A geographic analysis for strengthening community capabilities to face variability and climate change, case of study: Cuajiniquil, La Cruz, Guanacaste, Costa Rica.

Keywords: physical geography, watershed, climate change, adaptation
Session Type: Virtual Poster Abstract
Day: Monday
Session Start / End Time: 2/28/2022 11:20 AM (Eastern Time (US & Canada)) - 2/28/2022 12:40 PM (Eastern Time (US & Canada))
Room: Virtual 33

Abstract

Cuajiniquil is a community that belongs to La Cruz municipality in Guanacaste province, located in the Northern Pacific Coast of Costa Rica and inside the Central America’s Dry Corridor (CADC). Cuajiniquil presents extreme hydrometeorological events that can affect its population livelihoods. Fishing, cattle, and tourism are developed, and surrounding areas are dedicated to wildlife conservation. A regular year in terms of precipitation sums about 1100 millimeters, with a dry season from December to April (5%), and the rainy season from May to November (95%). This marked dry season also promote water access problems for the human activities. Therefore, Cuajiniquil population need to improve their methods of managing water limitations in a warming world scenario.
Cuajiniquil river watershed has been analyzed geographically to better understand the relationships between environmental and social factors. To identify the land uses associated with each basin part, we elaborated a participatory basin diagram based on Geilfus (2002). In the upper catchment, SRNP protects the natural resources. In the middle section, there are some cattle, but no agricultural production due to the limited-developed edaphic conditions. Tourism, fishing, and conservation are developed at the bottom section of the catchment.
The second phase of this investigation involves an interdisciplinary team working on strengthening community capabilities to understand the environment characteristics, variability and climate change that will affect them in the short term (IPCC, 2021). Stakeholders will be able to understand scientific data and how to interpret and communicate it on a local level to project future investments.