Pebble Counts Research Articles

Landscape changes and watershed erosion in Prince George's County, Maryland

AbstractThis study evaluated erosion rates and sediment production in streams, and factors potentially influencing them throughout the Anacostia, Patuxent, and Potomac (non‐Anacostia) River watersheds within Prince George's County, Maryland, US. As part of the County's watershed‐scale biological monitoring program, from approx. 1999 to 2008, permanent monuments were established to allow measurement of stream channel cross‐sectional (XS) area. The intent of this study was to characterize the intensity and spatial distribution of fluvial geomorphic instability across the county and use the results to target and plan stormwater management and stream restoration actions. For this study, 78 stream locations were re‐surveyed in 2020, representing a time lapse of from 12 to 21 years. Data collected included XS dimensions, modified Wolman 100‐particle pebble counts, and reach‐specific soil bulk density. Land use/land cover data were compiled from the National Land Cover Dataset (NLCD), precipitation from the National Weather Service Center for Environmental Information (NCEI), and soils from the Natural Resources Conservation Service Web Soil Survey (NRCS/WSS). We calculated percent change in XS area, rates of erosion, sediment yield, and assigned geomorphic classifications, and interpreted them in the context of spatial positions relative to changes in land cover characteristics. Sediment yields among the 78 reaches exhibited a combination of those undergoing enlargement/erosion (67.9%), reduction/deposition (25.6%), and the remaining 6.4% with essentially no change over the period of record. Of the top 20 most geomorphically active reaches surveyed in the County, 12 are in the Anacostia River basin, with the other scattered among the Patuxent River and Potomac River basins.

COMPUTATIONAL SIMULATION OF SEDIMENT MOTION STABILITY PROCESS ON BRIDGE ABUTMENT DUE TO CRIB PLACEMENT (CASE STUDY: HARAPAN RIVER, JAYAPURA REGENCY)

Erosion occurs when the flow of velocity in a channel exceeds the threshold velocity that causes the bed material to move. This phenomenon is observed in the Harapan River, resulting in significant impacts, such as riverbed lowering and narrowing due to the presence of water structures (bridge abutments) spanning across the river. The objective of this study is to investigate the sediment motion stability around bridge abutments before and after the installation of cribs in order to prevent structural failures. Sediment sampling was conducted at six points around the bridge abutments, using the Pebble Count method along zigzag paths. The grain size of the bed material was classified according to the Sturgess classification standard, and the material dispersion process was analysed using the Hjustorm curve. Design rainfall was transformed into design flood discharge, which was then simulated using the Two-Dimensional Hydrodynamic, comparing the river conditions before and after crib installation. In abutments without cribs, erosion occurred in direct contact with the abutment on the right side for each sediment grain diameter. However, in abutments with cribs, erosion still occurred, but it did not directly contact either abutment despite the presence of a crib. The crib prevented and protected the abutments from being eroded by the riverbed.

Large-Scale Hydromorphological Characteristics Of The Proglacial River Katun (Ob Headwaters)

During the industrialization in Europe, rivers were straightened and designed to fit human activities, thus nowadays only a few natural river systems remain as reference conditions as well as guiding principles for river restoration projects. Therefore, the natural state of some river types is often described using historic records and maps. This study aims to analyze the key characteristics of a pristine proglacial river Katun in the Altai mountains and contribute to the knowledge about reference conditions. For this purpose, hydromorphological characteristics like slope, sinuosity and river width of the river Katun were analysed and summarized using different GIS techniques. Additionally, pebble counts were carried out to assess the changing sediment composition along the longitudinal continuum. Combined with River Habitat Surveys and a one-dimensional flow simulation using HEC-RAS it was possible to give a holistic overview of the dynamic fluvial system Katun in its upper, middle and lower reaches. The results confirmed the relationship between the river and its surrounding topography as they clearly show the lateral development of the Katun. As shown for the individual parameters (e.g., slope, width, depth, flow velocity, shear stress), they influence each other and are strongly dependent and characteristic for each river section. In the context of revitalisation of straightened and / or channelized river courses, it is important to focus on the processes of this interaction and provide suitable space for lateral expansion. The study can be seen as a recommendation on how to analyse hydromorphological characteristics of fluvial systems as well as to establish guiding principles in river restoration using remote sensing.

Fine sediment dynamics over a gravel bar. Part 1: Validation of a new image-based segmentation method

In this paper, we present a new image processing algorithm to analyse fine sediment deposits on gravel bars. The method is based on pictures taken from the river bank with an average resolution of a few centimetres per pixel. The proposed image processing algorithm consists of two steps. In the first step, the raw image is orthorectified with a 5 cm pixel size. In second step, we used an original combination of two well-known image techniques to classify pixel. First, a high-pass filter is applied in the Fourier domain to correct grey-value potential bias, i.e. to merge wet and dry deposits. Then, an unsupervised classification process based on K-means clustering is conducted to partition image pixels into K classes. The area of fine sediment deposits is calculated by summing the area of each class multiplied by weighting parameters (surface area percentage of fine deposits for each class). The value of K and the weighting parameters are calibrated using local close range photos of the bar surface representing the spatial variation of surface fine sediment distribution. The algorithm is then validated with field measurement using the finest class (d<4 mm) of Wolman pebble count method. The impact of image resolution is investigated: the algorithm was found suitable for pixel size between 1 and 10 cm. The robustness of the present algorithm to images taken at different times and with different illuminations is studied by comparing it to two methods from the literature. The new method yields the most robust results with an average standard deviation lower than 5%. It yields larger surface of fine sediment since it includes all possible patches around coarse particles. Such results imply that the algorithm can be applied on a long image series to help us understand the temporal dynamics of fine sediment deposits on the bar surface.

Investigating the Granulometric Distribution of Fluvial Sediments through the Hybrid Technique: Case Study of the Baganza River (Italy)

Sediment characterization is a key parameter to understand the geomorphological attributes of a catchment (i.e., assessing the variability of the sediment transport capacity and surface roughness of a hydraulic channel). This assessment can be performed in several ways, for instance, through numerous sampling techniques (i.e., pebble count and zig-zag methods). Sediment sampling using manual sieving inside a laboratory is a hectic process as it requires ample time and physical effort, particularly when the scale of interest is at the catchment level. In order to find the granulometric distribution of some sections of the Baganza streambed (northern Italy), in order to carry out analysis at the catchment scale, a hybrid technique (a combination of the conventional and photogrammetric method) is introduced. Different grain size distribution curves (GSDs) obtained from the image processing technique using Digital Gravelometer software and traditional sediment sieve analysis (sieve-by-weight method) were compared. Sediment sampling was limited to sections of the streambed that were visible during lower flows in the dry summer season. Sediment samples including fine soil fraction, were collected up to a depth of 30 cm, although the exposed areas behaved as gravels and cobble bars. The adopted hybrid technique approach for the characterization of fluvial sediments is desirable in order to accommodate the full range of particle sizes inside the riverbed. Digital photography was performed at ten different cross sections, along the longitudinal profile of the 30 km long reach of the Baganza River, to examine the sediment distribution, grading, and representative particle sizes (D10, D50, D90) at each of the respective cross sections. A comparison of the photogrammetric method and traditional sieve analysis revealed strong agreement in coarser segments of the grain size distributions, but it was deficient in the finer part (&lt;2 mm) due to the shielding effect produced by bigger particles. However, the adopted hybrid technique appears to be quite efficient and promising in determining the GSD by reducing the costs and the sediment sample collection time in the field.

Convolutional neural networks for image-based sediment detection applied to a large terrestrial and airborne dataset

Abstract. Image-based grain sizing has been used to measure grain size more efficiently compared with traditional methods (e.g., sieving and Wolman pebble count). However, current methods to automatically detect individual grains are largely based on detecting grain interstices from image intensity which not only require a significant level of expertise for parameter tuning but also underperform when they are applied to suboptimal environments (e.g., dense organic debris, various sediment lithology). We proposed a model (GrainID) based on convolutional neural networks to measure grain size in a diverse range of fluvial environments. A dataset of more than 125 000 grains from flume and field measurements were compiled to develop GrainID. Tests were performed to compare the predictive ability of GrainID with sieving, manual labeling, Wolman pebble counts (Wolman, 1954) and BASEGRAIN (Detert and Weitbrecht, 2012). When compared with the sieving results for a sandy-gravel bed, GrainID yielded high predictive accuracy (comparable to the performance of manual labeling) and outperformed BASEGRAIN and Wolman pebble counts (especially for small grains). For the entire evaluation dataset, GrainID once again showed fewer predictive errors and significantly lower variation in results in comparison with BASEGRAIN and Wolman pebble counts and maintained this advantage even in uncalibrated rivers with drone images. Moreover, the existence of vegetation and noise have little influence on the performance of GrainID. Analysis indicated that GrainID performed optimally when the image resolution is higher than 1.8 mm pixel−1, the image tile size is 512×512 pixels and the grain area truncation values (the area of smallest detectable grains) were equal to 18–25 pixels.

Measuring Organization of Large Surficial Clasts in Heterogeneous Gravel Beach Sediments

The natural stratification and interlocking “organization” of armored sediments in heterogeneous, coarse-grained, beaches provides protection and enhances habitat for borrowing sedentary megafauna and macrofauna such as hard-shelled clams. Here, we develop a novel metric for quantifying sediment organization of large surficial beach clasts through sedimentologic and photogrammetric analyses of 37 lower intertidal heterogeneous gravel beaches in western Prince William Sound, Alaska (USA). Grain size, photogrammetric, and Wolman Pebble Count clast-size data from 64, ~1-m2 study plots are combined into a clast-size-independent “Organization Metric” to quantify the degree of organization in the meshed arrangement of larger surficial sediments. This metric was validated through field manipulation experiments and comparisons of adjacent plots characterized by different clast sizes. Application of this metric to subsets of Prince William Sound beaches that underwent differential treatment following the Exxon Valdez oil spill reveals persistent physical effects of artificial beach disturbance even 21 years after the cleanup. This has important implications for beach management (e.g., cleaning or dredging) and for the diverse and productive sedentary megafaunal assemblages that live within these sediments. Overall, this study provides a new approach for quantifying organization of heterogenous coarse sediments in diverse natural settings; in particular, heterogenous gravel beaches.

Measuring the grain‐size distributions of mass movement deposits

AbstractMass movement deposit grain‐size distributions (GSDs) record initiation, transport and deposition mechanisms, and contribute to the rate at which sediment is exported from hillslopes to channels. Defining the GSD of a mass movement deposit is a significant challenge because they are often difficult to access, are heterogeneous in planform and with depth, contain grain sizes from clay (&lt;63 μm) to boulders (&gt;1 m), and require considerable time to calculate accurately. There are numerous methods used to measure mass movement GSDs, but no single method alone can measure the entire range of grain sizes. This paper compares five common methods for determining mass movement deposit GSDs to assess how their accuracy may affect their applicability to different research areas. We applied an automated wavelet analysis (pyDGS), Wolman pebble counts, survey tape counts, manual photo counts and sieving to three different mass movement deposits (two debris flows, one rockslide) in Tredegar, Wales and the Longmen Shan, China. We found that pyDGS and survey tape counts produced comparable GSDs to sieving over a single order of magnitude. PyDGS required calibration to achieve accurate results, limiting its use for many applications. In Tredegar, Wolman pebble counts over‐estimated grain sizes in the lower 80% of the distribution relative to the other four methods used. We demonstrate that method choice can introduce significant uncertainties, particularly at the edges of the distributions, such that D16 values differ by up to a factor of five. These methodological uncertainties limit GSD comparisons across studies, particularly where these are used to infer processes within deposits. To minimize these challenges, the methods chosen should be both carefully reported and consistent with the research question.

Correlation between physico-chemical water quality and river ecosystems in Malaysia rivers with different land uses

River water quality is one of the major issues in water supply in Malaysia. Most people understand that, water pollution caused by the discharge from the factories and municipal waste but is that the real case? So, in order to answer the above question, this study was done to determine the interaction or correlation between physico-chemical water quality and river ecosystems. Component of river ecosystems measured are river riparian composition, large woody debris (LWD), canopy cover and substrate composition (D50). This study was conducted in Sungai Mengkibol, Sungai Madek and Sungai Dengar in Johor. There were a total of five sampling sites, three for impact stations and two as reference stations, including one highland station. For water quality, six in-situ parameters were measured namely temperature, conductivity, dissolved oxygen (DO), pH, turbidity and salinity using a multi parameter probe as well as a single parameter probe. Meanwhile, field survey form was used to assess river habitat namely river riparian compositions, canopy cover and LWD. In addition, Pebble Count Method was used to measure substrate compositions (D50). Results shows that, physico-chemical water quality was correlated (p < 0.05) with riparian cover, LWD and canopy cover but it was not correlated (p>0.05) with substrate composition (D50) of the river. Based on the results obtained from the study, it can be suggested that physico-chemical river water quality was not caused by pollution alone but river ecosystems were also played significance role in determining the quality of water. Hopefully, this finding can be used by the responsible authorities for effective river management in order to sustain our drinking water supply.

Determining the spatio-temporal response of downstream coarse sediment sorting process in the Chel river (North Bengal, India) using cluster analysis

The fluvial transportation efficiency related to rainstorm events is important to understand the variability of sediment sorting process in the channel. The supply limitation of different size of sediment grades in downstream reveals the nature of geomorphological scale of response (spatio-temporal). Pebble count method has been attempted here for determination of d50 (median) particle size associated with frequency distribution of sediment samples from 13 study reaches on the basis of standard sediment grade scale of Wentworth and modified Udden-Wentworth grain scale seasonally. Intra temporal variability (IATV) and inter temporal variability (IETV) results were categorized under hierarchical cluster analysis to view the sediment movement downstream from minimum distance algorithm. On the piedmont, the bed configuration is mostly boulder infested of heavier size class (> 256 mm) and that remains greater than 86% in pre-monsoon condition. It comes out on the basis of random mixing of sediment load (> 2 mm) while transporting as discharge. In Chel basin, the process of sediment load dispersal indicates less heterogeneity in the sediment sorting process towards downstream. The haphazard distribution of very coarse to medium boulders (4096–512 mm) up to reach 6 indicates the limit of channel competency. The paper seeks to know the seasonal variability in the sediment dispersal process i.e. finding the reach wise variability of the sediment mixing process downstream and the sediment supply limits of median particle size.

Use of terrestrial photosieving and airborne topographic LiDAR to assess bed grain size in large rivers: a study on the Rhine River

AbstractMost grain size monitoring is still being conducted by manual sampling in the field, which is time consuming and has low spatial representation. Due to new remote sensing methods, some limitations have been partly overcome, but methodological progress is still needed for large rivers as well as in underwater conditions. In this article, we tested the reliability of two methods along the Old Rhine River (France/Germany) to estimate the grain size distribution (GSD) in above‐water conditions: (i) a low‐cost terrestrial photosieving method based on an automatic procedure using Digital Grain Size (DGS) software and (ii) an airborne LiDAR topo‐bathymetric survey. We also tested the ability of terrestrial photosieving to estimate the GSD in underwater conditions. Field pebble counts were performed to compare and calibrate both methods. The results showed that the automatic procedure of terrestrial photosieving is a reliable method to estimate the GSD of sediment patches in both above‐water and underwater conditions with clean substrates. Sensitivity analyses showed that environmental conditions, including solar lighting conditions and petrographic variability, significantly influence the GSD from the automatic procedure in above‐water conditions. The presence of biofilm in underwater conditions significantly altered the GSD estimation using the automatic procedure, but the proposed manual procedure overcame this problem. The airborne LiDAR topographic survey is an accurate method to estimate the GSD of above‐water bedforms and is able to generate grain size maps. The combination of terrestrial photosieving and airborne topographic LiDAR methods is adapted to assess the GSD over several kilometers long reaches of large rivers. © 2020 John Wiley &amp; Sons, Ltd.

Percentile-based grain size distribution analysis tools (GSDtools) – estimating confidence limits and hypothesis tests for comparing two samples

Abstract. Most studies of gravel bed rivers present at least one bed surface grain size distribution, but there is almost never any information provided about the uncertainty in the percentile estimates. We present a simple method for estimating the grain size confidence intervals about sample percentiles derived from standard Wolman or pebble count samples of bed surface texture. The width of a grain size confidence interval depends on the confidence level selected by the user (e.g., 95 %), the number of stones sampled to generate the cumulative frequency distribution, and the shape of the frequency distribution itself. For a 95 % confidence level, the computed confidence interval would include the true grain size parameter in 95 out of 100 trials, on average. The method presented here uses binomial theory to calculate a percentile confidence interval for each percentile of interest, then maps that confidence interval onto the cumulative frequency distribution of the sample in order to calculate the more useful grain size confidence interval. The validity of this approach is confirmed by comparing the predictions using binomial theory with estimates of the grain size confidence interval based on repeated sampling from a known population. We also developed a two-sample test of the equality of a given grain size percentile (e.g., D50), which can be used to compare different sites, sampling methods, or operators. The test can be applied with either individual or binned grain size data. These analyses are implemented in the freely available GSDtools package, written in the R language. A solution using the normal approximation to the binomial distribution is implemented in a spreadsheet that accompanies this paper. Applying our approach to various samples of grain size distributions in the field, we find that the standard sample size of 100 observations is typically associated with uncertainty estimates ranging from about ±15 % to ±30 %, which may be unacceptably large for many applications. In comparison, a sample of 500 stones produces uncertainty estimates ranging from about ±9 % to ±18 %. In order to help workers develop appropriate sampling approaches that produce the desired level of precision, we present simple equations that approximate the proportional uncertainty associated with the 50th and 84th percentiles of the distribution as a function of sample size and sorting coefficient; the true uncertainty in any sample depends on the shape of the sample distribution and can only be accurately estimated once the sample has been collected.

Modelling submerged fluvial substrates with structure‐from‐motion photogrammetry

AbstractNatural sediment regimes of fluvial systems are variable and important to the biological and physical structures of rivers, yet watershed degradation has led to increased fine sediments entering and aggrading in rivers. As a result, quantifying substrate composition is important for targeting and monitoring restoration. Conventional methods for assessing substrate composition (e.g., pebble counts) can be time‐consuming and biased. We examined the use of the photogrammetric technique, structure‐from‐motion (SfM), as an alternative method by measuring streambed roughness. We expanded its application to submerged substrates in an artificial streambed to assess if roughness could predict pebble count substrate size percentiles across a range of manipulated levels of fine sediment aggradation. We then assessed the use of SfM in a free‐flowing river streambed. Results from the artificial streambed with coarse substrates (≤31% added fine sediment) revealed that repeated SfM models of the same streambed had a high degree of similarity (mean difference = 1 mm) and a strong relationship between SfM‐derived roughness and pebble counts (r2 &gt; .95). This relationship was weaker (r2 &lt; .66) and violated regression variance assumptions when substrates had up to 47% (55.7 kg) fines added, possibly due to SfM characterizing details not captured by pebble counts. In the natural streambed, there was a strong relationship between percentiles from the SfM model roughness and pebble count diameter (r2 = .96). SfM appears to be an efficient and appropriate alternative to direct substrate measurements across a broad range of streambed substrate compositions and thus a useful tool to model streambed morphology.

Terrestrial laser scanning and structure-from-motion photogrammetry concordance analysis for describing the surface layer of gravel beds

Terrestrial laser scanning (TLS) and structure-from-motion photogrammetry (SfMp) offer rapid, non-invasive surveying of in situ gravels. Numerous studies have used the point clouds derived from TLS or SfMp to quantify surface layer characteristics, but direct comparison of the methods for grain-scale analysis has received relatively little attention to date. Comparing equivalent products of different data capture methods is critical as differences in errors and sampling biases between the two methods may produce different outputs, effecting further analysis. The sampling biases and errors related to SfMp and TLS lead to differences in the point clouds produced by each method. The metrics derived from the point clouds are therefore likely to differ, potentially leading to different inputs for entrainment threshold models, different trends in surface layer development being identified and different trajectories for physical processes and habitat quality being predicted. This paper provides a direct comparison between TLS and SfMp surveys of an exposed gravel bar for three different survey periods following inundation and reworking of the bar surface during high flow events. The point clouds derived from the two methods are used to describe changes in the character of the surface layer between bar inundation events, and comparisons are made with descriptions derived from conventional pebble counts. The results found differences in the metrics derived using each method do exist, but the grid resolution used to detrend the surfaces and identify spatial variations in surface layer characteristics had a greater impact than survey method. Further research is required to understand the significance of these variations for quantifying surface texture and structure and for predicting entrainment thresholds and transport rates.

Relative performance of three stream bed stability indices as indicators of stream health.

Bed stability is an important stream habitat attribute because it affects geomorphology and biotic communities. Natural resource managers desire indices of bed stability that can be used under a wide range of geomorphic conditions, are biologically meaningful, and are easily incorporated into sampling protocols. To eliminate potential bias due to presence of instream wood and increase precision of stability values, we modified a stream bed instability index (ISI) to include measurements of bankfull depth (d bf) and median particle diameter (D 50) only in riffles and increased the pebble count to decrease variability (i.e., increase precision) in D 50 . The new riffle-based instability index (RISI) was compared to two established indices: ISI and the riffle stability index (RSI). RISI and ISI were strongly associated with each other but neither was closely associated with RSI. RISI and ISI were closely associated with both a diatom- and two macrovertebrate-based stream health indices, but RSI was only weakly associated with the macroinvertebrate indices. Unexpectedly, precision of D 50 did not differ between RISI and ISI. Results suggest that RISI is a viable alternative to both ISI and RSI for evaluating bed stability in multiple stream types. With few data requirements and a simple protocol, RISI may also better conform to riffle-based sampling methods used by some water quality practitioners.

OBTAINING AND TESTING COARSE GRAIN SIZE DISTRIBUTIONS FROM PHOTOGRAPHIC GRID COUNTS

The grain size distribution (GSD) of surface bed material in alluvial rivers is of interest in many geological, ecological and engineering applications. In this work, which is a part of our broader Ph.D research in Vouraikos river on sediment transport, we are testing the possibility of obtaining such a distribution from photographs taken at the field (grid sampling), compared with the standard method which is the “pebble count”. We have also examined and quantified the errors resulting from radial distortion of the photographs. The motive of the work was to explore the opportunity of substituting field work for laboratory work. Results show that for this method to give reliable results, a better knowledge of the site-specific conditions is needed, which, in turn, requires more field work.

Probabilistic flood inundation mapping at ungauged streams due to roughness coefficient uncertainty in hydraulic modelling

Abstract. Probabilistic flood inundation mapping is performed and analysed at the ungauged Xerias stream reach, Volos, Greece. The study evaluates the uncertainty introduced by the roughness coefficient values on hydraulic models in flood inundation modelling and mapping. The well-established one-dimensional (1-D) hydraulic model, HEC-RAS is selected and linked to Monte-Carlo simulations of hydraulic roughness. Terrestrial Laser Scanner data have been used to produce a high quality DEM for input data uncertainty minimisation and to improve determination accuracy on stream channel topography required by the hydraulic model. Initial Manning's n roughness coefficient values are based on pebble count field surveys and empirical formulas. Various theoretical probability distributions are fitted and evaluated on their accuracy to represent the estimated roughness values. Finally, Latin Hypercube Sampling has been used for generation of different sets of Manning roughness values and flood inundation probability maps have been created with the use of Monte Carlo simulations. Historical flood extent data, from an extreme historical flash flood event, are used for validation of the method. The calibration process is based on a binary wet-dry reasoning with the use of Median Absolute Percentage Error evaluation metric. The results show that the proposed procedure supports probabilistic flood hazard mapping at ungauged rivers and provides water resources managers with valuable information for planning and implementing flood risk mitigation strategies.

Alluvial mining and its impact on deterioration of physical health of Malekhu Khola, Central Nepal

The Malekhu Khola is accessible and potential for the construction materials in today’s developing phase. The study mainly concerns with mining of construction aggregate and effect of indiscriminate mining from river and its basin area which may impose many harmful effects on environment. The objective of the study is to identify the condition of river using morphological and physical parameters, and to investigate the factors which are directly responsible for the environmental degradation. Such study of rivers in present context is essential as it provides insights of strength of the river. To examine the circumstance of river, the study was proceed by selecting the area into three reaches of each 500 m, and further each reaches are divided into six transects. Both reach-scale and transect-scale attributes were assessed. The scoring was done by adding all the attributes of the standard survey sheet. A cross-sectional study was carried out along 3 different stations, Reach 1 to Reach 3 from upstream to downstream. Various fluvial parameters and data from pebble count were used to calculate morphological parameter and grain size distribution. The channel sediments were found to be extremely poorly sorted, the distribution of grain size is varied from transect to transect, which might be the result of unplanned mining. All the result acquired from field study and satellite image confirms that the river is worsening day by day. The formation of pools and deposition of organic matter show that the river is not flowing in its natural way. After all the examination, it indicates that the Malekhu Khola is being violated by the human and mining activities, thus the river reclamation measure is required at abandoned mining sites to maintain the Malekhu Khola channel morphology and habitat of the river.Bulletin of the Department of Geology, Vol. 18, 2015, pp. 59-66

Fluvial morphology and sediment transport of the Malekhu Khola, Central Nepal Lesser Himalaya

Areas near the rivers and streams have been widely used for settlement, development works and agriculture due to availability of the resources such as water, aggregates and comparatively easier terrain. It is very important to understand prevailing fluvial conditions for sustainable output. The fluvial conditions of the Malekhu Watershed including the river characteristics, sediment transport and sediment dynamics were studied. Ten river transects and the corresponding segments of the Malekhu Khola were surveyed for cross-sections and longitudinal profiles. Samples were collected in each of the transects and were analysed for suspended sediment concentration. The riverbed sampling was made using Wolman’s pebble count for establishing grain size distribution. Manning’s roughness coefficients were determined to estimate discharge. The study shows that the Malekhu Khola is a sixth order stream. It has been classified into A4-, B4- and C4-type streams. The hypsometric analysis of the Malekhu Watershed shows that it is in mature stage of erosion. Sediment grain size slightly increases downstream but sorting remains extremely poor to moderately poor. The Malekhu Khola shows eroding tendency at 1.2 km, 16.6 km and 20 km from the origin and brings larger particles only during high flow period at the remaining transects. Mean Suspended Sediment Concentrations (SSC) for the Malekhu Khola was 72.14 mg/L, and it increases with increasing discharge and increasing watershed area and is related to velocity of the river, mining activities and local tributaries.Bulletin of the Department of Geology, Vol. 18, 2015, pp. 35-48

Sediment size distribution at three rivers with different types of land use in Endau Catchment Area, Kluang, Johor, Malaysia

Land use along the river will determine the substrate size and distributions. Substrate particle size will influence aquatic life because substrate is one of the main components forming aquatic habitat. This aquatic habitat is very important in determining river water quality as well as river health. Therefore, identifying the sediment size distribution based on land use is very crucial in river maintenance. The objective of this study is to determine the particle size variation between upper reach and lower reach of the sampling station as well as variation from different land use cover at different sub-catchment areas. The pebble counts was conducted at upper reach station and lower reach station by applying the Pebble Count Protocols developed by the West Virginia Department of Environmental Protection and Wolmen Pebble Count Procedure. The average median (D50) for Dengar River ranged between 4.5 mm for upper portion and 2.4 mm for lower portion. Similar observations were found at the Mengkibol River, where particle size ranged between 3.0 mm for upper portion and 2.4 mm for lower portion. As for Madek River which represents land use area for logging activity, the results obtained were different in which the upper portion the particle size was smaller (D50 = 4.5 mm) than the lower portion (D50 = 41.5 mm). The finding of this study will be a basis for river catchment management study and can be used by river management authorities in the country for river management planning.Keyword: pebble count, sediment size, average median, fine gravel, very fine gravel, urban, oil palm, logging, land use