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Revista Digital Novasinergia

versão On-line ISSN 2631-2654

Novasinergia vol.5 no.2 Riobamba Jun./Dez. 2022  Epub 05-Jul-2022

https://doi.org/10.37135/ns.01.10.10 

Research article

Influence of geomorphology and flow on the water quality of Guano river, Ecuador

Influencia de la geomorfología y el caudal en la calidad del agua del río Guano, Ecuador

Nelly Guananga1 

Benito Mendoza2  * 

Freddy Guananga1 

Jaime Bejar1 

Carlos Carbonel3 

Sandra Noemí Escobar Arrieta1 

Absalón Wilberto Guerrero Rivera4 

1Escuela Superior Politécnica de Chimborazo, Riobamba, Ecuador, 060106; nguananga@espoch.edu.ec; freddy.guananga@espoch.edu.ec; bejarjaime@gmail.com

2Universidad Nacional de Chimborazo, Riobamba, Ecuador, 060150

3Universidad Nacional Mayor de San Marcos, Ciudad Universitaria, Lima, Perú, 15081, ccarbonelh@unmsm.edu.pe

4Universidad Estatal de Milagro, Milagro, Ecuador, 091701; aguerreror@unemi.edu.ec


Abstract:

The present study determines the water quality of the Guano River in Ecuador through the water quality indices WQI-NSF, WQI-Dinius, and a variant of the WQI-Dinius index that includes the average slope of the riverbed and the flow. To obtain qualitative values of water quality that allow better use of the river water. The results obtained with the three indices show that there is slight contamination in river sections caused by human activities, decreased flow, and wastewater discharge. Furthermore, the work shows that when applying the WQI-Dinius modified, the values of the weights of the water quality are lower concerning the other indices. But, even when the WQI-Dinius modified values are common, the valuation range for agricultural use is similar among the three indices, maintaining the criterion that the Guano River is slightly contaminated. Therefore, treating the water before using it in agricultural activities is necessary.

Keywords: Flow; geomorfología; solpe; water quality; WQI

Resumen:

El presente estudio determina la calidad del agua del río Guano en Ecuador mediante los índices de calidad del agua ICA-NSF, ICA-Dinius y una variante al índice ICA-Dinius que incluye la pendiente media del cause y el caudal. Para de esta manera obtener valores cualitativos de calidad de agua que permitan un mejor aprovechamiento del agua del río. Los resultados obtenidos con los tres ínidces muestran que existe contaminación leve en ciertos tramos del río, provocada por las actividades humanas, la disminución del caudal en el río y por la descarga de aguas residuales. Por otra parte, muestra que al aplicar el ICA-Dinius modificado los valores de las ponderaciones de la calidad del agua son más bajos respecto a los otros índices. Aún cuando los valores presentados por ICA- Dinius modificado son bajos, el rango de valoración para uso agropecuario es similar entre los tres índices, manteniendo el criterio que el río Guano está levemente contaminado. Por lo tanto, es necesario dar tratamiento al agua del río antes de usarla en actividades agropecuarias.

Palabras clave: Calidad del agua; caudal; geomorfología; ICA; pendiente

Introduction

Water is the most abundant natural resource on the planet; its quantity is approximately 1.385 billion km3. Out of this overall volume, as little as 1% is usable freshwater; 81% of it is present in glaciers and polar zones, while the remaining 18% is distributed among soil moisture, lakes, atmospheric vapor, rivers, and living organisms (Bitsch et al., 2021). All lifeforms on our planet, including flora, fauna, and human beings, have developed due to water availability (Singh, Yadav, Pal, & Mishra, 2020). Ecuador possesses a significant quantity of water resources; its average total runoff is 43,500 m3 per inhabitant a year, four times greater than the world average of 10800 m3 per inhabitant (Machado, dos Santos, Alves, & Quindeler, 2019). Water quality is at risk due to human activities near water sources. These activities are usually related to urban areas, mining areas, oil exploitation, and agriculture. These activities generate pollutant discharges with high concentrations of organic matter, nitrogen, phosphorus, heavy metals, and hydrocarbons (Ustaoğlu, Tepe, & Taş, 2020). Agricultural activity is extensive in the province of Chimborazo due to favorable climatic and geographical conditions (Moreano-Logroño & Mancheno-Herrera, 2020). In the last ten years, the Guano River has been used mainly in agricultural activities; in its course, it receives sanitary, agricultural, and industrial discharges. In addition, its flow has been reduced by 50%, changing the water quality and affecting the balance of the aquatic ecosystem, the soil, and people’s health (Shakir, Chaudhry, & Qazi, 2012).

To study the characteristics of water resources, quality indexes are used to verify whether the water complies with the specifications for its intended use; in addition, the effects of pollutants need to be assessed (Akhtar et al., 2021; Gupta & Gupta, 2021; Nong, Shao, Zhong, & Liang, 2020; Uddin, Nash, & Olbert, 2021; Villa-Achupallas, Rosado, Aguilar, & Galindo-Riaño, 2018). These indexes allow researchers to gather information on trends and identify river disturbances sources. Additionally, these indexes are necessary to study the characteristics of water resources and their quality to ensure the balance between human activities and the water ecosystem (Rivera, Encina, Muñoz-Pedreros, & Mejias, 2004). The US National Sanitation Foundation - water quality index (WQI-NSF) is used worldwide for this type of study. This method referred to here as Ramirez’s approach, is based on characteristics of North American rivers, which relate physical-chemical variables to average weights assigned to each for evaluating the specific pollution type (Gradilla-Hernández et al., 2020; Nugraha, Cahyo, & Hardyanti, 2020).

Works carried out in the area it is shown that the Guano River is affected by human activities, such as the excessive use of water for irrigation and the reception of wastewater (Castillejos & Arévalo, 2018; Castillo-López, Salas-Cisneros, Logroño-Veloz, & Vinueza-Veloz, 2021; Cevallos, 2015; Quevedo, 2020). But in these works, contamination is not related to other characteristics present in the area, such as geomorphology and flow.

Therefore, this work proposes a novel study to determine the water quality of the Guano River, using a variation of the WQI-Dinius that includes variables such as the average slope and the river’s flow. In addition, this work compares the results obtained with this variant in the index with WQI-NSF and WQI-Dinius.

Methodology

Sampling sites

The Guano River basin (Figure 1) is located in the Ecuadorian highland between Tungurahua and Chimborazo; the river is the product of the thaws from Chimborazo’s volcano and the runoffs generated in the Igualata moorland. The river’s source is downstream of Andaluza, in the area of Llío, where the Agags and Puluchaca streams merge at 3090 masl. The Guano River flows from northwest to southeast and runs into the Chambo River after traveling 21 km. Runoff from slopes in the area feeds the Guano River on its course (Chidichimo et al., 2018).

Figure 1: Location of the Guano River basin. 

According to the vegetation cover and the use of the soil (Table 1), the main anthropic activity is agriculture since it has a higher percentage of the area than the rest of the micro basin areas. In addition, the rate of population area corresponds mainly to the town of Guano, which sits on the banks of the river and is the one that shows the most significant interference in its quality. To determine the sampling points, vegetation and land use information (Mendoza et al., 2021) were analyzed (Table 1). The river was traversed from the upper part to the river mouth, corroborating what was identified in the characteristics of land use and vegetation data.

Table 1: Area of the vegetal coverage and use of soil. 

Vegetal coverage and use of soil Area (km 2 )
Natural forest 3.60
Crops 277.58
Grass 28.01
Paramo 69.44
Cities 5.65

In addition, the anthropic activities that affect the environmental conditions of the same are identified from the preliminary information on the cover and soil use. The river was explored from the mouth, identifying the characteristics of vegetation cover and soil use and the human activities that affect the river’s environmental conditions; thus, 29 observation points of anthropic activities were found (Table 2).

Table 2: Observation points of anthropic activities with their UTM coordinates. 

Code Description X Y Masl.
P_RIVER 1 Guano river, Llío 754395 9826549 3120
P_CHANNEL 1 Irrigation Channel 1 759572 9822858 2800
P_DISCHARGE 1 Wastewater discharge Colegio Pérez Guerrero 761098 9822398 2760
P_DISCHARGE 2 Wastewater discharge 80 m before the town of Guano1 761646 9822235 2725
P_DISCHARGE 3 Waste water discharge beginning of the town of Guano 761717 9822241 2720
P_DISCHARGE 4 Waste water discharge 70 m downstream 761753 9822178 2720
P_DISCHARGE 5 Waste water discharge 25 m downstream 761774 9822169 2720
P_DISCHARGE 6 Waste water discharge 27 m downstream 761799 9822159 2720
P_DISCHARGE 7 Waste water discharge 25 m downstream 761857 9822135 2720
P_DISCHARGE 8 Discharge of wastewater before the town of Guano 761891 9822121 2720
P_SLOPE 1 Spring Park of the slopes 761940 9822074 2720
P_SLOPE 2 Spring Park of the slopes 761969 9822046 2720
P_DISCHARGE 6 Discharge of residual water 40 m after the park of the slopes 762003 9822014 2720
P_SLOPE 3 Spring Park of the slopes 762029 9822004 2720
P_DISCHARGE 7 Discharge of residual water 40 m after the park of the slopes 762057 9821994 2720
P_SLOPE 4 Spring Park of the slopes 762093 9821980 2720
P_DISCHARGE 8 Discharge of residual water 40 m after the park of the slopes 762122 9821969 2720
P_SLOPE 5 Spring Park of the slopes 762179 9821922 2720
P_RIVER 2 Guano River, before Pebble Spinning Mill 762877 9821879 2680
P_DISCHARGE 9 Wastewater discharge Pebble Spinning Mill 763684 9821858 2680
P_RIVER 3 Guano River, before unloading Santa Teresita sector 763959 9821894 2673
P_DISCHARGE 10 Waste water discharge Santa Teresita 764249 9821860 2640
P_RIVER 4 Guano River, before the Chingazo Canal - Pungal 765041 9821806 2640
P_CHANNEL 3 Canal Chingazo - Pungal 765533 9821776 2607
P_SLOPE 6 Spring of the Elenes 765959 9821465 2600
P_SLOPE 7 Spring of the Elenes 766022 9821436 2600
P_DISCHARGE 13 Wastewater discharge San José Alto 767236 9819720 2560
P_DISCHARGE 14 Waste water discharge Quimiac sector 767383 9819519 2556
P_RIVER 5 Guano River, before the mouth of the Chambo River 769511 9817696 2480

From these sampling points: P_RIVER1, P_RIVER 2, P_RIVER 3, P_RIVER 4, and P_RIVER 5 were selected to determine the water quality of the Guano River concerning the interference of human activities. In addition to these sampling points, by areas, from the upper part to the mouth of the river. Once these sampling points were chosen, over the time frame encompassing July to November 2018 (dry season), the water samples were taken in triplicate for 18 days at each monitoring point, giving 240 pieces for water quality analysis. All models were collected by the authors manually in plastic containers. For the physical-chemical parameters, the bottle (1000 mL) was submerged 20 cm below the water surface with the peak of the bottle in the direction of the current until filled the bottle free of bubbles that may form at the mouth of the bottle. For the microbiological analysis, 100 mL of sample was taken in a sterile plastic container (Rice, Baird, & Eaton, 2017).

Parameters used in the indexes

Laboratory analysis for water was performed according to the Standard Methods for the Examination of Water and Wastewater (23rd ed.) (Rice et al., 2017) as described below:

The Electrometric Method 4550-H+ B for pH was carried out with a Model HI99121 pH meter, using a model HI1230B electrode by HANNA INSTRUMENTS of Woonsocket, Rhode Island, United States, which enables a measuring range from pH 2.00 to 16.00. The method consists of shaking a 100 mL aliquot of water to ensure homogeneity. Then the electrode is immersed in the sample for 1 min and the pH value is read when the equipment stabilizes.

The Electrical Conductivity Method 2510 B was performed using a Model SEVEN COMPACT CONDUCTIVITY S230 conductivity meter, with an electrode Cond probe InLab 710 by METTLER TOLEDO of Greifensee, Switzerland. The range of measurement was from 0.001 to 1000 mS/cm. The method involves shaking an aliquot of 100 mL of water to ensure homogeneity. Then, the electrode was immersed in the sample for 1 min, and the conductivity value was read when the equipment stabilized.

The Total Dissolved Solids Method 2540 C was conducted with the previous equipment, with a measuring range from 0.00 mg/L...1000 g/L. The method involves shaking an aliquot of 100 mL of water to ensure homogeneity. Then the electrode is immersed in the sample for 1 min, and the total dissolved solids value is read when the equipment stabilizes.

The Membrane Electrode Method 4500-O G for determining Dissolved Oxygen was carried out with the Model HI98198 OD and a model HI764113 electrode by HANNA INSTRUMENTS of Woonsocket, Rhode Island, United States; the measuring range was from 0.00 to 50 mg/L. This method consists of introducing the electrode into the river bed so that the water covers the electrode membrane completely. The equipment is allowed to stabilize for 1 min, and the optical density (OD) value is reported as a concentration in mg/L.

The Nephelometric Method 2130 B for determining Turbidity is carried out with a Model HI93703 (HANNA INSTRUMENTS of Woonsocket, Rhode Island, United States) with a measuring range from 0.00 a 1000 FTU. This method involves gently agitating the sample for 1 min; then the sample is poured into the cell of HANNA INSTRUMENTS HI93700d tr of Woonsocket, Rhode Island, United States. The turbidity value is read when the equipment stabilizes and all air bubbles disappear.

A modified phosphates Method 4500-P-E was applied with a range of 0.02 to 2.50 mg/L PO4 -3. This method is carried out with the spectrophotometer HACH DR 5000 of Loveland, Colorado, United States, using sample cells of 10 mL (HACH 2495402 5000 of Loveland, Colorado, United States). This method involves gently agitating the sample for 1 min before placing it into the cell. Then, the contents of one PhosVer3 Reagent Powder Pillow (HACH, catalog number: 2106069 5000 of Loveland, Colorado, United States) is added to the cell; a blue color develops if phosphorus is present in the sample. If so, the sample cell should be closed immediately and shaken vigorously for 20-30 s. After this, the sample should be allowed to stand still for 2 min. Next, start program 490 P with the spectrophotometer set to a wavelength of 880 nm. Insert the blank into the cell holder, push zero, and the display shows 0.00 mg/L PO4 -3. Then, the prepared sample cell is cleaned with reagent, and the prepared sample is inserted into the cell holder; results are displayed in mg/L PO4 -3.

The Nitrogen Method (Nitrate) 4500 NO3 - E modified to HACH method 8039 had a measuring range from 0.3 to 30.0 mg/L NO3 -. This method is carried out with a HACH DR 5000 spectrophotometer and Model HACH 2495402 sample cells of 10 mL 5000 of Loveland, Colorado, United States. This method involves gently agitating the sample for 1 min. Then, the sample is placed in the cell, and the contents of one NitraVer 5 Reagent Powder Pillow are added. The sample cell was closed immediately, shaken vigorously for 60 s, and let to still stand for 5 min. Next, prepare the blank and fill it in a second sample cell. Start program 355 N with wavelength set to 500 nm. Zero the instrument for the blank, clean the sample cell with reagent, and introduce the sample into the cell holder; results will be shown in mg/L NO3 -.

EDTA Titrimetric Method 2340 C for Total hardness (mgCaCO3/L). This method needs 25 mL of sample. First, one adds to the sample 1 to 2 mL buffer solution (ammonium chloride and ammonium hydroxide) to give a pH of 10.0 to 10.1. Next, 1 to 2 drops of indicator solution or an appropriate amount of dry-powder indicator formulation (Eriochrome Black T -NET) are added. Add standard EDTA (0.01M) titrant slowly, under continuous magnetic stirring, until the last reddish tinge disappears. The last few drops should be added at 3 to 5 s intervals. At the endpoint, the solution typically turns blue.

The Titration Method 2320 CB for Alkalinity (mgCaCO3/L). In this method, 25 mL of sample 1 to 2 drops indicator solution (Methyl Orange) are added and titrated with a standard 0.1 N sulfuric acid solution. The reagent should be added slowly, under continuous stirring, until the sample color changes to purple.

Biochemical Oxygen Demand (BOD) 5210 B. 5-Day BOD modified to VELP BOD EVO Sensor of Usmate, Italy; for this measurement, one used a BOD sensor set consisting of a BOD Sensor, a dark glass bottle, an alkali holder to absorb the carbon dioxide, and a stirring bar. BOD (mg/L) value will be obtained directly from the display at any time, even after five days. For 5 days, the set is kept in an incubator VELP SCIENTIFICA FOC 120I at 20 °C in Usmate, Italy. Then, a magnetic stirrer is inserted in an amber glass bottle (500 mL), and the BOD sensor is installed. The sensor reports that the value after 5 days is the one that determines the BOD5.

Chemical Oxygen Demand (COD) 5220 D, Closed Reflux, Colorimetric Method. One used HACH DR 5000 spectrophotometer 5000 of Loveland, Colorado, United States. Samples were gently agitated for 1 min and held in a vial reagent HACH LR (range 3-150 mg COD/L) at an angle of 45º. A clean pipet was utilized for dispensing 2.00 mL of sample to the vial. The same procedure was used for another vial filled with deionized water and utilized as the blank. After closing the vial it should be held by the cap, over a sink. The content of the vial can be mixed by inverting the vial gently several times. Next, vials are placed in A preheated DRB200 reactor for 2 h at 120 ºC. After turning off the heat, vials should cool in the reactor for 20 min to 120 ºC or less and then cool to room temperature in a tube rack. The spectrophotometer should be set at 420 nm, and 430 COD LR program should be started. Samples are recorded relative to the blank, and results are displayed in mg/L COD.

Membrane filter technique for members of the coliform group 9222 modified to Petrifilm Coliform Count Plate of Northern Minnesota, United States. This method consists of gently agitating samples for 1 min and placing Petrifilm Coliform Count Plates on the surface. Lift the top film and, with Pipettor or equivalent held perpendicularly to the plate, place 1 mL of sample or diluted sample onto the center of the bottom film. Prevent pushing sample off film to avoid entrapping air bubbles. Do not let top film drop. With the flat side down, place 3MTM PetrifilmTM Spreader on top film over inoculum. Gently apply pressure on the 3M Petrifilm Spreader to distribute inoculum over a circular area before the gel is formed. Do not twist or slide the spreader. Lift 3M Petrifilm Spreader. Wait a minimum of 1 min for the gel to solidify. Incubate plates clear side up in stacks of up to 20. It may be necessary to humidify the incubator MEMMERT model BE500. 3M Petrifilm Coliform Count Plates can be counted using the 3MTM Petrifilm Plate Reader on a standard colony counter or other illuminated magnifiers. Colonies may be isolated for further identification. Lift the top film and pick the colony from the gel.

The flow was obtained with the float method, this is based on the speed-area principle, where (n) cross-sectional areas (depth and width) were measured, and the velocity was obtained from the time the float takes to travel a distance (5m). The Manning coefficient corrects the flow (Davids et al., 2019). Flow information of the different sampling points was obtained according to equation (1).

Where: Q is the flow rate (m3/s), V is the velocity (m/s), AT is the transverse area (m2), K is a correction factor (Manning coefficient) for rivers with a depth greater than 15 cm.

From the heights of the contour lines, the tool-created TIN is used to develop the digital terrain elevation model (DEM). Owing to the transform tool of TIN, the elevation raster of the study area is generated. From this raster, the Spatial Analysis slope tool is used to spatially determine the Slope (Sc) in the basin. This is done in the ArcGis 10.1 software (Mendoza et al., 2021).

Water Quality Indexes

In this study, the river course was divided into transects according to the natural conditions and the human activities present, leaving five monitoring points for studying the water quality; these points were chosen based on the pressure on different transects, as shown in table 2. The methodology of the water quality indices applied at the sampling points is described below.

The first methodology is the WQI-NSF, proposed by the National Sanitation Foundation; this is used to assess changes in water quality in specific sections of rivers at different times. The calculations of this method were carried out by weighting according to the parameter type (Table 3); that is, a percentage value was assigned to each parameter analyzed, their total sum being 1. This value was then transformed into a percentage value, with a range from 0 to 100 (Akhtar et al., 2021; Gupta & Gupta, 2021; Mukate, Wagh, Panaskar, Jacobs, & Sawant, 2019; Uddin et al., 2021; Ustaoğlu et al., 2020). Finally, equation (2) was used to calculate the WQI.

where W i is the weighting coefficient for parameter i, I is the index for each parameter, and n is the total number of parameters.

Table 3 Parameter of quality index WQI-NSF (Akhtar et al., 2021; Gupta & Gupta, 2021; Mukate et al., 2019; Uddin et al., 2021; Ustaoğlu et al., 2020

Parameter Weigth
DO 0.17
Faecal Coliforms 0.16
pH 0.11
BOD 0.11
Nitrates 0.10
Phosphates 0.10
Temperature 0.10
Turbitity 0.08
Dissolved solids 0.07

The second methodology described by Dinius determines the water quality of the sample according to the degree of water pollution. Thus, it will have a quality index close to 0 for utterly contaminated water. The index will be 100 for water with excellent conditions (Hoseinzadeh, Khorsandi, Wei, & Alipour, 2015; Mukate et al., 2019; Zotou, Tsihrintzis, & Gikas, 2019, 2020). Subsequently, this index indicates that a correction should be made to the results (Table 4). Each parameter has a weighting value of W that allows obtaining the corresponding WQI; the weight for each parameter was given in table 4.

Table 4 Parameter of WQI-Dinius (Hoseinzadeh et al., 2015; Mukate et al., 2019; Zotou et al., 2019, 2020) 

Parameter I for WQI calculation W for WQI calculation
Dissolved Oxygen - OD 0.82*OD + 10.56 0.109
Chemical Oxygen Demand - COD 108 (COD)-0.3494 0.097
Total Coliforms - CT 136 (ColiTotal)-0.1311 0.090
Fecal Coliforms -CF 106 (EColi)-0.1286 0.116
Conductivity 506 (SPC)-0.3315 0.079
Chloride 391 (CL)-0.3480 0.074
Total Hardness 552(Hardness)-0.4488 0.065
Alkalinity 110(Alc)-0.1342 0.063
pH < 6.9 100.6803+0.1856(pH) 0.077
pH = 6.9 - 7.1 1
pH > 7.1 103.65+0.2216(pH)
Nitrates 125(N)-0.2718 0.09
Color Pt-Co 127(Color)-0.2394 0.063
Turbidity 102.004-0.382|Ta-Ts| 0.077

The numerical evaluation of the WQI-Dinius is obtained from the geometric mean (Equation (3)):

where W i are the specific weights assigned to each parameter (i), and weighed between 0 and 1, so the sum is equal to 1. Q i is the quality of the parameter (i), which depends on its concentration, and is rated from 0 to 100. PI represents the multiplication of the variables Q elevated to power W.

To contemplate the geomorphology and flow of the Guano River in the calculation of water quality, the WQI-Dinius was modified; therefore three steps were considered: (i) selecting the parameters, (ii) determining the sub-indexes, and (iii) determining the index by aggregation (Mukate et al., 2019; Samboni et al., 2007). For this purpose, the selection of parameters was separated into groups as follows: (a) organic matter: dissolved oxygen in % saturation and mg/L, biochemical oxygen demand and chemical oxygen demand, (b) bacteriological matter: total coliforms and fecal coliforms, (c) physical characteristics of water: color, Turbidity and electrical conductivity, (d) inorganic matter: alkalinity, hardness, chlorides, hydrogen ion concentration (pH), suspended solids, and total dissolved solids, (e) nutrients: nitrates, nitrites, phosphates, total phosphorus, and sulfates, (f) geomorphology characteristics: mean average of the Slope, Slope of the river course in the area under study, and flow. To apply the WQI-Dinius Modified, equation (4) was used. The I values were obtained from table 4, and the geomorphological characteristics (I) are equal to 1. The importance of W (WQI- Dinius Modified) for this method are described in table 5.

where Wi is the weighting coefficient for parameter i, I is the index for each parameter, and n is the total number of parameters.

The importance of parameter groups is identified for this case. Then the importance of the parameters within the parameter group is identified and the weight value is given at the end

Table 5: Weighing (W) for WQI- Dinius Modified. 

Importance between groups Parameter Weighing (W) Dinius Importance between parameters Weighing (W) WQI- Dinius Modified
1 Dissolved Oxygen 0.109 1 10.9
COD 0.097 2 9.7
2 Fecal Coliforms 0.116 1 11.6
Total Coliforms 0.09 2 9
3 Flow - 1 7.25
Average slope of the main cause - 2 6.45
4 Nitrates 0.09 1 9
5 Conductivity 0.079 1 7.9
Turbidity 0.077 2 7.7
pH 0.077 1 7.7
Total Hardness 0.065 2 6.5
Alkalinity 0.063 3 6.3

The criteria that were used to determine the quality of the water once calculated with the WQI-NSF, Dinius-WQI, and modified WQI are shown in table 6 (Akhtar et al., 2021; Gradilla-Hernández et al., 2020; Gupta & Gupta, 2021; Hoseinzadeh et al., 2015; Mukate et al., 2019; Nong et al., 2020; Nugraha et al., 2020; Uddin et al., 2021; Ustaoğlu et al., 2020; Zotou et al., 2020, 2019). The results obtained by this methodology are analyzed according to the information in table 5 to identify whether the quality is excellent or bad as endpoints of the valuation.

Table 6: General criteria of WQI (Akhtar et al., 2021). 

Type of use Color Evaluation range Quality description Treatment
USE IN AGRICULTURE E 90-100 EXCELLENT It does not require purification to be consumed
A 79-90 ACCEPTABLE Minor purification is needed for crops that require high water quality
LC 50-79 SLIGHTLY CONTAMINATED Treatment required for most crops
C 30-50 CONTAMINATED Treatment required for most crops
FC 20-30 STRONGLY CONTAMINATED Use only in very resistant crops
EC 0-20 EXCESSIVE Inacceptable for irrigation

Results

The geomorphology of the Guano River (Table 7) shows that the micro-basin is small according to the area. The average slope of the micro-basin is medium-rough, the sections of the leading cause have medium-rough slopes in the upper part, and the lower part has gentle slopes.

Table 7: Geomophology of the Guano river. 

Parameter Initials Unit Value
Area A km2 384.28
Perimeter P km 94.26
Length of the main channel Lc km 39.15
The average slope of the basin Sm % 13.74
The average slope of the main channel Sc % 16.35
Slope first section Sc1 % 11.2
Slope the second section Sc2 % 3.93
Slope third section Sc3 % 0.07
Slope fourth section Sc4 % 2.59
Slope the fifth section Sc5 % 2.39

In the high areas, the Guano River has an average flow of 0.68 m3/s, reaching the mouth with a flow of 1.83 m3/s. The flow decreases in the central region because there are irrigation channels along the river that redirect water from the river’s natural course (Table 8). Still, the flow recovers because springs provide additional fresh water to the river. Moreover, the physical-chemical and microbiological parameters that constitute the WQI were analyzed and performed for the five sampling points, as shown in Tables 9, table 10, table 11, table 12, and table13.

Table 8: Average flow of the Guano river at the sampling points (m3/s). 

Sampling P_RIVER 1 P_RIVER 2 P_RIVER 3 P_RIVER 4 P_RIVER 5
Sampling 1 0.79 0.97 0.94 1.83 2.14
Sampling 2 0.81 0.99 0.96 1.87 2.19
Sampling 3 0.60 0.74 0.71 1.39 1.63
Sampling 4 0.73 0.90 0.87 1.70 1.99
Sampling 5 0.75 0.92 0.90 1.74 2.04
Sampling 6 0.56 0.69 0.66 1.29 1.51
Sampling 7 0.68 0.84 0.81 1.58 1.85
Sampling 8 0.70 0.86 0.83 1.62 1.90
Sampling 9 0.52 0.64 0.62 1.20 1.41
Sampling 10 0.64 0.78 0.76 1.47 1.72
Sampling 11 0.65 0.80 0.77 1.51 1.76
Sampling 12 0.48 0.59 0.57 1.12 1.31
Sampling 13 0.59 0.73 0.70 1.37 1.60
Sampling 14 0.61 0.74 0.72 1.40 1.64
Sampling 15 0.73 0.90 0.87 1.70 1.99
Sampling 16 0.83 1.02 0.99 1.93 2.26
Sampling 17 0.85 1.05 1.02 1.98 2.31
Sampling 18 0.63 0.78 0.75 1.47 1.72

Table 9: Results of the physical-chemical and microbiological analysis in P_RIVER 1. 

Sampling pH Conductivity Temperature Dissolved Oxygen Turbidity STD Phosphate Nitrate Total hardness Alkalinity BOD COD Total Coliforms Fecal Coliforms
- µS/cm ºC mg/L NTU mg/L mg/L mg/L mg CaCO3/L mg CaCO3/L mg O2/L mg/L ufc/100 mL ufc/100 mL
1 7.75 617 17.15 6.39 5.80 273 0.99 15.47 292 54.40 1.89 16.80 321 130
2 7.80 599 17.56 5.96 6.30 279 1.80 10.14 311 48.93 2.15 27.39 239 59
3 7.60 616 16.82 5.03 9.11 272 0.98 10.60 291 48.93 1.65 16.43 333 83
4 7.67 651 17.20 4.77 10.42 275 0.89 10.27 270 50.02 1.55 12.05 662 141
5 6.89 657 18.05 5.72 13.63 302 1.11 24.18 304 56.23 3.66 21.18 399 141
6 7.62 933 17.98 5.72 8.98 366 1.96 20.77 393 53.93 1.01 20.81 587 147
7 7.54 795 15.98 4.20 8.08 435 0.81 7.64 304 46.81 3.42 21.18 408 136
8 7.00 966 15.94 4.94 10.18 673 1.02 11.12 397 48.02 3.64 20.08 500 154
9 7.61 644 16.08 7.35 7.79 310 1.11 20.42 320 59.74 2.04 18.56 424 172
10 7.66 626 16.48 6.91 8.29 315 2.02 13.38 342 53.72 2.32 30.26 315 78
11 7.46 643 15.75 5.99 11.10 310 1.10 13.99 319 53.72 1.78 18.16 440 110
12 7.52 678 16.13 5.73 12.41 311 1.00 13.56 296 54.93 1.67 13.31 874 186
13 6.75 684 16.97 6.68 15.62 338 1.24 31.92 334 61.74 3.94 23.40 527 186
14 7.48 960 16.90 6.68 10.97 402 2.20 21.81 431 59.21 1.59 23.00 775 194
15 7.40 822 14.91 5.15 10.06 471 0.91 10.08 334 51.40 3.69 23.40 539 179
16 6.86 993 14.87 5.90 12.17 709 1.15 14.67 436 52.72 3.92 22.19 660 203
17 7.47 671 15.01 8.31 9.78 346 1.24 26.95 352 65.59 2.20 20.51 559 227
18 7.52 653 17.56 7.87 10.28 352 2.26 17.67 376 58.99 2.50 33.44 416 103

Table 10: Results of the physical-chemical and microbiological analysis in P_RIVER 2. 

Sampling pH Conductivity Temperature Dissolved Oxygen Turbidity STD Phosphate Nitrate Total hardness Alkalinity BOD COD Total Coliforms Fecal Coliforms
- µS/cm ºC mg/L NTU mg/L mg/L mg/L mg CaCO3/L mg CaCO3/L mg O2/L mg/L ufc/100 mL ufc/100 mL
1 7.90 721 18.95 7.39 4.19 197 0.94 14.71 350 65.28 2.27 20.15 988 314
2 7.94 700 19.40 6.89 4.55 201 1.71 9.64 374 58.71 2.58 32.86 734 143
3 7.74 720 18.59 5.82 6.58 197 0.93 10.07 349 58.71 1.98 19.72 1025 201
4 7.81 761 19.01 5.52 7.53 198 0.85 9.76 324 60.02 1.86 14.46 2038 340
5 7.02 768 19.94 6.62 9.85 218 1.06 22.99 365 67.47 4.39 25.41 1229 340
6 7.76 1091 19.86 6.62 6.49 264 1.87 19.74 471 64.71 1.71 24.97 1806 355
7 7.68 929 17.66 4.85 5.83 314 0.77 7.26 365 56.17 4.11 25.41 1256 328
8 7.13 1129 17.62 5.71 7.36 486 0.97 10.57 476 57.61 4.36 24.10 1538 372
9 7.75 752 17.77 8.50 5.63 224 1.05 19.41 384 71.68 2.45 22.27 1304 414
10 7.80 732 18.21 8.00 5.99 228 1.92 12.72 410 64.46 2.78 36.31 969 188
11 7.60 752 17.40 6.92 8.02 224 1.04 13.29 383 64.46 2.14 21.79 1353 266
12 7.66 792 17.83 6.63 8.96 225 0.95 12.89 356 65.91 2.01 15.98 2690 449
13 6.87 799 18.76 7.72 11.29 244 1.18 30.34 400 74.08 4.73 28.08 1622 449
14 7.61 1123 18.68 7.72 7.93 291 2.09 20.73 517 71.05 1.91 27.60 2384 469
15 7.54 961 16.47 5.96 7.27 340 0.86 9.58 400 61.67 4.43 28.08 1657 433
16 6.99 1160 16.43 6.82 8.79 512 1.09 13.95 523 63.26 4.70 26.63 2030 490
17 7.61 784 16.58 9.61 7.07 250 1.18 25.62 422 78.70 2.64 24.61 1721 547
18 7.66 763 19.40 9.10 7.42 254 2.15 16.80 450.56 70.78 3.00 40.12 1279 248

Table 11: Results of the physical-chemical and microbiological analysis in P_RIVER 3. 

Sampling pH Conductivity Temperature Dissolved Oxygen Turbidity STD Phosphate Nitrate Total hardness Alkalinity BOD COD Total Coliforms Fecal Coliforms
- µS/cm ºC mg/L NTU mg/L mg/L mg/L mg CaCO3/L mg CaCO3/L mg O2/L mg/L ufc/100 mL ufc/100 mL
1 6.71 613 16.11 6.28 3.56 168 0.80 12.50 298 55.49 1.93 17.13 839 267
2 6.75 595 16.49 5.86 3.87 171 1.46 8.19 318 49.90 2.19 27.93 624 121
3 6.58 612 15.80 4.94 5.59 168 0.79 8.56 296 49.90 1.69 16.76 871 171
4 6.64 647 16.16 4.69 6.4 169 0.72 8.30 275 51.02 1.58 12.29 1732 289
5 6.70 652 16.95 5.62 8.37 185 0.90 19.54 310 57.35 3.73 21.60 1044 289
6 6.59 928 16.88 5.62 5.52 225 1.59 16.78 400 55.00 1.41 21.23 1535 302
7 6.53 790 15.01 4.13 4.96 267 0.65 6.17 310 47.74 3.49 21.60 1067 279
8 6.66 959 14.97 4.86 6.25 413 0.83 8.98 405 48.97 3.71 20.48 1307 316
9 6.59 640 15.10 7.22 4.79 190 0.89 16.50 327 60.93 2.08 18.93 1108 352
10 6.63 622 15.48 6.80 5.09 194 1.63 10.82 349 54.79 2.36 30.86 823 160
11 6.46 639 14.79 5.88 6.82 190 0.89 11.30 325 54.79 1.82 18.52 1150 226
12 6.51 674 15.15 5.63 7.62 191 0.81 10.95 302 56.02 1.71 13.58 2287 382
13 6.57 679 15.94 6.56 9.59 208 1.01 25.79 340 62.97 4.02 23.87 1378 382
14 6.47 954 15.88 6.56 6.74 247 1.78 17.62 440 60.39 1.62 23.46 2026 399
15 6.41 817 14.00 5.07 6.18 289 0.73 8.15 340 52.42 3.77 23.87 1409 368
16 6.41 986 13.97 5.80 7.48 436 0.93 11.86 444 53.77 4.00 22.63 1726 417
17 6.47 666 14.10 8.16 6.01 213 1.00 21.78 359 66.90 2.24 20.92 1463 465
18 6.51 649 16.49 7.74 6.31 216 1.83 14.28 383 60.16 2.55 34.10 1087 211

Table 12: Results of the physical-chemical and microbiological analysis in P_RIVER 4. 

Sampling pH Conductivity Temperature Dissolved Oxygen Turbidity STD Phosphate Nitrate Total hardness Alkalinity BOD COD Total Coliforms Fecal Coliforms
- µS/cm ºC mg/L NTU mg/L mg/L mg/L mg CaCO3/L mg CaCO3/L mg O2/L mg/L ufc/100 mL ufc/100 mL
1 7.68 570 16.32 5.94 6.83 321 1.01 15.87 266 49.67 1.73 15.33 333 84
2 7.73 554 16.70 5.54 7.41 328 1.85 10.40 284 44.67 1.96 25.00 286 38
3 7.53 570 16.00 4.68 10.72 321 1.00 10.87 265 44.67 1.51 15.00 340 54
4 7.60 602 16.37 4.44 12.26 323 0.92 10.53 246 45.67 1.42 11.00 528 91
5 6.83 607 17.17 5.32 16.04 355 1.14 24.80 277 51.33 3.34 19.33 378 91
6 7.55 863 17.10 5.32 10.57 430 2.01 21.30 358 49.23 1.51 19.00 485 95
7 7.47 735 15.20 3.90 9.50 511 0.83 7.83 277 42.73 3.14 19.33 383 87
8 6.94 893 15.17 4.59 11.98 791 1.05 11.40 362 43.83 3.22 18.33 435 99
9 7.54 595 15.30 6.83 9.17 364 1.13 20.94 292 54.53 1.86 16.94 392 110
10 7.59 579 15.68 6.43 9.75 371 2.07 13.73 312 49.04 2.12 27.63 330 50
11 7.39 595 14.98 5.57 13.06 364 1.12 14.34 291 49.04 1.63 16.58 401 71
12 7.46 627 15.35 5.33 14.60 366 1.03 13.90 270 50.14 1.53 12.16 649 120
13 6.69 632 16.15 6.21 18.38 398 1.28 32.74 305 56.36 3.60 21.36 451 120
14 7.41 888 16.08 6.21 12.91 473 2.25 22.37 393 54.05 1.45 21.00 592 125
15 7.33 760 14.18 4.79 11.84 554 0.93 10.34 305 46.92 3.38 21.36 457 115
16 6.80 918 14.15 5.48 14.32 834 1.18 15.05 398 48.13 3.47 20.26 526 131
17 7.40 620 14.28 7.72 11.51 408 1.27 27.65 321 59.88 2.01 18.72 469 146
18 7.45 604 16.70 7.32 12.09 414 2.32 18.12 343 53.85 2.28 30.53 387 66

Table 13 Results of the physical-chemical and microbiological analysis in P_RIVER 5. 

Sampling pH Conductivity Temperature Dissolved Oxygen Turbidity STD Phosphate Nitrate Total hardness Alkalinity BOD COD Total Coliforms Fecal Coliforms
- µS/cm ºC mg/L NTU mg/L mg/L mg/L mg CaCO3/L mg CaCO3/L mg O2/L mg/L ufc/100 mL ufc/100 mL
1 7.16 590 18.96 6.15 7.07 333 1.05 16.42 276 51.41 1.79 15.87 189 52.00
2 7.20 573 17.28 5.73 7.67 339 1.91 10.76 294 46.23 2.03 25.88 141 24.00
3 7.02 590 18.63 4.84 11.09 333 1.04 11.25 275 46.23 1.56 15.53 197 33.00
4 7.08 623 21.08 4.60 12.69 334 0.95 10.90 255 47.27 1.47 11.39 391 56.00
5 6.36 629 19.84 5.51 16.60 367 1.18 25.67 287 53.13 3.46 20.01 236 56.00
6 7.03 894 20.80 5.51 10.94 445 2.08 22.05 371 50.95 1.76 19.67 346 59.00
7 6.96 761 19.87 4.04 9.83 529 0.86 8.11 287 44.23 2.67 20.01 241 54.00
8 6.46 924 20.87 4.75 12.40 819 1.09 11.80 375 45.37 2.89 18.98 295 61.00
9 7.03 616 17.90 7.07 9.49 377 1.17 21.68 303 56.44 1.93 17.54 250 69.00
10 7.07 599 16.23 6.66 10.09 384 2.14 14.21 323 50.76 2.19 28.59 186 31.00
11 6.89 616 17.57 5.76 13.51 377 1.16 14.85 302 50.76 1.68 17.16 260 44.00
12 6.95 649 20.02 5.52 15.11 379 1.06 14.39 280 51.90 1.58 12.58 516 74.00
13 6.23 654 18.78 6.43 19.02 412 1.32 33.88 315 58.34 3.73 22.11 311 74.00
14 6.90 919 19.75 6.43 13.36 490 2.33 23.15 407 55.95 1.50 21.73 457 78.00
15 6.83 787 18.82 4.96 12.25 574 0.96 10.70 315 48.56 2.89 22.11 318 72.00
16 6.33 950 19.82 5.68 14.82 864 1.22 15.57 412 49.81 2.56 20.97 389 81.00
17 6.90 642 16.85 7.99 11.91 422 1.32 28.61 332 61.97 2.11 19.38 330 91.00
18 6.94 625 17.28 7.58 12.51 429 2.40 18.76 355 55.74 2.05 31.59 245 41.00

Figure 2 shows the mean values obtained through the three indices for July to November 2018. The values are between 59 and 73. It is observed that July presents high values and October low values. Once the samples were analyzed, the quality index was determined via three methods, as described, for each sampling point (Table 14). The results show two types of quality and water, acceptable (A) and slightly contaminated (LC), predominating the LC classification in the three indices for type A.

Figure 2: Values for WQI-NSF, WQI-Dinius and WQI-Dinius Modified. 

Table 14: Results of WQI index for the Guano River. 

SAMPLE WQI-NSF WQI-Dinius WQI-Dinius Modified
Sampling 1 A A LC
Sampling 2 LC A LC
Sampling 3 LC A LC
Sampling 4 LC A LC
Sampling 5 LC LC LC
Sampling 6 LC A LC
Sampling 7 LC LC LC
Sampling 8 LC LC LC
Sampling 9 A LC LC
Sampling 10 LC A LC
Sampling 11 LC A LC
Sampling 12 LC LC LC
Sampling 13 LC LC LC
Sampling 14 LC LC LC
Sampling 15 LC LC LC
Sampling 16 LC LC LC
Sampling 17 LC LC LC
Sampling 18 LC LC LC

Discussion

According to the results, the Guano River is a small micro-basin, with slopes ranging from medium-rough to gentle. It also shows the results of the slopes in the sections studied since the river slopes range from medium-rough to soft. In addition, it is observed that the flow at the sampling points varies depending on human activities and natural conditions. In the upper part of the river (P_RIVER 1), the flow is small; at point P_RIVER 2, it increases a little due to the effect of the runoff of the sector. From point P_RIVER 3 the flow decreases, because there are irrigation canals (Castillo-López et al., 2021; Mendoza et al., 2021; Quevedo, 2020). P_RIVER 4 and P_RIVER 5 show an increase in the flow due to the presence of a spring that again provides water to the river (Chidichimo et al., 2018). Moreover, the water quality results also depend on anthropic and natural conditions. In other matters, the water quality results also depend on the anthropic and natural conditions.

From a geomorphological point of view, it is evident that the slope influences the water quality because the effect of the slope on the rivers is essential; it allows the self-purification of the water with high slopes (Marimón-Bolívar, Jiménez, Toussaint-Jiménez, & Domínguez, 2021; Šaulys, Survile, & Stankevičiene, 2019; Toussaint-Jimenez, Marimon-Bolivar, & Dominguez, 2020).

This is perceptible in the water quality in the upper part of the river, where there are medium-rough slopes, allowing the presence of surface runoff, oxygenation of the water, and the dissolution of pollutants. The slope is gentle in the middle and lower part of the river, minimizing self-purification conditions. In addition, 88% of the river area is affected by agricultural activity, extending from 3000 to 2480 masl. The actions of towns (San Andres and Guano) are notoriously detrimental to the water quality by wastewater discharges directly into the riverbed.

Furthermore, Guano's artisan activities, such as leather and textile garment making, produce organic contaminants, including detergents, dyes, and heavy metals. Furthermore, non-technical agriculture has deteriorated the water quality indicators. This includes the riparian forests, which have disappeared almost entirely from the river banks, causing erosion and drag of the materials (Quevedo, 2020). In this context, the water quality assessment was carried out at the five sampling points of the fundamental cause; the values shown are the average of the 5 points. The qualitative evaluation of the water quality of the Guano River is: WQI-NSF values acceptable (A) in 2 samples and slightly contaminated (LC) in the rest of the samples. WQI-Dinius values seven samples as good (A) and 11 as slightly soiled (LC). In the case of the modified WQI, the evaluation is somewhat contaminated (LC) in all the samples. That is to say; water treatment is necessary to improve its condition so that it should not affect the quality of the crops.

Conclusions

The three indices reveal that the water is slightly contaminated and must be treated before use. The WQI-Dinius Modified gives lower values concerning the other two indices, as it shows the effects of flow and slope in determining water quality. When there is less flow and the water is contaminated in areas of human activity, such as areas with wastewater discharge. In this context, the water Quality with WQI-NSF and WQI-Dinius has been used and validated in several rivers worldwide. Therefore, the results obtained with these indices for the Guano River are considered valid, showing that the river is slightly contaminated.

The study of the water quality of the Guano River allowed us to see the approximation to reality of the WQI-Dinius modified since when comparing them with WQI-NSF and WQI-Dinius, the results are lower. Still, the qualitative assessment is similar regarding the water quality along the river. In the same way, it was possible to assess how the slope and flow parameters affect the value of the WQI-Dinius Modified since it was noticed that there is a more significant contamination in the areas with slope and low flow, other areas with higher flow and greater slope. In the lower part of the river, the water quality improves due to the greater volume of water and the presence of springs, which allows the dilution of pollutants and oxygenation of the water.

Although the index shows somewhat different values, it should be studied in greater detail, with a more significant number of physical-chemical data, for several years and in other rivers with similar characteristics. In the same way, the sampling of the parameters should be carried out in the dry season, where there is less flow. The effect of the flow and the slope on the self-purification of the river water would probably be observed better: This is because the slope and the flow are new parameters in the WQI that need further study for the method to be reliable. In addition, the results in rivers already studied must be validated to verify if this can contribute to improving this type of water quality study.

Interest conflict

The funders had no role in the study design; in the collection, analysis or interpretation of data; in the writing of the manuscript or in the decision to publish the results.

Authors’ contributions

Following the internationally established taxonomy for assigning credits to authors of scientific articles (https://casrai.org/credit/). The authors declare their contributions in the following matrix:

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Received: December 03, 2021; Accepted: June 27, 2022

*Correspondence: benitomendoza@unach.edu.ec

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