Alongshore Sediment Transport Near Tidal Inlets of Chilika Lagoon; East Coast of India

ABSTRACT

Chilika, a lagoon along the east coast of India, is undergoing transformation due to frequent shoreline change near inlet(s). Shoreline change near inlet includes change in position and shape of inlet, inlet channel length, and spit growth/erosion. These variable features of lagoon inlet(s) critically depend on alongshore sediment transport (LST) and discharge (water and sediment) from the lagoon to the sea. The LST and the processes responsible for sand spit growth/erosion, considered as important attributes of inlet stability, are the subject matter of the present investigation and hence the study assumes importance. The study includes integration of observational and modeling framework. Observations include nearshore wave, bathymetry, beach profile, shoreline and sediment grain size of spits while numerical modeling includes simulation of the wave using MIKE 21 Spectral Wave model and LST simulation using LITtoral DRIFT. The results indicate that the predominant wave directions as S and SSE, which induces round the year south to north alongshore transport with significant seasonal variation in magnitude. The estimated LST closely matches with previous studies near Chilika inlet and for other locations along the Odisha coast. Besides temporal variability, the study reveals spatial variability in alongshore transport near Chilika inlet and considers it as one of the important attributes along with northward spit growth for inlet migration/closure/opening.     

Retrieval and validation of soil moisture from FRS-1 data set of radar imaging satellite (RISAT-1)

In this work, we estimated soil moisture (SM) by using dielectric constant properties of soil with radar backscattering coefficient (bc) from simulated annealing techniques of RISAT-1 (radar imaging satellite, based on synthetic aperture radar (SAR) technique) data. We examined the performance of simulated annealing in retrieving SM where the vegetation cover is not very high (NDVI ≈ 0.35 for wheat-dominated area on January 19, 2013).To overcome the land surface model limits on SM estimation accuracy, point measurement spatial coverage limits, and microwave remote sensing spatial-temporal sampling limits, we reduced uncertainties through a combination of these approaches. Near-surface SM measurements from the 5.35-GHz (C-band) channels of RISAT-1 were collocated against ground-truth data (collected during the flight time of RISAT-1 over the study area), to establish SAR-SM relationships for FRS-1(circular horizontal (RH) and circular vertical (RV)) data set of RISAT-1. Comparison with the limited ground-based point (total 24 points) measurements of SM content exhibited a net improvement when near-surface SM observations were assimilated. Comparison of the SM derived from the sigma naught (σ ⁰) (of RISAT-1 data set FRS-1) using the inversion algorithm with the observed measurements (using time domain reflectometry) of SM showed root mean square error of 0.24, nRMSE = 0.03, R-RMSE = 0.38, MAE = 0.63, NRMSE = 1.02, NSE = 1, d = 0.87, r ² = 0.65, and RMSE% = 12.79 for RH polarized image while RV polarized image failed each statistical test for predicting good SM with respect to the observed SM. The ability to extract additional information comes at the expense of including more measurements, especially at frequencies lower than the L-band. This approach is therefore intended for future space-borne systems.     

Evaluation of groundwater vulnerability to pollution using DRASTIC framework and GIS

Groundwater management has a prominent role in the world especially in arid and semi-arid areas which have a shortage of water, and due to this serious problem, many researchers work on that for prevention and managing the water recourses to conserve and monitor sources. DRASTIC index can be put forward for estimating of groundwater vulnerability to such pollution. The main purpose of using the groundwater vulnerability model is to map groundwater susceptibility to pollution in different areas. However, this method has been used in various areas without modification, disregarding the effects of pollution type and characteristics. Thus, this technique must be standardized and approved for Kerman plain. Vulnerability evaluation to explain areas that are more vulnerable to contamination from anthropogenic sources has become a prominent element for land use planning and tangible resource management. This contribution aims at evaluating groundwater vulnerability by applying the DRASTIC index as well as employ sensitivity analyses to evaluate the comparative prominent of the model parameters for groundwater vulnerability in Kerman plain in the southeastern part of Iran. Moreover, the potential of vulnerability to pollution is more accurately assessed by optimizing the weights of the DRASTIC parameters with the single-parameter sensitivity analysis (SPSA). The new weights were calculated. The result of the study revealed that the DRASTIC-Sensitivity analysis exhibit more efficiently than the traditional method for a nonpoint source pollution. Observation of ultimate nitrate showed the result of DRASTIC-SPSA has more accuracy. The GIS method offers an efficient environment for carrying out assessments and greater capabilities for dealing with a huge quantity of spatial data.     

Integrated model for earthquake risk assessment using neural network and analytic hierarchy process:Aceh province,Indonesia

Catastrophic natural hazards,such as earthquake,pose serious threats to properties and human lives in urban areas.Therefore,earthquake risk assessment(ERA)is indispensable in disaster management.ERA is an integration of the extent of probability and vulnerability of assets.This study develops an integrated model by using the artificial neural network–analytic hierarchy process(ANN–AHP)model for constructing the ERA map.The aim of the study is to quantify urban population risk that may be caused by impending earthquakes.The model is applied to the city of Banda Aceh in Indonesia,a seismically active zone of Aceh province frequently affected by devastating earthquakes.ANN is used for probability mapping,whereas AHP is used to assess urban vulnerability after the hazard map is created with the aid of earthquake intensity variation thematic layering.The risk map is subsequently created by combining the probability,hazard,and vulnerability maps.Then,the risk levels of various zones are obtained.The validation process reveals that the proposed model can map the earthquake probability based on historical events with an accuracy of 84%.Furthermore,results show that the central and southeastern regions of the city have moderate to very high risk classifications,whereas the other parts of the city fall under low to very low earthquake risk classifications.The findings of this research are useful for government agencies and decision makers,particularly in estimating risk dimensions in urban areas and for the future studies to project the preparedness strategies for Banda Aceh.     

Spatial and temporal variations in source,diagenesis, and fate of organic matter in sediments of the Netravati River,India

Organic matter (OM) such as organic nitrogen plays a substantial role in the global biogeochemical cycling of bio‐reactive components—amino acids (AA) in aquatic environments. Spatial and temporal variations in source, diagenesis, and fate of organic nitrogen such as AA in sediments of small tropical rivers and the role of oxbow/meandering loops under changing climatic conditions are poorly investigated. This study assessed the spatial and seasonal variations in OM composition, source, and diagenesis of a tropical small mountainous river—Netravati River, India, for 1 year. Water samples were determined for suspended particulate matter, and surface sediments were examined for bulk parameters, surface area (SA), and the L‐ and D‐enantiomers of AA. The L‐ and D‐enantiomers of AA displayed subtle seasonal variations in composition and depicted varying degrees of diagenesis. The concentration of D‐enantiomer of AA was high and showed substantial contributions from bacteria, terrestrial source, and in situ production. The D‐arginine was the most abundant D‐enantiomer of AA in the study area, possibly due to extracellular secretion by bacterial species and adsorption onto sediments, and thus, it was protected from degradation. Degradation index was more negative at the oxbow and meandering loop stations during the dry season suggesting that local geomorphologic settings steer the diagenesis of OM within the river. A negative relationship between gamma‐aminobutyric acid and organic carbon:surface area (OC:SA) ratio and a positive correlation between tyrosine and OC:SA ratio suggested accelerated loss of OM. Furthermore, the concentrations of most bulk parameters were higher in the lower reaches during monsoon and premonsoon seasons. Taken together, changes in seasons have an operational control in distinguishing the composition, source, and diagenesis of spatial OM distribution. Moreover, oxbows and river meandering loops influence the diagenetic processes in small tropical river systems.     

Internal waves over the shelf in the western Bay of Bengal: a case study

Generation and propagation of internal waves (IWs) in the coastal waters of the extended shelf of the western Bay of Bengal are investigated for late winter by using the Massachusetts Institute of Technology General Circulation Model (MITgcm). The model is forced with astronomical tides and daily winds. Monthly climatological temperature and salinity fields are used as initial conditions. The simulations are compared with time series observations of temperature and currents from acoustic Doppler current profiler (ADCP) and conductivity-temperature-depth (CTD) moored at three locations south of Gopalpur: two at a local depth of 100 m and another at 400-m depth during 19–21 February 2012. The comparison of the spectral estimates for the time series of temperature from the model and observations are in reasonable agreement for the near-tidal frequency waves. The peak of temperature spectra is always found near the shelf break region which steadily lost its intensity over the continental shelf. The calculation of Richardson number reflected the presence of local mixing due to density overturning in the shelf region. To understand further the generation and propagation of internal tides in the region, energy flux and conversion of barotropic-to-baroclinic M₂ tidal energy are examined. The model simulations suggest that the internal tide is generated all along the shelf slope. The energy flux analysis shows that the internal tides propagate to either side of the generation sites.     

Self-Learning Random Forests Model for Mapping Groundwater Yield in Data-Scarce Areas

Globally, groundwater plays a major role in supplying drinking water for urban and rural population and is used for irrigation to grow crops and in many industrial processes. A novel self-learning random forest (SLRF) model is developed and validated for groundwater yield zonation within the Yeondong Province in South Korea. This study was conducted with an inventory data initially divided randomly into 70% for training and 30% for testing and 13 groundwater-conditioning factors. SLRF was optimized using Bayesian optimization method. We also compared our method to other machine learning methods including support vector machine (SVM), artificial neural networks (ANN), decision trees (DT), and voting ensemble models. Model validation was accomplished using several methods, including a confusion matrix, receiver operating characteristics, cross-validation, and McNemar’s test. Our proposed self-learning method improves random forest (RF) generalization performance by about 23%, with SLRF success rates of 0.76 and prediction rates of 0.83. In addition, the optimized SLRF performed better [according to a threefold cross-validated AUC (area under curve) of 0.75] than that using randomly initialized parameters (0.57). SLRF outperformed all of the other models for the testing dataset (RF, SVM, ANN, DT, and Voted ANN-RF) when the overall accuracy, prediction rate, and cross-validated AUC metrics were considered. The SLRF also estimated the contribution of individual groundwater conditioning factors and showed that the three most influential factors were geology (1.00), profile curvature (0.97), and TWI (0.95). Overall, SLRF effectively modeled groundwater potential, even within data-scarce regions.

     

Spit and Inlet Morphodynamics of a Tropical Coastal Lagoon

The morphological changes of spits and inlets of the Chilika lagoon, the largest brackish water tropical coastal lagoon in Asia, are investigated using real-time kinematic GPS observation and numerical models during 2009–2013. The seasonal/interannual variations of the spit and inlet cross-sectional areas with varying widths and depths are recorded in association with different physical processes. The results show significant changes in spit morphology: particularly, the south spit accreted continuously, while the middle and north spits eroded. The cross-sectional depth of inlets becomes narrower and deeper during summer and winter seasons, while they are wider and shallower during the monsoon. The model results show that sediment transport rate is larger during monsoon and summer, while it is relatively less during the winter. Alongshore, sediment transport is predominantly northward throughout the study period. The result shows that gain/loss of the spits and closure/opening of inlets are significantly controlled by the high wave power, longshore drifts, and river discharge. The study demonstrates that the combined use of observational and numerical models is very effective to understand the changes of spit and inlet morphology and their impact on ecological conditions of the lagoon environment.     

Stability of LRS Bianchi type-I cosmological models in f(R,T)-gravity

This paper examines the stability of the transition from the early decelerating stage of the Universe to the recent accelerating stage for the perfect fluid cosmological locally rotationally symmetric(LRS) Bianchi-I model in f(R, T) theory. To determine the solution of field equations, the idea of a timevarying deceleration parameter(DP) which yields a scale factor, for which the Universe attains a phase transition scenario and is consistent with recent cosmological observations, is used. The time-dependent DP yields a scale factor a=exp■, where β and k are respectively arbitrary and integration constants. By using the recent cons_traints(H_0 _= 73.8, and q_0 =-0.54) from Type Ia Supernova(SN Ia) data in combination with Baryonic Acoustic Oscillations(BAO) and Cosmic Microwave Background(CMB) observations(Giostri et al.), we obtain the values of β = 0.0062 and k = 0.000016 for which we have derived a cosmological model from the early decelerated phase to the present accelerating phase. By applying_ other r_ecent constraints(H_0 = 73.8, q_0 =-0.73) from SNe Ia Union data(Cunha), we obtain the values of β = 0.0036 and k = 0.000084 for which we have derived a cosmological model in the accelerating phase only. We have compared both models with experimental data. The stability of the background solution has been examined also for the metric perturbations alongside the properties of future singularities in a Universe ruled by dark energy with phantom type fluid. We demonstrate the presence of a stable fixed point with a condition of state ω <-1 and numerically affirm this is really a late-time attractor in the ghost overwhelmed Universe. Some physical and geometric properties of the model are found and examined.     

Water Resources Management Through Flood Spreading Project Suitability Mapping Using Frequency Ratio,k-nearest Neighbours,and Random Forest Algorithms

Natural Resources Research - Lack of water resources is a common issue in many countries, especially in the Middle East. Flood spreading project (FSP) is an artificial recharge technique, which is...