Climate Change-Induced Shifts in the Hydrological Regime of the Upper Amazon Basin and Its Impacts on Local Eco-Hydrology

Monday, 15 December 2014: 4:15 PM
Zed Diyana Zulkafli, Imperial College London, London, SW7, United Kingdom; Universiti Putra Malaysia, Department of Civil Engineering, Serdang, Malaysia, Wouter Buytaert, Imperial College London, Civil and Environmental Engineering and Grantham Institute for Climate Change, London, SW7, United Kingdom and Claudia Veliz, Universidad Nacional Agraria La Molina, Centro de Datos para La Conservacion, Lima, Peru
The potential impact of a changing climate on Andean-Amazonian hydrology is an important question for scientists and policymakers alike, because of its implications for local ecosystem services such as water resources availability, river flow regulation, and eco-hydrology. This study presents new projections of climate change impacts on the hydrological regime of the upper Amazon river in Peru, and the consequent effect on two vulnerable species of freshwater turtle populations Podocnemis expansa (Amazon turtle) and Podocnemis unilis (yellow-spotted side neck turtle), which nest on its banks.

To do this, the global climate model outputs of radiation, temperature, precipitation, wind, and humidity data from the Coupled Model Inter-comparison Project Phase 5 (CMIP5) are propagated through a hydrological model to simulate changes in river flow. The model consists of a land surface scheme called the Joint-UK Land Environment Simulator (JULES) that is coupled to a distributed river flow routing routine, which also accounts for floodplain attenuation of flood peaks. It is parameterized using a combination of remote sensing (TRMM, MODIS, an Landsat) and ground observational data to reproduce reliably the historical floodplain regime.

The climate-induced shifts are inferred from a comparison between the RCP 4.5 and 8.5 projections against the historical scenario. Changes in the 10th and 95th percentile of flows, as well as the distributions in the length of the dry and wet seasons are analysed. These parameters are then used to construct probability models of biologically significant events (BSEs - extreme dry year, extreme wet year and repiquete), which are negative drivers of the turtle-egg ovipositioning, nesting and hatching. The results indicate that the projected increase in wet-season precipitation overcome the increase in evapotranspirative demand from an increase in temperature, resulting in more frequent and longer term flooding that causes a net loss of total turtle-egg counts. Additionally, changes in air and water temperature may alter the male / female ratio of the turtles.