Environmental flow assessment in Andean rivers of Ecuador, case study: Chanlud and El Labrado dams in the Machángara River

The allocation of water flowing through a river-with-reservoirs system to optimally meet spatially distributed and temporally variable demands can be conceived as a network flow optimization (NFO) problem and addressed by linear programming (LP). In this paper, we present an extension of the strategic NFO-LP model of our previous model to a mixed integer linear programming (MILP) model to simultaneously optimize the allocation of water and the location of one or more new reservoirs; the objective function to minimize only includes two components (floods and water demand), whereas the extended LP-model described in this paper, establishes boundaries for each node (reservoir and river segments) and can be considered closer to the reality. In the MILP model, each node is called a “candidate reservoir” and corresponds to a binary variable (zero or one) within the model with a predefined capacity. The applicability of the MILP model is illustrated for the Machángara river basin in the Ecuadorian Andes. The MILP shows that for this basin the water-energy-food nexus can be mitigated by adding one or more reservoirs.

“…The maximum depth of the reservoir is 13 m and the reservoir's storage capacity is 6.15 hm 3 [10][11][12]. The regulated discharge is 2.4 m 3 /s [11][12][13].…”

Section: Reservoirs Hydropower Production and Other Water Usesmentioning

confidence: 99%

MILP for Optimizing Water Allocation and Reservoir Location: A Case Study for the Machángara River Basin, Ecuador

Veintimilla-Reyes

Meyer

Cattrysse

et al. 2019

“…During spring and autumn, their preferences were more variable, but in general, a preference for shallower and slow-flowing habitats was observed, with the habitat suitability peaking at the lowest discharges mostly in spring. Although seasonal differences in macroinvertebrate-community abundance and composition have long been reported in literature [48][49][50][51][52], community-shifts in their habitat preferences have not been studied; we assume that such 'shifting behavior' may be associated with the seasonal fluctuation of environmental variables, which are known primary drivers of BMI-community changes, that is, shading, water temperature and dissolved oxygen [53]. As summer approaches, shading from the surrounding riparian vegetation is reduced, the water temperature increases, the dissolved oxygen concentration decreases [54] and consequently, faster flowing, deeper, better oxygenated habitats provide shelter against the changing environment.…”

Section: Seasonal and Temporal Variation In The Habitat Preferences Omentioning

confidence: 99%

Spatiotemporal Variation in Benthic-Invertebrates-Based Physical Habitat Modelling: Can We Use Generic Instead of Local and Season-Specific Habitat Suitability Criteria?

Theodoropoulos

Skoulikidis

Stamou

et al. 2018

Generic habitat suitability criteria (HC) are often developed from spatially and temporally variable hydroecological datasets to increase generality, cost-effectiveness, and time-efficiency of habitat models. For benthic macroinvertebrates (BMIs), however, there is no prior knowledge on the spatiotemporal variation in their habitat preferences and how this may be reflected in the final environmental flow (e-flow) predictions. In this study, we used a large, spatiotemporally variable BMI-hydroecological dataset and developed generic, local, and season-specific subsets of HC for three seasons and two river types within various data pre-treatment options. Each subset was used to train a fuzzy habitat model, predict the habitat suitability in two hydrodynamically-simulated river reaches, and develop/compare model-based e-flow scenarios. We found that BMIs shift their habitat preferences among seasons and river types; consequently, spatiotemporally variable e-flow predictions were developed, with the seasonal variation being greater than the typological one. Within this variation, however, we found that with proper data pre-treatment, the minimum-acceptable e-flows from the generic models mostly (65–90%) lay within the acceptable e-flows predicted by the local and season-specific models. We conclude that, within specific limitations, generic BMI-HC can be used for geographically extended, cost-effective e-flow assessments, compensating for the within-limits loss of predictive accuracy.

“…Even though such issues are of worldwide concern, these fears are not seriously judged in developing countries [39][40][41]. For instance, in Ecuador's capital, Quito, indiscriminate wastewater discharges carrying several EPs are released from the city into the Machángara River (pretreatment) channel, which is, in turn, discharged to the river basin [42][43][44]. Downstream, the river captures sewage from most of Quito's population and the northeastern valleys, making the natural pretreatment ineffective [45][46][47][48].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Physicochemical Parameters, Carbamazepine and Diclofenac as Emerging Pollutants in the Machángara River, Quito, Ecuador

Ibarra,

Bolaños-Guerrón,

Cumbal-Flores

2024

This study evaluates the pollution of the Machángara River basin in Ecuador. For the assessment, water samples were pumped from the river for 1 to 4 h, with a representative water sample of 4 L collected. In the site and laboratory, the physicochemical parameters, carbamazepine (CBZ), and diclofenac (DIC) concentrations were measured using standardized analytical methods. On average, a temperature of 17.02 °C, pH of 7.06, electrical conductivity of 760.96 µS/cm, and turbidity of 83.43 NTU were found. Furthermore, the average solids content was 72.88, 495.47, and 568.35 mg/L for total suspended solids (TSS), total dissolved solids (TDS), and total solids (TS) in that order. The highest chloride concentration (Cl− = 87.97 mg/L) was below the maximum permissible limit (MPL) based on the Ecuadorian regulations for surface and underground water for human consumption and domestic use, which only require conventional treatment. In contrast, levels of nitrate (NO3− = 27.75–288.25 mg/L) and nitrite in five points (NO2− = 2.02–5.42 mg/L) were higher than the MPLs. Moreover, sulfate (SO42− = 34.75–110 mg/L) and phosphate (PO4−P = 4.15–16.58 mg/L) contents caused turbidity and eutrophication in the river water., Additionally, concentrations of copper (Cu2+ = 0.002–0.071 mg/L), zinc (Zn2+ = 0.001–0.011 mg/L) and iron (Fe3+ = 0.000–0.287 mg/L) were within the permissible limits. On the other hand, carbamazepine concentrations in the Machángara River basin were below the limit of detection (LOD) up to a value of 0.121 mg/L. At the same time, diclofenac levels ranged from 9.32 to 48.05 mg/L. The concentration discrepancy for both pharmaceuticals is linked with the trend of drug consumption by Quito’s inhabitants. As measured in this investigation, meaningful amounts of CBZ and DIC are released to the Machángara River. Accordingly, the two pharmaceuticals in the river water may be dangerous for aquatic species.