Using GIS for spatio-temporal assessment of some physicochemical parameters in the bay of Algiers

This work proposes a procedure to quantify spatiotemporal variation of some coastal water quality parameters measured in the bay of Algiers by implementing a Geographical Information System (GIS). The study area is the receptacle of several and various pollution sources which has significant impacts on the marine environment. Therefore, several studies are conducted [1], [2] and campaigns are organized each year in order to measure physicochemical parameters to assess the impact of those sources of pollution on the coastal water quality. Nevertheless, those measurements are punctual and spatially irregular making spatiotemporal analysis slightly difficult. However, environmental managers often require spatially continuous data over the region of interest to make effective and confident decisions and scientists need accurate spatially continuous data across a region to make justified interpretations [3]. Indeed, to obtain an estimate of the parameters in a continuous space, we calculate interpolated grids for each parameter using the appropriate interpolation method (Inverse Distance Weighted, Ordinary kriging, etc.). The purpose of monitoring the qualitative and quantitative parameters of aquatic ecosystems (springs, streams, rivers, fiords, estuaries, offshore and marine waters) is the approximation and estimation of their environmental situation and trends [4]. Traditionally, the spatiotemporal assessment of a parameter measured in mainland is done by observing the evolution of measured values at all stations all along the time axis or by calculating a mean value for each date. In [5], spatiotemporal assessment of a multi-decadal European climate dataset is done by using temporal GIS TGrass; seasonal temperature trends of Europe and some capitals were given by calculating mean temperatures. At sea, things are different; the measured stations are not stationary and there's very low probability for a site to be measured more than once especially when campaigns are organized by different operators. To make possible the spatiotemporal assessment cited previously, we propose in this study, a procedure to do the analysis on a configuration of "not sampled" or "theoretical" stations but representative of any changes. The physicochemical measurements associated with these theoretical stations will be retrieved from the estimated respective grids. The spatiotemporal assessment can be done so on the basis of these theoretical but fixed stations. Value-added products are also obtained from the GIS such as spatial distribution maps with a representation of iso-value curves of each parameter. This procedure is especially interesting when one wants to analyze multi-sources (from different campaigns) in-situ measurements.