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Box and whisker plots of (a) carbon (b) nitrogen and (c) phosphorus, in relation to sediment textural groups in the study area. Significance groupings presented at bottom of each graph. Categories with different letters are significantly different. For each box and whisker plot the median, 95th and 5th percentile are displayed.
Source publication
This paper investigated the textural character of surface sediments across a range of inset-flood plain surfaces on the Barwon Darling River, Australia. Surface sediments ranged in size from clay to coarse sand (-1Φ) - <4.75Φ) but varied in composition between different inset-flood plain surfaces. Multivariate entropy analysis detected five sedimen...
Contexts in source publication
Context 1
... 1 contained samples with finer grained sediments, while Group 5 contained coarser grained sediments, with median grain sizes for the five sediment texture groups being 0.1 mm, 0.118 mm, 0.153 mm, 0.156 mm, and 0.217 mm, respectively, for groups one through to five. Grouping the nutrient dataset with respect to these sediment texture groups (a bottom-up influence) revealed statistically sig- nificant differences among the five sediment texture groups for all three nutrient variables (Figure 4). With the exception of Group 2 sedi- ments, TC showed a decreasing trend in mean concentration with increasing sediment texture (Figure 4a). ...
Context 2
... the nutrient dataset with respect to these sediment texture groups (a bottom-up influence) revealed statistically sig- nificant differences among the five sediment texture groups for all three nutrient variables (Figure 4). With the exception of Group 2 sedi- ments, TC showed a decreasing trend in mean concentration with increasing sediment texture (Figure 4a). TN and TP showed more variable trends with sediment texture (Figure 4b,c). ...
Context 3
... the exception of Group 2 sedi- ments, TC showed a decreasing trend in mean concentration with increasing sediment texture (Figure 4a). TN and TP showed more variable trends with sediment texture (Figure 4b,c). Group 3 sediments displayed the highest mean TN content Group 5 sediments the lowest. ...
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... La capacidad de transporte de las aguas clasifica los sedimentos por tamaño, llegando a las zonas más alejadas o bajas los de menor tamaño o de mayor facilidad de transporte. El carácter textural de los sedimentos en un punto dado refleja el balance entre suministro desde fuentes aguas arriba y de la salida de ellos durante la inundación (Southwell y Thoms, 2006). De esta forma, el tamaño de los sedimentos debe disminuir desde las cabeceras hasta la desembocadura de los ríos, debido a la meteorización, fraccionamiento y desgaste por fricción (González del Tánago y García de Jalón, 1995). ...
... De esta forma, el tamaño de los sedimentos debe disminuir desde las cabeceras hasta la desembocadura de los ríos, debido a la meteorización, fraccionamiento y desgaste por fricción (González del Tánago y García de Jalón, 1995). Las variaciones locales en la topografía y los procesos hidráulicos pueden alterar este patrón, lo que resulta en una distribución "irregular" de la textura de los suelos (Southwell y Thoms, 2006). ...
... Previous work on floodplain grain-size distribution (Southwell & Thoms, 2006) and organic carbon (Southwell & Thoms, 2011) in rivers of south-eastern Australia that share characteristics of process and form with the prairie rivers described here indicates that floodplain characteristics may best be described as a patch mosaic rather than a gradient with distance from the active channel. ...
Two data sources, field‐collected samples and values in the NRCS SSURGO database, were used to estimate organic carbon concentration (%) and stock (Mg C/ha) in floodplain soils along rivers of the tallgrass and shortgrass prairie within the United States. Field sampling of 6 sites in the tallgrass prairie and 6 sites in the shortgrass prairie (total sample size of 370 vertical cores) indicates that percent organic carbon within a planar cross section through floodplain sediment at a site is spatially heterogeneous and does not decline systematically with depth, but statistical analyses indicate that soil organic carbon is randomly distributed. The median values of organic carbon concentration at both field‐sampled and sites remotely sampled based on soil maps in the tallgrass prairie are significantly higher than those of the shortgrass prairie. Median values of organic carbon stock are not significantly different between those obtained from forested sites for comparison and either shortgrass or tallgrass prairie sites but are significantly higher at tallgrass than at shortgrass prairie sites. These results are surprising because upland net primary productivity in prairies is lower than in forested sites. We infer that the historical abundance of floodplain wetlands in river corridors of the tallgrass prairie results in high organic carbon stocks in tallgrass prairie river corridors. This implies that management designed to enhance carbon sequestration should focus on floodplain soils, especially in the tallgrass prairie region, as well as on upland forests.
... There is often little evidence to suggest that the patterns observed occur across large scales or in multiple directions (Thoms and Parsons, 2011). Additionally, spatial pattern in floodplains may not be continuous, as is implied by the gradient paradigm (Southwell and Thoms, 2006), and important boundaries in floodplains may be overlooked due to scale and resolution limitations. ...
River Science is a rapidly developing interdisciplinary field at the interface of the natural sciences, engineering and socio-political sciences. It recognises that the sustainable management of contemporary rivers will increasingly require new ways of characterising them to enable engagement with the diverse range of stakeholders. This volume represents the outcome of research by many of the authors and their colleagues over the last 40 years and demonstrates the integral role that River Science now plays in underpinning our understanding of the functioning of natural ecosystems, and how societal demands and historic changes have affected these systems. The book will inform academics, policy makers and society in general of the benefits of healthy functioning riverine systems, and will increase awareness of the wide range of ecosystem goods and services they provide.
... There is often little evidence to suggest that the patterns observed occur across large scales or in multiple directions (Thoms and Parsons, 2011). Additionally, spatial pattern in floodplains may not be continuous as is implied by the gradient paradigm (Southwell and Thoms, 2006), and important boundaries in floodplains may be overlooked due to scale and resolution limitations. ...
This chapter focuses on measuring spatial pattern in floodplains and reviews 108 publications from 1934-2013 to determine trends, dominant paradigms, and approaches to measuring spatial pattern in floodplains. The development of new technologies, especially those associated with remotely sensed data capture, increases the ability to quantitatively measure the spatial complexity of floodplain surfaces. Satellite imagery, aerial photography and airborne laser scanning (LiDAR) now provide quantitative numerical data on many physical and biological attributes of floodplain ecosystems, at increasingly fine resolutions and over vast spatial extents. The chapter provides a case study that highlights the importance of considering scale, self-emergence, spatial organisation, and location when measuring spatial pattern in floodplains. Measuring spatial pattern is one of many steps towards understanding how floodplain ecosystems will respond to increasing pressures, identifying thresholds between multiple stable states, and maintaining the diversity of components, interactions, and feedbacks.
... Variables can be distributed continuously, in patches, a combination of both or randomly throughout space (Gustafson, 1998), and this has important implications for sampling and for understanding ecosystem patterns and processes. First, the location of measurements can greatly influence results obtained when measuring any spatial phenomena (Southwell and Thoms, 2006;Legleiter, 2014a;Scown et al., in press); and if a good geographic distribution of samples is not taken, results can be unrepresentative of the entire area and misleading. This issue applies to raw elevation data, which has implications for uncertainty in DEMs (Rayburg et al., 2009;Wheaton et al., 2010;Carley et al., 2012), as well as to derived data (such as surface metrics), which has implications for the conclusions drawn about topography across entire floodplains when only small areas are actually measured (Scown et al., in press). ...
... Discrepancies in how floodplains are considered to be structured may lie in the scale or location of observation. Over small areas, or at coarse resolutions, spatial patterns in floodplains may appear as gradients, for example; whereas at other spatial extents and resolutions patches may be clear (Southwell and Thoms, 2006). The question of how floodplain topography is spatially organised-or at a higher level how complex floodplain topography is-may therefore depend on the scales and locations at which it is measured Scown et al., in press). ...
Interactions between fluvial processes and floodplain ecosystems occur upon a floodplain surface that is often physically complex. Spatial patterns in floodplain topography have only recently been quantified over multiple scales, and discrepancies exist in how floodplain surfaces are perceived to be spatially organised. We measured spatial patterns in floodplain topography for pool 9 of the Upper Mississippi River, USA, using moving window analyses of eight surface metrics applied to a 1 × 1 m2 DEM over multiple scales. The metrics used were Range, SD, Skewness, Kurtosis, CV, SDCURV, Rugosity, and Vol:Area, and window sizes ranged from 10 to 1000 m in radius. Surface metric values were highly variable across the floodplain and revealed a high degree of spatial organisation in floodplain topography. Moran’s I correlograms fit to the landscape of each metric at each window size revealed that patchiness existed at nearly all window sizes, but the strength and scale of patchiness changed within window size, suggesting that multiple scales of patchiness and patch structure exist in the topography of this floodplain. Scale thresholds in the spatial patterns were observed, particularly between the 50 and 100 m window sizes for all surface metrics and between the 500 and 750 m window sizes for most metrics. These threshold scales are ~ 15-20% and 150% of the main channel width (1-2% and 10-15% of the floodplain width), respectively. These thresholds may be related to structuring processes operating across distinct scale ranges. By coupling surface metrics, multi-scale analyses, and correlograms, quantifying floodplain topographic complexity is possible in ways that should assist in clarifying how floodplain ecosystems are structured.
... The stable nature of these features reflects the stability of the river channel -the planform has not shifted significantly since at least 1848 (Woodyer et al., 1979). In the mid- reaches of the Barwon-Darling River, the texture of surface sediments on inset floodplains border- ing the main river channel shows a patchy distri- bution at the landscape scale ( Southwell and Thoms, 2006). Here, sediment texture does not appear to be associated with large-scale top- down factors, such as floodplain elevation or landscape position. ...
... Here, sediment texture does not appear to be associated with large-scale top- down factors, such as floodplain elevation or landscape position. Rather, sediment texture appears to be influenced by both spatial and tem- poral variations in sediment supply ( Southwell and Thoms, 2006). Therefore, in this system, the relationship between landscape position (whether it is vertical, lateral or longitudinal) and sediment texture appears to be decoupled. ...
... The spatial distributions of carbon, nitrogen, and phosphorus across the various floodplain sur- faces of the Barwon-Darling River reflects a spatial mosaic rather than defined longitudinal or lateral gradients imparted by larger scale geo- morphic constraints. This spatial mosaic of nutri- ent concentrations can be linked to the sediment textural mosaic defined by Southwell and Thoms (2006). Recent models of river ecosystem structure and function (Thorp et al., 2006) emphasise the patchy nature of riverine landscapes. ...
Deciphering patterns and inferring processes in multicausal floodplain river ecosystems is a challenge in river science. The effects of larger-scale top-down constraints and smaller-scale bottom-up influences on the spatial patterns of nutrient concentrations across multiple inset-floodplain surfaces was studied in a large dryland floodplain river (Barwon-Darling River, south-east Australia). The distribution of sediment-associated carbon, nitrogen, and phosphorus was primarily related with significant differences in the textural character of the different floodplain surfaces. Elevation of the different floodplain surfaces above the active channel was a secondary influence on the distribution of carbon and phosphorus. Combined, these factors produce a spatial patch mosaic of sediment associated carbon, nitrogen, and phosphorous across these floodplain surfaces.
... Two replicate surface samples were taken from each flood plain. The inset-flood plain surfaces were selected on the basis of their textural character and surface elevation (Southwell & Thoms, 2006) and included three elevation classes (low level, mid level and high level) and five sediment textural classes based on the full grain size distribution of surface sediments. Each flood plain textural class was determined using a multivariate procedure, as outlined in Southwell & Thoms (2006). ...
... The inset-flood plain surfaces were selected on the basis of their textural character and surface elevation (Southwell & Thoms, 2006) and included three elevation classes (low level, mid level and high level) and five sediment textural classes based on the full grain size distribution of surface sediments. Each flood plain textural class was determined using a multivariate procedure, as outlined in Southwell & Thoms (2006). ...
... In all cases sediments from flood plain surfaces at higher elevations released significantly more TOC and TN than those from mid or lower level elevation (Table 1). These patterns are similar to those observed by Southwell & Thoms (2006) for quantities of organic matter and particulate nutrient concentrations found on these flood plain surfaces and are assumed to be associated with increasing distance from the active channel and proximity to riparian vegetation. ...
Dissolved nutrients are mobilised from flood plain surfaces during periods of inundation. These dissolved materials are an essential resource for the functioning of flood plain-river ecosystems. However, little is known of the dynamics of nutrient release during periods of flood plain inundation or the factors controlling their release. Patterns of total organic carbon (TOC), total nitrogen (TN) and total phosphorus (TP) released from flood plain sediments were investigated in this study. In a series of experiments conducted over a 72-h period, sediments collected from various flood plain surfaces were wetted in order to assess possible controls, spatial patterns, and the influence of changing hydrology on the release of dissolved nutrients. Top-down constraints, including the reach location, degree of confinement and elevation above the river bed, all had a significant impact on release rates for TOC, as well as release rates and concentrations of TN. Sediment texture was significantly associated with TP concentrations only; although sediment texture was associated with TN and TOC release rates over time. These results indicate that larger scale constraints, such as position in the broader riverine landscape, influence spatial patterns of nutrient release rates over time more than smaller scale influences such as sediment texture. Using the release data for the various flood plain surfaces, combined with long-term flow data for several flow scenarios, simple budgets for dissolved nutrients were calculated for the study reach over the 1922-2000 period. A 43% reduction in the potential supply of dissolved nutrients was demonstrated with changes in river hydrology over this 78-year period associated with water resource developments.
... Benches have most commonly been investigated in southeastern Australia (Woodyer 1968;Woodyer 1975;Woodyer 1978;Woodyer et al. 1979;Page and Nanson 1982;Nanson and Page 1983;Sherrard and Erskine 1991;Thoms and Walker 1993;Erskine 1994;Thoms and Sheldon 1996;Erskine and Livingstone 1999;Webb et al. 1999;Cohen 2003;Thoms 2003;Thoms and Olley 2004;Southwell and Thoms 2006). However, benches are also reported in the United States (Kilpatrick and Barnes 1964;Carey 1969;Grams and Schmidt 2001), western Canada (Hickin 1978;Hickin 1979;Page and Nanson 1982;Nanson and Page 1983;Hickin 1986;Burge 1997;Burge and Smith 1999), and to a lesser extent in the United Kingdom and Europe (Lewin 1978;Changxing et al. 1999;Steiger et al. 2001;Makaske and Weerts 2005). ...
... ' (p. 120) This approach of Kilpatrick and Barnes (1964) and Woodyer (1968), describing benches by relative elevation, has been commonly but inconsistently used in the succeeding years ( Warner et al. 1975;Woodyer et al. 1979;Thoms and Sheldon 1996;Erskine and Livingstone 1999;Cohen 2003;Thoms and Olley 2004;Southwell and Thoms 2006). In some cases up to six or seven bench levels have been identified based on elevation, see Figure 2.2. ...
Simple models continue to be important for continental‐scale floodwater depth mapping due to the prohibitively expensive cost of calibrating and applying hydrodynamic models. This paper investigates the accuracy of three simple models for floodwater depth estimation from remote sensing derived water extent and/or Digital Elevation Models (DEMs) in semiarid regions. The three models are Height Above Nearest Drainage (HAND; Nobre et al., 2011, https://doi.org/10.1016/j.jhydrol.2011.03.051), Teng Vaze Dutta (TVD; Teng et al., 2013, http://hdl.handle.net/102.100.100/97033?index=1), and Floodwater Depth Estimation Tool (FwDET; Cohen, Brakenridge, et al., 2018, https://doi.org/10.1111/1752-1688.12609). The model accuracy and nature of errors are established using industry's best practice hydrodynamic models as benchmarks in three regions in eastern Australia. The overall results show that FwDET tends to underestimate (by 0.32 m at 50th percentile) while HAND and TVD overestimate floodwater depth for almost all floods (by 0.97 and 0.98 m, respectively). We quantify how switching DEM from 5 m LiDAR to national or global data sets DEM‐H (Gallant et al., 2011, https://ecat.ga.gov.au/geonetwork/srv/eng/catalog.search#/metadata/72759), MERIT (Yamazaki et al., 2019, https://doi.org/10.1029/2019WR024873), or FABDEM (Hawker et al., 2022, https://doi.org/10.1088/1748-9326/ac4d4f) can affect different models differently; and we evaluate model performance against reach geomorphology and magnitude of flood events. The findings emphasize the importance of choosing a model that is fit for the intended application. By describing the applicability, advantages, and limitations of these models, this paper assists practitioners to choose the most appropriate model based on characteristics of their study area, type of problems they try to solve, and data availability.
Ethnopedology has significantly contributed to understanding local perceptions of soil, and its uses and management, and has complemented technical (scientific) surveys. This study focused on indigenous soil classification of the Zulu and Xhosa ethnic groups of eastern South Africa. The study area comprised four villages, viz Khokhwane (104 ha) and Potshini (577 ha) in KwaZulu-Natal Province and Ntshiqo (629 ha) and Zalaze (80 ha) in Eastern Cape Province. Ethnographic methods were used to elicit general local knowledge of soils and ethnopedologic techniques to gain in-depth understanding of soil and theories associated with local taxonomy. Knowledgeable farmers were chosen (upon recommendation and/or based on interest and detail given during interviews) to produce participatory soil maps. These local maps were later compared with scientific soil mapping at 1:10000 scale using a free survey method. Local classification criteria reflected a detailed understanding of soil behaviour, use potential based on long-term observations, and experience with key soil morphological properties such as texture, consistence and colour. Local soil terminology was mostly different for all four villages as well as across ethnic groups. However, some differences between ethnic groups (e.g. Zulu-isibomvu and Xhosa-obomvu; Zulu-ubumba and Xhosa-udongwe) were mainly linguistic and did not indicate inherent differences in soil properties. Terrain features were important for both indigenous and scientific soil classification. Consequently, soil maps produced by local farmers in areas with distinct geomorphic units were generally closely correlated with scientific maps. Although on a floodplain the correlation was poor, the flexibility of the local classification was demonstrated as farmers manipulated the classification criteria to capture changes with distance away from the river. Farmers classified soils at higher levels than the two-tier system of the South African classification and so these could be incorporated as higher categories in the current South African classification system. Irrespective of the level of correlation between scientific and local maps, farmers’ local classifications contained detailed pedological information that can contribute to the development of classifications systems that are both user-friendly and relevant for local needs.
