One-Dimensional Hydraulic Analysis of the Effect of Sea Level Rise on Salinity Intrusion in the Sebou Estuary,Morocco

Global climate change has resulted in a gradual sea-level rise. Sea-level rise can cause saline water to migrate upstream in estuaries and rivers, thereby threatening freshwater habitat and drinking water supplies. On the other hand, sea-level rise, resulting from thermal expansion of ocean waters and increased melting of glaciers and ice caps, is one of the most apparent and widespread consequences of climate change. This phenomenon has been taken into account in all the Assessment Reports published by the Intergovernmental Panel on Climate Change (IPCC). In this paper, salinity intrusion and intrusion length due to possible sea-level rise in the Sebou estuary (Morocco) was investigated. A one-dimensional hydrodynamic-salinity transport model was used for the simulation of the salinity intrusion and associated water quality, with observed field data being used for model calibration and validation. Additionally, the model validation process showed that the model results fit the observed data fairly well. A coupled gas-cycle/climate model was used to generate the climate change scenarios in the studied area that showed sea-level rises varying from 0.3 to 0.9 m for 2100. The models were then combined to assess the impact of future sea-level rise on the salinity distribution and intrusion length in the Sebou estuary. The response of salt intrusion length to changes in important dimensional parameters are presented, showing that the salinity intrusion length is inversely correlated with the river discharge, i.e., a high river discharge results in a reduced salt intrusion and vice versa, and directly with the sea-level rise. Additionally, the magnitude and frequency of the salinity standard violations at the two pump stations were predicted for 2100, showing that the salinity violations under climate change effects can increase to ～45–48% of the times at these locations. Finally, the main objective of this simulation method is to accelerate and facilitate of systems' behavior learning in the current and future situation.