Geospatial Analysis of coastal environment: A case from Bhitarkanika Mangroves forest, Odisha

Study on Remote Sensing Data Classification Using Statistical Techniques

Statistical Assessment of Long-term Shoreline Changes along the Odisha Coast

Abstract: Odisha, a coastal state on eastern seaboard of India possesses a ~450 km long coastline vulnerable to a multitude of natural and anthropogenic threats. The present study reports a systematic assessment of rates of shoreline change over a period of 25 years from 1990- 2015, using Landsat 5 and 8 series of (Thematic Mapper and Operational Land Imager) satellite images. An analysis of rate of shoreline change was carried out along select regions of Odisha coast using Digital Shoreline Analysis System (DSAS). Linear Regression Method (LRR) was used to estimate net shoreline change at sub decade time scale and End Point Rate (EPR) to estimate net shoreline change rate in between two consecutive years. The highest erosion with a coastline length of 63 km was observed between Rajnagar (around Satabhaya beach) and Mahakalapara (near to Hukitola beach) block of Kendrapara district and between Ersama (around Paradeep port) and Balikuda blocks (northern parts of Devi River mouth) of Jagatsinghpur coastal district. The result suggest that both EPR and LRR techniques were used to estimate shoreline change rate and the similar result of erosion by both EPR and LRR technique indicated weaker cyclic trend in erosion.

Statistical Assessment of Long-term Shoreline Changes along the Odisha Coast

K K Barik, R. Annaduari, P C Mohanty, R S Mahendra, J K Tripathy and D Mitra (2019) Statistical Assessment of Long-term Shoreline Changes along the Odisha Coast

GROUNDWATER HYDROCHEMISTRY AROUND THE SHRIMP PONDS OF ERSAMA AND BALIKUDA BLOCKS OF JAGATSINGHPUR DISTRICT, ODISHA

PRAKASH CHANDRA DALEI, J.K. TRIPATHY, K.K. BARIK AND SMRUTI R. PANDA (2019) GROUNDWATER HYDROCHEMISTRY AROUND THE SHRIMP PONDS OF ERSAMA AND BALIKUDA BLOCKS OF JAGATSINGHPUR DISTRICT, ODISHA

Satellite Retrieved Spatio-temporal Variability of Phytoplankton Size Classes in the Arabian Sea

Kamal Kumar Barik, Sanjiba Kumar Baliarsingh, Amit Kumar Jena, Suchismita Srichandan (2020) Satellite Retrieved Spatio-temporal Variability of Phytoplankton Size
Classes in the Arabian Sea
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Alakes Samanta2
• Aneesh Anandrao Lotliker2

GIS based saltwater vulnerability mapping of northern coast of Odisha, East coast of India

Inter-Comparison of Gauge-Based Gridded Data, Reanalysis and Satellite Precipitation Product with an Emphasis on Hydrological Modeling

Sridhara Setti, Rathinasamy Maheswaran, Venkataramana Sridhar ,
Kamal Kumar Barik, Bruno Merz and Ankit Agarwal 

https://doi.org/10.3390/atmos11111252 

Deltaic Expansions of the Mahanadi Tri-delta and the Chilika Lagoon: Geospatial Approach

Binod Kumar Sethi, Siba Prasad Mishra, Kabir Sethi and Kamal Barik

Erratum for “Attribution of Hydrologic Changes in a Tropical River Basin to Rainfall Variability and Land-Use Change: Case Study from India

https://doi.org/10.1061/(ASCE)HE.1943-5584.0001937

S. Setti, R. Maheswaran, D. Radha, V. Sridhar,
K. K. Barik, and M. L. Narasimham

Qualty assessment of Groundwater in the Western parts of Chhattisgarh, India

Prithviraj N, Tripathy J K, Panda S R and Barik K K

Earth Observation Technique-Based Coastal Vulnerability Assessment of Northern Odisha, East Coast of India

The coastal zones of northern Odisha coast, western Bay of Bengal, are highly exposed to natural forcing. These regions are vulnerable due to natural hazards such as cyclones, tsunamis, floods, shoreline/beach erosion and sea-level rise. Further, the increased intensity and density of the extreme events in the recent decades have contributed more to the coastal vulnerability, thereby causing floods and inundation. Therefore, there is a need of sustainable use of the coastal zone with proper management practices. In this context, coastal vulnerability index (CVI) has been proved as an effective method for assigning the vulnerability status to any coastal zone. The present research work aims to develop a CVI by integrating risk values of nine input variables and to segment them into low, moderate, high and very high vulnerability categories as per their degree of vulnerability. The study area exhibits a long 273.8 km coastal tract, and about 9.6% of the coastal tract is under very high vulnerability category, followed by 29.7% under high vulnerability, 46.3% under medium vulnerability and rest 14.3% under low vulnerability.

Response of coastal phytoplankton pigment composition to tropical cyclone Fani

Phytoplankton pigment composition was evaluated during the pre-cyclone phase (PRCP) and post-cyclone phase (POCP) of tropical cyclone Fani in the coastal waters of the northwestern Bay of Bengal. The chromatographic analysis revealed higher pigment diversity and an increase in individual pigment concentration during POCP. Chlorophyll–a (chl–a) was the dominant pigment during PRCP and POCP, followed by fucoxanthin. However, chl–a and fucoxanthin concentrations increased 18- and 14-folds, respectively, during the POCP, signifying Bacillariophyta bloom. Complementing microscopy confirmed the dominance of the toxic Bacillariophyta species Pseudo-nitzschia pungens (reaching 5.47 × 104 cells l ? 1 ) during the POCP. The cyclone-induced nutrient recharge of the ambient medium could have promoted phytoplankton growth, causing the reappearance of diatom bloom during the later phase of the pre-southwest monsoon. Small-sized Prymnesiophyta and Cryptophyta were not detected microscopically; however, they were identified by chromatographic analysis through pigment markers during POCP.

Investigating the impact of calibration timescales on streamflow simulation, parameter sensitivity and model performance for Indian catchments

Hydrological model calibration is a quintessential step in model development, and the time scale of calibration depends on the application. However, the implications of choice of time scale of calibration have not been explored extensively. Here, we evaluate the effect of the time scale of calibration on model sensitivity, best parameter ranges, and predictive uncertainty for three river basins using the Soil and Water Assessment Tool (SWAT) model. Multiple models were set up for three different catchments from southern India. Our results showed that the sensitivity of the parameters, best parameter ranges, and model performance are conditioned on the time scale of calibration. The models calibrated at coarser time scales marginally outperformed the models calibrated at fine time scale in terms of Nash-Sutcliffe efficiency and percentage bias. Transfer of parameters across scales (both from coarse to fine and from fine to coarse) have a general tendency to worsen the model performance in all three catchments, with few exceptions.

Implementation of Road Safety Audit to Highlight the Deformities in the Design and Environmental Safety Features

Satellite-Based Characterization of Phytoplankton Blooms in Coastal Waters of the Northwestern Bay of Bengal

Environmental–Economical Aspects of Protonibea diacanthus: A Heavily Priced Marine Fish of India

Response of coastal phytoplankton pigment composition to tropical cyclone Fani

Cloud GIS Model for Coastal Geospatial Big Data Analytics