Landcover Dynamics and their Influence on the Seasonal and Interannual
Hydrology of an Amazonian Floodplain Using Hydrological Model and
Satellite
Abstract
The spatio-temporal land cover dynamics of a medium‐size floodplain
system along the Amazon/Solimões River (Janauacá Lake, 786 km
2) and their hydrological impacts are studied through
remote sensing and modeling. Hence, the analysis of 5 satellite-derived
land cover maps (1972-2016 period) reveals a decrease in natural
environments (from 65% to 35%) to the benefit of anthropic classes
(from 17% to 51%) through deforestation vectors (two highways and lake
banks). Deforestation is a non-stationary process with significant
increase over specific subperiods (1972-1986, and 2005-2016). It occurs
in stages with conversions into secondary vegetation then into
non-natural environments. 7 land cover scenarios (5 satellite-derived, 1
deforested and 1 forest, used as reference) are used as inputs to run
simulations with the same meteorology over the 2006-2018 period. Beside
high ( ≥ 24%) and low ( ≤ 7%) interannual variability of
runoff-rainfall ratio (RRR) and evapotranspiration (ET), the numerical
experiments evidence, on an annual scale, the RRR decreases and the ET
increases with deforestation increases. Deforested scenario suggests a
convergence: for the RRR, around 0.34 (-87%) and for the ET, around
1146 mm.yr -1 (+6%). At the seasonal scale, the
landuse/landcover changes (LUCC) induce positive wet season ET anomaly
(<9%) and large negative dry season RRR anomaly (-87%). The
highest LUCC-induced disturbances (from -15% to 18%) in the FP mixture
are recorded at seasonal scale, during LW and RW and, at interannual
scale, during dry and normal HY. The LUCC-induced disturbances patterns
of FP mixture mainly concern river and runoff. They are different
regarding the hydrological period or HY type. Our experiments suggest
the existence of a tipping point between present land cover (2016) and
fully deforested cover associated with reversal phenomena and enhancing
of seasonal and interannual LUCC-induced disturbance. At last, the model
shows the LUCC augment the vulnerability associated with drought
periods.