Integrating hydraulic, physicochemical and ecological models to assess the effectiveness of water quality management strategies for the River Cuenca in Ecuador

During the past decades, the development and use of ecological models to predict the presence or absence of macroinvertebrates as water quality indicators for decision support in river management has gained a lot of interest. However, these models rarely integrate hydromorphological, physicochemical, and biological components in the submodels. We developed a generic framework for decision support in water management that can be applied to any river basin based on an integrated modelling approach. This approach integrates a mechanistic hydraulic and physicochemical water quality model with aquatic ecological models. Two types of ecological models were developed, habitat suitability models to predict the occurrence of macroinvertebrates and ecological assessment models to predict a biotic index score. Our main purpose was to assess the effectiveness of different wastewater treatment/disposal strategies considering receiving water's ecological aspects and to determine water quality requirements. This paper presents the testing and validation of this integrated framework on a case study of a mountain river (River Cuenca) in the Andes of Ecuador. Three wastewater management scenarios were tested. The different scenarios indicated that the foreseen investments in sanitation infrastructure will lead to modest improvements of the ecological water quality. This improvement (i.e. increase of the biotic index) was only identified in 6 of the 21 monitoring stations considered in the River Cuenca and its tributaries. Therefore, it is necessary to control the impact of the industrial wastewaters discharges and the diffuse pollution at the upper catchment of the tributaries to achieve a good ecological status. With these results, we proved that integrated models, like the one presented here, have an added value for decision support in water management by coupling ecological water quality to a set of hydraulic and chemical water quality measures based on a water quality model. In order to improve these models, it is necessary to change the river monitoring strategy towards collection of data which include simultaneous measurements of physicochemical, hydromorphological and biological data.