Flooding dynamics on the lower Amazon floodplain: 1. Hydraulic controls on water elevation, inundation extent, and river-floodplain discharge

Abstract

[1] Modeling the routing of flood waters across large floodplains is challenging because flows respond to dynamic hydraulic controls from complex geomorphology, vegetation, and multiple water sources. In this study, we analyzed the topographic and hydrologic controls of inundation dynamics of a large floodplain unit (2440 km 2 ) along the lower Amazon River. We combined land topography derived from the Shuttle Radar Topography Mission (SRTM) with underwater topography derived from an extensive echo-sounding survey to generate a seamless digital elevation model (DEM). Floodplain inundation was simulated using LISFLOOD-FP, which combines one-dimensional river routing with two-dimensional overland flow, and a local hydrological model. For the first time, accurate simulation of filling and drainage of an Amazon floodplain was achieved with quantification of changes in water elevation, flooding extent, and river-floodplain exchange. We examined the role of diffuse overbank versus channelized flows on river-floodplain exchange. Diffuse overbank flows represent 93% of total river to floodplain discharge and 54% of floodplain to river discharge. Floodplain discharge during high-water was four times higher than field observation values when the SRTM v.4 DEM with no correction was used for simulation because of a 24.4 m elevation bias originating from residual motion errors of the SRTM interferometric baseline.

Correction of Interferometric and Vegetation Biases in the SRTMGL1 Spaceborne DEM with Hydrological Conditioning towards Improved Hydrodynamics Modeling in the Amazon Basin

“…SRTM data products have been validated on continental scales: the absolute and relative vertical accuracies over South America are 6.2 m and 5.5 m, respectively [31]. Rudorff et al [26] found a local negative bias of 4.4 m in an Amazonian floodplain located downstream from the Janauacá floodplain. Satgé et al…”

“…According to Hess et al [38], the classification accuracy varies from 94% for the flooded class and 76% for the non-flooded class at the HW level and 84% for the flooded and 89% for the non-flooded class at the LW level. Flood maps during the LW and HW seasons (denoted LWFM and HWFM, respectively) deduced from the WM are commonly used to assess the ability of hydrological and hydraulic models to reproduce the inundation in the central Amazon basin [4,26,27,35,40].…”

“…Hydrodynamics models, such as LISFLOOD-FP, originally developed by Bates and De Roo [20] and progressively improved [21][22][23], are attractive in this context. This model (or an adapted version) has been applied in the Amazon, from regional (thousands of km) [5,24] to medium (hundreds of km) spatial scales [25][26][27]. However, relatively high quality topographic data are obviously required to produce consistent results.…”

Characteristics and Factors Influencing the Hysteresis of Water Area–Stage Curves for Poyang Lake

“…Regarding area-stage relationships, clockwise hysteresis is reported for river floodplain systems, as some water remains in local low-lying zones during the water-falling period, producing an area larger than that of the water-rising period (e.g., [11]). With regard to discharge-stage relationships caused by flooding, counter-clockwise hysteresis appears due to an additional surface gradient originating from flooding occurring during the flood rising period [14].…”

“…In some lakes, hysteretic phenomena can be observed, i.e., a given stage value may correspond to different area values. Rudorff et al simulated the flood dynamics of the lower Amazon floodplain, observing that inundation areas are smaller during the water-rising period than during the water-falling period for the same water level [11]. Ogilvie …”