Estimating overland flow erosion capacity using unit stream power

Soil erosion caused by water flow is a complex problem. Both empirical and physically based approaches were used for the estimation of surface erosion rates. Their applications are mainly limited to experimental areas or laboratory studies. The maximum sediment concentration overland flow can carry is not considered in most of the existing surface erosion models. The lack of erosion capacity limitation may cause over estimations of sediment concentration. A correlation analysis is used in this study to determine significant factors that impact surface erosion capacity. The result shows that the unit stream power is the most dominant factor for overland flow erosion which is consistent with experimental data. A bounded regression formula is used to reflect the limits that sediment concentration cannot be less than zero nor greater than a maximum value. The coefficients used in the model are calibrated using published laboratory data. The computed results agree with laboratory data very well. A one dimensional overland flow diffusive wave model is used in conjunction with the developed soil erosion equation to simulate field experimental results. This study concludes that the non-linear regression method using unit stream power as the dominant factor performs well for estimating overland flow erosion capacity.     

Estimating restorable wetland water storage at landscape scales

Globally, hydrologic modifications such as ditching and subsurface drainage have significantly reduced wetland water storage capacity (i.e., volume of surface water a wetland can retain) and consequent wetland functions. While wetland area has been well documented across many landscapes and used to guide restoration efforts, few studies have directly quantified the associated wetland storage capacity. Here, we present a novel raster‐based approach to quantify both contemporary and potential (i.e., restorable) storage capacities of individual depressional basins across landscapes. We demonstrate the utility of this method by applying it to the Delmarva Peninsula, a region punctuated by both depressional wetlands and drainage ditches. Across the entire peninsula, we estimated that restoration (i.e., plugging ditches) could increase storage capacity by 80%. Focusing on an individual watershed, we found that over 59% of restorable storage capacity occurs within 20 m of the drainage network, and that 93% occurs within 1 m elevation of the drainage network. Our demonstration highlights widespread ditching in this landscape, spatial patterns of both contemporary and potential storage capacities, and clear opportunities for hydrologic restoration. In Delmarva and more broadly, our novel approach can inform targeted landscape‐scale conservation and restoration efforts to optimize hydrologically mediated wetland functions.     

Estimating trends of Atlantic meridional overturning circulation from long-term hydrographic data and model simulations

The ocean meridional overturning circulation (MOC) plays a central role for the climate in the Atlantic realm. Since scenarios for future climate change indicate a significant reduction of the MOC under global warming, an assessment of variations and trends of the real MOC is important. Using observations at ocean weather ship (OWS) stations and along oceanic sections, we examine the hydrographic information that can be used to determine MOC trends via its signature in water mass properties obtained from model simulations with the climate model ECHAM5/MPI-OM. We show that temperature trends at mid-latitudes provide useful indirect measure of large-scale changes of deep circulation: A mid-depth warming is related to MOC weakening and a cooling to MOC strengthening. Based on our model experiments, we argue that a continuation of measurements at key OWS sites may contribute to a timely detection of a possible future MOC slowdown and to separate the signal from interannual-to-multidecadal MOC variability. The simulations suggest that the subsurface hydrographic information related to MOC has a lower variability than the MOC trend measured directly. Based on our model and the available long-term hydrographic data, we estimate non-significant MOC trends for the last 80 years. For the twenty-first century, however, the model simulations predict a significant MOC decline and accompanied mid-depth warming trend.     

Generation of endurance time excitation functions using spectral representation method

In this study, application of the spectral representation method for generation of endurance time excitation functions is introduced. Using this method, the intensifying acceleration time series is generated so that its acceleration response spectrum in any desired time duration is compatible with a time-scaled predefined acceleration response spectrum. For this purpose, simulated stationary acceleration time series is multiplied by the time dependent linear modulation function, then using a sim...     

Estimating temperature and salinity profiles using empirical orthogonal functions and clustering on historical measurements

Oceanographic climatology is normally estimated by dividing the world’s oceans into geographical boxes of fixed shape and size, where each box is represented by a climatological salinity and temperature profile. The climatological profile is typically an average of historical measurements from that region. Since an arbitrarily chosen box may contain different types of water masses both in space and time, an averaged profile may be a statistically improbable or even non-physical representation. This paper proposes a new approach that employs empirical orthogonal functions in combination with a clustering technique to divide the world’s oceans into climatological regions. Each region is represented by a cluster that is determined by minimising the variance of the state variables within each cluster. All profiles contained in a cluster are statistically similar to each other and statistically different from profiles in other clusters. Each cluster is then represented by mean temperature and salinity profiles and a mean position. Methods for estimating climatological profiles from the cluster information are examined, and their performances are compared to a conventional method of estimating climatology. The comparisons show that the new methods outperform conventional methods and are particularly effective in areas where oceanographic fronts are present.     

An objective method for determining principal time scales of coherent eddy structures using orthonormal wavelets

A new, parameter-free method, based on orthonormal wavelet expansions is proposed for calculating the principal time scale of coherent structures in atmospheric surface layer measurements. These organized events play an important role in the exchange of heat, mass, and momentum between the land and the atmosphere. This global technique decomposes the energy contribution at each scale into organized and random eddy motion. The method is demonstrated on vertical wind velocity measurements above bare and vegetated surfaces. It is found to give nearly identical results to a local thresholding approach developed for signal de-noising that assigns the wavelet coefficients to organized and random motion. The effect of applying anti- and/or near-symmetrical wavelet basis functions is also investigated.     

Soil–structure interaction in the time domain using halfspace Green's functions

A time-domain formulation is proposed for the transient response analysis of general, three-dimensional structures resting on a homogeneous, elastic halfspace subjected to either external loads or seismic motions. The formulation consists of two parts: (a) the time domain formulation of the soil behaviour and (b) the coupling of the corresponding soil algorithms to the Finite Element Code ANSYS. As far as the structure is concerned, this coupling opens the way for the analysis of non-linear soil–structure interaction. The approach is based on halfspace Green's functions for displacements elicited by Heaviside time-dependent surface point loads. Hence, the spatial discretisation can be confined to the contact area between the foundation and the soil, i.e. no auxiliary grid beyond the foundation as for conventional boundary element formulations is required. The method is applied to analyse the dynamic response of a railway track due to a moving wheel set by demonstrating the influence of ‘through-the-soil coupling’.     

Brunhes time scales and the interpretation of climatic change

Two new δ¹⁸O time scales have been developed for the Brunhes Epoch using equatorial Pacific core V28-238. The first is based on a constant accumulation rate of aluminum, an assumption which has been shown to be acceptable for the last 360,000 years of the record by comparison with ²³⁰Th ages determined via the continuous strip-sample technique. The aluminum scale yields an age of 138,000 years for termination II and 693,000 years for the Brunhes-Matuyama reversal. Spectral and cross spectral analysis of the δ¹⁸O records of V28-238 and a detailed composite Indian Ocean record, using the aluminum time scale as well as two earlier time scales, indicates that the Pleistocene climate has been forced by periodic fluctuations of the earth's obliquity and precession. Based on this result, the second new time scale (TWEAQ) has been derived by tuning the δ¹⁸O record of V28-238 to the record of the earth's obliquity. TWEAQ yields an age of 127,000 years for termination II and 728,000 years for the Brunhes-Matuyama reversal. Spectral analysis of the δ¹⁸O record dated by TWEAQ indicates that 30% of the variance of the ice volume record can be ascribed to linear forcing by the earth's orbital parameters, but the trend of the data is consistent with a stochastic model.     

Probabilistic eruption forecasting at short and long time scales

Any effective volcanic risk mitigation strategy requires a scientific assessment of the future evolution of a volcanic system and its eruptive behavior. Some consider the onus should be on volcanologists to provide simple but emphatic deterministic forecasts. This traditional way of thinking, however, does not deal with the implications of inherent uncertainties, both aleatoric and epistemic, that are inevitably present in observations, monitoring data, and interpretation of any natural system. In contrast to deterministic predictions, probabilistic eruption forecasting attempts to quantify these inherent uncertainties utilizing all available information to the extent that it can be relied upon and is informative. As with many other natural hazards, probabilistic eruption forecasting is becoming established as the primary scientific basis for planning rational risk mitigation actions: at short-term (hours to weeks or months), it allows decision-makers to prioritize actions in a crisis; and at long-term (years to decades), it is the basic component for land use and emergency planning. Probabilistic eruption forecasting consists of estimating the probability of an eruption event and where it sits in a complex multidimensional time–space–magnitude framework. In this review, we discuss the key developments and features of models that have been used to address the problem.     

Testing bedload transport equations with consideration of time scales

Bedload transport is known to be a highly fluctuating temporal phenomenon, even under constant (mean) flow conditions, as a consequence of stochasticity, bedform migration, grain sorting, hysteresis, or sediment supply limitation. Because bedload transport formulas usually refer to a single mean transport value for a given flow condition, one can expect that prediction accuracy (when compared to measurements) will depend on the amplitude and duration of fluctuations, which in turn depend on the time scale used for observations. This paper aims to identify how the time scale considered can affect bedload prediction. This was done by testing 16 common bedload transport formulas with four data sets corresponding to different measurement period durations: (i) highly fluctuating (quasi‐)instantaneous field measurements; (ii) volumes accumulated at the event scale on two small alpine gravel‐bed rivers, potentially affected by seasonal fluctuations; (iii) volumes accumulated at the interannual scale in a meandering gravel bed river, thought to be weakly subject to fluctuations; (iv) time‐integrated flume measurements with nearly uniform sediments. The tests confirmed that the longer the measurement period, the better the precision of the formula's prediction interval. They also demonstrate several consequential limitations. Most threshold formulas are no longer valid when the flow condition is below two times the threshold condition for the largest elements' motion on the bed surface (considering D₈₄). In such conditions, equations either predict zero transport, or largely overestimate the real transport, especially when D₈₄ is high. There is a need for new sediment data collected with highly reliable techniques such as recording slot bedload samplers to further investigate this topic. Copyright © 2012 John Wiley & Sons, Ltd.     

An improved time series model for monthly stream flows

This study aims to develop an improved time series model to overcome difficulties in modeling monthly short term stream flows. The periodic, serial dependent and independent components of the classical time series models are improved separately by information transfer from a surrounding long term gauging station to the considered flow section having short term records. Eventually, an improved model preserving the mathematical model structure of the classical time series model, while improving general and monthly statistics of the monthly stream flows, is derived by using the improved components instead of the short term model components in the time series modeling. The correlative relationships between the current short term and surrounding long term stations are used to improve periodic and serial dependent behaviors of monthly flows. Independent components (residuals) are improved via the parameters defining their theoretical probability distribution. The improved model approach is tested by using 50 year records of Göksu-Himmetli (1801) and Göksu-Gökdere (1805) flow monitoring stations located on the Ceyhan river basin, in south of Turkey. After 50 year records of the station 1801 are separated into five 10 year sub series, their improved and classical time series models are computed and compared with the real long-term (50 year) time series model of this station to reveal efficiencies of the improved models for each subseries (sub terms with 10 year observation). The comparisons are realized based on the model components, model estimates and general/monthly statistics of model estimates. Finally, some evaluations are made on the results compared to the regression method classically applied in the literature.     

Changes in transfer functions with time

The paper contains data on the transfer functions of the electromagnetic field of the Earth and their changes with time.The results show that these changes are caused by the instability of parameters of the external sources of the geomagnetic field variations in high latitudes and by the changes in the physical properties of rocks and deep matter in the region of recordings of electromagnetic field components.A statement is made that under certain conditions the observations of changes in transfer functions of the electromagnetic field of the Earth can be used as long-term forerunners of earthquakes.     

Exchange and transport time scales in the Seto Inland Sea

Five typical water volumes in the Seto Inland Sea are defined, and their average residence times, remnant functions, and residence time distribution functions are obtained, mainly from results of hydraulic model experiments; the average residence times and the functions well describe characteristics of exchange and transport of materials in the sea. A representative residence time, which is the average residence time of the total water in the inland sea, is about 15 months.     

Separation of time scales in the HCA model for sand

Separation of time scales is used in a high cycle accumulation (HCA) model for sand. An important difficulty of the model is the limited applicability of the Miner’s rule to multiaxial cyclic loadings applied simultaneously or in a combination with monotonic loading. Another problem is the lack of simplified objective HCA formulas for geotechnical settlement problems. Possible solutions of these problems are discussed.     

Estimating ground motions using recorded accelerograms

A procedure for estimating ground motions using recorded accelerograms is described. The premise of the study is the assumption that future ground motions will be similar to those observed for similar site and tectonic situations in the past. Direct techniques for scaling existing accelerograms have been developed, based on relative estimates of local magnitude,M _L . Design events are described deterministically in terms of fault dimension, tectonic setting (stress drop), fault distance, and site conditions. A combination of empirical and theoretical arguments is used to develop relationships betweenM _L and other earthquake magnitude scales. In order to minimize scaling errors due to lack of understanding of the physics of strong ground motion, the procedure employs as few intermediate scaling laws as possible. The procedure conserves a meaningful measure of the uncertainty inherent when predicting ground motions from simple parameterizations of earthquake sources and site conditions.     

利用互相关函数求地震波衰减

与传统利用单事件波形求介质衰减的方法不同,我们提出一种以一系列事件为源,以源与远处记录波形的互相关函数为基础计算介质品质因子的方法.依据野外现场实验的数据,我们分别以单次和多次激发为源,讨论了事件波形和互相关函数波形的振幅变化及相应的介质品质因子,结果发现,与事件波形一样,互相关函数波形也可以用于计算介质的衰减系数.计算结果表明：（1）实验场地浅层介质在原场条件下的品质因子Q值在40左右;（2）互相关函数的最大幅度与事件波形的振幅随距离具有相同的衰减规律.     

Relative scales of time and effectiveness of climate in watershed geomorphology

Peak rainfalls and peak runoff rates per unit area are comparable over a worldwide spectrum of climates. However, while the magnitude of the external contribution of energy or force in diverse regions is similar, the impact on the landscape varies markedly between regions. Absolute magnitudes of climatic events and absolute time intervals between such events do not provide satisfactory measures of the geomorphic effectiveness of events of different magnitudes and recurrence intervals. Although geomorphic processes are driven by complex sets of interrelated climatic, topographic, lithologic, and biologic factors, the work done by individual extreme events can be scaled as a ratio to mean annual erosion and the effectiveness of such events in forming landscape features can be related to the rate of recovery of channel form or mass wasting scars following alteration by the extreme event. Thus, a time scale for effectiveness may relate the recurrence interval of an event to the time required for a landform to recover the form existing prior to the event. River channels in temperate regions widened by floods of recurrence intervals from 50 to more than 200 years may regain their original width in matters of months or years. In semi-arid regions, recovery of channel form depends not only upon flows but upon climatic determinants of the growth of bottomland vegetation resulting in variable rates of recovery, on the order of decades, depending upon coincidence of average flows and strengthened vegetation. In truly arid regions the absence of vegetation and flow precludes recovery and the width of channels increases in drainage areas up to 100 km² but remains relatively constant at larger drainage areas. Area as well as time controls the effectiveness of specific events inasmuch as the likelihood of simultaneous peak discharges or rainfalls and large areas is less, particularly in arid regions where events spanning areas of more than several thousand km² are extremely rare if experienced at all. To some extent a decrease in area in a humid region is comparable with a regional change from humid toward more arid climate reflected in the increase in importance of episodic as contrasted with more continuous processes. Exceedingly rare floods of extreme magnitudes, estimated recurrence intervals of 500 years or longer, may exceed thresholds of competence otherwise unattainable in the ‘normal’ record resulting in ‘irreparable’ transformations of valley landforms. Denudation of hillslopes by mass wasting during relatively rare events can also be related to mean rates of denudation and to recovery of hillslope surfaces after scarring by different kinds of landslides. Measured recovery times described in the literature vary from less than a decade for some tropical regions to decades or more in temperate regions. Recurrence intervals of high magnitude storms which trigger mass wasting range from 1 to 2 years in some tropical areas, to 3 or 4 per hundred years in some areas of seasonal rainfall and to 100 or more years in some temperate regions. The effectiveness of climatic events on both hillslopes and rivers is not separable from gradient, lithology or other variables which control both thresholds of activity and recovery rate.     

Hydrological response of a humid agroforestry catchment at different time scales

Using data collected at the Mero catchment during three hydrological years (2005/06–2007/08), an analysis of rainfall–runoff relationships was performed at annual, seasonal, monthly, and event scales. At annual scale, the catchment showed low runoff coefficients (23–35%), due to high water storage capacity soils as well as high runoff inter‐annual variability. Rainfall variability was the main responsible for the differences in the inter‐annual runoff. At seasonal and monthly scales, there was no simple relationship between rainfall and runoff. Seasonal dynamics of rainfall and potential evapotranspiration in conjunction with different rainfall distribution during the study years could be the key factors explaining the complex relationship between rainfall and runoff at monthly and seasonal scale. At the event scale, the results revealed that the hydrological response was highly dependent on initial conditions and, to a lesser extent, on rainfall amount. The shapes of the different hydrographs, regardless of the magnitude, presented similar characteristics: a moderate rise and a prolonged recession, suggesting that subsurface flow was the dominant process in direct runoff. Moreover, all rainfall–runoff events had a higher proportion of baseflow than of direct runoff. A cluster‐type analysis discriminated three types of events differentiated mainly by rainfall amount and antecedent rainfall conditions. The study highlights the role of the antecedent rainfall and the need for caution in extrapolating relationships between rainfall amount and hydrological response of the catchment. Copyright © 2013 John Wiley & Sons, Ltd.     

Estimating reference evapotranspiration using numerical weather modelling

Evapotranspiration is an important hydrological process and its estimation usually needs measurements of many weather variables such as atmospheric pressure, wind speed, air temperature, net radiation and relative humidity. Those weather variables are not easily obtainable from in situ measurements in practical water resources projects. This study explored a potential application of downscaled global reanalysis weather data using mesoscale modelling system 5 (MM5). The MM5 is able to downscale the global data down to much finer resolutions in space and time for use in hydrological investigations. In this study, the ERA‐40 reanalysis data are downscaled to the Brue catchment in southwest England. The results are compared with the observation data. Among the studied weather variables, atmospheric pressure could be derived very accurately with less than 0·2% error. On the other hand, the error in wind speed is about 200–400%. The errors in other weather variables are air temperature (<10%), relative humidity (5–21%) and net radiation (4–23%). The downscaling process generally improves the data quality (except wind speed) and provides higher data resolution in comparison with the original reanalysis data. The evapotranspiration values estimated from the downscaled data are significantly overestimated across all the seasons (27–46%) based on the FAO Penman–Monteith equation. The dominant weather variables are net radiation (during the warm period) and relative humidity (during the cold period). There are clear patterns among some weather variables and they could be used to correct the biases in the downscaled data from either short‐term in situ measurements or through regionalization from surrounding weather stations. Artificial intelligence tools could be used to map the downscaled data directly into evapotranspiration or even river runoff if rainfall data are available. This study provides hydrologists with valuable information on downscaled weather variables and further exploration of this potentially valuable data source by the hydrological community should be encouraged. Copyright © 2010 John Wiley & Sons, Ltd.