Spatial Modeling of Flood Duration in Amazonian Floodplains Through Radar Remote Sensing and Generalized Linear Models
Abstract
Amazon floodplains play an important role in biodiversity maintenance and provide important ecosystem services. Flood duration is the prime factor modulating biogeochemical cycling in Amazonian floodplain systems, as well as influencing ecosystem structure and function. However, due to the absence of accurate terrain information, fine-scale hydrological modeling is still not possible for most of the Amazon floodplains, and little is known regarding the spatio-temporal behavior of flooding in these environments. Our study presents an new approach for spatial modeling of flood duration, using Synthetic Aperture Radar (SAR) and Generalized Linear Modeling. Our focal study site was Mamirauá Sustainable Development Reserve, in the Central Amazon. We acquired a series of L-band ALOS-1/PALSAR Fine-Beam mosaics, chosen to capture the widest possible range of river stage heights at regular intervals. We then mapped flooded area on each image, and used the resulting binary maps as the response variable (flooded/non-flooded) for multiple logistic regression. Explanatory variables were accumulated precipitation 15 days prior and the water stage height recorded in the Mamirauá lake gauging station observed for each image acquisition date, Euclidean distance from the nearest drainage, and slope, terrain curvature, profile curvature, planform curvature and Height Above the Nearest Drainage (HAND) derived from the 30-m SRTM DEM. Model results were validated with water levels recorded by ten pressure transducers installed within the floodplains, from 2014 to 2016. The most accurate model included water stage height and HAND as explanatory variables, yielding a RMSE of ±38.73 days of flooding per year when compared to the ground validation sites. The largest disagreements were 57 days and 83 days for two validation sites, while remaining locations achieved absolute errors lower than 38 days. In five out of nine validation sites, the model predicted flood durations with disagreements lower than 20 days. The method extends our current capability to answer relevant scientific questions regarding floodplain ecological structure and functioning, and allows forecasting of ecological and biogeochemical alterations under climate change scenarios, using readily available datasets.
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2017
- Bibcode:
- 2017AGUFM.H51D1302F
- Keywords:
-
- 1813 Eco-hydrology;
- HYDROLOGY;
- 1820 Floodplain dynamics;
- HYDROLOGY;
- 1830 Groundwater/surface water interaction;
- HYDROLOGY;
- 1852 Plant uptake;
- HYDROLOGY