Fluvial suspended sediment transport and mechanical erosionin the Maghreb (North Africa)

Abstract

Available data on suspended sediment transported by rivers in the Maghreb are reviewed for 130 drainage basins. These data allow a new estimate to be proposed for the delivery of river sediment to both the Atlantic Ocean and the Mediterranean Sea from the Maghreb region. The influences of several environmental factors (precipitation, runoff, drainage area size and lithology) on mechanical erosion and fluvial sediment transport are analysed. Finally, a multiple regression model is proposed to estimate the river sediment yields in the Maghreb.     

Sediment yield variability in central Tunisia: a quantitative analysis of its controlling factors

Abstract

This paper refers to the quantification and prediction of the sedimentation rate of 26 hillside-dam reservoirs in Central Tunisia. The objectives of the study are to develop a simple and practical methodology to identify controlling factors of sedimentation, and to propose a regionalization from the study sites. Principal component analysis (PCA) and complementary multi-dimensional statistical methods are used to relate highly variable area-specific sediment yield to hydro-morphometric, lithological, geomorphological and anthropogenic characteristics of catchments. It appears that catchment area is not the main controlling factor of sedimentation in the studied area. The overall slope index, drainage network characteristics and runoff parameters are also important in characterizing sediment yield. Applied to the annual sedimentation rate series, PCA resulted in retaining the first three principal axes, explaining 65% of the total variance. Statistical methods showed that the overall slope index, the total drainage length, the compacity index and the runoff parameters are as important for the sedimentation quantification. This allowed a graphical clustering of the study zone into three distinct groups having similar behaviours: (i) watersheds characterized by high sediment transport rates and high runoff coefficients, (ii) basins distinguished by relatively low values of both flow discharge and sediment transport rates, and (iii) watersheds with an intermediate sediment yield, especially characterized by relatively high relief. In a second step, a multiple regression model including the four characteristic catchment properties was developed, presenting a valuable tool to predict area-specific sediment yield from catchments in central Tunisia. This model shows reasonable efficiency with an absolute prediction error of 81%.

Citation Ayadi, I., Abida, H., Djebbar, Y. & Mahjoub, M. R. (2010) Sediment yield variability in central Tunisia: a quantitative analysis of its controlling factors. Hydrol. Sci. J. 55(3), 446–458.     

Streamwater hydrograph separation in an alpine glacier area in the Qilian Mountains,northwestern China

ABSTRACT

Glacier-melt-induced changes in runoff are of concern in northwestern China where glacier runoff is a major source for irrigation, industries and ecosystems. Samples were collected in different water mediums such as precipitation, glacial ice/snowcover, meltwater, groundwater and streamwater for the analysis of stable isotopes and solute contents during the 2009 runoff season in the Laohugou Glacial Catchment. The multi-compare results of δ¹⁸O values showed that significant difference existed in different water mediums. Source waters of streamflow were determined using data of isotopic and geochemical tracers and a three-component hydrograph separation model. The results indicated that meltwater dominated (69.9 ± 2.7%) streamflow at the catchment. Precipitation and groundwater contributed 17.3 ± 2.3% and 12.8 ± 2.4% of the total discharge, respectively. According to the monthly hydrograph, the contribution of snow and glacier meltwater varied from 57.4% (September) to 79.1% (May), and that of precipitation varied from 0% (May) to 34.6% (September). At the same time, the monthly contribution of groundwater kept relatively steady, varying from 9.7% (June) to 20.9% (May) in the runoff season. Uncertainties for this separation were mainly caused by the variation of tracer concentrations. It is suggested that the end-member mixing analysis (EMMA) method can be used in the runoff separation in an alpine glacial catchment.

Editor Z.W. Kundzewicz; Associate editor Not assigned     

Estimating the sensitivity of runoff to climate change in an alpine-valley watershed of Xinjiang,China

ABSTRACT

The spatial-temporal variation of runoff in an inland basin is very sensitive to climate change. Investigation of runoff change in arid areas is typically limited by lack of meteorological and hydrogeological data. This study focused on runoff change in the Yarkand River source area of the Tarim Basin, China, with the aim of analysing the influence of climate change on the response characteristics of discharge. Sensitivity analysis was introduced to reflect the degree of influence of climate on runoff. Based on the sensitivity factors, over 30 sets of schemes including the IPCC Fourth Assessment Report were simulated using the MIKE 11/NAM rainfall–runoff model and the response of runoff was analysed. The results indicate that there are significant correlations and synchronous fluctuations between runoff and precipitation, evaporation and temperature. The characteristics of the sensitivity of runoff can be fitted well by Bi-Gaussian functions. The functions show that high sensitivity indexes mainly appear in the interval of 165 ± 100 m³ s^-1. The influence of precipitation on runoff is greater than that of other climate factors. Through simulation using the NAM model, we found that change of annual runoff was related to the initial climate condition. Annual runoff will have an increasing trend if it has a strong sensitivity to the initial meteorological condition. Moreover, the runoff decreases linearly with evaporation. Also it has a positive relationship with temperature and precipitation. Across the four seasons, the impact in summer and winter is greater than that in spring and autumn. Estimation of the spatial-temporal influence of climate on runoff could provide insight for water resource development in arid areas.

Editor Z.W. Kundzewicz Associate editor not assigned     

Rainfall–runoff simulation using a normalized antecedent precipitation index

Abstract

The normalized antecedent precipitation index (NAPI) model by Heggen for the prediction of runoff yield is analytically derived from the water balance equation. Heggen's model has been simplified further to a rational form and its performance verified with the Soil Conservation Service Curve Number (SCS-CN) model. The simplified model has three coefficients specific to a watershed, and requires two inputs: rainfall and the derived parameter, NAPI. The characteristic behaviour of the NAPI has resonance with the curve number (CN) of the SCS model. The proposed NAPI model was applied to three watersheds in the semi-arid region of India to simulate runoff yield. The model showed improved correlation between the observed and predicted runoff data compared to the SCS-CN model. The F test and paired t test also confirmed the reliability of the model with significance levels of 0.01 and 0.001%, respectively. The proposed model could be used successfully for rainfall–runoff modelling in a watershed.

Citation Ali, S., Ghosh, N. C. & Singh, R. (2010) Rainfall–runoff simulation using a normalized antecedent precipitation index. Hydrol. Sci. J. 55(2), 266–274.     

Spatial scale effects on sediment concentration in runoff during flood events for hilly areas of the Loess Plateau,China

The spatial scale effect on sediment concentration in runoff has received little attention despite numerous studies on sediment yield or sediment delivery ratio in the context of multiple spatial scales. We have addressed this issue for hilly areas of the Loess Plateau, north China where fluvial processes are mainly dominated by hyperconcentrated flows. The data on 717 flow events observed at 17 gauging stations and two runoff experimental plots, all located in the 3906 km² Dalihe watershed, are presented. The combination of the downstream scour of hyperconcentrated flows and the downstream dilution, which is mainly caused by the base flow and is strengthened as a result of the strong patchy storms, determines the spatial change of sediment concentration in runoff during flood events. At the watershed scale, the scouring effect takes predominance first but is subordinate to the downstream dilution with a further increase in spatial scale. As a result, the event mean sediment concentration first increases following a power function with drainage basin area and then declines at the drainage basin area of about 700 km². The power function in combination with the proportional model of the runoff‐sediment yield relationship we proposed before was used to establish the sediment‐yield model, which is neither the physical‐based model nor the regression model. This model, with only two variables (runoff depth and drainage basin area) and two parameters, can provide fairly accurate prediction of event sediment yield with model efficiency over 0·95 if small events with runoff depth lower than 1 mm are excluded. Copyright © 2011 John Wiley & Sons, Ltd.     

Factors controlling variations in suspended sediment concentration for single-valued sediment rating curves,Fraser River,British Columbia,Canada

Functional (regression) and cause-and-effect analytical methods were employed in the investigation of factors controlling single-value sediment–discharge relationships for individual hydrological events in the Fraser River Basin. Of 1025 hydrological events identified in the 97 years of the 9-stations discharge record monitored by the Water Survey of Canada (1960–1988), 49 were associated with linear, non-linear (concave and convex) sediment rating curves. Analysis revealed that time of events offered a partial explanation for the occurrence of single-valued curves because events occurring in isolation or in quick succession did not always produce single-valued curves owing to variations in hydrograph characteristics and temporal and spatial peak attenuation factors. Hydrologically, linear and non-linear sediment rating curves were distinguished by the influence of preceding discharge or antecedent moisture, which tends to generate quick or delayed runoff, thereby causing rapid or slow increases in sediment concentration in concert with discharge changes. Hydraulically, linear curves were shown to be controlled by rates of stream bed scour (rising stage) similar to those for channel filling (falling stage); concave curves by rates of scouring (rising stage) similar to those of filling but different from those of rescouring (falling stage); and convex curves by rates of filling and scouring (rising stage) different from those of filling and rescouring (falling stages), all in relation to the timing of the exceedance of the threshold discharge for stream bed scour. Meteorologically, bed scour and fill approximately coincided with the timing of precipitation, if any, on the rising and/or falling stages under subzero (T≤0 °C), low (1≤T≤9 °C) and moderate (10≤T≤19 °C) temperature conditions. It is concluded that a combination of temporal, spatial, hydrological, hydraulic and meteorological factors control variations in sediment concentration during single hydrological events on the Fraser River in a complex fashion. Multivariate analysis of these factors should greatly improve prediction of sediment transport in the Fraser River Basin. © 1998 John Wiley & Sons, Ltd.     

The nonlinear hydro-climatic process in the Yarkand River, northwestern China

Based on the hydrologic and meteorological data in the Yarkand River Basin during 1957–2008, the nonlinear hydro-climatic process was analyzed by a comprehensive method, including the Mann–Kendall trend test, wavelet analysis, wavelet regression analysis and correlation dimension. The main findings are as following: (1) The annual runoff, annual average temperature and annual precipitation showed an increasing trend during the period of 1957–2008, and the average increase extent in runoff, temperature and precipitation was 2.234 × 10⁸ m³/10 year, 0.223 °C/10 year, and 4.453 mm/10 year, respectively. (2) The nonlinear pattern of runoff, temperature and precipitation was scale-dependent with time. In other words, the annual runoff, annual average temperature and annual precipitation at five time scales resulted in five patterns of nonlinear variations respectively. (3) Although annual runoff, annual average temperature and annual precipitation presented nonlinear variations at different time scales, the runoff has a linear correlation with the temperature and precipitation. (4) The hydro-climatic process of the Yarkand River is chaotic dynamic system, in which the correlation dimension of annual runoff, annual average temperature and annual precipitation is 3.2118, 2.999 and 2.992 respectively. None of the correlation dimensions is an integer, and it indicates that the hydro-climatic process has the fractal characteristics.     

Uncertainty and sensitivity analysis of runoff and sediment yield in a small agricultural watershed with KINEROS2 / Analyse d'incertitude et de sensibilité des simulations d'écoulement et de transport solide de KINEROS2 dans un petit bassin versant agricole

Abstract

Using the Monte Carlo (MC) method, this paper derives arithmetic and geometric means and associated variances of the net capillary drive parameter, G, that appears in the Parlange infiltration model, as a function of soil texture and antecedent soil moisture content. Approximate expressions for the arithmetic and geometric statistics of G are also obtained, which compare favourably with MC generated ones. This paper also applies the MC method to evaluate parameter sensitivity and predictive uncertainty of the distributed runoff and erosion model KINEROS2 in a small experimental watershed. The MC simulations of flow and sediment related variables show that those parameters which impart the greatest uncertainty to KINEROS2 model outputs are not necessarily the most sensitive ones. Soil hydraulic conductivity and wetting front net capillary drive, followed by initial effective relative saturation, dominated uncertainties of flow and sediment discharge model outputs at the watershed outlet. Model predictive uncertainty measured by the coefficient of variation decreased with rainfall intensity, thus implying improved model reliability for larger rainfall events. The antecedent relative saturation was the most sensitive parameter in all but the peak arrival times, followed by the overland plane roughness coefficient. Among the sediment related parameters, the median particle size and hydraulic erosion parameters dominated sediment model output uncertainty and sensitivity. Effect of rain splash erosion coefficient was negligible. Comparison of medians from MC simulations and simulations by direct substitution of average parameters with observed flow rates and sediment discharges indicates that KINEROS2 can be applied to ungauged watersheds and still produce runoff and sediment yield predictions within order of magnitude of accuracy.     

Factors controlling sediment yield in China's Loess Plateau

The Loess Plateau in China, an area with some of the highest sediment yield in the world, contributes predominant proportion of the sediments found in the Yellow River. We examined sediment yield and its control variables in the plateau based on a multi‐year dataset from 180 gauging stations in areas varying in size from 10² to 10⁴ km². Various morphometric, hydrologic, climatic and land cover variables were estimated in order to understand and predict the variations in sediment yield. The results show a spatial pattern of sediment yield exhibiting an obvious zonal distribution and a coupling between precipitation and vegetation cover that fits the Langbein–Schumm law. A critical threshold of precipitation and vegetation cover was observed among the relationships of sediment yield and precipitation/vegetation cover. A multiple regression equation with three control variables, i.e. vegetation cover, percentage of cultivated loess and annual runoff, explains 65% of the total variation in sediment yield. For the loess dominated basins, where the cultivated loess accounts for more than 60% of the total area, annual runoff was the dominant variable, explaining 76% of the observed variation in sediment yield. The established equation could be a valuable tool for predicting total sediment yield in the Loess Plateau. Copyright © 2010 John Wiley & Sons, Ltd.     

Hydrological and sediment yield response to summer rainfall in a small high Arctic watershed

In cold regions, the response and related antecedent mechanisms that produce flood flows from rainfall events have received limited study. In 2007, a small watershed at Cape Bounty, Melville Island, Nunavut, was studied in detail during the melt season. Two rainfall events on June 30 and July 22, totalling 9·2 and 10·8 mm, respectively, represented significant contributions to seasonal discharge and sediment transport in a year with a low winter snowpack. The precipitation events elevated discharge and suspended sediment concentrations to twice the magnitude of the nival melt, and generated the only measurable downstream lacustrine turbidity current of the season. In two days, rainfall runoff transported 35% of the seasonal suspended sediment load, in contrast to 29% transported over the nival freshet. The magnitude and intensity of the rain events were not unusual in this setting, but the rainfall response was substantial in comparison with equivalent past events. Exceptional temperatures of July 2007 generated early, deep permafrost thaw, and ground ice melt. The resultant increase in soil moisture amplified the subsequent rainfall runoff and sediment transport response. These results demonstrate the importance of antecedent moisture conditions and the role of permafrost active layer development as an important factor in the rainfall runoff and sediment transport response to precipitation events. Copyright © 2009 John Wiley & Sons, Ltd.     

Connectivity of post-fire runoff and sediment from nested hillslopes and watersheds

Wildfire increases the potential connectivity of runoff and sediment throughout watersheds due to greater bare soil, runoff and erosion as compared to pre-fire conditions. This research examines the connectivity of post-fire runoff and sediment from hillslopes (< 1.5 ha; n = 31) and catchments (< 1000 ha; n = 10) within two watersheds (< 1500 ha) burned by the 2012 High Park Fire in northcentral Colorado, USA. Our objectives were to: (1) identify sources and quantify magnitudes of post-fire runoff and erosion at nested hillslopes and watersheds for two rain storms with varied duration, intensity and antecedent precipitation; and (2) assess the factors affecting the magnitude and connectivity of runoff and sediment across spatial scales for these two rain storms. The two summer storms that are the focus of this research occurred during the third summer after burning. The first storm had low intensity rainfall over 11 hours (return interval <1–2 years), whereas the second event had high intensity rainfall over 1 hour (return interval <1–10 years). The lower intensity storm was preceded by high antecedent rainfall and led to low hillslope sediment yields and channel incision at most locations, whereas the high intensity storm led to infiltration-excess overland flow, high sediment yields, in-stream sediment deposition and channel substrate fining. For both storms, hillslope-to-stream sediment delivery ratios and area-normalised cross-sectional channel change increased with the percent of catchment that burned at high severity. For the high intensity storm, hillslope-to-stream sediment delivery ratios decreased with unconfined channel length (%). The findings quantify post-fire connectivity and sediment delivery from hillslopes and streams, and highlight how different types of storms can cause varying magnitues and spatial patterns of sediment transport and deposition from hillslopes through stream channel networks.     

Suspended sediment estimation using neuro-fuzzy and neural network approaches/Estimation des matières en suspension par des approches neurofloues et à base de réseau de neurones

Abstract

The abilities of neuro-fuzzy (NF) and neural network (NN) approaches to model the streamflow–suspended sediment relationship are investigated. The NF and NN models are established for estimating current suspended sediment values using the streamflow and antecedent sediment data. The sediment rating curve and multi-linear regression are also applied to the same data. Statistic measures were used to evaluate the performance of the models. The daily streamflow and suspended sediment data for two stations—Quebrada Blanca station and Rio Valenciano station—operated by the US Geological Survey were used as case studies. Based on comparison of the results, it is found that the NF model gives better estimates than the other techniques.     

Hydrological model comparison and assessment: criteria from catchment scales and temporal resolution

ABSTRACT

This study examines the performance of three hydrological models, namely the artificial neural network (ANN) model, the Hydrologiska Byråns Vattenbalansavdelning-D (HBV-D) model, and the Soil and Water Integrated Model (SWIM) over the upper reaches of the Huai River basin. The assessment is done by using databases of different temporal resolution and by further examining the applicability of SWIM for different catchment sizes. The results show that at monthly scale the performance of the ANN model is better than that of HBV-D and SWIM. The ANN model can be applied at any temporal scale as it establishes an artificial precipitation–runoff relationship for various time scales by only using monthly precipitation, temperature and runoff data. However, at daily scale the performance of both HBV-D and SWIM are similar or even better than the ANN model. In addition, the performance of SWIM at a small catchment size (less than 10 000 km²) is much better than at a larger catchment size. In view of climate change modelling, HBV-D and SWIM might be integrated in a dynamical atmosphere-water-cycle modelling rather than the ANN model due to their use of observed physical links instead of artificial relations within a black box.

Editor D. Koutsoyiannis; Associate editor D. Hughes     

Climate change impacts on surface water resources in the Rheraya catchment (High Atlas,Morocco)

This study aimed to quantify possible climate change impacts on runoff for the Rheraya catchment (225 km²) located in the High Atlas Mountains of Morocco, south of Marrakech city. Two monthly water balance models, including a snow module, were considered to reproduce the monthly surface runoff for the period 1989?2009. Additionally, an ensemble of five regional climate models from the Med-CORDEX initiative was considered to evaluate future changes in precipitation and temperature, according to the two emissions scenarios RCP4.5 and RCP8.5. The future projections for the period 2049?2065 under the two scenarios indicate higher temperatures (+1.4°C to +2.6°C) and a decrease in total precipitation (?22% to ?31%). The hydrological projections under these climate scenarios indicate a significant decrease in surface runoff (?19% to ?63%, depending on the scenario and hydrological model) mainly caused by a significant decline in snow amounts, related to reduced precipitation and increased temperature. Changes in potential evapotranspiration were not considered here, since its estimation over long periods remains a challenge in such data-sparse mountainous catchments. Further work is required to compare the results obtained with different downscaling methods and different hydrological model structures, to better reproduce the hydro-climatic behaviour of the catchment.

EDITOR M.C. Acreman

ASSOCIATE EDITOR R. Hirsch     

Piecewise prediction model for watershed‐scale erosion and sediment yield of individual rainfall events on the Loess Plateau,China

Establishing a universal watershed‐scale erosion and sediment yield prediction model represents a frontier field in erosion and soil/water conservation. The research presented here was conducted on the Chabagou watershed, which is located in the first sub‐region of the hill‐gully area of the Loess Plateau, China. A back‐propagation artificial neural model for watershed‐scale erosion and sediment yield was established, with the accuracy of the model, then compared with that of multiple linear regression. The sensitivity degree of various factors to erosion and sediment yield was quantitatively analysed using the default factor test. On the basis of the sensitive factors and the fractal information dimension, the piecewise prediction model for erosion and sediment yield of individual rainfall events was established and further verified. The results revealed the back‐propagation artificial neural network model to perform better than the multiple linear regression model in terms of predicting the erosion modulus, with the former able to effectively characterize dynamic changes in sediment yield under comprehensive factor conditions. The sensitivity of runoff erosion power and runoff depth to the erosion and sediment yield associated with individual rainfall events was found to be related to the complexity of surface topography. The characteristics of such a hydrological response are thus closely related to topography. When the fractal information dimension is greater than the topographic threshold, the accuracy of prediction using runoff erosion power is higher than that of using runoff depth. In contrast, when the fractal information dimension is smaller than the topographic threshold, the accuracy of prediction using runoff depth is higher than that of using runoff erosion power. The developed piecewise prediction model for watershed‐scale erosion and sediment yield of individual rainfall events, which introduces runoff erosion power and runoff depth using the fractal information dimension as a boundary, can be considered feasible and reliable and has a high prediction accuracy. Copyright © 2013 John Wiley & Sons, Ltd.     

Application of newly developed ensemble machine learning models for daily suspended sediment load prediction and related uncertainty analysis

ABSTRACT

Ensemble machine learning models have been widely used in hydro-systems modeling as robust prediction tools that combine multiple decision trees. In this study, three newly developed ensemble machine learning models, namely gradient boost regression (GBR), AdaBoost regression (ABR) and random forest regression (RFR) are proposed for prediction of suspended sediment load (SSL), and their prediction performance and related uncertainty are assessed. The SSL of the Mississippi River, which is one of the major world rivers and is significantly affected by sedimentation, is predicted based on daily values of river discharge (Q) and suspended sediment concentration (SSC). Based on performance metrics and visualization, the RFR model shows a slight lead in prediction performance. The uncertainty analysis also indicates that the input variable combination has more impact on the obtained predictions than the model structure selection.     

On the estimation of antecedent wetness conditions in rainfall–runoff modelling

The analysis of the physical processes involved in a conceptual model of soil water content balance is addressed with the objective of its application as a component of rainfall–runoff modelling. The model uses routinely measured meteorological variables (rainfall and air temperature) and incorporates a limited number of significant parameters. Its performance in estimating the soil moisture temporal pattern was tested through local measurements of volumetric water content carried out continuously on an experimental plot located in central Italy. The analysis was carried out for different periods in order to test both the representation of infiltration at the short time‐scale and drainage and evapotranspiration processes at the long time‐scale. A robust conceptual model was identified that incorporated the Green–Ampt approach for infiltration and a gravity‐driven approximation for drainage. A sensitivity analysis was performed for the selected model to assess the model robustness and to identify the more significant parameters involved in the principal processes that control the soil moisture temporal pattern. The usefulness of the selected model was tested for the estimation of the initial wetness conditions for rainfall–runoff modelling at the catchment scale. Specifically, the runoff characteristics (runoff depth and peak discharge) were found to be dependent on the pre‐event surface soil moisture. Both observed values and those estimated by the model gave good results. On the contrary, with the antecedent wetness conditions furnished by two versions of the antecedent precipitation index (API), large errors were obtained. Copyright © 2007 John Wiley & Sons, Ltd.     

Runoff and suspended sediment yields from an unpaved road segment,St John,US Virgin Islands

Unpaved roads are believed to be the primary source of terrigenous sediments being delivered to marine ecosystems around the island of St John in the eastern Caribbean. The objectives of this study were to: (1) measure runoff and suspended sediment yields from a road segment; (2) develop and test two event‐based runoff and sediment prediction models; and (3) compare the predicted sediment yields against measured values from an empirical road erosion model and from a sediment trap. The runoff models use the Green–Ampt infiltration equation to predict excess precipitation and then use either an empirically derived unit hydrograph or a kinematic wave to generate runoff hydrographs. Precipitation, runoff, and suspended sediment data were collected from a 230 m long, mostly unpaved road segment over an 8‐month period. Only 3–5 mm of rainfall was sufficient to initiate runoff from the road surface. Both models simulated similar hydrographs. Model performance was poor for storms with less than 1 cm of rainfall, but improved for larger events. The largest source of error was the inability to predict initial infiltration rates. The two runoff models were coupled with empirical sediment rating curves, and the predicted sediment yields were approximately 0·11 kg per square meter of road surface per centimetre of precipitation. The sediment trap data indicated a road erosion rate of 0·27 kg m^?2 cm^?1. The difference in sediment production between these two methods can be attributed to the fact that the suspended sediment samples were predominantly sand and silt, whereas the sediment trap yielded mostly sand and gravel. The combination of these data sets yields a road surface erosion rate of 0·31 kg m^?2 cm^?1, or approximately 36 kg m^?2 year^?1. This is four orders of magnitude higher than the measured erosion rate from undisturbed hillslopes. The results confirm the importance of unpaved roads in altering runoff and erosion rates in a tropical setting, provide insights into the controlling processes, and provide guidance for predicting runoff and sediment yields at the road‐segment scale. Copyright © 2006 John Wiley & Sons, Ltd.