Hidrogeoquímica de la Calidad del Agua para determinar el Origen de Fuentes Contaminantes y Zonas para Uso Agropecuario en la Subcuenca Hornillos Alto

.title[
# Hidrogeoquímica de la Calidad del Agua para determinar el Origen de Fuentes Contaminantes y Zonas para Uso Agropecuario en la Subcuenca Hornillos Alto
]
.subtitle[
## Sustentación de Tesis
]
.author[
### Autor: Alonso Otiniano Zavala
]
.author[
### Asesor: M.Sc.ING.Esteban Dionicio Manrique Zuñiga
]
.date[
### 2022-09-05
]

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# Problemática

---

## Problematica

En el área de estudio se están realizando **diversas actividades antrópicas** (setiembre del 2021), entre ellas *mineras* (Mina Bateas - Compañía Minera Bateas S.A.C – Ag y Au), *agropecuarias*, *geoturísticas*, *geotermal* (Proyecto Geotermal del Valle del Colca - Cooperación Internacional Perú-México, 1992), además de la **existencia de pasivos ambientales** (reconocidos por el MINAM) ubicadas *cerca del cauce del río Apurímac*, que ocasiona un **riesgo potencial de contaminación** (pasivos en la zona de Caylloma) debido a que el río Apurímac discurre por el área de conservación regional Tres Cañones. Además, se presentan *zonas de alteración* (óxidos y arcillas), *ocurrencias minerales* (Tambomayo, Bateas, Madrigal, San Cristobal y Caylloma) y *surgencias de agua termal* (La Calera, Yanque, El Oasis - Sangalle).

> Todas estas actividades impactan el medio ambiente y principalmente a los suelos agrícolas.

---
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# Objetivos

---

## Objetivos

### General

*   Caracterizar hidrogeoquímicamente la Subcuenca Hornillos Alto para determinar el origen de material contaminante para encontrar zonas aptas de uso agropecuario.

### Específicos

*   Caracterizar geológicamente la Subcuenca Hornillos Alto para identificar los componentes que modifican el recurso hídrico.

*   Caracterizar hidroquímicamente la Subcuenca Hornillos Alto para obtener los hidrotipos predominantes y su relación con los parámetros físico-químicos.

*   Correlacionar mediante estadística los datos químicos del agua con los aspectos antropogénicos y geológicos.

---
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# Introducción

---
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<div class="figure" style="text-align: center">
<img src="figuras/Mapa_Ubicacion.jpg" alt="Mapa de Ubicación Hornillos Alto" width="80%" />
Mapa de Ubicación Hornillos Alto
</div>

---

class:middle

<div class="figure" style="text-align: center">
<img src="figuras/Mapa_Climatico.jpg" alt="Mapa de Climático Hornillos Alto" width="70%" />
Mapa de Climático Hornillos Alto
</div>

---

class:middle

<div class="figure" style="text-align: center">
<img src="figuras/Boxplot_Historico.PNG" alt="Boxplot Histórico de Precipitación" width="70%" />
Boxplot Histórico de Precipitación
</div>

---

<div class="figure" style="text-align: center">
<img src="figuras/Mapa_Hidrografico.jpg" alt="Mapa de Hidrográfico Hornillos Alto" width="80%" />
Mapa de Hidrográfico Hornillos Alto
</div>

---
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# Metodología

---

# Metodología:

.pull-left[
* Etapa **Pre Campo**:
    + Recolección de Información Bibliográfica
    + Generación de Malla de Muestreo
    + Generación de Base de Datos (recopilada)

* Etapa **Campo**:
    + Recolección de Información Insitu
        + Características de Zona de Muestreo
        + Parámetros Insitu
        + Geología de la estación de muestreo
        + Toma de muestras
    + QA/QC de data recolectada
]

.pull-right[
* Etapa **Post Campo**:
    + Integración de toda la información recolectada en campo
    + QA/QC de data de laboratorio
    + Integración de la información total:
        + Mapa Geomorfológico, Geológico
        + Base de Datos Análisis de Laboratorio
        + Base de Datos Campo
    + Tratamiento de la Información:
        + Generación de Estadísticos Descriptivos
        + Análisis Hidrogeoquímico
        + Análisis Univariantes y Bivariantes
        + Análisis de Componentes Principales (ACP)
    + Generación de Mapa Final
        + Mapa Clusterizado Multivariable
    + Propuesta Ingenieril
]

---
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# Geomorfología y Geología

---

<div class="figure" style="text-align: center">
<img src="figuras/Mapa_Geomorfologico.PNG" alt="Mapa de Geomorfológico Hornillos Alto" width="80%" />
Mapa de Geomorfológico Hornillos Alto
</div>

---
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<div class="figure" style="text-align: center">
<img src="figuras/Area_Geo_Hor.jpg" alt="Áreas Geomorfológicas" width="70%" />
Áreas Geomorfológicas
</div>

---

<div class="figure" style="text-align: center">
<img src="figuras/Mapa_Geologico.png" alt="Mapa de Geológico Hornillos Alto" width="70%" />
Mapa de Geológico Hornillos Alto
</div>

---
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# Geología Estructural

---

.pull-left[
<img src="figuras/Zona_Clusterizada_Multivariable_Borde.jpg" width="90%" style="display: block; margin: auto;" />
]

<div class="figure" style="text-align: left">
<img src="figuras/Estructural_f.jpg" alt="Corte" width="200px" />
Corte
</div>

]

---
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# Hidrogeoquímica - Puntos de Inventario

---

.pull-left[
<img src="figuras/Mapa_Inventario_Hornillos_Alto.jpg" width="85%" style="display: block; margin: auto;" />
]

<div class="figure" style="text-align: left">
<img src="figuras/Hidroquimica_Inventario/Leyenda.PNG" alt="Leyenda" width="100px" />
Leyenda
</div>

<div class="figure" style="text-align: left">
<img src="figuras/Hidroquimica_Inventario/Simologia.PNG" alt="Simbologia" width="100px" />
Simbologia
</div>

]

<div class="figure" style="text-align: left">
<img src="figuras/Hidroquimica_Inventario/Apurimac1.PNG" alt="Apurimac1" width="100px" />
Apurimac1
</div>

<div class="figure" style="text-align: left">
<img src="figuras/Hidroquimica_Inventario/Apurimac2.PNG" alt="Apurimac2" width="100px" />
Apurimac2
</div>

<div class="figure" style="text-align: left">
<img src="figuras/Hidroquimica_Inventario/Hornillos.PNG" alt="Hornillos" width="100px" />
Hornillos
</div>
]
]

]
---
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# Resultados

---
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# Hidrogeoquímica - Mapa

---

.pull-left[
<img src="figuras/Zona Clusterizada Multivariable.jpg" width="90%" style="display: block; margin: auto;" />
]

<div class="figure" style="text-align: left">
<img src="figuras/Mapa_Hidroegeoquímico/Leyenda1.PNG" alt="Leyenda" width="100px" />
Leyenda
</div>

<div class="figure" style="text-align: left">
<img src="figuras/Mapa_Hidroegeoquímico/Leyenda2.PNG" alt="Simbologia" width="100px" />
Simbologia
</div>

]

<div class="figure" style="text-align: center">
<img src="figuras/Mapa_Hidroegeoquímico/Ap01.PNG" alt="Apurimac1" width="150px" />
Apurimac1
</div>

<div class="figure" style="text-align: center">
<img src="figuras/Mapa_Hidroegeoquímico/Ap02.PNG" alt="Apurimac1" width="150px" />
Apurimac1
</div>

<div class="figure" style="text-align: center">
<img src="figuras/Mapa_Hidroegeoquímico/Ap03.PNG" alt="Apurimac1" width="150px" />
Apurimac1
</div>
]

<div class="figure" style="text-align: center">
<img src="figuras/Mapa_Hidroegeoquímico/Ap_02.PNG" alt="Apurimac2" width="150px" />
Apurimac2
</div>

]

<div class="figure" style="text-align: center">
<img src="figuras/Mapa_Hidroegeoquímico/HA01.PNG" alt="Hornillos1" width="150px" />
Hornillos1
</div>

<div class="figure" style="text-align: center">
<img src="figuras/Mapa_Hidroegeoquímico/HA02.PNG" alt="Hornillos2" width="150px" />
Hornillos2
</div>

<div class="figure" style="text-align: center">
<img src="figuras/Mapa_Hidroegeoquímico/HA03.PNG" alt="Hornillos3" width="150px" />
Hornillos3
</div>
]

]

---
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# Complementarios

---
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.pull-left[
<div class="figure" style="text-align: center">
<img src="figuras/Adicionales/Aforos.PNG" alt="Aforos" width="150px" />
Aforos
</div>

<div class="figure" style="text-align: center">
<img src="figuras/Adicionales/Estadisticos_PFQ.PNG" alt="Estadisticos Fico" width="150px" />
Estadisticos Fico
</div>

<div class="figure" style="text-align: center">
<img src="figuras/Adicionales/Piper.PNG" alt="Diagramas Piper" width="150px" />
Diagramas Piper
</div>
]

<div class="figure" style="text-align: center">
<img src="figuras/Adicionales/Gibss.PNG" alt="Diagramas Gibbs" width="150px" />
Diagramas Gibbs
</div>

<div class="figure" style="text-align: center">
<img src="figuras/Adicionales/HQ_Av.png" alt="HQ" width="150px" />
HQ
</div>
]

---
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## Tidydata para Análisis

---

```r
*geologia <- st_read(dsn="Data_final/geologia_shp/geo.shp")
st_is_valid(geologia)
geologia$validacion <- st_is_valid(geologia, reason=T)
geologia <- geologia %>% filter(validacion=="Valid Geometry")
st_is_valid(geologia)
geologia <- geologia %>% st_transform(crs = 4326)

*geomorfologia <- sf::st_read(dsn="Data_final/geomorfologia_shp/geom_hornillos.shp")
geomorfologia <- geomorfologia %>% st_transform(crs = 4326)

*puntos_data <- read.csv(file="Data_final/BD_PARA_ALONSO.csv", header =TRUE)
puntos_data <- puntos_data %>% rename(ID=ï..ID)
puntos_data <- puntos_data %>% filter(Subcuenca=="Hornillos Alto")

puntos_data2 <-puntos_data[ ,c("Norte","Este")]
puntos_data2 <- puntos_data2[ ,order(c(names(puntos_data2)))]
sputm <- SpatialPoints(puntos_data2, proj4string=CRS("+proj=utm +zone=19 +south +datum=WGS84")) 
spgeo <- spTransform(sputm, CRS("+proj=longlat +datum=WGS84"))
spgeo <- as.data.frame(spgeo)
colnames(spgeo) <- c("lng","lat")
puntos_data2 <- cbind(puntos_data,spgeo)
puntos_data2 <- st_as_sf(puntos_data2, coords = c("lng", "lat"),
 remove = FALSE, crs = st_crs(geomorfologia),
 agr = "constant")

*union <- st_intersection(geomorfologia, puntos_data2)
*union2 <- st_intersection(geologia, union)
```

---

```
union2
Simple feature collection with 164 features and 177 fields
Geometry type: POINT
Dimension:     XY
Bounding box:  xmin: -71.895 ymin: -15.40654 xmax: -71.57217 ymax: -15.09729
Geodetic CRS:  WGS 84
First 10 features:
      OBJECTID CODI    NAME                 DESCRIP                        Litología Shape_Leng Shape_Area
400        439  632    Q-fg  Depósito fluvioglaciar          Cantos, gravas y arenas  288318.96   79683393
400.1      439  632    Q-fg  Depósito fluvioglaciar          Cantos, gravas y arenas  288318.96   79683393
417        456 4693 Np-co/1 Centro Volcánico Cosana Lavas afaníticas, tobas de pómez   90816.15  100971381
400.2      439  632    Q-fg  Depósito fluvioglaciar          Cantos, gravas y arenas  288318.96   79683393
400.3      439  632    Q-fg  Depósito fluvioglaciar          Cantos, gravas y arenas  288318.96   79683393
          validacion etiqueta                  sub_uni codigeom codigodepa departamen      Area Proyecto
400   Valid Geometry    V-gfl Vertiente glacio-fluvial      512          4   Arequipa   3.16389    GA47C
400.1 Valid Geometry    V-gfl Vertiente glacio-fluvial      512          4   Arequipa  26.84433    GA47C
417   Valid Geometry    Cal-v        Caldera volcánica      411          4   Arequipa 276.78412    GA47C
400.2 Valid Geometry    V-gfl Vertiente glacio-fluvial      512          4   Arequipa  26.84433    GA47C
400.3 Valid Geometry    V-gfl Vertiente glacio-fluvial      512          4   Arequipa  10.13142    GA47C
      Temporada           Código Código.Corto     Nombre      Nombre.completo      Fecha                Hora
400     Avenida 499991-19-GW-038       GW-038 León Pampa Manantial León Pampa 2019-04-16 1899-12-31 11:52:00
400.1   Avenida 499991-19-GW-088       GW-088  Coñosmayo     Termal Coñosmayo 2019-04-20 1899-12-31 16:15:00
417     Avenida 499991-19-SW-018       SW-018  Utahuanta   Quebrada Utahuanta 2019-04-15 1899-12-31 09:05:00
400.2   Avenida 499991-19-SW-019       SW-019    Ajajato     Quebrada Ajajato 2019-04-15 1899-12-31 09:45:00
400.3   Avenida 499991-19-SW-021       SW-021     Ccacca      Quebrada Ccacca 2019-04-15 1899-12-31 10:30:00
        Norte   Este Cota Zona           Lugar Distrito Provincia Vertiente        Cuenca      Subcuenca
400   8319674 206110 4248 19 S      León Pampa Caylloma  Caylloma Atlántico Alto Apurímac Hornillos Alto
400.1 8322985 205797 4325 19 S       Coñecmayo Caylloma  Caylloma Atlántico Alto Apurímac Hornillos Alto
417   8311082 211680 4543 19 S Anexo Pusa Pusa Caylloma  Caylloma Atlántico Alto Apurímac Hornillos Alto
400.2 8325702 212576 4277 19 S        Tacohuir Caylloma  Caylloma Atlántico Alto Apurímac Hornillos Alto
400.3 8318423 214154 4209 19 S        Totorana Caylloma  Caylloma Atlántico Alto Apurímac Hornillos Alto
      Microcuenca Tipo.de.fuente Clase.de.fuente             Uso.de.la.fuente
400    Apurímac 1    Subterránea       Manantial                      Ninguno
400.1  Apurímac 1    Subterránea          Termal                 Balneológico
417     Hornillos    Superficial        Quebrada Agropecuario, Consumo humano
400.2  Apurímac 1    Superficial        Quebrada                    Ganadería
400.3  Apurímac 1    Superficial        Quebrada                      Ninguno
```

---
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## Estructura Información

---

```
> str(dt2 %>% select(1:6,44:ncol(dt2)))
tibble [164 × 31] (S3: tbl_df/tbl/data.frame)
 $ CODI                : num [1:164] 632 632 4693 632 632 ...
 $ Temporada           : Factor w/ 2 levels "Avenida","Estiaje": 1 1 1 1 1 1 1 1 1 1 ...
 $ Litologia           : Factor w/ 10 levels "Acumulaciones de arenas y limos",..: 4 4 6 4 4 4 4 6 1 4 ...
 $ Microcuenca         : Factor w/ 3 levels "Apurímac 1","Apurímac 2",..: 1 1 3 1 1 1 1 1 1 1 ...
 $ Tipo.de.fuente      : Factor w/ 2 levels "Subterránea",..: 1 1 2 2 2 2 2 2 2 2 ...
 $ Geomorfologia       : Factor w/ 11 levels "Cal-v","Es-v",..: 11 11 1 11 11 11 11 1 11 11 ...
 $ pH                  : num [1:164] 7.55 6.62 7.25 6.96 7.65 6.85 7.94 7.55 7.73 7.39 ...
 $ ORP_mv              : num [1:164] 273 162.9 177.4 -39.7 228.2 ...
 $ CE_uS.cm            : num [1:164] 54.4 5671 145.6 60 101.2 ...
 $ TDS_mg.L            : num [1:164] 27.1 2779 73.2 29.9 50.3 ...
 $ Salinidad_PSU       : num [1:164] 0.075 3.117 0.118 0.08 0.098 ...
 $ Resistividad_Kohm.cm: num [1:164] 18.41 0.176 6.852 16.68 9.924 ...
 $ Na_tot              : num [1:164] 3.1 748 2.9 5.7 7.8 29.3 11 9.7 6 2.9 ...
 $ Mg_tot              : num [1:164] 1.2 16.5 1 1.1 1.4 1.7 3 2 2.2 1.6 ...
 $ K_tot               : num [1:164] 1.9 21.1 3.3 1.4 1.9 2.2 2 2 1.9 1.5 ...
 $ Ca_tot              : num [1:164] 4.5 266.6 2.2 4.6 7.9 ...
 $ Sr_tot              : num [1:164] 0.084 5.3011 0.0324 0.0483 0.0974 ...
 $ Li_tot              : num [1:164] 8.94e-05 7.69 1.50e-04 7.00e-03 1.50e-03 ...
 $ Si_tot              : num [1:164] 15.28 33.32 18.08 8.55 13.46 ...
 $ Al_tot              : num [1:164] 0.021 0.009 0.081 0.02 0.016 ...
 $ As_tot              : num [1:164] 2.87e-05 1.34 4.60e-05 3.50e-02 3.00e-03 ...
 $ B_tot               : num [1:164] 8.79e-04 2.15e+01 1.40e-03 3.60e-01 1.10e-01 ...
 $ Ba_tot              : num [1:164] 0.0047 0.0654 0.0066 0.0271 0.017 0.0228 0.0555 0.032 0.0112 0.0143 ...
 $ Cu_tot              : num [1:164] 0.000321 0.0033 0.0016 0.0042 0.0021 ...
 $ Fe_tot              : num [1:164] 0.0108 0.62 0.06 0.06 0.17 ...
 $ Mn_tot              : num [1:164] 0.0004 2.4337 0.0022 0.0066 0.0115 ...
 $ Mo_tot              : num [1:164] 9.06e-06 3.80e-03 1.28e-05 2.00e-04 3.00e-04 ...
 $ Ni_tot              : num [1:164] 4.19e-05 8.00e-04 9.00e-04 5.63e-05 1.90e-03 ...
 $ Pb_tot              : num [1:164] 1.73e-05 2.69e-05 1.29e-02 3.57e-05 4.90e-03 ...
 $ V_tot               : num [1:164] 0.0085 0.0141 0.0089 0.0008 0.0013 0.0017 0.0015 0.0022 0.0021 0.001 ...
 $ Zn_tot              : num [1:164] 0.000256 0.005 0.003 0.006 0.003 ...
```

---
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# Análisis Univariante (AU)

---

<div class="figure" style="text-align: center">
<img src="figuras/Univariante/Estadisticas.png" alt="Estadisticas Avenida" width="60%" />
Estadisticas Avenida
</div>
]

<div class="figure" style="text-align: center">
<img src="figuras/Univariante/Estadisticas.png" alt="Estadisticas Estiaje" width="60%" />
Estadisticas Estiaje
</div>

]
]

---

<div class="figure" style="text-align: center">
<img src="figuras/Univariante/Al_graph.png" alt="Estadistica Univariante" width="60%" />
Estadistica Univariante
</div>
]

<div class="figure" style="text-align: center">
<img src="figuras/Univariante/Al_clasi.png" alt="Tabla Clasificación Al" width="60%" />
Tabla Clasificación Al
</div>

]
]

---

<div class="figure" style="text-align: center">
<img src="figuras/Univariante/Univariante.jpg" alt="Estadistica Univariante" width="60%" />
Estadistica Univariante
</div>
]

<div class="figure" style="text-align: center">
<img src="figuras/Univariante/TablapH.PNG" alt="Tabla Clasificación" width="60%" />
Tabla Clasificación
</div>

]
]

---
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# Análisis Bivariante (AB)

---

<div class="figure" style="text-align: center">
<img src="figuras/Bivariantes/Bivariante_Temporada.PNG" alt="Temporada" width="80%" />
Temporada
</div>
]

<div class="figure" style="text-align: center">
<img src="figuras/Bivariantes/Bivariante_Microcuenca.PNG" alt="Avenida" width="80%" />
Avenida
</div>

]

<div class="figure" style="text-align: center">
<img src="figuras/Bivariantes/Bivariante_Microcuenca_Estiaje.PNG" alt="Estiaje" width="80%" />
Estiaje
</div>

]

---
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## Análisis de Componentes Principals (PCA)

---

## PCA y Clusterización

El análisis PCA se basó en **Härdle y Simar**, (2015) y **Kassambara**, (2017). Se utilizó como base el análisis de correlación de Pearson y el conocimiento de la distribución puntual de los valores por tiempo (temporada) de los parámetros físico-químicos, hidroquímicos y metales disueltos contaminantes de forma espacial. Con ello, se determina el comportamiento multivariable y tempo-espacial básico de la información hidrogeoquímica para la generación del mapa clusterizado.

---

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<div class="figure" style="text-align: center">
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Estiaje
</div>

]

---

## Cluster Encontrados en el Análisis Multivariable

---

## Mapa Clusterizado Multivariable (Geo-Antro)

---

---

---

## Aplicación Ingenieril

Existen dos zonas donde se deben generar herramientas para el tratamiento y gestión de la calidad del recurso hídrico, priorizando la **Zona C**, como factor de nivel de baja calidad de agua y altas concentraciones de contaminantes, y la **Zona B** como factor de baja calidad de agua y de medianos a altos valores de concentración de contaminantes.

1. Determinación de la carga contaminante
2. Análisis de Trazadores Isotópicos
3. Sistemas de remediación mediante Nanoabsorbentes
4. Evaluacion de Costos Implicados

---
class: middle, center, inverse

# Conclusiones

---

## Conclusiones

* Las distribuciones de las variables de parámetros físico-químicos y concentraciones de elementos químicos en las aguas se identificó que son lognormal (en su mayoría), esta distribución se debe a que los fenómenos geohidrológicos no están en la naturaleza en equilibrio perpetuo debido a la acción de factores de geológicos o antrópicos determinados, la log normalidad permitió un análisis más preciso de los estadísticos de centralización, forma y dispersión; además de aportar al desarrollo de inferencias geomatemáticas. Los outliers y faroutliers son valores existentes que no deben ser eliminados de la información para su análisis y modelamiento.

* El análisis de datos se debe desarrollar de manera univariante y multivariable tanto numérica como gráfica usando técnicas desarrolladas en esta tesis (estadísticas descriptivas, hidroquímicas, correlaciones, análisis de componentes principales de variables geológicas) asociando factores de espacio y tiempo para generar interpretaciones con mayor confiabilidad y precisión.

* El proyecto minero Gaby no supera los ECAs, ni posee valores anómalos en elementos metálicos según los puntos determinados en el estudio.

---
class: middle

* La geología muestra una predominancia netamente volcánica siendo modificador directo del recurso hídrico superficial, caracterizado en el Grupo Barroso con la marca hidrogeoquímica más importante que genera variaciones geoquímicas en la Subcuenca Hornillos Alto.

* Se identificó que las distribuciones de las variables de parámetros físico-químicos y concentraciones de elementos químicos en las aguas son lognormal (en su mayoría). Esta distribución se debe a que los fenómenos geohidrológicos no están en la naturaleza en equilibrio perpetuo debido a la acción de factores geológicos o antrópicos determinados. La lognormalidad permitió un análisis más preciso de las estadísticas de centralización, forma y dispersión; además de aportar al desarrollo de inferencias geomatemáticas. Los outliers y faroutliers son valores existentes que no deben ser eliminados de la información para su análisis y modelamiento.

* Los valores pH superan ECA en toda la subcuenca y en todas las microcuencas analizadas. Esto se debe a que en la zona predominan las rocas andesíticas que tienen característica básica de los complejos volcánicos. Estos son mayoría en toda la subcuenca, y por la erosión hídrica de roca, en general, tienden a aumentar los valores de pH. Además, podrían influir los procesos de neutralización de pasivos ambientales por influencia humana que, al adicionar cal, basifican el agua (en algunas zonas se determinó este evento).

---
class: middle

* Los puntos SW-019, SW-022, SW-036, SW-096, SW-097, SW-100, SW-101, SW-102 y SW-106, además de superar los ECA en alguna temporada, presentan los niveles más altos de consideraciones multivariables y se encuentran todos en la microcuenca Apurímac 1, exceptuando las aguas subterráneas (GW-024, GW-088). Por ello, esta zona es considerada como origen de fuentes contaminantes debido a la existencia de alteraciones geológicas, zonas de alto fallamiento, pasivos ambientales y minas abandonadas y activas.

* Las zonas identificadas para desarrollo de agricultura en cuanto a la calidad de agua para su uso están de forma predominante en la microcuenca Hornillos (Zona D) y la parte alta de la microcuenca Apurímac (Zona A). Estas no superan los ECA, HQ. Geoespacial y estadísticamente, los valores en el análisis multivariable son de moderados a bajos y los factores de balance geológico no están asociados a zonas de alteración detectadas ni estructuras con alto fallamiento, minas cercanas o pasivos ambientales.

* La propuesta ingenieril desarrollada es eficiente y eficaz, en función a las zonas identificadas, la propuesta ingenieril consiste en un conjunto de estudios por etapas sobre la determinación de la carga contaminante, análisis de trazadores isotópicos y el sistema de remediación mediante nanoabsorbentes. El costo anual de un contenedor puesto en una zona contaminante para un caudal de 10m3/s es aproximadamente 19 600 dólares americanos.

---
class: middle, center, inverse

# Recomendaciones

---

## Recomendaciones

* Se recomienda hacer estudios específicos en las zonas C y B, donde se ha determinado contaminación antrópica y/o geológica. Se deben tomar puntos para monitoreo constante, muestra de isótopos para determinar la procedencia de aguas (con mayor precisión), muestras de roca y suelo para hacer comparaciones geoquímicas para definir claramente la procedencia del contaminante.

* Se recomienda aplicar técnicas de correlación para realizar comparaciones múltiples como correlación de Spearman o Kendal y realizar un PCA robusto, FAMD (Factor Analysis Mixed Data) o técnicas para determinar patrones con aprendizaje no supervisado usando Machine Learning y redes neuronales artificiales para comparar con lo realizado (se requiere más puntos de muestreo).

* Se debe tomar en cuenta, que los análisis de agua pueden llevar a identificar los threshold y encontrar anomalías que, asociadas a análisis de sedimentos, son guías para la exploración de yacimientos minerales.

* Se recomienda una mayor toma de muestras en zonas C y D donde existe alteración geológica, fallamiento, minas, pasivos, entre otros, para determinar la procedencia a menor escala que caracteriza las fuentes del recurso hídrico.

---
class: center

# Avanzando en Geociencias y Programación (印)

Siempre Adelante

![](https://upload.wikimedia.org/wikipedia/commons/7/7e/Mudra-Naruto-KageBunshin.svg)

---

# Gracias Totales!

Slides son creados via el R package [**xaringan**](https://github.com/yihui/xaringan).

El chacra proviene de [remark.js](https://remarkjs.com), [**knitr**](https://yihui.org/knitr/), y [R Markdown](https://rmarkdown.rstudio.com).

---

# EL TRABAJO DEL GEOLOGO