasons runoff decreased during the two drier periods of 1980–1989 and 2000–2008. Increased runoff during the wetter period of 1990–1999 is mainly attributed to climate variability. This study quantitatively separates the effects of climate variability and human activities on runoff, which can serve as a reference for regional water resources assessment and management. Copyright © 2011 John Wiley & Sons, Ltd.     

The relative impacts of climate change and urbanization on the hydrological response of a Korean urban watershed

We assessed the relative hydrological impacts of climate change and urbanization using an integrated approach that links the statistical downscaling model (SDSM), the Hydrological Simulation Program—Fortran (HSPF) and the impervious cover model (ICM). A case study of the Anyangcheon watershed, a representative urban region in Korea, illustrates how the proposed framework can be used to analyse the impacts of climate change and urbanization on water quantity and quality. The evaluation criteria were measurements of low flow (99, 95, and 90 percentile flow), high flow (10, 5, and 1 percentile value), pollutant concentration (30, 10, and 1 percentile value), and the numbers of days required to satisfy the target water quantity and quality for a sensitive comparison of subtle impacts of variations in these measures. Nine scenarios, including three climate scenarios (present conditions, A1B, and A2) and three land use change scenarios, were analysed using the HSPF model. The impacts of climate change on low flow (34·1–59·8% increase) and high flow (29·1–37·1% increase) were found to be much greater than those on the biochemical oxygen demand (BOD) (3·8–10·0% decrease). On the other hand, the impacts of urbanization on water quality (19·0–44·6% increase) are more significant than those on high (1·0–4·4% increase) and low flow (11·4–25·6% decrease). Furthermore, low flows are more sensitive to urbanization than high flows. The number of days required to satisfy the target water quantity and quality can be a sensitive criterion to compare the subtle impacts of climate and urbanization on human society, especially as they are much more sensitive than low flow and pollutant concentration. Finally, urbanization has a potent impact on BOD while climate change has a high impact on flow rate. Therefore, the impacts of both climate change and urbanization must be included in watershed management and water resources planning for sustainable development. Copyright © 2010 John Wiley & Sons, Ltd.     

Simulating hydrologic and hydraulic processes throughout the Amazon River Basin

Presented here is a model framework based on a land surface topography that can be represented with various degrees of resolution and capable of providing representative channel/floodplain hydraulic characteristics on a daily to hourly scale. The framework integrates two models: (1) a water balance model (WBM) for the vertical fluxes and stores of water in and through the canopy and soil layers based on the conservation of mass and energy, and (2) a routing model for the horizontal routing of surface and subsurface runoff and channel and floodplain waters based on kinematic and diffusion wave methodologies. The WBM is driven by satellite‐derived precipitation (TRMM_3B42) and air temperature (MOD08_M3). The model's use of an irregular computational grid is intended to facilitate parallel processing for applications to continental and global scales. Results are presented for the Amazon Basin over the period Jan 2001 through Dec 2005. The model is shown to capture annual runoff totals, annual peaks, seasonal patterns, and daily fluctuations over a range of spatial scales (>1, 000 to < 4·7M km²). For the period of study, results suggest basin‐wide total water storage changes in the Amazon vary by approximately + /? 5 to 10 cm, and the fractional components accounting for these changes are: root zone soil moisture (20%), subsurface water being routed laterally to channels (40%) and channel/floodplain discharge (40%). Annual variability in monthly water storage changes by + /? 2·5 cm is likely due to 0·5 to 1 month variability in the arrival of significant rainfall periods throughout the basin. Copyright © 2009 John Wiley & Sons, Ltd.     

Land cover effects on runoff patterns in eastern Piedmont (USA) watersheds

Physiography and land cover determine the hydrologic response of watersheds to climatic events. However, vast differences in climate regimes and variation of landscape attributes among watersheds (including size) have prevented the establishment of general relationships between land cover and runoff patterns across broad scales. This paper addresses these difficulties by using power spectral analysis to characterize area‐normalized runoff patterns and then compare these patterns with landscape features among watersheds within the same physiographic region. We assembled long‐term precipitation and runoff data for 87 watersheds (first to seventh order) within the eastern Piedmont (USA) that contained a wide variety of land cover types, collected environmental data for each watershed, and compared the datasets using a variety of statistical measures. The effect of land cover on runoff patterns was confirmed. Urban‐dominated watersheds were flashier and had less hydrologic memory compared with forest‐dominated watersheds, whereas watersheds with high wetland coverage had greater hydrologic memory. We also detected a 10–15% urban threshold above which urban coverage became the dominant control on runoff patterns. When spectral properties of runoff were compared across stream orders, a threshold after the third order was detected at which watershed processes became dominant over precipitation regime in determining runoff patterns. Finally, we present a matrix that characterizes the hydrologic signatures of rivers based on precipitation versus landscape effects and low‐frequency versus high‐frequency events. The concepts and methods presented can be generally applied to all river systems to characterize multiscale patterns of watershed runoff. Copyright © 2013 John Wiley & Sons, Ltd.     

CHOSEN: A synthesis of hydrometeorological data from intensively monitored catchments and comparative analysis of hydrologic extremes

Comparative hydrology has been hampered by limited availability of geographically extensive, intercompatible monitoring data on comprehensive water balance stores and fluxes. These limitations have, for example, restricted comprehensive assessment of multiple dimensions of wetting and drying related to climate change and hampered understanding of why widespread changes in precipitation extremes are uncorrelated with changes in streamflow extremes. Here, we address this knowledge gap and underlying data gap by developing a new data synthesis product and using that product to detect trends in the frequencies and magnitudes of a comprehensive set of hydroclimatic and hydrologic extremes. CHOSEN (Comprehensive Hydrologic Observatory Sensor Network) is a database of streamflow, soil moisture, and other hydroclimatic and hydrologic variables from 30 study areas across the United States. An accompanying data pipeline provides a reproducible, semi-automated approach for assimilating data from multiple sources, performing quality assurance and control, gap-filling and writing to a standard format. Based on the analysis of extreme events in the CHOSEN dataset, we detected hotspots, characterized by unusually large proportions of monitored variables exhibiting trends, in the Pacific Northwest, New England, Florida and Alaska. Extreme streamflow wetting and drying trends exhibited regional coherence. Drying trends in the Pacific Northwest and Southeast were often associated with trends in soil moisture and precipitation (Pacific Northwest) and evapotranspiration-related variables (Southeast). In contrast, wetting trends in the upper Midwest and the Rocky Mountains showed few univariate associations with other hydroclimatic extremes, but their latitudes and elevations suggested the importance of changing snowmelt characteristics. On the whole, observed trends are incompatible with a ‘drying-in-dry, wetting-in-wet’ paradigm for climate-induced hydrologic changes over land. Our analysis underscores the need for more extensive, longer-term observational data for soil moisture, snow and evapotranspiration.     

Shuffled Complex Evolution model calibrating algorithm: enhancing its robustness and efficiency

Shuffled Complex Evolution—University of Arizona (SCE‐UA) has been used extensively and proved to be a robust and efficient global optimization method for the calibration of conceptual models. In this paper, two enhancements to the SCE‐UA algorithm are proposed, one to improve its exploration and another to improve its exploitation of the search space. A strategically located initial population is used to improve the exploration capability and a modification to the downhill simplex search method enhances its exploitation capability. This enhanced version of SCE‐UA is tested, first on a suite of test functions and then on a conceptual rainfall‐runoff model using synthetically generated runoff values. It is observed that the strategically located initial population drastically reduces the number of failures and the modified simplex search also leads to a significant reduction in the number of function evaluations to reach the global optimum, when compared with the original SCE‐UA. Thus, the two enhancements significantly improve the robustness and efficiency of the SCE‐UA model calibrating algorithm. Copyright © 2008 John Wiley & Sons, Ltd.     

太湖流域汛期河湖等水位线的判读及其应用

在中国湖泊-流域数据库的技术支撑下,绘制出太湖流域20世纪内5次(1931,1954,1983,1991,1999年)梅雨洪水期,不同雨情、水情下的河湖等水位线.以上述系列图幅为基础,解读了水情及水位发展过程,同时初步分析了等水位线在防洪中的应用,以及新出现的太湖流域第三次水势演变等研究结果.     

Patterns of hydrologic connectivity in the McMurdo Dry Valleys,Antarctica: a synthesis of 20 years of hydrologic data

Streams in the McMurdo Dry Valleys (MDVs) of Antarctica moderate an important hydrologic and biogeochemical connection between upland alpine glaciers, valley‐bottom soils, and lowland closed‐basin lakes. Moreover, MDV streams are simple but dynamic systems ideal for studying interacting hydrologic and ecological dynamics. This work synthesizes 20 years of hydrologic data, collected as part of the MDVs Long‐Term Ecological Research project, to assess spatial and temporal dynamics of hydrologic connectivity between glaciers, streams, and lakes. Long‐term records of stream discharge (Q), specific electrical conductance (EC), and water temperature (T) from 18 streams were analysed in order to quantify the magnitude, duration, and frequency of hydrologic connections over daily, annual, and inter‐annual timescales. At a daily timescale, we observe predictable diurnal variations in Q, EC, and T. At an annual timescale, we observe longer streams to be more intermittent, warmer, and have higher median EC values, compared to shorter streams. Longer streams also behave chemostatically with respect to EC, whereas shorter streams are more strongly characterized by dilution. Inter‐annually, we observe significant variability in annual runoff volumes, likely because of climatic variability over the 20 record years considered. Hydrologic connections at all timescales are vital to stream ecosystem structure and function. This synthesis of hydrologic connectivity in the MDVs provides a useful end‐member template for assessing hydrologic connectivity in more structurally complex temperate watersheds. Copyright © 2016 John Wiley & Sons, Ltd.     

A top–down soil moisture and sap flux sampling design of a rain–snow transition mountain watershed

This paper presents a top–down approach for soil moisture and sap flux sampling design with the goal of understanding ecohydrologic response to interannual climate variation in the rain–snow transition watersheds. The design is based on a priori estimates of soil moisture and transpiration patterns using a physical distributed model, Regional Hydro‐Ecologic Simulation System (RHESSys). RHESSys was initially calibrated with existing snow depth and streamflow data. Calibrated model estimates of seasonal trajectories of snowmelt, root‐zone soil moisture storage, and transpiration were used to develop five hydrologic similarity indicators and map these at (30 m) patch scale across the study watershed. The partitioning around medoids‐clustering algorithm was then used to define six distinctive spatially explicit clusters based on the five hydrologic similarity indictors. A representative site within each cluster was identified for sampling. For each site, soil moisture sensors were installed at the 30‐ and 90‐cm depths and at the five soil pits and a sap flux sensor at the averaged‐size white fir tree for each site. The model‐based cluster analysis suggests that the elevation gradient and topographically driven flow drainage patterns are the dominant drivers of spatial patterns of soil moisture and transpiration. The comparison of model‐based calculated hydrological similarity indicators with measured‐data‐based values shows that spatial patterns of field‐sampled soil moisture data typically fell within uncertainty bounds of model‐based estimates for each cluster. There were however several notable exceptions. The model failed to capture the soil moisture and sap flux dynamics in a riparian zone site and in a site where lateral subsurface flow may not follow surface topography. Results highlight the utility of using a hypothesis driven sampling strategy, based on a physically based model, for efficiently providing new information that can drive both future measurements and strategic refinements to model inputs, parameters, or structure that might reduce these errors. Future research will focus on strategies for using of finer scale representations of microclimate, topography, vegetation, and soil properties to improve models.     

Quantifying the altered hydrologic connectivity of forest roads resulting from decommissioning and relocation

The decommissioning of roads is occurring in many forest environments with the aim of reducing the negative impacts of road runoff on water quality and aquatic habitat. Works associated with decommissioning are expensive so prior assessment of the outcomes of various options is merited. This paper presents a method of quantifying the degree to which a road is hydrologically connected to the stream network and thus the likely impacts of constructing a road of different configurations upon water quality. The method permits comparisons between different road network management options and is useful for assessing the likely result of decommissioning works. Emphasis is placed on quantifying the uncertainty of key performance measures. The procedures developed here are an extension of the probabilistic ‘volume to breakthrough’ model recently formulated by Australian water quality researchers and allow the quantification of road/stream connectivity without the need for extensive parameterization. To demonstrate its utility, the model was applied to an actual road decommissioning and replacement project in southeast Australia. Road areas and drainage outlets were surveyed in the field and flow paths to streams derived from a 1 metre resolution LiDAR based digital elevation model. The results demonstrate that the actual road decommissioning examined in this case was unlikely to reduce runoff to the stream network and that the overall impact of the works in conditions of design storms are likely to result in a net reduction in stream water quality. Copyright © 2007 John Wiley & Sons, Ltd.     

Landscape metrics as predictors of hydrologic connectivity between Coastal Plain forested wetlands and streams

Geographically isolated wetlands, those entirely surrounded by uplands, provide numerous landscape‐scale ecological functions, many of which are dependent on the degree to which they are hydrologically connected to nearby waters. There is a growing need for field‐validated, landscape‐scale approaches for classifying wetlands on the basis of their expected degree of hydrologic connectivity with stream networks. This study quantified seasonal variability in surface hydrologic connectivity (SHC) patterns between forested Delmarva bay wetland complexes and perennial/intermittent streams at 23 sites over a full‐water year (2014–2015). Field data were used to develop metrics to predict SHC using hypothesized landscape drivers of connectivity duration and timing. Connection duration was most strongly related to the number and area of wetlands within wetland complexes as well as the channel width of the temporary stream connecting the wetland complex to a perennial/intermittent stream. Timing of SHC onset was related to the topographic wetness index and drainage density within the catchment. Stepwise regression modelling found that landscape metrics could be used to predict SHC duration as a function of wetland complex catchment area, wetland area, wetland number, and soil available water storage (adj‐R² = 0.74, p < .0001). Results may be applicable to assessments of forested depressional wetlands elsewhere in the U.S. Mid‐Atlantic and Southeastern Coastal Plain, where climate, landscapes, and hydrological inputs and losses are expected to be similar to the study area.     

Quantifying the relative impact of hydrological and hydraulic modelling parameterizations on uncertainty of inundation maps

ABSTRACT

Flood risk management strongly relies on inundation models for river basin zoning in flood-prone and risk-free areas. Floodplain zoning is significantly affected by the diverse and concurrent uncertainties that characterize the modelling chain used for producing inundation maps. In order to quantify the relative impact of the uncertainties linked to a lumped hydrological (rainfall–runoff) model and a FLO-2D hydraulic model, a Monte Carlo procedure is proposed in this work. The hydrological uncertainty is associated with the design rainfall estimation method, while the hydraulic model uncertainty is associated with roughness parameterization. This uncertainty analysis is tested on the case study of the Marta coastal catchment in Italy, by comparing the different frequency, extent and depth of inundation simulations associated with varying rainfall forcing and/or hydraulic model roughness realizations. The results suggest a significant predominance of the hydrological uncertainty with respect to the hydraulic one on the overall uncertainty associated with the simulated inundation maps.     

How much complexity is needed to simulate watershed streamflow and water quality? A test combining time series and hydrological models

Modelled hydrologic processes are represented in a set of numerical equations; the complexity of which can be measured by the total number of variables needed. A single dominant hydrologic process could control the hydrologic response of a watershed, and so the identification of the corresponding dominant variable(s) would aid in identifying a parsimonious model and in collecting more reliable data. By accounting for both model complexity and serial correlation in the variables, a model is used to identify the dominant variables for representing watershed scale streamflow, sediment transport and phosphorus yields. Long‐term water quantity and quality data were used to show that rainfall and non‐linear soil water storage were the dominant variables for weekly streamflow, suspended sediment and particulate phosphorus. Model accuracy did not consistently improve when other statistically significant variables were included. The results suggest that improved model performance may not justify the added model complexity. As such, identification of dominant variables would be the priority for developing parsimonious hydrologic models, especially at watershed scales. Copyright © 2013 John Wiley & Sons, Ltd.     

Characterizing stream temperature hysteresis in forested headwater streams

Stream temperature (T_s) is a key water quality parameter that controls several biological, ecological, and chemical processes in aquatic systems. In forested headwaters, exchanges of energy across air-water-streambed interfaces may influence T_s regimes, especially during storm events as the sources of runoff change over space and time. Analysis of the hysteretic behaviour of T_s during storm events may provide insights into rainfall-runoff responses, but such relationships have not been thoroughly investigated. As such, our objectives were to (a) quantify the variability of stream temperature hysteresis across seasons in different sub-regions and (b) investigate the relationship between the hysteretic response and catchment characteristics. T_s hysteresis during storm events was assessed based on the hysteresis index (HI), which describes the directionality of hysteresis loops, and the temperature response index (TRI), which indicates whether T_s increased or decreased during a storm event. We analysed T_s data from 10 forested headwater reaches in two sub-regions (McGarvey and West Fork Tectah) in Northern California. We also performed a clustering analysis to examine the relationship amongst HI, TRI, topographic metrics, and meteorological characteristics of the study areas. Overall, the hysteretic behaviour of T_s varied across seasons—the greatest HI occurred during spring and summer. Interestingly, in the McGarvey streams the variability in T_s hysteresis co-varied strongly with topographic metrics (i.e., upslope accumulative area, average channel slope, topographic wetness index). Comparatively, in West Fork Tectah the variability of T_s hysteresis co-varied most strongly with meteorological metrics (i.e., antecedent rainfall events, solar radiation, and air temperature). Variables such as the gradient between stream and air temperatures, slope, and wetted width were significant for both sub-regional hysteretic patterns. We posit that the drivers of T_s response during storms are likely dependent on catchment physiographic characteristics. Our study also illustrated the potential utility of stream temperature as a tracer for improving the understanding of hydrologic connectivity and shifts in the dominant runoff contributions to streamflow during storm events.     

A field‐scale infiltration model accounting for spatial heterogeneity of rainfall and soil saturated hydraulic conductivity

This study first explores the role of spatial heterogeneity, in both the saturated hydraulic conductivity K_s and rainfall intensity r, on the integrated hydrological response of a natural slope. On this basis, a mathematical model for estimating the expected areal‐average infiltration is then formulated. Both K_s and r are considered as random variables with assessed probability density functions. The model relies upon a semi‐analytical component, which describes the directly infiltrated rainfall, and an empirical component, which accounts further for the infiltration of surface water running downslope into pervious soils (the run‐on effect). Monte Carlo simulations over a clay loam soil and a sandy loam soil were performed for constructing the ensemble averages of field‐scale infiltration used for model validation. The model produced very accurate estimates of the expected field‐scale infiltration rate, as well as of the outflow generated by significant rainfall events. Furthermore, the two model components were found to interact appropriately for different weights of the two infiltration mechanisms involved. Copyright © 2005 John Wiley & Sons, Ltd.     

“Amount effect” of water isotopes and quantitative analysis of post‐condensation processes

A numerical model is proposed that describes the interaction between raindrops and water vapour near the planetary boundary layer to explain the “amount effect”. This model relates the intensity to the isotopic composition of precipitation. The model resolves raindrop sizes, and explicitly includes: (1) the isotopic equilibration time of raindrops that is drop‐size dependent; (2) raindrop transit times through the atmosphere; and (3) the evolution of the isotopic composition of vapour at various rain rates. At high rain rate, the precipitation through a layer is less equilibrated with the vapour because the isotopic equilibration time is long compared to the fast transit time, and there is a preponderance of large drops, which take longer to equilibrate. The δ¹⁸O of vapour in the lower atmosphere becomes lower as a result of the interaction with these raindrops of low δ¹⁸O, and the degree of depletion of ¹⁸O is higher when precipitation rates are high. The model reproduces time‐series observations of isotopic composition of precipitation in Japan, and a vapour replenishment rate is inferred by either advection or evaporation of about 5% of the precipitation rate. The results could be the basis for a new parameterization of the isotopic equilibration for different precipitation types and rates in General Circulation Models (GCMs). When the model is applied to a GCM, this parameterization is important for places where precipitation occurs at cold temperatures (<15 °C). Copyright © 2007 John Wiley & Sons, Ltd.