A framework for evaluating the spatial configuration and temporal dynamics of hydraulic patches

Wallis, Caroline; Maddock, Ian; Visser, Fleur; Acreman, Mike

doi:10.1002/rra.1468

Cited by 25 publications

(29 citation statements)

References 55 publications

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“…Elsewhere, it has already been argued, in fact, that morphology accurately reflects the range of flows that move through the channel (Emery et al, 2003) and can be used as a surrogate of the flow condition in a stream (Bartley & Rutherford, 2005). In other studies, hydraulic variables were defined as a result of the interplay between flow and morphology (Maddock, 1999) and were thus stated to characterize the hydromorphological template of a stream at an ecologically relevant scale (Wallis et al, 2010). In concordance with the latter, we think that focusing directly on hydraulic variables in lieu of studying morphological characteristics of a stream is a valid approach as hydraulic variables reflect not only the hydrologic framework of a stream, but also its geomorphic template.…”

Section: Hydraulic Variables: Representative Descriptors Of Stream Comentioning

confidence: 99%

The hydro-morphological index of diversity: a tool for describing habitat heterogeneity in river engineering projects

et al. 2012

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We present a new hydro-morphological index of diversity (HMID), a tool aimed for use in river engineering projects and firstly developed at gravel-bed streams in Switzerland, but intended for a broader use. We carried out field work with extensive hydraulic and geomorphic data collection, conducted correlation analysis with hydro-morphological variables, formulated the HMID, and analyzed the correlation between HMID and a visual habitat assessment method. The HMID is calculated by means of the coefficient of variation of the hydraulic variables flow velocity and water depth, which have been demonstrated to sufficiently represent the hydro-morphological heterogeneity of alpine gravel-bed stream reaches.Based on numerical modeling, the HMID can be calculated easily for a comparison of different alternatives in river engineering projects and thus achieves predictive power for design decisions. HMID can be applied at a reach-related scale in engineering programs involving geomorphic measures that aim at the enhancement of habitat heterogeneity of a stream. However, the application of HMID has to be integrated with evaluations of the long-term streambed evolvements that are considered at a catchment scale and strongly related to the sediment regime of the stream under study.

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Section: Hydraulic Variables: Representative Descriptors Of Stream Comentioning

confidence: 99%

The hydro-morphological index of diversity: a tool for describing habitat heterogeneity in river engineering projects

et al. 2012

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“…The inconsistent of river width and depth were caused by the Pahang River possessed for meandering characteristic which showing the sinuosity along it river course. Indeed, river meanders are one of the most common patterns in fluvial morphology (Chitale, 1970;Allen, 1982;Howard, 1992;Wallis et al, 2012;Toriman et al, 2012). But decrease their water stage during second sampling (February) which was ranged from 0.956 m to 9.158 m. The difference of water stage for 17 stations for both samplings was different from 0.9 m to 2.5 m. Low of total rainfall due to dry season during second sampling has bearing to decreasing of water stage along Pahang River (Fig.…”

Section: Ajasmentioning

confidence: 99%

River Flow Conditions and Dynamic State Analysis of Pahang River

Ahmad¹

2013

American Journal of Applied Sciences

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Pahang River (Sg. Pahang) is the longest river in Peninsular Malaysia. Flood is a common event in Pahang River Basin during wet season which triggered by monsoon season. The hydrodynamic study of Pahang River should be well understood especially when it is a target of northeast monsoon which influenced the Pahang River Basin every year (from November to March). 17 river cross section stations were selected and used to measure its drainage capacity, hydraulic parameters and estimation of flow discharge. Long term (1980 to 2009) variation of hydrologic data series comprised of river flow, river stage and rainfall data were analyzed based on the Department of Irrigation and Drainage (DID) Malaysia record. Monthly rainfall was recorded from Sg. Yap, Temerloh and Lubuk Paku Rainfall Stations. Two hydrologic sampling trips had been carried out; first sampling on January 2010 and second sampling on February 2010. The study indicates that velocity and river flow measurement during first sampling ranged from 0.308 to 0.582 m sec −1 and 153.282 to 439.684 m 3 sec −1 . Meanwhile, during second sampling, the velocity and river flow ranged from 0.217 to 0.484 and 52.071 to 304.485 m 3 sec −1 , respectively. Floods were occurred annually at Pahang River especially during northeast monsoon, these events are expected to be stimulated by the inconsistent condition of width and depth along Pahang River which finally create sedimentation and meandering characteristic.

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“…In stream ecosystems, mesoscale interactions between channel morphology [23,24] and discharge [25] generate a heterogeneous hydraulic environment and spatial pattern that provide various in-stream habitats for freshwater biota [26,27]. Greater stream habitat heterogeneity frequently results in greater diversity of aquatic species [23,28] and the improved success and survival of individual species [24,29].…”

Section: Introductionmentioning

confidence: 99%

“…Greater stream habitat heterogeneity frequently results in greater diversity of aquatic species [23,28] and the improved success and survival of individual species [24,29]. Habitat heterogeneity in rivers can be characterized by the relative proportion of mesohabitats (composition), as well as their spatial arrangement (configuration) and temporal dynamics (variation with discharge) [27,30]. Although the characterization of hydromorphological conditions at an ecologically relevant scale is made possible by quantifying the hydraulic environment of streams via empirical data and an increasing number of models to choose from [27], the quantification of both uncertainty and stream habitat heterogeneity is not so straight forward [12,24].…”

Section: Introductionmentioning

confidence: 99%

“…Habitat heterogeneity in rivers can be characterized by the relative proportion of mesohabitats (composition), as well as their spatial arrangement (configuration) and temporal dynamics (variation with discharge) [27,30]. Although the characterization of hydromorphological conditions at an ecologically relevant scale is made possible by quantifying the hydraulic environment of streams via empirical data and an increasing number of models to choose from [27], the quantification of both uncertainty and stream habitat heterogeneity is not so straight forward [12,24]. Additionally, few methods for quantifying variability in SDM outputs are available, not to mention methods for quantifying habitat heterogeneity and relating it to aquatic species ecology [12,24].…”

Section: Introductionmentioning

confidence: 99%

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Uncertainty in Various Habitat Suitability Models and Its Impact on Habitat Suitability Estimates for Fish

Lin

2015

Water

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Species distribution models (SDMs) are extensively used to project habitat suitability of species in stream ecological studies. Owing to complex sources of uncertainty, such models may yield projections with varying degrees of uncertainty. To better understand projected spatial distributions and the variability between habitat suitability projections, this study uses five SDMs that are based on the outputs of a two-dimensional hydraulic model to project the suitability of habitats and to evaluate the degree of variability originating from both differing model types and the split-sample procedure. The habitat suitability index (HSI) of each species is based on two stream flow variables, including current velocity (V), water depth (D), as well as the heterogeneity of these flow conditions as quantified by the information entropy of V and D. The six SDM approaches used to project fish abundance, as represented by HSI, included two stochastic models: the generalized linear model (GLM) and the generalized additive model (GAM); as well as three machine learning models: the support vector machine (SVM), random forest (RF) and the artificial neural network (ANN), and an ensemble model (where the latter is the average of the preceding five models). The target species Sicyopterus japonicas was found to prefer habitats with high current velocities. The relationship between mesohabitat diversity and fish abundance was indicated by the trends in information entropy and weighted usable area (WUA) over the study area. This study proposes a method for quantifying habitat suitability, and for assessing the uncertainties in HSI and WUA that are OPEN ACCESSWater 2015, 7 4089 introduced by the various SDMs and samples. This study also demonstrated both the merits of the ensemble modeling approach and the necessity of addressing model uncertainty.

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A framework for evaluating the spatial configuration and temporal dynamics of hydraulic patches

Cited by 25 publications

References 55 publications

The hydro-morphological index of diversity: a tool for describing habitat heterogeneity in river engineering projects

The hydro-morphological index of diversity: a tool for describing habitat heterogeneity in river engineering projects

River Flow Conditions and Dynamic State Analysis of Pahang River

Uncertainty in Various Habitat Suitability Models and Its Impact on Habitat Suitability Estimates for Fish

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