Development of digital bathymetry maps for Lakes Azuei and Enriquillo using sonar and remote sensing techniques

This article presents an improved algorithm for optimization and development of a digital bathymetric model (DBM) for Lake Azuei (LA) (Haiti) and Lake Enriquillo (LE) (Dominican Republic) using the ANUDEM method. Both sonar data and contour lines of the lakes’ layout extracted using Landsat imagery were compiled for bathymetry development. We show that the performance of the ANUDEM method was strongly dependent on the density and irregularity of the spatial distribution of the data. Changing the resolution of the output grids and deriving auxiliary topographically corrected contours improved the ANUDEM performance and minimized the systematic errors of the method. Statistical analysis showed no significant difference between measured and interpolated depths, characterized by a root mean square error of less than 0.71 m (LE) and 0.96 m (LA), and a median difference of −0.009 m (LE) and 0.012 m (LA) on average. The shape reliability analysis revealed a relationship between accuracy and the depth and slope values, increasing in the center of the lakes where they are deep and the slope is gentle

Lake Volume Data Analyses: A Deep Look into the Shrinking and Expansion Patterns of Lakes Azuei and Enriquillo, Hispaniola

This paper presents the development of an evenly spaced volume time series for Lakes Azuei and Enriquillo both located on the Caribbean island of Hispaniola. The time series is derived from an unevenly spaced Landsat imagery data set which is then exposed to several imputation methods to construct the gap filled uniformly‐spaced time series so it can be subjected to statistical analyses methods. The volume time series features both gradual and sudden changes the latter of which is attributed to North Atlantic cyclone activity. Relevant cyclone activity is defined as an event passing within 80 km and having regional monthly rainfall averages higher than a threshold value of 87 mm causing discontinuities in the lake responses. Discontinuities are accounted for in the imputation algorithm by dividing the time series into two sub‐sections: Before/after the event. Using leave‐p‐out cross‐validation and computing the NRMSE index the Stineman interpolation proves to be the best algorithm among 15 different imputation alternatives that were tested. The final time series features 16‐day intervals which is subsequently resampled into one with monthly time steps. Data analyses of the monthly volume change time series show Lake Enriquillo’s seasonal periodicity in its behavior and also its sensitivity due to the occurrence of storm events. Response times feature a growth pattern lasting for one to two years after an extreme event, followed by a shrinking pattern lasting 5–7 years returning the lake to its original state. While both lakes show a remarkable long term increase in size starting in 2005, Lake Azuei is different in that it is much less sensitive to storm events and instead shows a stronger response to just changing seasonal rainfall patterns