Effects of hillslope dynamics and network geometry on the scaling properties of the hydrologic response

This paper investigates the specific contributions of river network geomorphology, hillslope flow dynamics and channel routing to the scaling behavior of the hydrologic response as function of drainage area. Scaling relationships emerged from the observations of geomorphological and hydrological data and were reproduced in previous works through mathematical models, for both idealized self-similar networks and natural basins. Recent literature highlighted that scale invariance of hydrological quantities depends not only on the metrics of the drainage catchment but also on effective flow routing. In this study we employ a geomorphological width function scheme to test the simple scaling hypothesis adopting more realistic dynamic conditions than in previous approaches, specifically taking into account the role of hillslopes. The analysis is based on the derivation of the characteristic distributions of path lengths and travel times, inferred from DEM processing and measurements of rainfall and runoff data. The study area is located in the Tiber River region (central Italy).Results indicate that, while scaling properties clearly emerge when the hydrologic response is defined on the basis of the sole geomorphology, scale invariance is broken when less idealized flow dynamics are taken into account. Lack of scaling appears in particular as a consequence of the catchment to catchment variability of hillslope velocities.     

River flow mass exponents with fractal channel networks and rainfall

An important problem in hydrologic science is understanding how river flow is influenced by rainfall properties and drainage basin characteristics. In this paper we consider one approach, the use of mass exponents, in examining the relation of river flow to rainfall and the channel network, which provides the primary conduit for transport of water to the outlet in a large basin. Mass exponents, which characterize the power-law behavior of moments as a function of scale, are ideally suited for defining scaling behavior of processes that exhibit a high degree of variability or intermittency. The main result in this paper is an expression relating the mass exponent of flow resulting from an instantaneous burst of rainfall to the mass exponents of spatial rainfall and that of the network width function. Spatial rainfall is modeled as a random multiplicative cascade and the channel network as a recursive replacement tree; these fractal models reproduce certain types of self-similar behavior seen in actual rainfall and networks. It is shown that under these modeling assumptions the scaling behavior of flow mirrors that of rainfall if rainfall is highly variable in space, and on the other hand flow mirrors the structure of the network if rainfall is not so highly variable.     

Dissecting the effect of rainfall variability on the statistical structure of peak flows

This study examines the role of rainfall variability on the spatial scaling structure of peak flows using the Whitewater River basin in Kansas as an illustration. Specifically, we investigate the effect of rainfall on the scatter, the scale break and the power law (peak flows vs. upstream areas) regression exponent. We illustrate why considering individual hydrographs at the outlet of a basin can lead to misleading interpretations of the effects of rainfall variability. We begin with the simple scenario of a basin receiving spatially uniform rainfall of varying intensities and durations and subsequently investigate the role of storm advection velocity, storm variability characterized by variance, spatial correlation and intermittency. Finally, we use a realistic space–time rainfall field obtained from a popular rainfall model that combines the aforementioned features. For each of these scenarios, we employ a recent formulation of flow velocity for a network of channels, assume idealized conditions of runoff generation and flow dynamics and calculate peak flow scaling exponents, which are then compared to the scaling exponent of the width function maxima. Our results show that the peak flow scaling exponent is always larger than the width function scaling exponent. The simulation scenarios are used to identify the smaller scale basins, whose response is dominated by the rainfall variability and the larger scale basins, which are driven by rainfall volume, river network aggregation and flow dynamics. The rainfall variability has a greater impact on peak flows at smaller scales. The effect of rainfall variability is reduced for larger scale basins as the river network aggregates and smoothes out the storm variability. The results obtained from simple scenarios are used to make rigorous interpretations of the peak flow scaling structure that is obtained from rainfall generated with the space–time rainfall model and realistic rainfall fields derived from NEXRAD radar data.     

Temporal analysis of the frequency and duration of low and high streamflow: years of record needed to characterize streamflow variability

A temporal analysis of the number and duration of exceedences of high- and low-flow thresholds was conducted to determine the number of years required to detect a level shift using data from Virginia, North Carolina, and South Carolina. Two methods were used—ordinary least squares assuming a known error variance and generalized least squares without a known error variance. Using ordinary least squares, the mean number of years required to detect a one standard deviation level shift in measures of low-flow variability was 57.2 (28.6 on either side of the break), compared to 40.0 years for measures of high-flow variability. These means become 57.6 and 41.6 when generalized least squares is used. No significant relations between years and elevation or drainage area were detected (P>0.05). Cluster analysis did not suggest geographic patterns in years related to physiography or major hydrologic regions. Referring to the number of observations required to detect a one standard deviation shift as ‘characterizing’ the variability, it appears that at least 20 years of record on either side of a shift may be necessary to adequately characterize high-flow variability. A longer streamflow record (about 30 years on either side) may be required to characterize low-flow variability.     

Selection of ground motion time series and limits on scaling

A procedure to select time series for use in non-linear analyses that are intended to result in an average response of the non-linear system is proposed that is not based simply on magnitude, distance, and spectral shape. A simple model of a yielding system is used as a proxy for the non-linear behavior of a more complicated yielding system. As an example, Newmark displacements are used as a proxy for more complex slope-stability models. The candidate scaled time series are evaluated to find those that yield a response of the simple non-linear system that is near the expected response for the design event. Those scaled time series with responses near the expected value are selected as the optimum time series for defining average response even if the scale factors are larger than commonly accepted (e.g. scale factors >factor of 2).     

Regularity of sediment transport and sedimentation during floods in the lower Yellow River,China

The flood season is the main period of flow,sediment transport,and sedimentation in the lower Yellow River(LYR).Within the flood season,most of the flow,sediment transport,and sedimentation occurs during flood events.Because of the importance of floods in forming riverbeds in the LYR,the regularity of sediment transport and sedimentation during floods in the LYR was studied.Measured daily discharge and sediment transport rate data for the LYR from 1960 to 2006 were used.A total of 299 floods wer...     

The effects of soil piping on contributing areas and erosion patterns

Natural piping doubles the dynamic contributing area on the upper Maesnant stream in mid-Wales, mainly through linking points well beyond the riparian zones of seepage to the stream. Both discharge and sediment transport rates in the major pipes are closely related to the size of shallow surface microtopographic hollows in which they lie, and which themselves are largely created by piping erosion. However, pipe dischrges are frequently generated by contributing areas larger than these surface depressions and some pipes run counter to the surface topography. The redistribution and acceleration of hillslope drainage processes by piping has implications for theories of hillslope development, especially through plan-form modifications, and also for channel discharge and erosion.     

1999年11月29日岫岩5.4级地震序列震源参数测定及标度关系分析

根据Andrews谱积分的方法, 采用近震源Brune圆盘模型, 测定了1999年11月29日辽宁岫岩M_S5.4地震序列的震源参数。 结果表明, 得到辐射能量与震级的关系, 与古登堡-里克特给出的关系基本一致; 地震矩与震级的关系中斜率和截距都小于陈培善等给出的全球结果; 视应力与震级呈半对数线性关系; 在双对数坐标下视应力随地震矩的增加而增加; 地震矩随拐角频率的7次方衰减, 在地震序列的不同阶段各参数的拟合关系斜率也不完全相同。     

Effects of extreme climate events on the macrobenthic communities' structure and functioning of a temperate estuary

The Mondego estuary (Portugal) experienced profound structural and functional modifications due to eutrophication, which was exacerbated by consecutive weather extremes that compromised a previous restoration project. This work explores multiple climate impacts on macrobenthic communities’ structure and functioning and its implications on ecosystem’s recovery. Floods and heat waves had a stronger negative effect on macrobenthic assemblages than the droughts, imposing a total abundance decline. Contrarily, biomass was not so affected by climate events, being stable and even increased in a mudflat area, where seagrass is re-colonizing. Bivalves and oligochaetes decreased with the flooding episodes, likewise subsurface-deposit feeders and suspension feeders, while crustaceans were particularly sensitive to heat waves. Species richness declined with the floods and heat waves, whilst evenness increased in sandflat area, constituting a positive sign towards recovery. Succession of different climate extremes affected ecosystem structure and functioning, delaying its recovery with possible consequent effects at higher trophic levels.     

A preliminary investigation on the scaling behaviour of rainfall observed in two different climates

Abstract

The problem of transformation of rainfall data from one scale to another has been gaining considerable importance in recent years. Though the application of the concept of fractal theory, in the studies conducted thus far, nearly unanimously points at the possibility of such a transformation, the suitability of the theory to the highly variable rainfall in time and space has very often been questioned. A preliminary attempt is made herein to address this issue by investigating the existence of temporal scaling behaviour in rainfall data observed in two different climatic regions: (a) a subtropical climatic region (Leaf River basin, Mississippi, USA) and (b) an equatorial climatic region (Singapore). Rainfall data of three different resolutions, six-hourly, daily, and weekly, observed over a period of 25 years, are investigated. A mono- or simple-scaling method (box dimension method) is employed. The results achieved for the different data sets clearly indicate the existence of temporal scaling in rainfall observed in the two regions, an encouraging news on the suitability of fractal theory in understanding and modelling the rainfall process. However, the insufficiency of a single dimension to characterize the rainfall behaviour is realized, as the dimension depends on the rainfall intensity level, which, in turn, may be related to the rainfall generating mechanisms. A comparison of the box-dimension results obtained for data of different resolutions, from each of the regions, seems to indicate a possible connection between them, a prospect of tremendous practical importance. Another interesting observation is the similarity between the box dimension results obtained for rainfall data from Leaf River basin and Singapore, but this is also clearly related to the intensity level. The dependence of the dimension on the intensity threshold suggests the use of a multi-dimensional fractal approach, where the process is characterized by more than one dimension (or a dimension function) instead of one single dimension. On the basis of the present results, some potential areas for further study are identified.     

Planform dynamics of the Iquitos anabranching structure in the Peruvian Upper Amazon River

The upper reach of the Amazon River has a very dynamic morphology, with the highest rates of migration observed in the entire Amazon River. It has an anabranching channel pattern which alternates between a condition of single channel and anabranching structures; in particular, the anabranching structure near Iquitos City shows an interesting channel behavior. Its channels migrate at different rates, where there are processes of narrowing and widening, and also collision and development of new channels. The temporal evolution of the Iquitos anabranching structure is described during the period from 1985 to 2014. The study is carried out by using satellite images to track the migration patterns, which are contrasted to the underlying geological units in the valley. Bathymetry of the structure and several velocity transects were obtained during a field campaign prior to the 2012 historic flood event. This information allowed for numerical modeling in order to compute the hydrodynamic flow field that complements the temporal analysis, aiming to understand the planform migration patterns after the 2012 flood event. It is observed that the geological units play an important role in modulating the migration rates and planform development of the channels. The channels in the structure are in contention to be the main channel, which become the secondary channel after migration. This causes the channels to experience a rise in bed elevation and narrowing of the channel itself; if this trend continues for several more years, these channels will detach from the Iquitos anabranching structure, thus forming paleo‐channels. This geomorphic process is important for horizontal and vertical soil heterogeneity along the floodplain. In general, the analysis shows a complex interaction between the underlying geological units, flow structure, morphology of the bed and planform migration. Copyright © 2016 John Wiley & Sons, Ltd.     

Exploring effects of rainfall intensity and duration on soil erosion at the catchment scale using openLISEM: Prado catchment,SE Spain

In semi‐arid areas, high‐intensity rainfall events are often held responsible for the main part of soil erosion. Long‐term landscape evolution models usually use average annual rainfall as input, making the evaluation of single events impossible. Event‐based soil erosion models are better suited for this purpose but cannot be used to simulate longer timescales and are usually applied to plots or small catchments. In this study, the openLISEM event‐based erosion model was applied to the medium‐sized (～50 km²) Prado catchment in SE Spain. Our aim was to (i) test the model's performance for medium‐sized catchments, (ii) test the ability to simulate four selected typical Mediterranean rainfall events of different magnitude and (iii) explore the relative contribution of these different storms to soil erosion using scenarios of future climate variability. Results show that because of large differences in the hydrologic response between storms of different magnitudes, each event needed to be calibrated separately. The relation between rainfall event characteristics and the calibration factors might help in determining optimal calibration values if event characteristics are known. Calibration of the model features some drawbacks for large catchments due to spatial variability in K_sat values. Scenario calculations show that although ～50% of soil erosion occurs as a result of high frequency, low‐intensity rainfall events, large‐magnitude, low‐frequency events potentially contribute significantly to total soil erosion. The results illustrate the need to incorporate temporal variability in rainfall magnitude–frequency distributions in landscape evolution models. Copyright © 2011 John Wiley & Sons, Ltd.     

The subdivision of a slope profile on the basis of soil properties: A case study from mid-wales

Sedimentological analysis of particle size data from a hillslope profile in mid-Wales allows the identification of two distinct upper slope units. These are described and analyzed in greater detail for clay and organic matter distribution. The original slope subdivision is substantiated by the results and the major differences in soils between the upper units are attributed to drainage contrasts.     

New estimates of future changes in extreme rainfall across the UK using regional climate model integrations. 2. Future estimates and use in impact studies

Under enhanced greenhouse conditions, climate models suggest an increase in rainfall intensities in the northern Hemisphere. Major flood events in the UK during autumn 2000 and central Europe in August 2002, have focussed attention on the dramatic impacts these changes may have on many sectors of society. In the companion paper [Fowler et al., J. Hydrol. (2004) this issue], we suggested that the HadRM3H model may be used with some confidence to estimate extreme rainfall distributions, showing good predictive skill in estimating statistical properties of extreme rainfall during the baseline period, 1961–1990. In this study, we use results from the future integration of HadRM3H (following the IPCC SRES scenario A2 for 2070–2100) to assess possible changes in extreme rainfall across the UK using two methods: regional frequency analysis and individual grid box analysis. Results indicate that for short duration events (1–2 days), event magnitude at a given return period will increase by 10% across the UK. For longer duration events (5–10 days), event magnitudes at given return periods show large increases in Scotland (up to +30%), with greater relative change at higher return periods (25–50 years). In the rest of the UK, there are small increases in the magnitude of more frequent events (up to +10%) but reductions at higher return periods (up to −20%). These results provide information to alter design storm depths to examine climate change impacts on various structures. The uncertainty bounds of the estimated changes and a ‘scaling’ methodology are additionally detailed. This allows the estimation of changes for the 2020s, 2050s and 2080s, and gives some confidence in the use of these estimates in impact studies.     

降雨对土层标与基岩标影响的差异性分析

通过对南京地震台短水准测量中的基岩标志和土层标石的抗干扰分析,发现:温度、气压的影响可以通过改变观测时间段来尽量减小,使其对两类观测点观测资料没有明显影响;降雨量大小对基岩点的影响很弱,对土石点影响较大,则没办法消除.表明,在选择好的观测场地的同时,也要根据观测资料的需要埋设合理的测点标志类型.     

Effect of zero measurements on the spatial correlation structure of rainfall

In this study, the effect of zero measurements on the spatial correlation function of rainfall is analyzed for the quantification of a rainfall field. The use of a bivariate mixed distribution function made it possible to analyze and compare the spatial correlation functions for these three different data sets: only the positive measurements at both gauge locations, positive measurements at either one or both gauge locations, and all measurements including zero at both locations. As an example, the spatial correlation functions are derived for the Geum River Basin, Korea and evaluated for the wet and dry seasons, respectively. Results show that the effect of zero measurements on spatial correlation structures is significant during the wet season, when the inter-station correlations were estimated significantly lower than those during the dry season. It was also found that only the case considering positive measurements are valid for the quantification of rainfall field. Even during the wet season, the inter-station correlation coefficients derived by considering the zero measurements show their high variability along with many abnormally looking high estimates, which made the quantification of the spatial correlation function become very ambiguous.     

Effect of extreme rainfall events on the water resources of the Jordan River

As a response to climate change, shifting rainfall trends including increased multi-year droughts and an escalation in extreme rainfall events are expected in the Middle East. The purpose of this study is to evaluate the potential impact of these shifting trends on stream flow in the Jordan River and its tributaries. We use a non-homogeneous hidden Markov model to generate artificial daily rainfall simulations which capture independently shifting trends of increased droughts and escalated extreme. These simulations are then used as input into a hydrological model calibrated for the upper catchments of the Jordan River to compare the impact on stream flow and water resources between the different rainfall scenarios. We compare the predicted baseflow and surface flow components of the tested watersheds, and find that while an increase in extreme rainfall events increases the intensity and frequency of surface flow, the over all flow to the Jordan River, and the characteristics of the baseflow in the Jordan River system is not largely impacted. In addition, though it has been suggested that in the case of a multi-year drought the karstic nature of the aquifer might lead to more intense, non-linear reductions in stream flow, here we quantify and show the conditions when annual stream flow reduce linearly with rainfall, and when these relations will become non-linear.     

Performance of an artificial neural network on forecasting the daily occurrence and annual depth of rainfall at a tropical site

Performance of a feed‐forward back‐propagation artificial neural network on forecasting the daily occurrence and annual depth of rainfall at a single meteorological station is presented. Both short‐term and long‐term forecasting was attempted, with ground level data collected by the meteorological station in Colombo, Sri Lanka (79° 52′E, 6° 54′N) during two time periods, 1994–2003 and 1869–2003. Two neural network models were developed; a one‐day‐ahead model for predicting the rainfall occurrence of the next day, which was able to make predictions with a 74·3% accuracy, and one‐year‐ahead model for yearly rainfall depth predictions with an 80·0% accuracy within a ± 5% error bound. Each of these models was extended to make predictions several time steps into the future, where accuracies were found to decrease rapidly with the number of time steps. The success rates and rainfall variability within the north‐east and south‐west monsoon seasons are also discussed. Copyright © 2007 John Wiley & Sons, Ltd.