Keywords
minimum sustainable flow, water quality modelling, fuzzy reasoning, fuzzy inference systems, artificial intelligence
Start Date
1-7-2008 12:00 AM
Abstract
Water resources in temperate and Mediterranean regions are increasingly scarce and water authorities need efficient criteria for the management of this precious commodity, guaranteeing an amount of water which ensures the preservation of aquatic life. This minimal discharge is referred to as the Minimum Sustainable Flow (MSF) and has been subject to many differing definitions in differing contexts. Gradually the purely hydraulic definition, very popular in the past, has given way to more comprehensive indicators taking into account the river ecosystem, and fish in particular, leading to very popular methods such as the IFIM (Instream Flow Incremental Methodology). The drawback of this approach is that it requires extensive field measurements and is very localized in space. This paper presents an extension of IFIM, extending its validity from the microhabitat to the macrohabitat and introducing several water quality parameters. From the methodological viewpoint, the new MSF definition is based on a Sugeno fuzzy inferential system, enhancing the system flexibility in producing environmental scenarios. As an example the method is applied to the middle-lower course of the Arno river, flowing in central Italy, showing that this method is better able to detect critical situations than the conventional IFIM approach.
A new definition of Minimum Sustainable Flow based on water quality modelling and fuzzy processing
Water resources in temperate and Mediterranean regions are increasingly scarce and water authorities need efficient criteria for the management of this precious commodity, guaranteeing an amount of water which ensures the preservation of aquatic life. This minimal discharge is referred to as the Minimum Sustainable Flow (MSF) and has been subject to many differing definitions in differing contexts. Gradually the purely hydraulic definition, very popular in the past, has given way to more comprehensive indicators taking into account the river ecosystem, and fish in particular, leading to very popular methods such as the IFIM (Instream Flow Incremental Methodology). The drawback of this approach is that it requires extensive field measurements and is very localized in space. This paper presents an extension of IFIM, extending its validity from the microhabitat to the macrohabitat and introducing several water quality parameters. From the methodological viewpoint, the new MSF definition is based on a Sugeno fuzzy inferential system, enhancing the system flexibility in producing environmental scenarios. As an example the method is applied to the middle-lower course of the Arno river, flowing in central Italy, showing that this method is better able to detect critical situations than the conventional IFIM approach.
