Riverine Sand Research Articles

Flood‑Induced Health Vulnerability: A Case Study of Nirmal Char in Murshidabad District, West Bengal

The chars (riverine sand bars) are poorly connected to the mainland and are prone to natural hazards like floods. Char lands are occupied by people from lower-income groups who have been living in an ecologically fragile landscape. The frequent floods affect the char dwellers’ health and health infrastructures and limit access to health care services. A study has been conducted to assess the health vulnerability of char dwellers in Nirmal Char in the Murshidabad district. The current study explores the impact of floods on the health of char dwellers during pre-flood season which differs from or is similar to flood season. The health vulnerability of the char dwellers was measured in terms of flood exposure, flood sensitivity and flood adaptive capacity. The primary data collected from selected households reveals that the livelihood conditions of most of the char dwellers have been severely affected during the flood, introducing different health-related diseases (i.e. typhoid fever, malaria, diarrhea and dengue) catalysed due to the lack of accessibility to health care facilities. The present study showed that up to 97.87% of households had a high level of vulnerability and 2.13% had a moderate level of vulnerability. We concluded that early flood warning, flood prevention measures and long-term mitigation strategies must be strengthened for char dwellers as they face greater health problems. Therefore, a context-specific sustainable health policy intervention is required to improve the adaption capacity of char dwellers.

Mapping and modeling riverine sand and gravel mining at the sub-continental scale: A case study for India

Sand and gravel are amongst the most mined and consumed resources in the world, especially in the Global South where the demand for sand increases due to urbanization. Large parts of this extraction occur in rivers, with adverse environmental consequences. Mitigation of riverine sand and gravel mining (RSM) impacts on freshwater systems requires a robust understanding of the scale and controlling factors of RSM. However, very limited data exist on the occurrence of this process. This is especially true over larger spatial scales. Here we aim to bridge this gap and gain more insight into the occurrence of RSM at a subcontinental scale. More specifically, we (1) develop a systematic mapping procedure of RSM to collect the first large-scale dataset of RSM occurrence focusing on India as a case study. Using this dataset, we then (2) statistically analyze the factors potentially controlling spatial patterns of RSM across India. Factors were included that represent both the demand and supply of sand. Based on these results, we (3) develop a logistic regression model to estimate the probability of RSM occurrence. Overall, our work shows the enormous scale of RSM in India: of the 808 randomly selected and investigated river reaches (with lengths of ca. 10 km), 61.6 % showed clear evidence of RSM. Statistical analyses revealed that the presence of RSM is mainly linked to variables describing the demand for sand (e.g. distance to city, percentage of built-up area around the river reach), while variables relating to supply (e.g. soil texture, expected sediment discharge) showed much weaker correlations. Only rainfall variability was a clearly significant factor, which may relate to river reach accessibility. Based on these findings, we present a first model and map that predicts the susceptibility to RSM in India.

A model based on the evolutionary game theory for implementing green mining principles in riverine sand and gravel resources

An evolutionary Game Theory (GT) model was presented to study the dynamics between the mine management and government for implementing Green Mining (GM) principles in riverine sand and gravel mines. In this regard, a game was planned in which the mine management is the executing agent, while the government acts as the supervisor. Investigating the performance of the proposed model, regulatory factors such as governmental incentives and penalties were introduced. In order to compare the results, the effects of regulatory measures on strategy changes by mine management were analyzed into two distinct scenarios: classical GT and evolutionary GT, which provide valuable insights into the complex interactions between mine management and government. The Shahed sand and gravel mine near the Kordan River in Alborz province, Iran, was selected as a case study to validate the developed GT models. The results obtained from the classical GT model showed that a fine of $ 0.2 per tonne and a 30% governmental incentive for the mining and equipment costs, may encourage the mine management to choose the GM strategy. Conversely, the results of the evolutionary GT model indicated that by increasing the government subsidy from 30% to 50%, the rate of encouraging the mine management to choose the GM strategy could be accelerated. This situation is similar to the government incentive for mine management in case of fines from $0.2 to $1 per tonne. According to the results of the evolutionary GT model, when the population ratio increases over time, the selected strategy is more compatible and powerful compared to other ones. Therefore, it is concluded that the mine management in Shahed mine may turn to the GM strategy by imposing a penalty more than $0.6 per tonne.

“Local people want to keep their sand”: Variations in community perceptions and everyday resistance to sand mining across the Red River, Vietnam

The Red River Delta is Vietnam's most densely populated catchment, with its communities intertwined with, and dependent upon, the delta and its resources. Intensive, widespread riverine sand extraction is linked to substantial degradation of the delta, directly threatening these livelihoods. The response of rural communities is to resist in various ways, dependent upon a complex matrix of geospatial factors. Using an ethnographic approach, we explore factors contributing to the scale and patterns of resistance to sand mining of both an upstream riverine community and downstream coastal community in the Red River Delta. The riverine community protest openly to illegal mining directly threatening their river-connected livelihoods, manifest through reporting to authorities, bankside protests and involvement of mass media. In contrast, the coastal community have shifted from open protest, through openly reporting to the authorities, to closed forms of within-village gossip. Here, resistance patterns are driven by proximity to mining sites, perceived impact of mining, and pre-existing structural legislative mechanisms. Under scenarios of rapidly increasing rates of sand extraction to satisfy wider global needs, there is an urgent need for studies of local-scale impacts and resistance, capturing socio-economic characteristics of communities, to better plan for future scenarios of resource extraction and exploitation.

Study the effect of MRF Model based NC classifier with different distance measures and parameters

The accuracy of satellite image classification and the computational complexity is reduced due to the image's noisy pixels. Therefore, spatial contextual information-based classifiers are required to handle the noisy pixels and obtain the neighborhood information. This paper represents Noise clustering (NC) based Markov Random Field (MRF) models (SP, DA (H1, H2, H3, and H4)) that handle the noisy pixels and provide the information. The Smoothing Prior (SP) and Discontinuity Adaptive (DA) models are useful for reducing noise by smoothing the images and showing the boundary of classes, respectively. This study has carried out a comparative study among MRF model-based NC classifiers SP and DA for different distance measures and parameters. MRF models based on NC classifiers were tested for classifying Eucalyptus, Water, Riverine sand, Grassland, Dense Forest, and Wheat classes using the Formosat-2 and Landsat-8 multispectral images of the Haridwar area. The DA (H1) model provides the best overall accuracy (85.09%) for m=1.3, λ=0.2, δ=104,γ=0.8, and Mean Absolute Difference.

Spatial and Temporal Changes of Sand Mining in the Yangtze River Basin since the Establishment of the Three Gorges Dam.

The global demand for sand and gravel is at 50 billion tons per year, far exceeding global resource capacities. It reached 7.6 billion tons in 2021 in the Yangtze River Basin (YRB), China. However, production is severely limited in the YRB. Therefore, the incongruity between the supply and demand of river sand is prominent. Wise management of decreasing sand resources in the YRB has become critical since the Three Gorges Dam became operational in 2003. This study synthesized spatial and temporal changes in sand mining activities and quantities along the Yangtze River and its major tributaries from 2004 to 2020. Results from the study show that the mining amount during the period reached 76.2 million tons annually. At the same time, riverine suspended sediment discharge (SSD) downstream of the Three Gorges Dam decreased largely. SSD reduction leads to riverbed erosion, further limiting the riverine sand and gravel sources for mining. Thus, alternative sand and gravel resources, as well as optimizing supply/demand balance, are necessary for sustainable development. There is an urgent need to assess the relationship between river sand resources and exploitation in the YRB for creating a sand and gravel data management system in order to cope with the increasing incongruity between their supply and demand.

Soil degradations in the IGP of central Haryana, India-a spatial assessment for reclamation and management.

Natural and anthropogenic processes are primary drivers for soil degradations in the Gangetic plain of India. Indian Remote Sensing (IRS) data was used to assess soil degradations and study spatial changes comparing with the legacy datasets. Based on the nature, extent, and degrees of limitations, these soils were evaluated to suggest suitable reclamation and management options. Typical strong signature (white tones) from a barren highly salinized soil (P3, P6, P9, P11, and P15) and higher energy absorption (blue-black tones) from a permanent waterlogged surface (P13, P14, P10) in the irrigated areas have favored delineation of salt-affected, strong, and permanent waterlogged areas. Moderate and slightly salt-affected soils (P1, P2, P4, P5, P7, P8, and P12) and the areas with high water table depths (P13 and P14) have shown mixed spectral signatures for associations of soil, water, and crops and were mapped using ground truth and soil chemical analysis data. Irrigation with poor quality ground water (RSC: 1.2 to 12.3 me L-1) has prompted developing salinity and sodicity in P2, P5, and P11, while irrigation in poorly drained areas caused appearance of waterlogging (WTD < 1.5m) and salinization (P3, P5, P7, P9, P13, P14). The gypsum application and sub-surface drainage (SSD) techniques have enhanced soil reclamation by (i) neutralizing CO32 - and HCO3 - in P12 (pH 9.2, ESP 24) and (ii) controlling soil salinity (EC 3.0 dS m-1) and waterlogging (WTD > 1.5m) in P14. Soils with CaCO3 layers at shallow depth in P3 (0.7-4.2%), P6 (1.2-7.1%), P9 (8-16%), P11 (4-15%), and P13 (0.9-9.4%) were managed using forest plantations. Ground water with high SAR in T1 to T7 can be applied for agriculture using mixing or cyclic mode. Water with high RSC in T4, T5, T7, T8, T9, and T10 needs treatment with gypsum. A significant area (~ 24.87%) of salt-affected soils was reclaimed since 1971. Prominent changes (3.27 to 17.71%) were shown in Panipat and Karnal districts. Small areas of brick kiln (P11), industrial effluent (P10), riverine sand, partially stabilized dunes, and mining have appeared due to anthropogenic activities.

Augmenting possibilistic c-means classifier to handle noise and within class heterogeneity in classification

A conventional possibilistic c-mean (PCM)-based algorithm uses means or variance–covariance statistical variables computed from training data sets for classification. Two objectives were covered; in the first objective, the PCM classifier using the training samples as “individual sample as mean” (PCM_IM) in place of “mean” was experimented with handling heterogeneity within the class. The second objective, the PCM-based local convolutional method, was tested with different parameters to handle the noisy pixel. Local convolution algorithms reduce the effect of noise, and PCM_IM handles heterogeneity to enhance the classification performance within the class. The optimized algorithm was first calculated in this research by applying the local convolutional methods for different distance measures and fuzziness factors. This optimized algorithm was obtained by classifying the dense forest, eucalyptus, riverine sand, water, wheat, and grassland classes using the multispectral images of Landsat-8 and Formosat-2 of the Haridwar area. It was observed that the Bray–Curtis distance measures at m = 2.9 (fuzziness factor) for possibilistic local information c-means using the base PCM classifier yields the highest overall accuracy (OA) (86.37%), irrespective of the classifier. Then, PCM_IM provides a classwise and OA that handles heterogeneity within the class. The classwise accuracy of dense forest, eucalyptus, grassland, sand, water, and wheat is 88.12%, 95.29%, 78.79%, 89.17%, 89.72%, and 92.43%, respectively, and the OA is 85.72%, whereas OA of the PCM classifier using the training sample as mean is 75.18%.

Feature selection for improved classification accuracy targeting riverine sand mapping

Regular monitoring of riverine sand is crucial for its sustainable management. Towards readily generating spatial information regarding the extent of riverine sand, this study utilizes satellite-based remote sensing data as input features while applying Support Vector Machine (SVM) classifier to discern the inherent land cover classes. The input features comprised of spectral bands, derived spectral indices, derived textural features and ancillary information such as elevation, slope and aspect. The objective of this study was to identify a set of features that help improve the SVM classification accuracy with respect to the benchmark accuracy achieved by using only the spectral bands. Apart from testing a few commonly used logical combinations of features, the study focused on employing the Correlation-based Feature Selection (CFS) method along with the best-first search algorithm to generate a feature-set that comprised of most relevant and least correlated features. This feature-set was found to improve the SVM classification accuracy by 2.9% with respect to the benchmark value. Further, when tested with the limited number of training samples, similar results were achieved. This study proves that it is beneficial to utilize the CFS method for feature selection prior to SVM classification and recommends a set of 19 remote sensing derived features that are relevant towards riverine sand mapping.

Turning a tragedy into large-scale barrier island restoration in Louisiana: A three-project case study

Louisiana has successfully utilized the proceeds from the fines imposed for the Deepwater Horizon incident to significantly jump start barrier island restoration as identified in the Coastal Protection and Restoration Authority (CPRA) of Louisiana Coastal Master Plan (CPRA 2017). The Riverine Sand Mining/ Scofield Island Restoration (BA-40) project was the first to be implemented through a commitment of remaining funds in the initial emergency protective berms’ construction budget formulated into the Berms to Barrier Islands plan. The berm/ restoration conversion at Scofield Island was the first to utilize this funding mechanism. The Caminada Headland Beach and Dune Restoration–Increment II (BA-143) project was funded through the National Fish and Wildlife (NFWF) Gulf Environmental Benefit Fund and capitalized on a prior project constructed to the west completing the beach and dune restoration of the entire headland. Lastly, the Caillou Lake Headlands Restoration (TE-100) project was funded through the Natural Resource Damage Assessment (NRDA). The TE-100 project restored the entire degraded beach and dune system backed by a created marsh habitat to complement a prior restoration effort. Scofield Island is located west of the active Mississippi River bird’s foot delta in Plaquemines Parish, Louisiana. A primary objective of this project was the excavation and delivery of Mississippi riverine sand for beach and dune restoration; a first in our nation’s history. Multiple design and construction challenges arose requiring the CPRA, consulting team, and construction contractor to adapt. Construction of the beach and dune component of this project required approximately 22 miles (mi) of pipeline and four booster pumps along a sediment pipeline corridor that crossed two hurricane protection levees, went underneath two highways and a navigation channel, traversed the Empire Waterway, crossed Pelican Island, entered the Gulf of Mexico, and extended to Scofield Island. The restoration footprint length was approximately 2.4 mi, total volume placed was approximately 3.5 million cubic yards (MCY), and the benefit equaled 510 restored acres (CEC 2014). The pipeline corridor has subsequently been utilized for two other restoration projects, Shell Island East Berm Barrier Island Restoration (BA-110) and Shell Island West NRDA Restoration (BA-111). As a first in Louisiana’s restoration history, the Caminada Headland Beach and Dune Restoration–Increments I and II (BA-45 and BA-143) utilized sand dredged from Ship Shoal, an Outer Continental Shelf (OCS) sand resource located approximately 26-38 mi from the restoration areas. The 13.3 mi long headland was restored with approximately 3.7 MCY for BA-45 and 5.5 MCY for BA-143 from the borrow area (CEC 2015 and CEC 2017). A combination of cutterhead dredge/scow barges and hopper dredges were used to construct the project. A key goal of this project was restoring and protecting the fragile ecosystem which provides critical habitat for nesting shorebirds. The headland is of critical importance in serving as a defense of our national energy infrastructure. The western portion of the headland directly protects Port Fourchon, one of the nation’s most important energy ports. Caillou Lake Headlands (TE-100), known locally as Whiskey Island, is centrally located in the Isle Dernieres chain and it is a remnant of the single, larger Isle Dernieres (Last Island), which was segmented into multiple smaller islands by a major hurricane in 1856. The project included restoring the beach and dune along approximately 4.5 mi while simultaneously creating a marsh platform along approximately 5,500 feet (ft) utilizing 10.4 MCY of sand from the borrow area (CEC 2018). The borrow area lies within Ship Shoal OCS Lease Block 88 located over 10 mi along the conveyance corridor offshore of Whiskey Island. This project represents the largest barrier island restoration project to date in terms of volume per linear foot of shoreline with an average density of over 441 cubic yards per linear foot (CEC 2018).

Impacts of riverine sand mining on freshwater ecosystems: A review of the scientific evidence and guidance for future research

AbstractSand mining (used here as a generic term that includes mining of any riverine aggregates regardless of particle size) is a global activity that is receiving increasing media attention due to perceived negative environmental and social impacts. As calls grow for stronger regulation of mining, there is a need to understand the scientific evidence to support effective management. This paper summarizes the results of a structured literature review addressing the question, “What evidence is there of impacts of sand mining on ecosystem structure, process, and biodiversity in rivers, floodplains, and estuaries?” The review found that most investigations have focused on temperate rivers where sand mining occurred historically but has now ceased. Channel incision was the most common physical impact identified; other physical responses, including habitat disturbance, alteration of riparian zones, and changes to downstream sediment transport, were highly variable and dependant on river characteristics. Ecosystem attributes affected included macroinvertebrate drift, fish movements, species abundance and community structures, and food web dynamics. Studies often inferred impacts on populations, but supporting data were scarce. Limited evidence suggests that rivers can sustain extraction if volumes are within the natural sediment load variability. Significantly, the countries and rivers for which there is science‐based evidence related to sand mining are not those where extensive sand mining is currently reported. The lack of scientific and systematic studies of sand mining in these countries prevents accurate quantification of mined volumes or the type, extent, and magnitude of any impacts. Additional research into how sand mining is affecting ecosystem services, impacting biodiversity and particularly threatened species, and how mining impacts interact with other activities or threats is urgently required.

Sand source and formation mechanism of riverine sand dunes: a case study in Xiangshui River, China

Riverine sand dunes develop as a result of fluvial-aeolian interactions. The primarily barchan dune chains along the Xiangshui River (a branch of the Xar Moron River in the western part of the Horqin Sandy Land of China) form a typical riverine dune field. We collected a series of samples from the riverine sand dunes parallel to the direction of the prevailing wind and investigated the sand sources and formation mechanisms of these dunes by determining the grain size, heavy mineral content and optically stimulated luminescence (OSL) of the samples. The sand of the near-river dunes was coarser than the sand of the dunes distant from the river, indicating that coarse sand of the valley mainly deposited on near-river dunes. The heavy mineral analysis suggested that wind-sand activity levels were intense on the upwind dunes, but relatively weak on the downwind dunes. This indicated that the sand sources for the near-river dunes were more abundant than those of the distant dunes. Our OSL analysis of samples suggested that the deposition rates on dunes near the river were greater than the deposition rates on dunes distant from the river. The development of dunes along the river indicated that the river played an important role in dune formation and development. In addition, airflow fluctuation and the formation of the waveform dunes had a type of feedback relationship. Grain size, heavy mineral and OSL analyses are widely used methods in wind-sand research. Sand dune grain size characteristics reflect the effects of airflow on the transport and separation of sand materials, as well as the physical characteristics of the sand sources. Heavy mineral characteristics are often used to investigate the relationships between sediments and sand sources. OSL indicates dune age, revealing formation of dunes. Therefore, it is useful to explore dune sand sources, as well as the mechanisms underlying dune formation, by determining grain size, heavy mineral content and OSL. This study investigated the sand sources of riverine dunes and provided new information about riverine dune formation and development.

Landscape Pattern and Variation of Riverine Sand Dunes in the Kunye River Basin, China

Landscape Pattern and Variation of Riverine Sand Dunes in the Kunye River Basin, China

Decadal‐Scale Riverbed Deformation and Sand Budget of the Last 500 km of the Mississippi River: Insights Into Natural and River Engineering Effects on a Large Alluvial River

AbstractAlluvial rivers are shaped by interactions of flow and sediment transport. Their lower reaches to the world's oceans are highly dynamic, often presenting engineering and management challenges. Here we analyzed over 6,000 single‐beam cross‐sectional measurements surveyed in 1992, 2004, and 2013 in the last 500‐km reach of the highly engineered Mississippi River, also known as the lowermost Mississippi River or LmMR, starting from the river's Gulf outlet to its avulsion into the Atchafalaya River. We applied inverse distance weighted interpolation to downscale the survey records into 10 × 10 m digital elevation models. We assessed riverbed deformation from bank to bank and quantified changes in riverbed sediment volume. The goal of our study is to test the hypothesis that the lower reach of a large alluvial river can function as a conduit for sediment transport under the current engineering focus of navigation safety and flood control. Our analysis shows that in the past two decades, nearly 70% of the riverine sand was trapped within the LmMR, and continuous riverbed aggradation occurred below the Mississippi‐Atchafalaya diversion, presenting favorable backwater conditions for avulsion. Backwater effects have mainly controlled riverbed deformation in the LmMR, while flow reduction may have also contributed to the channel aggradation in the uppermost and lowermost reaches. The study reveals the considerable complexity of geomorphic responses of a large alluvial river to human interventions, strongly suggesting that future river engineering and management of the world's alluvial rivers should focus on strategies and solutions that will improve sediment transport.

Observational and numerical particle tracking to examine sediment dynamics in a Mississippi River delta diversion

River diversions may serve as useful restoration tools along coastal deltas experiencing land loss due to high rates of relative sea-level rise and the disruption of natural sediment supply. Diversions mitigate land loss by serving as new sediment sources for land building areas in basins proximal to river channels. However, because of the paucity of active diversions, little is known about how diversion receiving-basins evacuate or retain the sediment required to build new land. This study uses observational and numerical particle tracking to investigate the behavior of riverine sand and silt as it enters and passes through the West Bay diversion receiving-basin located on the lowermost Mississippi River delta, USA. Fluorescent sediment tracer was deployed and tracked within the bed sediment over a five-month period to identify locations of sediment deposition in the receiving-basin and nearby river channel. A computational fluid dynamics model with a Lagrangian sediment transport module was employed to predict selective pathways for riverine flow and sand and silt particles through the receiving-basin. Observations of the fluorescent tracer provides snapshots of the integrated sediment response to the full range of drivers in the natural system; the numerical model results offer a continuous map of sediment advection vectors through the receiving basin in response to river-generated currents. Together, these methods provide insight into local and basin-wide values of sediment retention as influenced by grain size, transport time, and basin morphology. Results show that after two weeks of low Mississippi River discharge, basin silt retention was approximately 60% but was reduced to 4% at the conclusion of the study. Riverine sand retention was approximately near 100% at two weeks and 40% over the study period. Modeled sediment storage was predicted to be greatest at the margins of the primary basin transport pathway; this matched the observed dynamics of the silt tracer but did not match the behavior of the sand tracer. The degree to which the observational measurements deviate from the model predictions may indicate the relative influence of physical processes other than the mean riverine generated currents, such as tides, wind generated currents, and waves.

Soft sediment deformation associated with the East Patna Fault south of the Ganga River, northern India: Influence of the Himalayan tectonics on the southern Ganga plain

The geomorphic, tectonic and seismic aspects of the Ganga plain have been studied by several workers in the recent decades. However, the northern part of this tectonically active plain has been the prime focus in most of the studies. The region to the south of the Ganga River requires necessary attention, especially, regarding the seismic activities. The region lying immediately south of the Outer Himalayas (i.e. the Ganga plain) responds to the stress regime of the Himalayan Frontal Thrust Zone by movement along the existing basement faults (extending from the Indian Peninsula) and creating new surface faults within the sediment cover as well. As a result, several earthquakes have been recorded along these basement faults, such as the great earthquakes of 1934 and 1988 associated with the East Patna Fault. Large zones of ground failure and liquefaction in north Bihar (close to the Himalayan front), have been recorded associated with these earthquakes. The present study reports the soft sediment deformation structures from the south Bihar associated with the prehistoric earthquakes near the East Patna Fault for the first time.The seismites have been observed in the riverine sand bed of the Dardha River close to the East Patna Fault. Several types of liquefaction-induced deformation structures such as pillar and pocket structure, thixotropic wedge, liquefaction cusps and other water escape structures have been identified.The location of the observed seismites within the deformed zone of the East Patna Fault clearly indicates their formation due to activities along this fault. However, the distance of the liquefaction site from the recorded epicenters suggests its dissociation with the recorded earthquakes so far and hence possibly relates to any prehistoric seismic event. The occurrence of the earthquakes of a magnitude capable of forming liquefaction structure in the southern Ganga plain indicates the transfer of stress regime far from the Himalayan front into the peninsular region through these basement faults. Northward extension of the East Patna Fault coincides with the region of the Himalayan front, which corresponds to a less slip potential. Therefore, an association of frequent earthquakes in this region indicates strain release along the East Patna Fault.

Comparison between Possibilistic c-Means (PCM) and Artificial Neural Network (ANN) Classification Algorithms in Land use/ Land cover Classification

There are several statistical classification algorithms available for land use/land cover classification. However, each has a certain bias or compromise. Some methods like the parallel piped approach in supervised classification, cannot classify continuous regions within a feature. On the other hand, while unsupervised classification method takes maximum advantage of spectral variability in an image, the maximally separable clusters in spectral space may not do much for our perception of important classes in a given study area. In this research, the output of an ANN algorithm was compared with the Possibilistic c-Means an improvement of the fuzzy c-Means on both moderate resolutions Landsat8 and a high resolution Formosat 2 images. The Formosat 2 image comes with an 8m spectral resolution on the multispectral data. This multispectral image data was resampled to 10m in order to maintain a uniform ratio of 1:3 against Landsat 8 image. Six classes were chosen for analysis including: Dense forest, eucalyptus, water, grassland, wheat and riverine sand. Using a standard false color composite (FCC), the six features reflected differently in the infrared region with wheat producing the brightest pixel values. Signature collection per class was therefore easily obtained for all classifications. The output of both ANN and FCM, were analyzed separately for accuracy and an error matrix generated to assess the quality and accuracy of the classification algorithms. When you compare the results of the two methods on a per-class-basis, ANN had a crisper output compared to PCM which yielded clusters with pixels especially on the moderate resolution Landsat 8 imagery.

Impact assessment of watershed management programmes on land use/land cover dynamics using remote sensing and GIS

The semi-arid study area, which is the part of Khan-Kali watershed and Anas River from Gujarat, India, was intensely targeted for land reclamation by various government and non-government organizations since last decade. The present study aims at impact assessment of watershed management measure and determines the dynamics of land use/land cover (LU/LC) and vegetation cover in the agricultural area using multi-temporal Remote Sensing (RS) data and Geographical Information System (GIS). The entire study is divided into two parts. The first part deals with LU/LC classification, post classification analysis and change detection over 2001–2011. The ancillary data of both Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) were applied at during supervised classification stage and agricultural masks were applied at post supervised classification stage to improve the classification accuracy. In the second part of the study the RS data of the years 2001 and 2012 were used to calculate NDVI, and subsequently the NDVI differencing to detect the change of vegetation cover in agricultural land. Both the changes were estimated at watershed and mini-watershed levels. Specifically, the mini-watershed level changes were evaluated with respect to treated area. The results indicated that the integration of ancillary data with supervised classification has improved the classification accuracy of LU/LC maps by 91.8% and 95.5% for 2001 and 2011, respectively. The key LU/LC changes at watershed level were increased in both the water body and scrub forest areas and decrease in the forest/dense vegetation, barren land and riverine sand areas. At mini-watershed level, for the mini-watersheds treated- (1) less than 25% indicated decrease in forest/dense vegetation and increase in scrub forest area (2) between 25–50% increase in water body and decrease in scrub forest area; and (3) more than 50% indicated increase in water body and decrease in forest/dense vegetation area. To mitigate the observed localised deforestation, the immediate natural vegetation conservation is required. In spite of aridity remain present over the years 2011–2012, the area under agricultural crops showed an increase in high NDVI and decrease in low NDVI values at both watershed and mini-watershed levels. The ground water levels were also increased from 2001 to 2011. The study inferred that the watershed management programmes showed the overall positive impact on the study area.

Taxonomic revision of the genus Atopomesus Myers, 1927 (Characiformes: Characidae), with comments on its phylogenetic relationships

The monotypic genus Atopomesus, a poorly known member of the family Characidae, is re-described. Atopomesus pachyodus is endemic to the Rio Negro basin, where it feeds on aquatic insect larvae, and seems to occur mostly in riverine sand banks and beaches. A. pachyodus was originally described as a member of the Characidae subfamily Cheirodontinae, but has been considered as an Characidae incertae sedis based on relatively superficial studies of its dentition and external morphology. However, according to the morphological analyses presented herein, a close relationship between A. pachyodus and the members the subfamily Aphyoditeinae is hypothesized. The inclusion of A. pachyodus in the Aphyoditeinae is based on the shared presence of a long posteriorly directed spiniform process on the posteroventral margin of the orbitosphenoid, the elongation of the transverse process of the neural arch of the third vertebra, and the elongation of the posterior process of the parasphenoid.

The 'mystic' Sand Dune-Covered Temples of Talakad, Mysore District, Karnakata: Evidence of Earthquake-Related Destruction

Low-lying sediment mound, known as Talakad sand dunes, on the left bank of the meandering Kaveri River at Talakad, Mysore district, Karnataka, is an enigmatic geomorphic feature. Archaeological excavations in the area revealed the presence of a cluster of ancient temples, mostly in dilapidated condition, which were presumably built during the time-period dating back between 6th and 17th century AD. It is generally believed that the temples were entombed under a pile of riverine sand dunes during the 'ecodisaster' that lashed the region in the 17th century. Our field studies coupled with archaeological reports on excavations indicate that the mound is not entirely made of dune sands. Virtual absence of sand deposits over some severely damaged temples occurring near the top suggests that destruction could not have taken place only because of the load of the overlying sands. On the other hand, the scale of destruction witnessed in some of the affected temples can only be explained by the incidence of earthquakes of high magnitude. Additional proof of earthquake-related destruction comes from the occurrence of sedimentary layers (beds) containing fragmented pieces of building materials like bricks and stones in silt and clay-bearing flood plain deposits at the sites of the destructed temples and other buildings. Historical records of repeated renovation or rebuilding of temples at the same place provide further proof of recurrent incidence of earthquake-related destruction. Geomorphic changes manifested in the form of shifting of river courses consequent with the rise of the sediment mound also indicate uplift-related earth movements which must have ensued repeated earthquakes in the region.