Dynamic shoreline alterations and their impacts on Olive Ridley Turtle (Lepidochelys olivacea) nesting sites in Gahirmatha Marine Wildlife Sanctuary, Odisha (India).

Currently, sea turtle habitats are being altered by climate change and human activities, with habitat loss posing an urgent threat to Indian sea turtles. Thus, the objective of this study is to analyze the dynamic shoreline alterations and their impacts on Olive Ridley Sea Turtle (ORT) nesting sites in Gahirmatha Marine Wildlife Sanctuary from 1990 to 2022. Landsat satellite images served as input datasets to assess dynamic shoreline changes. This study assessed shoreline alterations and their rates across 929 transects divided into four zones using the Digital Shoreline Analysis System (DSAS) software. The results revealed a significant 14-km northward shift in the nesting site due to substantial coastal erosion, threatening the turtles' Arribada. This study underscores the need for conservation efforts to preserve nesting environments amidst changing coastal landscapes, offering novel insights into the interaction between coastal processes and marine turtle nesting behaviors.

Deciphering the impact of anthropogenic coastal infrastructure on shoreline dynamicity along Gopalpur coast of Odisha (India): An integrated assessment with geospatial and field-based approaches.

Odisha's coastline supports various development activities that are critical to the state and national economy, such as oil and gas, ports and harbors, power plants, fishing, tourism, and mining that continues to not only detriment the coastal ecology but also affect the overall shoreline morphodynamics. The morphological changes are complicated processes involving both natural and human-induced drivers, but it is critical to understand how recent development activities further impact beach morphodynamics and shoreline dynamicity. The study analyzes the overall shoreline morphodynamics in response to the recent development of port and other related infrastructure for annual and decadal scale using two-dimensional (2-D) shoreline changes along with detailed 3-D beach profile volumetric changes for different studied zones along the Gopalpur coast. The results reveal that nearly all studied zones of the Gopalpur shoreline, Zone-4 (EPR = -05.64 m a-1 and LRR = -04.25 m a-1), Zone-3 (EPR = -04.51 m a-1 and LRR = -07.01 m a-1) and Zone-1 (EPR = -2.85 m a-1 and LRR = -01.46 m a-1), experienced erosion between 2010 and 2020 except Zone-2 (EPR = 24.31 m a-1 and LRR = 25.96 m a-1), which showed overall sign of deposition. The interannual shoreline analysis depicted that Zone-1 (tourist beach area) remained almost stable, Zone-2 (south of the breakwater of Gopalpur Port) showed accretion trends, Zone-4 (north side of the port) dominantly showed an erosion pattern, whereas Zone-3 (port area) showed a high level of uncertainty in the context of erosional or deposition trends. Calculated volumetric loss along the surveyed 3-D beach profiles supports these 2-D changes for all the studied zones. The results showed substantial changes in coastal morphodynamics in different studied zones of the Gopalpur region and severe erosion along its northern segment of the constructed coastal infrastructure. These findings can potentially promote effective coastal zone management and prevent further deterioration along the Gopalpur coast in future.

Characterizing global satellite-based indicators for coastal vulnerability to erosion management as exemplified by a regional level analysis from Northeast Brazil.

The detection of coastal vulnerability to erosion is crucial for decision-making regarding the economy, ecology, health, security, among other issues. Most of the studies gather a large data set about physical and anthropogenic interference's on the vulnerability of coastal erosion regions around the world. However, for developing nations like Brazil, with extensive shoreline, it is challenging to develop and maintain an in situ infrastructure to offer a systematical scientific data set. In this context, several methods like Coastal Vulnerability Index (CVI) for monitoring the dynamic behavior of coastal systems require in situ collected data. Therefore, this contribution explores the use of global open source satellite-based indicators to assess coastal vulnerability to erosion at a regional level adopting an uncorrelated orthogonal basis set of Principal Component Analysis (PCA). For this, the data set covers many spheres of the environment like biophysical and social factors, adopting the Pernambuco State's coast, Brazil, as a case study. The results showed the direct relationship between a high level of urbanization and low vegetation with the high coastal vulnerability to erosion. PC1 revealed built-up and surface temperature vary inversely to the soil organic carbon and vegetation cover along about 20 km (≈10% of the shoreline extension). The hotspots were in the urban cluster (Paulista, Olinda, Recife, and Jaboatao dos Guararapes), combined with high shoreline change around -2 m/yr. PC2 showed the natural action of wind on wave heights combined with sediment removal and the backshore settlement along 10 km of extension (≈5.5% of the shoreline), with the highly vulnerable sites concentrated in Itamaraca Island and C. S. Agostinho. This approach benefits from the multi-satellite and multi-resolution data sets integration to unravel the statistical influence of each variable able to guide stakeholders.

Accounting for dynamics of mean precipitation in drought projections: A case study of Brazil for the 2050 and 2070 periods.

Changes in drought around the globe are among the most daunting potential effects of climate change. However, changes in droughts are often not well distinguished from changes in aridity levels. As drought constitutes conditions of aridity, the projected declines in mean precipitation tend to override changes in drought. This results in projections of more dire changes in drought than ever. The overestimate of changes can be attributed to the use of 'static' normal precipitation in the derivation of drought events. The failure in distinguishing drought from aridity is a conceptual problem of concern, particularly to drought policymakers. Given that the key objective of drought policies is to determine drought conditions, which are rare and so protracted that they are beyond the scope of normal risk management, for interventions. The main objective of this Case Study of Brazil is to demonstrate the differences between projections of changes in drought based on 'static' and '30-year dynamic' precipitation normal conditions. First we demonstrate that the 'static' based projections suggest 4-fold changes in the probability of drought-year occurrences against changes by the dynamic normal precipitation. The 'static-normal mean precipitation' based projections tend to be monotonically increasing in magnitude, and were arguably considered unrealistic. Based on the '30-year dynamic' normal precipitation conditions, the 13-member GCM ensemble median projection estimates of changes for 2050 under rcp4.51 and rcp8.52 suggest: (i) Significant differences between changes associated with rcp4.5 and rcp8.5, and are more noticeable for droughts at long than short timescales in the 2070; (ii) Overall, the results demonstrate more realistic projections of changes in drought characteristics over Brazil than previous projections based on 'static' normal precipitation conditions. However, the uncertainty of response of droughts to climate change in CMIP5 simulations is still large, regardless of GCMs selection and translation processes undertaken.

Hydrogeological characterisation of groundwater over Brazil using remotely sensed and model products.

For Brazil, a country frequented by droughts and whose rural inhabitants largely depend on groundwater, reliance on isotope for its monitoring, though accurate, is expensive and limited in spatial coverage. We exploit total water storage (TWS) derived from Gravity Recovery and Climate Experiment (GRACE) satellites to analyse spatial-temporal groundwater changes in relation to geological characteristics. Large-scale groundwater changes are estimated using GRACE-derived TWS and altimetry observations in addition to GLDAS and WGHM model outputs. Additionally, TRMM precipitation data are used to infer impacts of climate variability on groundwater fluctuations. The results indicate that climate variability mainly controls groundwater change trends while geological properties control change rates, spatial distribution, and storage capacity. Granular rocks in the Amazon and Guarani aquifers are found to influence larger storage capability, higher permeability (>10-4 m/s) and faster response to rainfall (1 to 3months' lag) compared to fractured rocks (permeability <10-7 m/s and lags > 3months) found only in Bambui aquifer. Groundwater in the Amazon region is found to rely not only on precipitation but also on inflow from other regions. Areas beyond the northern and southern Amazon basin depict a 'dam-like' pattern, with high inflow and slow outflow rates (recharge slope > 0.75, discharge slope < 0.45). This is due to two impermeable rock layer-like 'walls' (permeability <10-8 m/s) along the northern and southern Alter do Chão aquifer that help retain groundwater. The largest groundwater storage capacity in Brazil is the Amazon aquifer (with annual amplitudes of > 30cm). Amazon's groundwater declined between 2002 and 2008 due to below normal precipitation (wet seasons lasted for about 36 to 47% of the time). The Guarani aquifer and adjacent coastline areas rank second in terms of storage capacity, while the northeast and southeast coastal regions indicate the smallest storage capacity due to lack of rainfall (annual average is rainfall <10cm).