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On the use of GIS and DPSIR methods to analyse water quality in Seybouse Valley (North East of Algeria)

By: Aissam Ghrieb, Fethi Baali, Azzedine Hani, Larbi Djabri, Chemseddine Fehdi, Hicham Chaffai

Key Words: Water quality, GIS, DPSIR model, ANN, Seybouse Valley, Algeria.

J. Bio. Env. Sci. 14(6), 114-125, June 2019.

Certification: jbes 2019 0176 [Generate Certificate]

Abstract

Water sustainability in Seybouse Valley (North East of Algeria), must recognize the importance of water quantity and quality integration. So, there is a need for a better knowledge and understanding of the water quality determinants of groundwater abstraction to meet the municipal and agricultural uses. The quality of this ground water was determined by Water Abstraction from coastal aquifer (WAbs). This represents the amounts of water pumped by municipal wells in addition to the agricultural wells. It is measured by million cubic meters per year (hm3.y-1). The purposes of this investigation were to provide an overview of ground water quality and to determine spatial distribution of quality parameters in the study area using GIS tools. A new conceptual integrated water-management model has been developed, based on cause-effect relationships. The Driver-Pressure-State-Impact-Response was selected as a well-established framework to allocate the possible variables into five categories: namely socio-economic; pollution pressures; water quality; impacts; and management responses. In this paper, the artificial neural network (ANN) models were used to model and predict the relationship between groundwater abstraction and water quality determinants in the Seybouse Valley (North East of Algeria). The study area chosen is the Seybouse Valley and real data were collected from twenty-five wells for reference year 2006. Results indicate that the feed-forward multilayer perceptron models with back-propagation are useful tools to define and prioritize the important water quality parameters of groundwater abstraction and use. The model evaluation shows that the correlation coefficients are more than 97% for training, verification and testing data. The model aims to link the water quantity and quality with the objective to strengthen the Integrated Water Resources Management approach.

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On the use of GIS and DPSIR methods to analyse water quality in Seybouse Valley (North East of Algeria)

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Aissam Ghrieb, Fethi Baali, Azzedine Hani, Larbi Djabri, Chemseddine Fehdi, Hicham Chaffai.
On the use of GIS and DPSIR methods to analyse water quality in Seybouse Valley (North East of Algeria).
J. Bio. Env. Sci. 14(6), 114-125, June 2019.
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