Field Of Coastal Engineering Research Articles

Impact of focused wave groups on pier structures: a case study of severe breaking waves at Pont del Petroli during storm Gloria

In January 2020, the footbridge connecting the seaward platform of the Pont del Petroli pier to Badalona beach collapsed due to the severe sea storm named Gloria. Approximately 15 m of the footbridge fell into the sea as a result of prolonged wave action and strong impacts. To understand the complex interaction between waves and structures that led to the pier’s collapse during the storm, a composite modelling approach was developed. The loads on each pier element were initially evaluated using the meshless DualSPHysics code, which employs the Smoothed Particle Hydrodynamics (SPH) method. This evaluation was conducted under severe wave conditions analogous to those experienced during the storm. Numerical models informed the design of an experimental campaign carried out at the Maritime Engineering Laboratory of Universitat Politècnica de Catalunya—BarcelonaTech, using the CIEM large-scale wave flume facility in Barcelona, Spain. Post-storm bathymetric surveys revealed significant alterations in the seabed profile near the affected infrastructure, including sediment deposition and a reduction in water depth from 10 m to 8 m. Consequently, it was anticipated that wave transformation and breaking in the vicinity of the structure would be substantially affected. To explore this phenomenon, various extreme wave impacts were experimentally simulated using focused wave groups. The physical model findings unveiled the forces that the pier endured during the storm Gloria. The results indicate that wave phases influence individual waves, with waves that are biased and asymmetric experiencing higher peaks than those focused on the crest. This insight helps to explain the structural failure of the footbridge during the storm and underscores the importance of considering wave phase impacts in the design and assessment of coastal infrastructure. The combined numerical and experimental approach provides a comprehensive understanding of the forces at play, contributing valuable knowledge to the field of coastal engineering and infrastructure resilience.

Sustainable And Bioengineered Concrete For Armor Units Of Low-Crested Structures

In the last two decades, Eco-engineering has emerged to mitigate and compensate the environmental impacts of man-made structures while integrates benefits to society, being concrete the most widely alternative material used to natural rocks for construction of artificial coastal structures. Over the past three decades, an extensive literature has documented different supplementary cementitious materials (SCMs) to reduce CO2 emissions from Portland cement, with common SCMs used in marine and coastal structures such as fly ashes, ground granulated blast furnace slags, pozzolanas and limestones. However, there is a need to further investigate the suitability of SCMs for the construction of Low-Crested Structures (LCS) to decrease carbon footprint from concrete production and improve the bioreceptivity of concrete armor units during the breakwater lifetime. A literature review conducted in this study shows several advantages of slag cements compared to other SCMs to reduce carbon emissions and enhance biological colonization and durability of concrete submerged in seawater, identifying surface roughness as the most effective factor in design of bioreceptive concrete. This study also highlights the importance of the type and quantity of cement used in concrete mixes to reduce carbon footprint of the manufacture of concrete armor units of LCS and the implementation of long-term monitoring plans to fully understand the functioning of local communities that develop on concrete surfaces of artificial structures, and thus, to improve the integration of environmental parameters in the field of coastal engineering.

Evaluation of Accuracy of Aeolian Velocity Measurement Using Image Analysis

Study on Aeolian transport began in 1941 when Bagnold first conducted a study on aeolian transport in desert conditions. Aeolian transport study was mainly conducted on deserts, and the field of coastal engineering began with the application of Bagnold’s equation to the coast after 1980. However, many studies have shown that using the Bagnold equation on the coast overestimates the amount of aeolian transport. Currently, aeolian trap using various sensors ranging from simple forms have been developed and are being used in study. However, these aeolian traps have the disadvantage that there is a large difference in performance for each trap. In addition, in the case of existing traps, analysis is performed only on the amount of sand collected, and quantitative analysis of sand transport velocity or concentration is difficult. Therefore, in this study, we use image analysis techniques to evaluate the accuracy of aeolian transport velocity measurement and suggest a method that can be used in the study.

FLEXIBLE FLUID-STRUCTURE INTERACTION OF A FLEXIBLE PLANT MODEL FOR NATURE-BASED SOLUTIONS

Nature-based solutions (NBS) represent a new field of research and engineering applications, becoming increasingly popular in the coastal engineering field. Salt marsh restoration, an example of NBS, is particularly appealing due to the variety of benefits they can provide, especially their capacity to induce sediment accretion, potentially keeping pace with sea-level rise. This study investigates the applicability of the flexible fluid-structure (FSI) interaction module being developed for open-source software REEF3D to the motion of marsh plants under wave action using data from a physical model study performed by Paul et al. (2016). The model consistently overestimates the drag force response of a flexible plastic plant surrogate under wave action. This suggests that this new tool may not be suited for this case. However, further investigation must be performed to test the limits of the model’s application.

Prediction of wave overtopping discharges at coastal structures using interpretable machine learning

ABSTRACT Appropriate estimation and prediction of wave overtopping discharges are very important in terms of economics, port structure stability, and port operation. In recent years, machine learning (ML) techniques, which predict by finding statistical structures from input/output data using computers, have generated interest. However, as the complexity of ML models increases, interpreting their results becomes increasingly difficult. Interpretation of ML results is an important part in developing an efficient structure design strategy for improved wave overtopping discharge estimation. Therefore, in this study, eight linear/nonlinear ML models were applied to the same data, and a pipeline model for selecting an ML model suitable for data characteristics was developed. In addition, the importance of variables related to the prediction of wave overtopping discharges and their correlations were analyzed by interpretable ML. The research results showed that the extreme gradient boosting model had the highest prediction accuracy and significantly reduced the error. Accordingly, a data-based model can be a new alternative for analyzing the complex physical relationships in the field of coastal engineering and used as a starting point toward structure design and development for coastal disaster prevention.

Analysis of propagating wave structures of the cold bosonic atoms in a zig-zag optical lattice via comparison with two different analytical techniques.

The wave propagation has the significant role in the field of coastal engineering and ocean. In the geographical fields, waves are primary source of environmental process owed to energy conveyance on floating structure. This study aims to investigate the system of cold bosonic atoms in zig-zag optics lattices. The solitonic patterns of the considered model successfully surveyed by using two integrated analytical techniques new extended direct algebraic and frac{G'}{G^{2}} expansion method. The exact solutions are presented by rational, trigonometric, hyperbolic and exponential functions. On the basis of solitons, we need to show that which one is more integrated and robust scheme. These solutions will help to understood the dynamics of cold bosonic atoms in zig-zag optical lattices and the several other systems. Three dimensional as well as two dimensional comparison presented for a cold bosonic atoms model solutions which are revealed diagrammatically for appropriate parameters by using Mathematica. This study will help physicists to predict some new hypothesis and theories in the field of mathematical physics.

Prediction of Wave Transmission Characteristics of Low Crested Structures Using Artificial Neural Network

<i>Recently around the world, coastal erosion is paying attention as a social issue. Various constructions using low-crested and submerged structures are being performed to deal with the problems. In addition, a prediction study was researched using machine learning techniques to determine the wave attenuation characteristics of low crested structure to develop prediction matrix for wave attenuation coefficient prediction matrix consisting of weights and biases for ease access of engineers. In this study, a deep neural network model was constructed to predict the wave height transmission rate of low crested structures using Tensor flow, an open source platform. The neural network model shows a reliable prediction performance and is expected to be applied to a wide range of practical application in the field of coastal engineering. As a result of predicting the wave height transmission coefficient of the low crested structure depends on various input variable combinations, the combination of 5 condition showed relatively high accuracy with a small number of input variables defined as 0.961. In terms of the time cost of the model, it is considered that the method using the combination 5 conditions can be a good alternative. As a result of predicting the wave transmission rate of the trained deep neural network model, MSE was 1.3×10<sup>-3</sup>, I was 0.995, SI was 0.078, and I was 0.979, which have very good prediction accuracy. It is judged that the proposed model can be used as a design tool by engineers and scientists to predict the wave transmission coefficient behind the low crested structure.</i>

Wave attenuation by multiple slotted barriers with a zig-zag arrangement -A physical and numerical approach

In the present study, scattering of surface gravity waves by multiple slotted vertical barriers arranged in a zig-zag manner is analyzed by employing Computational Fluid Dynamics (CFD) and validated with physical model tests. The porosity of the vertical slotted barrier is varied from 10% to 40%, and the number of slotted barriers varied from 1 to 6. The results from CFD correlate well with the laboratory measurements on the scattering coefficients for a wide range of input conditions giving a high level of confidence. For relatively short waves (h/λ > 0.3, h- water depth and λ- wave length), slotted barriers up to 3 numbers and porosity from 20% to 30% are required to achieve wave transmission coefficient in the range of 0.2 to 0.3. For relatively long waves (h/λ < 0.3), slotted barriers of 5 to 6 numbers and porosity in the range of 10% to 20% are needed to obtain wave transmission of 0.2 to 0.3. The results presented in this study can be used for a wide range of wave damping applications in the field of coastal engineering.

A comparative study of the cumulant lattice Boltzmann method in a single-phase free-surface model of violent flows

Many coastal and ocean engineering flows, such as tsunamis inundating urban areas, tend to be violent. The characteristics of these damaging flow fields are three-dimensional, highly non-linear and non-hydrostatic. A fully three-dimensional free-surface fluid model is required to simulate such a flow field. Fluid simulations in the field of coastal engineering are often large-scale since large areas are the subject of the simulations. The numerical model must be not only accurate but also efficient. In recent years, the lattice Boltzmann method (LBM) has attracted much attention as a novel simulation method and has been successfully applied to various engineering fields. The LBM calculates complex phenomena in a simple framework. The density field determines the pressure field with the equation of state. This means that the LBM does not have to solve the pressure Poisson equation. However, the existing gas–liquid multi-phase flow models that employ the LBM have a critical problem. Pressure calculations with large density ratios easily become unstable, and the application of these models to violent flow fields is limited. The single-phase free-surface fluid model provides good approximations for flow problems in which the gas dynamics can be neglected. Moreover, the cumulant LBM has attracted attention because it has excellent numerical stability even for high Reynolds number flows. The single-phase free-surface flow model using the cumulant LBM is a suitable approach for simulating violent flow fields in coastal engineering. In this study, we propose a single-phase free-surface flow model based on the cumulant LBM using the volume-of-fluid (VOF) model to capture the interface. We demonstrate that the cumulant LBM is stable under violent flows and reproduces the density field well compared with the traditional single relaxation time model. We find that a larger bulk viscosity can reduce the numerical oscillation of the impact pressure acting on a structure, although a bulk viscosity that is too large reduces the accuracy and stability. The results of the proposed model are in good agreement with previous experimental results.

Method of the Laboratory Wave Generation for Two Dimensional Hydraulic Model Experiment in the Coastal Engineering Fields: Case of Random Waves

The experiments in coastal engineering are very complex and a lot of components should be concerned. The experience has an important role in the successful execution. Hydraulic model experiments have been improved with the development of the wave generator and the advanced measuring apparatus. The hydraulic experiments have the advantage, that is, the stability of coastal structures and the hydraulic characteristics could be observed more intuitively rather than the numerical modelings. However, different experimental results can be drawn depending on the model scale, facilities, apparatus, and experimenters. In this study, two-dimensional hydraulic experiments were performed to suggest the guide of the test wave(random wave) generation, which is the most basic and important factor for the model test. The techniques for generating the random waves with frequency energy spectrum and the range for the incident wave height [(HS)M/(HS)T = 1~1.05] were suggested. The proposed guide for the test wave generation will contribute to enhancing the reliability of the experimental results in coastal engineering.

Prediction of Wave Transmission Characteristics of Low-Crested Structures with Comprehensive Analysis of Machine Learning.

The adoption of low-crested and submerged structures (LCS) reduces the wave behind a structure, depending on the changes in the freeboard, and induces stable waves in the offshore. We aimed to estimate the wave transmission coefficient behind LCS structures to determine the feasible characteristics of wave mitigation. In addition, various empirical formulas based on regression analysis were proposed to quantitatively predict wave attenuation characteristics for field applications. However, inherent variability of wave attenuation causes the limitation of linear statistical approaches, such as linear regression analysis. Herein, to develop an optimization model for the hydrodynamic behavior of the LCS, we performed a comprehensive analysis of 10 types of machine learning models, which were compared and reviewed on the prediction accuracy with existing empirical formulas. We found that, among the 10 models, the gradient boosting model showed the highest prediction accuracy with MSE of 1.0 × 10−3, an index of agreement of 0.996, a scatter index of 0.065, and a correlation coefficient of 0.983, which indicates a performance improvement over the existing empirical formulas. In addition, based on a variable importance analysis using explainable artificial intelligence, we determined the significant importance of the input variable for the relative freeboard (RC/H0) and the relative freeboard to water depth ratio (RC/h), which confirms that the relative freeboard was the most dominant factor for influencing wave attenuation in the hydraulic behavior around the LCS. Thus, we concluded that the performance prediction method using a machine learning model can be applied to various predictive studies in the field of coastal engineering, deviating from existing empirical-based research.

Modeling studies on the behavior of single and double rubble mound breakwaters using genetic programming tool

Experimental investigation on wave transmission, reflection and dissipation characteristics of rubble mound breakwater models are time consuming and expensive. However, such studies are required for designing the rubble mound breakwaters for marine structures in an optimal condition. In order to overcome such problems many researchers used various soft computing techniques such as Artificial Neural Network (ANN), Adaptive Neuro Fuzzy Interference System (ANFIS), Genetic Programming (GP), Support Vector Machine (SVM) etc, in order to predict the design factors in the field of coastal engineering. The current work proposes Genetic Programming (GP) as a modeling tool to evolve mathematical models for the behavior of single and double breakwaters. Based on the detailed experimental data, GP models were performed to predict the reflected wave height (H r ), wave height on the breakwater (H 5 ) and transmitted wave height (H t ) by considering with and without trigonometric effects of those breakwaters. The quality of predictability of the present model is measured by the statistical parameter, RMSE (Root Mean Square Error). Since the waves were more complex in nature, it is very essential in considering the trigonometric function’s effect in the modeling aspects. It is evident that, the GP model accurately described the non linear complex effects.

Gravity wave interaction with a wave attenuating system

In the present study, gravity wave interaction with a wave attenuating system (WAS) comprised of a series of surface piercing thin vertical porous plates fixed on a fully submerged rigid pontoon is analyzed. For the wave past porous barriers, a quadratic pressure drop is considered to account for the energy dissipation due to changes in wave steepness. A numerical model based on iterative multi-domain boundary element method is developed under the assumption of a small amplitude water wave theory. The scattering coefficients (reflection and transmission) and wave force coefficients (horizontal, vertical and moments) are computed for different wave and structural parameters such as the number of plates, relative plate width, the relative depth of submergence, plate porosities, and relative wave steepness. The results demonstrate that with the creation of trap zones through multiple porous plates on a submerged rigid pontoon, it is possible to reduce wave transmission by 60–70%. For optimum performance across all water depths, it is suggested for the WAS to have 1 ≤ B/h ≤ 1.5 and h1/h ≤ 0.3. Also, interestingly there is a 25–30% reduction in the vertical wave forces which reduces the load acting on the ancillary equipment. The WAS is found to perform well for porosity μ=20%, above which the wave transmission increases gradually. The study results can be useful in the cost-effective design of this type of special wave barrier for a range of coastal engineering field applications.

Composite Modelling in Port Engineering

An introduction and review of the composite modelling, defined as the combining of physical and numerical models, are presented in this paper. Although the composite modelling is still in its infancy in the hydraulic community, in MSUCE it has been applied in many coastal projects, which will be described in this paper. The strengths and weaknesses of numerical and physical models for each case studies, are described. The optimal methodologies and guidelines on how to decide if the composite modelling is beneficial and how to set up a composite modelling experiment, are given. Finally, it was concluded that despite the challenges and difficulties, there is a growing trend toward applying the composite modelling as an effective tool in the field of coastal engineering.

Real Time Wave Prediction Using Neural Networks at Karwar, West Coast of India

The knowledge of ocean waves is an essential prerequisite for almost all activities in ocean. Traditional methods have disadvantages of excessive data requirement, time consumption and are tedious to carry out. ANN is being widely applied in coastal engineering field since last two decades in variety of time series forecasting. Study has been carried out to predict waves using FFBP and NARX networks. Wave data obtained from INCOIS is made use in the present study. Effect of network architecture on the performance of the model has been studied. It was found that for time series prediction NARX network outperforms FFBP.

MESSAGE FROM THE LOCAL ORGANIZING COMMITTEE

The 35th ICCE Conference took place in Antalya, over 17-20 November, 2016. We do believe that ICCE 2016 supported by the Turkish Chamber of Civil Engineers, organized under the auspices of the Coastal Engineering Research Council (CERC) of Coasts, Oceans, Ports and Rivers Institute (COPRI) of the American Society of Civil Engineers (ASCE), had a great impact nationally and globally, strengthened the bonds of knowledge in the field of Coastal Engineering, and reflected the colors of different cultures in addition to enriching the experience of young engineers and students.&#x0D; &#x0D; ICCE 2016, Istanbul was to be held in between 17-21 July, but was forced to be postponed to due to unpredictable events which took place in Turkey, beyond our control. During all these difficult times, we had no intention to yield under the pressure of these events. Therefore, we, the Local Organizing Committee (LOC) considered all viable alternatives, respecting the views of all parties involved, namely CERC, COPRI of ASCE, and the Turkish Chamber of Civil Engineers and the participants. We felt professionally and ethically committed to proceed regardless and to make ICCE happen. The LOC made the final decision about the new venue and date of the ICCE 2016. Accordingly, the postponed ICCE, 2016 was held in Mardan Palace Hotel, in Antalya over 17-20 November, 2016. We have to note that we do appreciate the support of the CERC and COPRI of ASCE during our journey from Istanbul to Antalya and COPRI secretary Prof. Dr. Patrick Lynett. We extend our gratitude to Antalya Metropolitan Municipality for their very valuable support and we are also thankful to our sponsors for their continuing valuable support. On the other hand, we duly noted and fully understood the hesitation of shown by some of the participants who could not attend the conference.&#x0D; From 26 different countries, 210 participants, including students and guests, attended the ICCE 2016, Antalya. Invited key note speakers, namely Prof. Dr. R. Dalrymple, Prof. Dr. M. Sumer, Prof. Dr. J. van der Meer, Prof. Dr. C. Synolakis, Prof. DR. S. Takahashi, who were also members of scientific committee and Prof. Dr. N.Kobayashi as chair of ICCE 2018, with their lectures in the opening ceremony and in the respective plenary sessions contributed significantly to the achievement of the goals and the success of the conference.&#x0D; &#x0D; The quality of the papers presented, the discussions in the sessions, and also the interaction between the participants contributed greatly to make the conference a success.&#x0D; &#x0D; The Early Career Scientist Event (ECSE) was planned within the ICCE 2016 to provide a specific time and place in the conference schedule where the early career attendees could meet with each other and discuss their research work in a comfortable and informal setting. The event was held on Thursday (November 17, 2016) after the conference sessions and around 50 young researchers attended the event. The resulting networking among the participants was very successful as the group was small, which enabled everyone to meet each other and all could talk about their experiences in detail.&#x0D; &#x0D; We have no doubt that this meeting was a valuable opportunity to be a part of the scientifically enriched environment of coastal engineering, not to mention items such as the historical beauties of magnificent Antalya and Turkish hospitality.&#x0D; &#x0D; On behalf of the Local Organizing Committee of ICCE 2016, we extend our special thanks to the Chamber of Turkish Civil Engineers ; Cemal Gokce (Chair), Aysegül Bildirici Suna (member) and Cem Oğuz (member), Antalya Branch of Chamber of Turkish Civil Engineers; Mustafa Balci (Chair) and finally Members of Technical Committee ; Yalcın Arisoy, Berna Burak Aydogan, Burak Aydogan, Cuneyt Baykal, Serdar Beji, Hulya K. Cihan, Yeşim Celikoglu, Mustafa Esen, H.Gokhan Guler, Anil A. Güler, Utku Kanolu, V.S. Ozgur Kırca, Dogan Kisacik, Bergüzar O. Ozbahçeci, Mehmet Ozturk, Ilgar Safak, Cihan Sahin, Gulizar O. Tarakcioğlu,Tugçe Yüksel,&#x0D; Last but not the least, we thank to Mayor of Antalya Metropolitan Municipality Menderes Turel for his interest and valuable support to the Conference. &#x0D; &#x0D; On behalf of the Local Organizing Committee of ICCE 2016 we had the pleasure and excitement of welcoming you in Antalya at ICCE 2016. The prestigious conference series will continue with ICCE 2018, Baltimore (USA) and ICCE 2020 Sidney, (Australia).&#x0D; &#x0D; With warm regards,&#x0D; Prof. Dr. Aysen Ergin (Chairperson)&#x0D; Prof. Yalcin Yüksel (Co -chair) &#x0D; Prof. Ahmet C. Yalciner ( Co-chair)&#x0D; Isikhan Güler (executive member) &#x0D; Esin Cevik (Executive member)

Calibrating and assessing uncertainty in coastal numerical models

Advanced numerical models used to predict coastal change at a variety of time and spatial scales often contain many free parameters that require calibration to the available field data. At present, little guidance (beyond the adoption of the default values provided) is available in the field of coastal engineering to inform the selection of best-fit parameter values. Common calibration techniques can often lack a rigorous quantification of model sensitivity to parameters and parameter-induced model uncertainty. Here we employ the Generalised Likelihood Uncertainty Estimation (GLUE) method to address these issues. The GLUE method uses Monte Carlo sampling to assess the skill of many different combinations of model parameters when compared to observational data. As a rigorous modelling framework, the GLUE method provides a series of standard tools that assist the modeller to analyse model sensitivity, undertake parameter optimisation and quantify parameter-induced uncertainty. In addition, new tools are presented here to identify where unique calibrated parameter sets are required for different observational data (e.g., should the calibrated parameter set differ between alongshore locations at a site) and investigate the convergence of GLUE estimated optimum parameter values over increasing numbers of Monte Carlo samples.As the methodology and philosophy of GLUE is well established in other fields, this paper presents a practical case study to explore the strengths and weaknesses of the method when applied to a relatively complex coastal numerical model (XBeach). The results obtained are compared to a previously reported and more ‘standard’ model calibration undertaken within the context of a coastal storm early warning system. While the GLUE method requires orders of magnitude more computational power, it is shown that its use in place of the more common one-at-a-time ‘trial-and-error’ approach to model calibration, provides: a significant improvement in predictive skill; a more rigorous evaluation of the model sensitivity to parameters; the ability to identify distinct differences in the XBeach model performance dependent on dune impact processes; and additional analysis including the quantification of parameter-induced uncertainty.

Impact resistance and evaluation of retained strength on geotextiles

Over the last few decades, geotextiles have progressively been incorporated into geotechnical applications, especially in the field of coastal engineering. Geotextile materials often act as separator and a filter layer between rocks laid above and subgrade beneath. This versatile material has gradually substituted traditional granular materials because of its ease of installation, consistent quality and labour cost-efficiency. However, geotextiles often suffer damage during installation due to high dynamic bulk loading of rock placement. This can degrade geotextiles' mechanical strength. The properties considered in this paper include the impact resistance and retained strength of geotextiles. In general, the greater the impact energy applied to geotextiles, the greater the potential for damage. Results highlight the inadequacy of using index derived values as an indicator to determine geotextile performance on site because test results shows that geotextiles (staple fibre (SF) and continuous filament (CF)) with better mechanical properties did not outperform lower mechanical strength materials. The toughest CF product with a CBR index value of 9696N shows inferior impact resistance compared to SF product with the least CBR strength (2719N) given the same impact energy of 9.02 kJ. Test results also indicated that the reduction of strength for CF materials were much greater (between 20 and 50%) compared to SF materials (between 0 and 5%) when subjected to the same impact energy of 4.52 kJ.

Stability assessment of rubble-mound breakwaters using genetic programming

This study investigates the possibility of applying genetic programming to the stability assessment of rubble-mound breakwaters. The genetic programming algorithm is employed to develop various explicit models to predict the stability number of armor blocks. The genetic programming models are trained and tested using the experimental data of Van Der Meer (1988). The results show that the genetic programming based models have better predictive performances than Van der Meer׳s stability equations, and that genetic programming has good potential for solving complex problems in the field of coastal engineering.

Applications of Remote Sensing in Satellite Oceanography: A Review

Remote sensing has got wide range of applications in the field of coastal engineering, including estimation of sea surface temperature, chlorophyll content, suspended sediment concentration, yellow substance concentration, wave characteristics, potential fishing zone (PFZ) and so on. Various satellite remote sensing data has provided rea data which can be used to monitor coastal resources. The present paper gives an overview of some of the applications of remote sensing in the field of satellite oceanography. From the present review, it can be conclude that, even though IR and microwave radiometers can be used for measuring temperatures at different depths in oceans, better choice is to use microwave data as it has got the advantage of penetrating through clouds and also it gives a clear view in all weather conditions except rain. Band ratio approach can be used for identifying different water quality parameters. In recent past, satellite remote sensing has become an ideal tool for identifying Potential fishing zone (PFZ).