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An Empirical Model for River Ecological Management with Uncertainty Evaluation

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River Basin District Authorities make use of water quality models in order to assess the environmental status of water bodies. The current Italian procedure aiming to classify the ecological status… Click to show full abstract

River Basin District Authorities make use of water quality models in order to assess the environmental status of water bodies. The current Italian procedure aiming to classify the ecological status of a watercourse employs the quality assessment of four biological elements with the support of some chemical and physical elements. Since many measures of the Directive 2000/60/CE affect the chemical and physical elements of the river, the Tiber River Basin Authority (TRBA) has designed an empirical model linking the anthropogenic pressures, the chemical and physical elements of impacts and river biological quality elements. The general model is named PARBLEU, which stands for Pressures/impacts/responses Assessment into River Basins Leading to Environmental Uses. In the present manuscript, only a sub-model of PARBLEU (ecological sub-model concerning the interactions of impacts on water and biota matrices) is discussed. The sub-model is able to simulate the ecological status of river water bodies by acting on the control of impacts, in particular relating to changes of nutrients and dissolved oxygen. The aim of the present study was threefold. First, to select an appropriate functional form for the model and choose which variables to be included (specification process but without validation). Second, to simulate the responses (and the associated uncertainty) on biological elements due to a hypothesized change of chemical and physical conditions. Third, to provide a user friendly tool, but sufficiently reliable, for the professionals, regional technical structures and Authorities.

Keywords: uncertainty; water; river; empirical model; chemical physical; model

Journal Title: Water Resources Management
Year Published: 2017

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