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Technological advancement and exponential rise in the human population have led to severe modification of the land surface area. These human‐induced geomorphic modifications are considered as an active geomorphic process that interrupts dynamic equilibrium between landform and anthropogeomorphologic processes. The present study aimed to evaluate the efficiency of Nir's 'Index of potential anthropic geomorphology' used to quantify anthropogeomorphic process (AGP) impact. The model was applied in 11 talukas (sub‐districts) of Goa State, India. Goa is a good candidate to understand the impact of anthropogeomorphological process because it has a varied topography with different geomorphological landforms along with rapid increase in urbanisation and mining activities which are anthropocentric. Decadal results show that, during 1991, 2001, and 2011, the tourism hubs of North Goa Bardez (0.32, 0.36, and 0.40) and Tiswadi (0.44, 0.42, and 0.47) required least attention to curb human impact, while the major economic and tourism hubs of South Goa Marmugao (0.55, 0.53, and 0.40) and Salcete (0.40, 0.40, and 0.40) surprisingly showed no increase but instead a decline in the values. In addition, prominent mining talukas Bicholim (0.25, 0.30, and 0.20), Quepem (0.45, 0.39, and 0.15), and Sanguem (0.24, 0.22, and 0.18) also showed declining values, which is indicative of decreased human activities. The index results suggest 'no requirement of urgent and efficient measures' in any talukas because none of the values have been found to be above 0.50, which according to the model represents considerable damage to geomorphology. However, Goa is a world‐renowned tourism destination and all these talukas have witnessed massive urban development, high literacy rate, and exponential growth in National State Domestic Product and mining activities, especially since the turn of the millennium, which are contrary to Nir's index results. Therefore, the model has been found to be over‐generalised and ineffective in indicating actual AGP at the meso level. [ABSTRACT FROM AUTHOR]

The research aims to propose the new ensemble models by combining the machine learning techniques, such as rotation forest (RF), nearest shrunken centroids (NSC), k-nearest neighbour (KNN), boosted regression tree (BRT), and logitboost (LB) with the base classifier adabag (AB) for flood susceptibility mapping (FSM). The proposed models were implemented in the central west coast of India, which is vulnerable to flood events. For flood inventory mapping, a total of 210 flood localities were identified. Twelve effective factors were selected using the boruta algorithm for FSM. The area under the receiver operating characteristics (AUROC) curve and other statistical measures (sensitivity, specificity, accuracy, kappa, root mean square error (RMSE), and mean absolute error (MAE)) were employed to estimate and compare the success rate of the approaches. The validation results of the individual models in terms of AUC value were AB (92.74%) >RF (91.50%) >BRT (90.75%) >LB (89.07%) >NSC (88.97%) >KNN (83.88%), whereas the ensemble models showed that the AB-RF (94%) was of the highest prediction efficiency followed by, AB-KNN (93.33%), AB-NSC (93.02%), AB-LB (92.83%), and AB-BRT (92.64%). The outcomes of the ensemble models established that the AB is more appropriate to increase the accuracy of different single models. Therefore, this study can be useful for proper planning and management of the study area and flood hazard mapping in alike geographic environment. [ABSTRACT FROM AUTHOR]

There is a constant conflict for water amongst various sectors. This is further aggravated by climate change. It is crucial to establish interaction between land-use combined with climate change and local hydrology to devise sustainable management strategies. This study used the Norwegian Earth System Model (NorESM) climate model, Land Change Modeler (LCM) and Soil and Water Assessment Tool (SWAT) hydrological model. This ensemble of models was used to predict Sal River flow in Goa, India under two Representative Concentration Pathway (RCP 4.5 and 8.5) climate scenarios. The statistically tested results indicate that the future rainfall and temperature is likely to increase and more pronounced under RCP 4.5 scenario. However, climate combined with land-use change reveals that the streamflow is likely to increase with increase in the urban/concrete areas and decline with reduction in the forest areas. For Sal River watershed, the forest cover is likely to decrease by 5.93% up to 2040s, with a corresponding increase in the urban/settlement areas. With the increase in the built-up areas, the surface runoff may increase and lead to an urban flooding-like situation. Dependable flows for this watershed were computed to comprehend future water availability. Site-specific recommendations have been formulated to aid the decisionmakers to implement the timely adaptation measures. [ABSTRACT FROM AUTHOR]

The Precambrian greywacke of Ribandar-Chimbel belonging to the Sanvordem Formation of the Goa Group, India, has been studied for petrography and analyzed for major trace elements. The greywacke is characterized by angular to sub-round grains of quartz, feldspar, biotite, chlorite and clay minerals. The abundance of clay in the matrix seems to have influenced the Al2O3 content and the K2O/Al2O3 ratio. The variation diagrams indicate a decreasing trend of TiO2, Al2O3, Fe2O3 and MgO; whereas Na2O and CaO exhibit a scatter which could be a result of the variable presence of feldspar within the sediments. The immobile elements, vanadium (25 to 144 ppm), nickel (up to 107 ppm) and chromium (up to 184 ppm), reflect abundance of clay minerals. The greywacke shows strongly fractionated REE patterns with LaN/YbN = 8 to 26 and with higher total REE abundances (up to 245 ppm). The low REE enrichment and depletion in heavier REE with prominent negative Eu anomaly (Eu/Eu*= 0.54 to 0.79) suggest a derivation of the greywacke from an old upper continental crust composed chiefly of felsic components. Petrological evidence and geochemical data suggest that the deposition of the greywacke largely took place in a deep to shallow basin that progressively changed from that of a continental island arc to an active continental setting. [ABSTRACT FROM AUTHOR]