Does variable channel morphology lead to dynamic salmon habitat?

Stream channel morphology forms the template upon which hydraulic aspects of aquatic habitat are created, yet spatial and temporal variability in habitat imposed by changing morphology is not well understood. This paper presents a conceptual model linking sediment supply patterns to spatial and temporal variability in channel form and aquatic habitat. To evaluate this model, change over time in three habitat variables is quantified using a 2D hydrodynamic modeling approach. A 45-year record of topographic data from Carnation Creek, a catchment in coastal British Columbia, is used for the flow modeling. Using the Nays2DH modeling platform, water depths and velocities are simulated in eight channel segments located at different positions relative to locations of historical colluvial input using seven flow levels ranging from 3% to 400% of mean annual discharge (0.02 to 3.31 m s ). Results indicate that habitat availability changes through time as a result of sediment supply-driven changes to channel morphology and wood loads, but patterns in habitat vary as a function of dominant channel segment morphology. Spatial and temporal variability in morphology also influences the relationship between habitat availability and river discharge, leading to non-stationary habitat-discharge rating curves. When habitat areas are predicted by applying these curves to daily flow series spanning annual dry seasons, over 50% of the variance in cumulative seasonal habitat area can be explained by year-to-year changes in channel morphology and wood loading, indicating that changing morphology is an important factor for driving temporal habitat variability. This variance is related to the morphological variability of a channel segment, which in turn is associated with the segment position relative to zones of colluvial input. Collectively, these results suggest that variability in habitat is impacted by channel morphology, and can be evaluated partly on the basis of a channel's sediment supply regime. © 2019 John Wiley & Sons, Ltd.     

Modelling-based assessment of suspended sediment dynamics in a hypertidal estuarine channel

We investigate the dynamics of suspended sediment transport in a hypertidal estuarine channel which displays a vertically sheared exchange flow. We apply a three-dimensional process-based model coupling hydrodynamics, turbulence and sediment transport to the Dee Estuary, in the north-west region of the UK. The numerical model is used to reproduce observations of suspended sediment and to assess physical processes responsible for the observed suspended sediment concentration patterns. The study period focuses on a calm period during which wave-current interactions can reasonably be neglected. Good agreement between model and observations has been obtained. A series of numerical experiments aim to isolate specific processes and confirm that the suspended sediment dynamics result primarily from advection of a longitudinal gradient in concentration during our study period, combined with resuspension and vertical exchange processes. Horizontal advection of sediment presents a strong semi-diurnal variability, while vertical exchange processes (including time-varying settling as a proxy for flocculation) exhibit a quarter-diurnal variability. Sediment input from the river is found to have very little importance, and spatial gradients in suspended concentration are generated by spatial heterogeneity in bed sediment characteristics and spatial variations in turbulence and bed shear stress.     

Development of spatial regression models for predicting summer river temperatures from landscape characteristics: Implications for land and fisheries management

There is increasing demand for models that can accurately predict river temperature at the large spatial scales appropriate to river management. This paper combined summer water temperature data from a strategically designed, quality controlled network of 25 sites, with recently developed flexible spatial regression models, to understand and predict river temperature across a 3,000 km² river catchment. Minimum, mean and maximum temperatures were modelled as a function of nine potential landscape covariates that represented proxies for heat and water exchange processes. Generalised additive models were used to allow for flexible responses. Spatial structure in the river network data (local spatial variation) was accounted for by including river network smoothers. Minimum and mean temperatures decreased with increasing elevation, riparian woodland and channel gradient. Maximum temperatures increased with channel width. There was greater between‐river and between‐reach variability in all temperature metrics in lower‐order rivers indicating that increased monitoring effort should be focussed at these smaller scales. The combination of strategic network design and recently developed spatial statistical approaches employed in this study have not been used in previous studies of river temperature. The resulting catchment scale temperature models provide a valuable quantitative tool for understanding and predicting river temperature variability at the catchment scales relevant to land use planning and fisheries management and provide a template for future studies.     

Spatial Variability of Nitrate and Ammonium in Pleistocene Aquifer of Central Yangtze River Basin

It becomes increasingly important and challenging for nitrogen pollution prevention to identify key controls for spatial variability of nitrogen in groundwater that could be affected by multiple factors, including anthropogenic input, groundwater flow, and local geochemistry. This study characterized spatial variability of both nitrate and ammonium in the Pleistocene aquifer of central Yangtze River Basin and assessed the effect of various factors in controlling nitrate and ammonium levels based on multiple statistical approaches (correlation, geostatistics, multiple liner regression). The results indicate that nitrate is mostly influenced by Cl⁻ that represents anthropogenic input, while Eh representing local redox state is a secondary variable influencing nitrate concentrations. The groundwater with elevated nitrate concentrations are estimated to occur mainly in areas with higher-permeability near-surface sediments which can facilitate more anthropogenic nitrate transport and less nitrate removal owing to more oxidized state. Ammonium is mostly correlated to Eh, followed by dissolved organic carbon (DOC), but only DOC improves significantly the accuracy of co-kriging prediction model. The groundwater with elevated ammonium concentrations are estimated to occur mainly in areas with more organic-rich sediments within or around the aquifer which can facilitate more ammonium release owing to natural organic matter consumption accompanying strong reducing conditions. The regional groundwater flow is not a factor significantly controlling nitrate or ammonium levels owing to flat topography and sluggish lateral flow.     

Characterization of the spatial variability of channel morphology

The spatial variability of two fundamental morphological variables is investigated for rivers having a wide range of discharge (five orders of magnitude). The variables, water‐surface width and average depth, were measured at 58 to 888 equally spaced cross‐sections in channel links (river reaches between major tributaries). These measurements provide data to characterize the two‐dimensional structure of a channel link which is the fundamental unit of a channel network. The morphological variables have nearly log‐normal probability distributions. A general relation was determined which relates the means of the log‐transformed variables to the logarithm of discharge similar to previously published downstream hydraulic geometry relations. The spatial variability of the variables is described by two properties: (1) the coefficient of variation which was nearly constant (0·13–0·42) over a wide range of discharge; and (2) the integral length scale in the downstream direction which was approximately equal to one to two mean channel widths. The joint probability distribution of the morphological variables in the downstream direction was modelled as a first‐order, bivariate autoregressive process. This model accounted for up to 76 per cent of the total variance. The two‐dimensional morphological variables can be scaled such that the channel width–depth process is independent of discharge. The scaling properties will be valuable to modellers of both basin and channel dynamics. Published in 2002 John Wiley & Sons, Ltd.     

Spatial variability in streambed hydraulic conductivity of contrasting stream morphologies: channel bend and straight channel

Streambed hydraulic conductivity is one of the main factors controlling variability in surface water‐groundwater interactions, but only few studies aim at quantifying its spatial and temporal variability in different stream morphologies. Streambed horizontal hydraulic conductivities (K_h) were therefore determined from in‐stream slug tests, vertical hydraulic conductivities (K_v) were calculated with in‐stream permeameter tests and hydraulic heads were measured to obtain vertical head gradients at eight transects, each comprising five test locations, in a groundwater‐dominated stream. Seasonal small‐scale measurements were taken in December 2011 and August 2012, both in a straight stream channel with homogeneous elevation and downstream of a channel meander with heterogeneous elevation. All streambed attributes showed large spatial variability. K_h values were the highest at the depositional inner bend of the stream, whereas high K_v values were observed at the erosional outer bend and near the middle of the channel. Calculated K_v values were related to the thickness of the organic streambed sediment layer and also showed higher temporal variability than K_h because of sedimentation and scouring processes affecting the upper layers of the streambed. Test locations at the channel bend showed a more heterogeneous distribution of streambed properties than test locations in the straight channel, whereas within the channel bend, higher spatial variability in streambed attributes was observed across the stream than along the stream channel. Copyright © 2014 John Wiley & Sons, Ltd.     

Monitoring spatial variability of forest interception

Field instrumentation was designed and installed to quantify the influence of forest interception on the spatial and temporal distribution of water flux onto and into the forest soil at the plot scale. An application is presented which demonstrates that the instrumentation has the required resolution to monitor the spatial variability and dynamics of the flux processes. The observations show that spatial variability of interception may play an important role, not only in small scale soil moisture heterogeneity, but also in the hydrological response of a forested catchment at the hillslope scale. They also highlight the need of gathering more field information on the effects of vegetation on the spatial variability of soil surface water input.     

Spatial and temporal variability of pore‐water pressures in residual soil slopes in a tropical climate

It is critical to understand and quantify the temporal and spatial variability in hillslope hydrological data in order to advance hillslope hydrological studies, evaluate distributed parameter hydrological models, analyse variability in hydrological response of slopes and design efficient field data sampling networks. The spatial and temporal variability of field‐measured pore‐water pressures in three residual soil slopes in Singapore was investigated using geostatistical methods. Parameters of the semivariograms, namely the range, sill and nugget effect, revealed interesting insights into the spatial structure of the temporal situation of pore‐water pressures in the slopes. While informative, mean estimates have been shown to be inadequate for modelling purposes, indicator semivariograms together with mean prediction by kriging provide a better form of model input. Results also indicate that significant temporal and spatial variability in pore‐water pressures exists in the slope profile and thereby induces variability in hydrological response of the slope. Spatial and temporal variability in pore‐water pressure decreases with increasing soil depth. The variability decreases during wet conditions as the slope approaches near saturation and the variability increases with high matric suction development following rainfall periods. Variability in pore‐water pressures is greatest at shallow depths and near the slope crest and is strongly influenced by the combined action of microclimate, vegetation and soil properties. Copyright © 2002 John Wiley & Sons, Ltd.     

Evaluating river morphology change with a geomorphic form variation approach

Geomorphic river design strives for natural resilience by encouraging geomorphic form complexity and morphological processes linked to greater habitat diversity. Increasing availability of high-resolution topographic data and spatial feature mapping methods provide advantages for morphological analysis and river restoration planning. We propose and evaluate an approach to quantifying topographic variability of geomorphic form and pixel-level surface roughness resulting from channel planform geometry differences using spatially continuous variety computation applied to component metrics including flow direction, aspect and planform curvature. We define this as the geomorphic form variation (GFV) approach and found it scalable, repeatable and a multi-stage analytical metric for quantifying physical aspects of river-bed topographic variability. GFV may complement process-based morphological feature mapping applications, hydraulic assessment indices and spatial habitat heterogeneity metrics commonly used for ecological quality evaluation and river restoration. The GFV was tested on controlled synthetic channels derived from River Builder software and quasi-controlled sinuous planform flume experiment channels. Component variety metrics respond independently to specific geometric surface changes and are sensitive to multi-scaled morphology change, including coarser-grained sediment distributions of pixel-level surface roughness. GFV showed systematic patterns of change related to the effects of channel geometry, vertical bed feature (pool-bar) frequency and amplitude, and bar size, shape and orientation. Hotspot analysis found that bar margins were major components of topographic complexity, whereas grain-scale variety class maps further supported the multi-stage analytical capability and scalability of the GFV approach. The GFV can provide an overall variety value that may support river restoration decision-making and planning, particularly when geomorphic complexity enhancement is a design objective. Analysing metric variety values with statistically significant hotspot cluster maps and complementary process-based software and mapping applications allows variety correspondence to systematic feature changes to be assessed, providing an analytical approach for river morphology change comparison, channel design and geomorphic process restoration.     

Spatio‐temporal patterns of channel changes in response to a major flood event: the case of the Magra River (central–northern Italy)

On October 25^th 2011, the Magra River (central–northern Italy) was affected by a significant flood event with an estimated return interval ranging from 30 to 200 years. This study investigates the morphological responses of the Magra River to this major flood event with the aims of (i) documenting the channel changes which occurred in response to the flood; (ii) analysing this response within the context of the historical trend of width changes; (iii) investigating the possible factors controlling the spatial pattern and the intensity of the observed changes. Significant channel widening was documented along the entire length studied (about 34 km), ranging from 3% to 90% of the pre‐flood channel width. Braided reaches were characterized by the most severe planimetric changes. Although characterized by high rates of change, these variations are, however, amply included in the historical range of channel width variability over approximately the last 150 years (from 1877 to present day), and are comparable with ( though generally lower than) the channel width of the 1950s. Statistical analyses (simple and multiple regressions) between the observed changes in channel width and a series of selected morphological and hydraulic controlling factors showed no robust correlations to explain the spatial pattern and the variability of channel adjustments. Instead, major adjustments occurred along reaches characterized by the confluence of those streams draining the sub‐catchments where the storm was concentrated. Copyright © 2014 John Wiley & Sons, Ltd.     

The spatial and temporal patterns of aggradation in a temperate,upland, gravel‐bed river

Intensive field monitoring of a reach of upland gravel‐bed river illustrates the temporal and spatial variability of in‐channel sedimentation. Over the six‐year monitoring period, the mean bed level in the channel has risen by 0·17 m with a maximum bed level rise of 0·5 m noted at one location over a five month winter period. These rapid levels of aggradation have a profound impact on the number and duration of overbank flows with flood frequency increasing on average 2·6 times and overbank flow time increasing by 12·8 hours. This work raises the profile of coarse sediment transfer in the design and operation of river management, specifically engineering schemes. It emphasizes the need for the implementation of strategic monitoring programmes before engineering work occurs to identify zones where aggradation is likely to be problematic. Exploration of the sediment supply and transfer system can explain patterns of channel sedimentation. The complex spatial, seasonal and annual variability in sediment supply and transfer raise uncertainties into the system's response to potential changes in climate and land‐use. Thus, there is a demand for schemes that monitor coarse sediment transfer and channel response. Copyright © 2009 John Wiley & Sons, Ltd.     

Impact of the spatial variability of daily precipitation on hydrological projections: A comparison of GCM‐ and RCM‐driven cases in the Han River basin,Korea

In this study, we investigate the impact of the spatial variability of daily precipitation on hydrological projections based on a comparative assessment of streamflow simulations driven by a global climate model (GCM) and two regional climate models (RCMs). A total of 12 different climate input datasets, that is, the raw and bias‐corrected GCM and raw and bias‐corrected two RCMs for the reference and future periods, are fed to a semidistributed hydrological model to assess whether the bias correction using quantile mapping and dynamical downscaling using RCMs can improve streamflow simulation in the Han River basin, Korea. A statistical analysis of the daily precipitation demonstrates that the precipitation simulated by the GCM fails to capture the large variability of the observed daily precipitation, in which the spatial autocorrelation decreases sharply within a relatively short distance. However, the spatial variability of precipitation simulated by the two RCMs shows better agreement with the observations. After applying bias correction to the raw GCM and raw RCMs outputs, only a slight change is observed in the spatial variability, whereas an improvement is observed in the precipitation intensity. Intensified precipitation but with the same spatial variability of the raw output from the bias‐corrected GCM does not improve the heterogeneous runoff distributions, which in turn regulate unrealistically high peak downstream streamflow. GCM‐simulated precipitation with a large bias correction that is necessary to compensate for the poor performance in present climate simulation appears to distort streamflow patterns in the future projection, which leads to misleading projections of climate change impacts on hydrological extremes.     

An Assessment of Two-Dimensional Past Sea Level Reconstructions Over 1950–2009 Based on Tide-Gauge Data and Different Input Sea Level Grids

We compare different past sea level reconstructions over the 1950–2009 time span using the Empirical Orthogonal Function (EOF) approach. The reconstructions are based on 91 long (up to 60?years) but sparsely distributed tide-gauge records and gridded sea level data from two numerical ocean models over 1958–2007 (the DRAKKAR/NEMO model without data assimilation and the simple ocean data assimilation ocean reanalysis-SODA-) and satellite altimetry data over 1993–2009. We find that the reconstructed global mean sea level computed over the?~60-year-long time span little depends on the input spatial grids. This is unlike the regional variability maps that appear very sensitive to the considered input spatial grids. Using the DRAKKAR/NEMO model, we test the influence of the period covered by the input spatial grids and the number of EOFs modes used to reconstruct sea level. Comparing with tide-gauge records not used in the reconstruction, we determine optimal values for these two parameters. As suggested by previous studies, the longer the time span covered by the spatial grids, the better the fit with unused tide gauges. Comparison of the reconstructed regional trends over 1950–2009 based on the two ocean models and satellite altimetry grids shows good agreement in the tropics and substantial differences in the mid and high latitude regions, and in western boundary current areas as well. The reconstructed spatial variability seems very sensitive to the input spatial information. No clear best case emerges. Thus, using the longest available model-based spatial functions will not necessarily give the most realistic results as it will be much dependent on the quality of the model (and its associated forcing). Altimetry-based reconstructions (with 17-year long input grids) give results somewhat similar to cases with longer model grids. It is likely that better representation of the sea level regional variability by satellite altimetry compensates the shorter input grids length. While waiting for much longer altimetry records, improved past sea level reconstructions may be obtained by averaging an ensemble of different model-based reconstructions, as classically done in climate modelling. Here, we present such a ‘mean’ reconstruction (with associated uncertainty) based on averaging the three individual reconstructions discussed above.     

Predicting river width,depth and velocity at ungauged sites in England and Wales using multilevel models

Using a dataset of gauged river discharges taken from sites in England and Wales, linear multilevel models (also known as mixed effects models) were applied to quantify the variability in discharge and the discharge‐hydraulic geometry relationships across three nested spatial scales. A jackknifing procedure was used to test the ability of the multilevel models to predict hydraulic geometry, and therefore width, mean depth and mean velocity, at ungauged stations. These models provide a framework for making predictions of hydraulic geometry parameters, with associated levels of uncertainty, using different levels of data availability. Results indicate that as one travels downstream along a river there is greater variability in hydraulic geometry than is the case between rivers of similar sizes. This indicates that hydraulic geometry (and therefore hydrology) is driven by catchment area, to a greater extent than by natural geomorphological variations in the streamwise direction at the mesoscale, but these geomorphological variations can still have a major impact on channel structure. Copyright © 2008 John Wiley & Sons, Ltd.     

Radar for hydrology: Unfulfilled promise or unrecognized potential?

Hydrology requires accurate and reliable rainfall input. Because of the strong spatial and temporal variability of precipitation, estimation of spatially distributed rain rates is challenging. Despite the fact that weather radars provide high-resolution (but indirect) observations of precipitation, they are not used in hydrological applications as extensively as one could expect. The goal of the present review paper is to investigate this question and to provide a clear view of the opportunities (e.g., for flash floods, urban hydrology, rainfall spatial extremes) the limitations (e.g., complicated error structure, need for adjustment) and the challenges for the use of weather radar in hydrology (i.e., validation studies, precipitation forecasting, mountainous precipitation, error propagation in hydrological models).     

Regionalization of annual runoff characteristics and its indication of co-dependence among hydro-climate–landscape factors in Jinghe River Basin,China

It is a challenge to properly generalize hydrological characteristics under the great heterogeneity of climate and landscape conditions across space because the linkage and interaction among hydro-climate–landscape factors are complicate and ambiguous at regional scale. In this study, multivariate statistical analyses including clustering, correlation and regression analysis were combined with Budyko and L’vovich frameworks to regionalize runoff characteristics over Jinghe River Basin of northwest China. For all 23 sub-basins, the hydrologic factors were quantified using the metrics of mean annual values and intra-annual variability of runoff. The climatic factors are determined from precipitation, potential evapotranspiration and aridity index, and the landscape factors were extracted from topography, soils and vegetation of the sub-basins. Results illustrated that the 23 sub-basins can be classified into two groups, the dry Loess Plateau (LP) and the wet Mountain Region (MR) in the study basin. The runoff metrics of sub-basins in each group present similarity in spatial distribution, intra-annual variations and the dominant influence factors of climate and landscape. But such runoff metrics characteristics and their co-dependence are significantly different between the two clustered sub-basins. Higher runoff and gentler hydrographs were observed in the MR in response to wetter and greater intra-annual variability in climate and greater spatial variability in landscape, whereas lower runoff and sharper hydrograph were seen in response to drier and greater intra-annual variability in climate, and less spatial variability in landscape in the LP. The runoff spatial distribution is more sensitive to climate spatial variation than to landscape in LP as opposed to the MR. Among the landscape factors, forest distribution is the dominant control on the spatial runoff characteristics in LP whereas topography is principal factor in MR. Our results highlight that current measures of reforestation plus marked change in climate in the Loess Plateau could lead to significant change in streamflow.     

Deducing the spatial variability of exchange within a longitudinal channel water balance

Developing an appropriate data collection scheme to infer stream–subsurface interactions is not trivial due to the spatial and temporal variability of exchange flowpaths. Within the context of a case study, this paper presents the results from a number of common data collection techniques ranging from point to reach scales used in combination to better understand the spatial complexity of subsurface exchanges, infer the hydrologic conditions where individual influences of hyporheic and groundwater exchange components on stream water can be characterized, and determine where gaps in information arise. We start with a tracer‐based, longitudinal channel water balance to quantify hydrologic gains and losses at a sub‐reach scale nested within two consecutive reaches. Next, we look at groundwater and stream water surface levels, shallow streambed vertical head gradients, streambed and aquifer hydraulic conductivities, water chemistry, and vertical flux rates estimated from streambed temperatures to provide more spatially explicit information. As a result, a clearer spatial understanding of gains and losses was provided, but some limitations in interpreting results were identified even when combining information collected over various scales. Due to spatial variability of exchanges and areas of mixing, each technique frequently captured a combination of groundwater and hyporheic exchange components. Ultimately, this study provides information regarding technique selection, emphasizes that care must be taken when interpreting results, and identifies the need to apply or develop more advanced methods for understanding subsurface exchanges. Copyright © 2013 John Wiley & Sons, Ltd.     

基于多尺度注意残差网络的地震波形分类研究

选用2010年2月—2016年12月发生在北京顺义及河北三河等首都圈邻近区域的117个地震事件(包括54个天然地震事件和63个非天然地震事件——爆炸事件)作为研究对象,利用文章所提出的多尺度注意残差网络对其中的天然地震事件和爆炸事件波形进行二分类。首先,对原始地震波形进行简单预处理并截取成相同长度的地震时序数据,直接将其作为网络模型的输入;其次,选用含有残差模块的深度神经网络作为基础网络,利用深度神经网络对特征的自动提取能力,省略了传统波形分类需要提前提取时域波形的特征作为分类算法输入的步骤;然后,融合通道注意力机制(ECA)并对其进行改进,将空间维度的信息融入通道信息,优化了网络对关键信息的关注,更好地聚焦重要特征;最后,使用空间金字塔池化代替最大池化进行多尺度特征融合,得到更多的特征信息,构成多尺度注意残差网络。实验结果表明,最高分类准确率为97.11%,平均分类准确率为96.53%,证明了多尺度注意残差网络在地震波形分类任务中的有效性,为震源类型识别工作提供了一种新的方法。     

Geostatistical modelling of the Wasia aquifer in Central Saudi Arabia

Aquifers in sedimentary basins provide a regional domain for the spatial variabilities in geologic, hydrologic, geomorphologic and hydrochemical phenomena. Their study should account for this spatial variability within the study area prior to any formal modelling. A cumulative semivariogram scheme is adopted in this paper for the spatial variability, which is then incorporated with the kriging technique to provide maps of regional variation concerning variables such as storativity, transmissivity, piezometric levels, total dissolved solids and groundwater flow velocity. It is shown that the classical semivariogram models are not capable of accounting for the spatial variability of the Wasia aquifer. Comparison between the cumulative and classical semivariograms are given on the basis of hydrogeologic variables observed in the field. It is concluded, in general, that the cumulative semivariogram modelling of the spatial variability is more effective and yields realistic regional variables.     

Spatio‐temporal variability of the isotopic input signal in a partly forested catchment: Implications for hydrograph separation

The isotopic composition of precipitation (D and ¹⁸O) has been widely used as an input signal in water tracer studies. Whereas much recent effort has been put into developing methodologies to improve our understanding and modelling of hydrological processes (e.g., transit‐time distributions or young water fractions), less attention has been paid to the spatio‐temporal variability of the isotopic composition of precipitation, used as input signal in these studies. Here, we investigated the uncertainty in isotope‐based hydrograph separation due to the spatio‐temporal variability of the isotopic composition of precipitation. The study was carried out in a Mediterranean headwater catchment (0.56 km²). Rainfall and throughfall samples were collected at three locations across this relatively small catchment, and stream water samples were collected at the outlet. Results showed that throughout an event, the spatial variability of the input signal had a higher impact on hydrograph separation results than its temporal variability. However, differences in isotope‐based hydrograph separation determined preevent water due to the spatio‐temporal variability were different between events and ranged between 1 and 14%. Based on catchment‐scale isoscapes, the most representative sampling location could also be identified. This study confirms that even in small headwater catchments, spatio‐temporal variability can be significant. Therefore, it is important to characterize this variability and identify the best sampling strategy to reduce the uncertainty in our understanding of catchment hydrological processes.