Browsing by Author "Goethals, Peter L"

Now showing 1 - 4 of 4

A methodology to model environmental preferences of EPT taxa in the Machangara river basin (Ecuador)
(2017) Jerves Cobo, Rubén Fernando; Everaert, Gert; Iñiguez Vela, Xavier Patricio; Córdova Vela, Gonzalo Esteban; Díaz Granda, Catalina Monserrat; Cisneros Espinoza, Felipe Eduardo ; Nopens, Ingmar; Goethals, Peter L
Rivers have been frequently assessed based on the presence of the Ephemeroptera— Plecoptera—Trichoptera (EPT) taxa in order to determine the water quality status and develop conservation programs. This research evaluates the abiotic preferences of three families of the EPT taxa Baetidae, Leptoceridae and Perlidae in the Machangara River Basin located in the southern Andes of Ecuador. With this objective, using generalized linear models (GLMs), we analyzed the relation between the probability of occurrence of these pollution-sensitive macroinvertebrates families and physicochemical water quality conditions. The explanatory variables of the constructed GLMs differed substantially among the taxa, as did the preference range of the common predictors. In total, eight variables had a substantial influence on the outcomes of the three models. For choosing the best predictors of each studied taxa and for evaluation of the accuracy of its models, the Akaike information criterion (AIC) was used. The results indicated that the GLMs can be applied to predict either the presence or the absence of the invertebrate taxa and moreover, to clarify the relation to the environmental conditions of the stream. In this manner, these modeling tools can help to determine key variables for river restoration and protection management.
Biological impact assessment of sewage outfalls in the urbanized area of the Cuenca river basin (Ecuador) in two different seasons
(2018) Jerves Cobo, Rubén Fernando; Lock, Koen; Van Butsel, Jana; Pauta Calle, Gladys Guillermina; Cisneros Espinoza, Felipe Eduardo; Nopens, Ingmar; Goethals, Peter L
We evaluated the biological water quality in relation to chemicals discharged through sewage outfall during both dry and rainy season. The lowland area of the Cuenca River basin in the southern Andes of Ecuador, including the city of Cuenca, constituted the study area. To perform an integrated water quality assessment, data were collected of macroinvertebrates, physicochemical conditions and morphological characteristics in 43 sites in the Cuenca River and its tributaries. The Andean Biotic Index (ABI) and the Biological Monitoring Working Party adapted to Colombia (BMWP-Col) were used to evaluate the biological water quality. Both biological indexes were higher upstream than downstream from the city. Moreover, these indexes indicated better conditions during the rainy season than in the dry season, based on the presence of more sensitive families. The biological indexes related more to the oxygen saturation than to the five-day biological oxygen demand (BOD5), nutrients and chloride concentrations. The relationship between BOD5 and nutrient concentrations with the variation of both biological indexes was clearer in the dry season than in the rainy season. However, in some sites, these indexes were influenced more by morphological aspects than by pollutants. Both biological indexes showed similar patterns along the rivers, generally the BMWP-Col scored higher than the ABI index. The latter index was shown to be more suitable for the high Andes region. These results could be used to support the implementation of river restoration actions, such as determining priorities for splitting sewer and precipitation water transport systems and needs for improved wastewater treatment facilities in specific locations. © 2018 Elsevier GmbH
Biological water quality in tropical rivers during dry and rainy seasons: a model-based analysis
(2020) Jerves Cobo, Rubén Fernando; Eurie Forio, Marie Anne; Lock, Koen; Van Butsel, Jana; Pauta Calle, Gladys Guillermina; Cisneros Espinoza, Felipe Eduardo; Nopens, Ingmar; Goethals, Peter L
Recent studies on water quality in tropical rivers indicate substantial differences between seasons. However, investigations on the needs and added value of season-specific models are lacking. Thus, this paper aims to determine the accuracy and relevance of season-specific and season-overarching models to predict biological water quality. Additionally, we investigated the variation of prediction accuracy using sub-datasets from different parts of the Cuenca River basin. This study was accomplished in the rivers that pass through the urban and suburban areas of the city of Cuenca, which is located in the southern Andes of Ecuador. The Andean Biotic Index (ABI) was used as an indicator of biological water quality. Subsequently, models were developed to predict the ABI, with physicochemical and morphological variables as predictors, which were collected in 43 sites during both the dry and the rainy seasons. The predictions were obtained using three kinds of generalized linear models (GLMs): Gaussian, Gamma and Inverse Gaussian. The season-specific models were more accurate than the season-overarching models. Similarly, the predictions of the biological water quality in sites sampled in the urban area were more accurate than the forecasts performed in reference sites. The major variables predicting the ABI during the dry season were five-day biological oxygen demand (BOD5), ammonium and orthophosphate, while dissolved oxygen (DO), oxygen saturation (OS), nitrate, total solids proved to be important during the rainy season. The results of this research emphasize the importance of developing season-specific models and the implementation of different key actions for river restoration during both the dry and rainy seasons. The accuracy and the replication of these models could be improved and checked with more data taken from new sampling events. The modelling approach developed in this study can be applied to similar basins in the tropics and reveals that environmental investments need to count on monitoring strategies and data and analyses of the biological water quality variation in dry and rainy seasons, within the context of sustainable development.
Model-based analysis of the potential of macroinvertebrates as indicators for microbial pathogens in rivers
(2018) Jerves Cobo, Rubén Fernando; Van Echelpoel, Wout; Cisneros Espinoza, Felipe Eduardo; Nopens, Ingmar; Goethals, Peter L
The quality of water prior to its use for drinking, farming or recreational purposes must comply with several physicochemical and microbiological standards to safeguard society and the environment. In order to satisfy these standards, expensive analyses and highly trained personnel in laboratories are required. Whereas macroinvertebrates have been used as ecological indicators to review the health of aquatic ecosystems. In this research, the relationship between microbial pathogens and macrobenthic invertebrate taxa was examined in the Machangara River located in the southern Andes of Ecuador, in which 33 sites, according to their land use, were chosen to collect physicochemical, microbiological and biological parameters. Decision tree models (DTMs) were used to generate rules that link the presence and abundance of some benthic families to microbial pathogen standards. The aforementioned DTMs provide an indirect, approximate, and quick way of checking the fulfillment of Ecuadorian regulations for water use related to microbial pathogens. The models built and optimized with the WEKA package, were evaluated based on both statistical and ecological criteria to make them as clear and simple as possible. As a result, two different and reliable models were obtained, which could be used as proxy indicators in a preliminary assessment of pollution of microbial pathogens in rivers. The DTMs can be easily applied by staffwith minimal training in the identification of the sensitive taxa selected by the models. The presence of selected macroinvertebrate taxa in conjunction with the decision trees can be used as a screening tool to evaluate sites that require additional follow up analyses to confirm whether microbial water quality standards are met. © 2018 by the authors.