Evaluation of efficiency of the index of potential anthropic geomorphology at meso level: a case study of Goa State, India

Abstract

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.