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Determinación de la variabilidad climática mediante la aplicación de índices de cambio climático, provincia de Orellana.

 

Determination Of Climate Variability Through The Application Of Climate Change Indices, Province Of Orellana.

 

María Paulina Poma Copa.[1], = Mirian Yolanda Jiménez Gutiérrez. [2], Marco Ramiro Usca Tiuquing= a. [3= ]& Mario Francisco Játiva Rey= es.[4]

 

Recibido: 20-04-2019 / Revisado: 25-05-2019 /Aceptado: 28-06= -2019/ Publicado: 30-07-2019

 

 

 Abstract.                              DOI: https://doi.org/10.33262/cienciadigital.v= 3i3.2.1.816

=  

The present study aims to generate basic information = for planning and adaptation to climate change and climate variability in the province of Orellana in the last 10 years. The volumes approved for forest management programs in native forest from the period 2011 to 2014 is 327,24= 1.22 m3 corresponding to 56%, forest management programs in pioneer formations a= nd regeneration 102,569.23 m3 with a percentage of 18%, forest management prog= rams in agroforestry systems it is 141,561.64 m3 with a percentage of 24%, forest management programs in forest plantations is 11,564.84 with 2% percentage activities that cause effects on the environment and contribute to climate change. To calculate the daily extreme events of maximum and minimum temperature and precipitation PRCP, TMAX, TMIN for the period 1982-2015 with the information provided by INAMHI, we used RClimdex software, through which 24 of 27 recommended climate change indexes were calculated. ETCCDI, climatic variability was also evaluated through the use= of isohyets and isotherms maps in ArcGIS. A change in precipitation and temperature indices has been detected since the year xxx. Information that requires future analysis to determine its causes.=

=  

Keywords: Forest management, Rclimdex, climatic changes, precipitation

Resumen.

 =

El presente estudio tiene = como objetivo generar información básica para la planificación y adaptación al cambio climático y la variabilidad climática para implementar sistemas de producción sostenibles para la agricultura en la provincia de Orellana. Los volúmenes aprobados para programas de manejo forestal en bosque nativo del período 2011 al 2014 es de 327.241,22 m3   correspondiente al 56 %, programas de manejo forestal en formaciones pioneras y regeneración 102.569,23 m3  con un porcentaje 18 %, programas de ma= nejo forestal en sistemas agroforestales  es de 141.561,64 m3 con un porcentaje 24 %, programas de manejo forestal en plantaciones forestales es de 11.564,84 con porcentaje 2 %  actividades que causan efectos al ambie= nte y aportan al cambio climático. Para calcular los eventos extremos diarios de temperatura máxima y mínima   y precipitación PRCP, TMAX, TMIN del período 1982-2015 con la información proporcionada por el INAMHI, utilizamos software RClim= dex, a través del cual se calculado 24 de 27 índices de cambios Climáticos recomendados ETCCDI, se evaluó también la variabilidad climática a través d= el uso de mapas de isoyetas e  isoterm= as en ArcGIS. Se ha detectado un cambio de los índices de precipitación y tempera= tura a partir de período 1900-2017 Información que requiere de futuras análisis = para determinar sus causas.

Palabras claves: Variable, cambio climático, precipitación, tempera= tura.

Introducción.

La provincia de Orellana, se encuentra ubicada al nororiente del país, en la Región Amazónica Ecuatoriana se extiende sobre un área de 123.000  de exuberante vegetación propia de los b= osques húmedos tropicales y corresponden al 45% del territorio nacional y al 1.67%= de la cuenca Amazónica en 1989, la Organización de las Naciones Unidas para la educación, la ciencia y la cultura (UNESCO), declaro al Yasuní como la Rese= rva de Biósfera Yasuní, ubicada en la provincia de Orellana, lugar donde además= se encuentra empresas hidrocarburíferas del Ecuado= r. Iniciando así la preocupación sobre la posibilidad de un cambio climático (GAPO, 2015).

Entendiéndose por cambio climático a una importante variación estadística en el estado habitual del clima o en su variabilidad,= que persiste durante un extenso período, por lo general durante decenios o perí= odos más largos. Puede ser consecuencia de procesos internos naturales o cambios antropogénicos constantes en la composición de la atmósfera o en la explota= ción de la tierra. (Organización Meterelógica Mundial, 2011)

Desde a mediados del siglo XIX, el aumento promedi= o de la temperatura de la superficie terrestre ha sido 0,05 grados centígrados (= °C). En el quinto informe de evaluación Intergubernamental de expertos sobre el cambio climático (IPCC), en la base científica física, evidenciaron un incremento de temperatura superior a la media global, más pronunciado en los meses estivales que en los invernales, una reducción de la precipitación an= ual, un aumento de los extremos relacionados con precipitación de tipo tormentos= o. Además, en el sexto informe de evaluación los miembros de (IPCC) han acorda= do realizar tres informes especiales uno sobre los impactos de un calentamiento global de 1,5 (°C), sobre los niveles preindustriales y las vías de emisión= de los gases de efectos invernadero (GEI) en ecosistemas terrestres, el cambio climático en los océanos y la criosfera informe= que será presentado en el año 2023.

El Clima

El clima es concebido como un sistema que se manti= ene en el espacio, y el tiempo gracias al intercambio de energía que se produce= a nivel de la superficie terrestre mediante la circulación general del aire. = El clima en la amazonia de acuerdo a la clasificación Köe= ppen es clima tropical húmedo Am. Los elementos del sistema climático consisten = en cualquiera de las propiedades del sistema climático que permiten describir = el tiempo y el clima en un lugar dado durante un determinado período de tiempo= los elementos climáticos más utilizados son:

 

Elementos geodinámicos

Elementos acuosos

Existen además factores que modifican los climas insolación, latitud, altitud, corrientes marinas, distribución de tierras y mares, vegetación y suelo entre otros (Teresa Ayllón, 2013).

Variabilidad climática

Es usada para destacar variabilidad dentro del cli= ma, o fluctuaciones en las propiedades estadísticas sobre períodos de meses, añ= os o décadas. De esta manera se determina límites dentro de los cuales los valor= es medios, desvíos o frecuencias de valores entre los límites establecidos pue= de ser aceptado como normal. Cuando las propiedades estadísticas de una secuen= cia de años, décadas difieren considerablemente respecto de otra secuencia de a= ños, décadas de referencia, podemos hablar de Cambio Climático sobre una escala = de tiempo adecuado. (Lowry, 1980)<= /span>

En el aspecto espacial el ejemplo más utilizado de esta variabilidad, es la clasificación climática por zonas, cada una de ell= as relativamente homogénea en espacio y tiempo con respecto a las variables consideradas durante períodos de tiempo previamente establecidos. (Jorge A. Amador , 2009).

Las variables climáticas que se utilizarán para el análisis estadístico son los registros diarios de precipitación (RP) medido= s en milímetros (mm) de lluvia, temperaturas máximas (Tmax<= /span> y Temperatura mínima (Tmin) en grados centígrad= os (°C).

Cambio Climático

 A nivel global se percibe por la elevación de las temperaturas comparadas con los registros históricos en cada zona del planeta en la época respectiva del año. En los últimos 25 años el proceso se ha acelerado donde= se cifra en 0,5 °C por década, lo que constituye una amenaza emergente para la salud pública. Los cambios del clima a larga el plazo influyen en la salud = y en la viabilidad de todos los ecosistemas, con afectación para la distribución= de plantas, los agentes patógenos, los animales e incluso el asentamiento huma= no (Días, 2013).

La convención de Marco de las Naciones Unidades so= bre el cambio climático  CMNUCC, se ref= iere aquel cambio producto de la actividad humana a través de su alteración sobr= e la composición química atmosférica, debido a la mayor  presencia de Gases de Efecto Invernadero (GEI), aunque estos cambios se debe sumar a la variabilidad natural que pue= den ser atribuidas al cambio climático, un incremento general y gradual de la temperatura, cambios en los comportamientos de las precipitaciones e increm= ento de eventos extremos (Zuleta, 2012).=

En la provincia de Orellana  el volumen aprobado para programas de m= anejo forestal en bosque nativo del período 2011 al 2014 es de 327.241,22 m3=    correspondiente al 56, el volumen aprobado para programas de manejo forestal en formaciones pioneras y regeneración 102.569,23 m3  con un porcentaje 18 %, el volumen aprobado para programas de manejo forestal en sistemas agroforestales  es de 141.561,64 m3 con un porcentaje 24 %, el volumen aprobado para programas de manejo forestal en plantaciones forestales es de 11.564,84 con= porcentaje 2 %  reportados por el sistema de administración forestal Ministerio del Ambiente,  actividades que aportan al cambio climá= tico ( Dirección Nacional Forestal, 2015).

Tabla 1. Manejo forestal en bosque nativo

 

Programas

m3<= /p>

%

Bosques Nativos

= 327241,22

56

Formaciones pioneras

= 102569,23

18

Plantaciones forestales

= 11564,84

2

Sistemas agroforestales

= 141561,64

24

Total

100

                                 

Fuente: (Dirección Na= cional Forestal, 2015)

        =          Elaborado Por: Los Autores

 

 

Figura 1. Volumen aprobado = de manejo forestal Orellana

 

 

 

 

 

                                = Elaborado por: Los Autores

Eventos Extremos

El cambio climático puede provoca= r un aumento en la frecuencia o intensidad de eventos climáticos extremos como s= on las sequias severas y precipitaciones intensas.

§   El incremento de Temperatura prom= edio se incrementa la presencia de vapor de agua.

§   La presencia de mayores cantidade= s de GEI y otros contaminantes en la atmósfera aumentan la probabilidad de los eventos lluviosos intensos.

§   El calentamiento acelera el secad= o de la superficie del suelo afectando fuentes de agua, creando condiciones propicias para incendios forestales (Zulet= a, 2012).

Índices de Cambios Climáti= cos

Los índices climáticos es combinar analíticamente varios elementos del clima con el fin de establecer diferent= es tipos climáticos sintéticos. Un inconveniente de estos índices es la falta = de generalidades y de objetividad, en el cálculo se utilizan valores medios prescindiendo de la variabilidad temporal. Dentro de los índices tenemos ín= dice de Aridez, índice de Lang, índice de Martonne, Índice de Emberger y criterios de aridez de la UNESCO (Ïnigo Aguirre de Cárcer Pilar Carral, 2009).

 

En el Ecuador se han realizado estudios con el fin de comprender la dinámica y evolución de los eventos climáticos extremos mediante el análisis de tendencias de los principales elementos del sistema climático como la temperatura máxima, mínima y la precipitación a resolución diaria.  El grupo de expertos en detección de Índices de cambios Climáticos (ETCCDI) han desarrollado una serie de índices para que los diferentes países y regiones puedan calcular los índices exactamente de la misma manera para que sus análisis encajen en el panorama global (Qu= isaguano, 2018). En la Tabla 1 se muestra los índices recomendados por el ETCC= DI de los cuales fueron elegidos como básicos 27 de una lista de 40 para un análisis de eventos climáticos extremos, considerando valores diarios de te= mperatura, cantidad de precipitación diaria y umbrales fijos de relevancia para aplicaciones particulares.

Tabla 2. Resumen Índices de cambios Climáticos recomendados ETCCDI.

 

Criterio

Nombre de Indicador

Indicador

Unidad

 Cumplimiento

 

Noches Frías

TN10p

Días

Porcentaje de días cuando la noctur= na (TN)<10 th.

 

 

Noches cálidas

TN90p

Días

Porcentaje de días cuando la TN>90th

 

Temperatura nocturna mínima

TNn

°C

Valor mensual mínimo de temperatura mínima diaria

 

Temperatura nocturna máxima

TNx

°C

Valor mensual máximo de temperatura mínima diaria

 

Duración de los periodos fríos

CSDI

Días

Contaje anual de días que por lo menos 6 días consecutivos en que TN>10th percentil

 

Días con heladas

FD0

Días

Número de días en un año cuando TN (mínimo diario) < 0 °C

 

Noches tropicales

TR20

Días

Número de días en un año cuando TN (mínimo diario) > 20 °C

Temperatura mínima ( en la noche)

Promedio de la

TMINmean

°C

Valor promedio de la temperatura mínima

 

Días fríos

TX10p

Días

Porcentaje de días cuando TX <10 th percentil

 

Días calurosos

TX90p

Días

Porcentaje de días cuando TX > 90 th percentil

 

Temperatura máxima durante el día

TXx

°C

Valor mensual máximo de temperatura máxima diaria

 

Temperatura mínima durante el día

TXn

°C

Valor mensual mínimo de temperatura máxima diaria

 

Duración de periodos cálidos

WSDI

Días

Contaje anual de días con por lo menos 6 días consecutivos en que = TX > 90 th percentil

Temperatura máxima ( en el día)

Días de verano

SU25

Días

Número de días en un año cuando TX (máxima diaria) > 25 °C

Temperatura máxima ( en el día)

Rango diurno de temperatura

DTR

°C

Diferencia media mensual entre TX y TN

 

Precipitación máxima en 1 día=

RX1 day<= /span>

mm

Máximo mensual de precipitación en 1 día.

 

Precipitación máxima en 5 día

Rx5day

mm

Máximo mensual de precipitación en 5 días consecutivos

 

Índice simple de intensidad

SDII

Mm/día

Precipitación anual total dividida para el número de días húmedos (definidos por PRCP > =3D 1.0 mm).

 

Días con lluvia mayor a 10 mm

R10

Días

Número de días en un año en que PRCP >=3D 20 mm.

 

Días secos consecutivos

CDD

Días

Número máximo de días consecutivos con RR >=3D 1 mm

 

Días lluviosos consecutivos

CWD

Días

Número máximo de días consecutivos con RR >=3D1 mm

 

Días muy lluviosos

R95p

mm

Precipitación anual total en que RR> 95 percentil

 

Días extremadamente lluviosos

R99p

mm

Precipitación anual total en que RR> 99 percentil

Precipitación

Precipitación total anual

PRCPTOT

mm

Precipitación anual total en los días húmedos (RR> =3D 1 mm).

 

 Fuente: Vázquez (2010)

Elaborado Por= : Los Autores

 

 

Área de estudio.

El instituto Nacional de Meteorol= ogía e Hidrología (INAMHI) es el encargado de operar y mantener la infraestructu= ra nacional de las estaciones Metereológicas e hidrológicas de recopilar, procesar, publicar y difundir la información Hidrometereológica en el Ecuador de acuerdo a las normas internacionales establecidas por la Organización Meteorológica (OMM).  

Tabla 3.  Estaciones Metereo= lógicas en Orellana

 

Estación

Código=

Latitud

Longitud

Elevación

Nuevo Rocafuerte

M0007

0G 55' 12" S

75G 24' 11" W

185.00

Loreto

M0563

0G 41' 56" S

77G 18' 47" W

420.00

Huaticocha

M1171

0G 44' 43" S

77G 29' 01" W

632.00

San José de Payamino

M1221

0G 30' 14" S

77G 19' 03" W

345.00

Cononaco 

M1232

0G 59' 34" S

76G 56' 15" W

281.00

        =       Fuentes: I= NAMHI -2018

        =       Elaborado Por: Los Autores

Mapa 1. Est= aciones Metereológicas con índices climáticos seleccionados

 

 

Metodología Aplicada=

La metodología general consiste en los siguientes pasos.

1.      Seleccionar las estaciones metereológicas, ubicadas en Orellana= .

2.      Revisión y análisis de datos diarios de precipitación y temperatura máxima y mínima.

3.      Cálculo de índices de cambio climático RClimdex.

4.      Elaboración de gráfic= os.

Revisión y análisis de datos.

El objetivo fundamental de la gestión = de los datos climáticos consiste en conservar, captar y proporcionar datos para obtener productos climáticos para que las instancias planificadas y decisor= ias, así como los investigadores lo utilicen el mismos que debe suministrar la información para describir el clima del ámbito para el que se haya establec= ido el archivo ya sea nacional, regional o mundial (Organización Metereólogica Mundial, 2011).

Para el análisis índice climático es necesario recurrir a datos proporcionada por el ente de control INAMHI. Los datos proporcionados se detallan a continuación:

Tabla 4. Período de datos INAMHI (1900-2017)<= /p>

 

Estación Metereología

Variable climática=

= Datos

 

Nuevo Rocafuerte

Nubosidad

1900

2017

Viento

Temperatura

1900

2017

Humedad

1900

2017

<= span lang=3Des-419 style=3D'font-size:12.0pt;font-family:"Times New Roman",ser= if; color:black;mso-ansi-language:#580A'>Heliofonía=

 

 

Loreto

Precipitación

1900

2017

<= span lang=3Des-419 style=3D'font-size:12.0pt;font-family:"Times New Roman",ser= if; color:black;mso-ansi-language:#580A'>Huaticocha=

Precipitación

1900

2017

<= span lang=3Des-419 style=3D'font-size:12.0pt;font-family:"Times New Roman",ser= if; color:black;mso-ansi-language:#580A'>Canonaco=

Precipitación

 

 

 

<= span lang=3Des-419 style=3D'font-size:12.0pt;font-family:"Times New Roman",ser= if; color:black;mso-ansi-language:#580A'>Payamino=

<= span lang=3Des-419 style=3D'font-size:12.0pt;font-family:"Times New Roman",ser= if; color:black;mso-ansi-language:#580A'>Heliofonía=

1900

2017

Viento

1900

2017

Nubosidad

 

 

Humedad

1900

2017

                  Fuentes: I= NAMHI -2018

                      Elaborado Por: L= os Autores

Análisis de datos diarios con RClimdex 

Para determinar los índices de cambio climáticos se contó con la información de las estaciones que cuenten con da= tos de 30 años diarios y que además contengan las variables precipitación, temperaturas máximas y temperaturas mínimas según las recomendaciones del G= rupo Intergubernamental de Expertos sobre el Cambio Climático ETCCDI.=

§&nb= sp; Control de calidad con Rclimdex.

§&nb= sp; Análisis de homogeneidad

§&nb= sp; Homogeneización de series de temperaturas

Cálculo de índices RClimdex

Con los datos proporcionados de temperatura, precipitación, heliofanía, humedad, nubosidad, viento por el Instituto Nacional de Meteorología e Hidrología INAMHI de la Estación Metereología de Nuevo Rocafuerte del período 1900 – 2= 017, ubicado en Latitud: 0G 55' 12" S, Longitud: 75G 24' 11" W, Elevación:  185.00. Se procede a ca= lcular cada índice de cambio climático utilizando el software libre R versión 3.5.1 (2018-07-02).

Las variables de estudio de RClimdex son (TX, Tn y R)= , para realizar el cálculo de los índices es necesario contar con estaciones que c= uenten con los datos diarios y que además contengan las variables de precipitación, temperaturas máximas y mínimas. A continuación, se detalla el procedimiento para el cálculo de los índices de cambio climático:

1.      Selección de datos completos y continuos.

2.      Análisis y control de calidad de datos.

3.      Análisis de homogenei= dad.

4.      Los datos deben formatearse como archivo de texto ASCII.

5.      Formar Columnas con la siguiente secuencia año, mes, día, PRCP, TMAX, TMIN.

6.      El formato descrito d= ebe estar delimitado por espacios.

7.      Los datos faltantes deben codificarse =
como -99.9; los registros de datos deben estar en orden de fecha del calend=
ario.

Figura 2. Registro de datos= RClimdex

 

Carga RClimdex

Carga de datos

Run QC

Cálculo de los índi= ces

<= span lang=3DES-EC style=3D'mso-fareast-language:EN-US'>

 

 

Preparación de la información

=  

La información proporcionada por el INAMHI son de = tipo ASCII siendo este incompatible con RClimdex, pr= evio a cargar la información en el software se debe cambiar a formato de tipo ACII= , la información debe estar en columnas con la siguiente secuencia: Año, Mes, Dí= a, PRCP, TMAX, TMIN.

Una vez cambiada la información al for= mato compatible con el software RClimdex, se procede= a cargar la información donde se calcula los índices de cambio climático el resultado generados por el software RClimdex se detallan a continuación:

Tabla 5. Resultados Índice= s de cambio climático Software RClimdex

 

Índices

Syear

Eyear

Slope

STD_of_ Slope<= o:p>

P_Value

txn

1900<= span style=3D'color:black'>

2017

0.055

0.015

0.2

txx

1900<= span style=3D'color:black'>

2017

0.058

0.020

0.018

Fd0

1900<= span style=3D'color:black'>

2017

0.028

0.356

0.568

Su20

1900<= span style=3D'color:black'>

2017

1.35

0.578

0.039

             

 Elaborado= Por: Los Autores

Resultados y Discusión

Temperatura

De la información proporcionada por el INAMHI la t= emperatura media mensual del período 1900-2017 es de Tm 24.2 °C y Tmx 26.1 registrados en la estación metereologíca S= an José de Payamino. De la estación Huaticocha no se registran datos en el período 1900-2017. En la estación meteorológica Nuevo Rocafuerte la Temperatura media mensual del período 1900-2017 es la Tm 22.8 °C y la Tmx 27,8 °C. Mediante la aplicació= n de un sistema Información Geográfica SIG, se observa la tendencia de la Tmx y Tm del área de estudio.

 

Mapa 2. Tem= peraturas Mínimas de la provincia de Orellana

=      Elaborador Por: Los Autores

Las flechas se refieren a tendencias significativas y el tamaño de la flecha significa el cambio de Temperatura. La Tm en el cantón Aguarico, Nuevo Rocafuerte es 17.94 °C Baja, en el cantón Loreto, San José de Payamino la Tm 22.29 °C alta con una tendencia significativa de 0.8 °C.

    Figura 3. Temperatura Mínima                                                 Fig= ura 4. Temperatura Máxim= a

    Elaborador Por: Los Autores                                                Elaborador Por: Los Autores

Precipitación

La precipitación total mensual del período 1900-2017 registrados en la estación meteorológica Cononaco   presenta una precipitación mínima 112.7 = mm y la precipitación máxima 588.8 mm, en San José de Payam= ino Precipitación máxima 673.1 mm, Huaticocha Pmm 81.1 mm y la Pmáx. 11= 52.5 mm y en Nuevo Rocafuerte Pmm 2.8 mm, Pmáx 616.9 mm como podemos observar en el mapa de precipitaciones.

Mapa 3. Precipitación máx= ima de la Provincia de Orellana

=

      Elaborador Por: Los Autores

La precipitación máxima valor mm/d, se evidencia u= na precipitación baja 72.1002 mm/d en Nuevo Rocafuerte y en San José de Payamino la precipitación alta 118.477 mm/d existe una tendencia a la baja precipitación -2.7 mm/d tal como se observa en el mapa3= .

Figura 5. Precipitación mínima                                                =      Fig= ura 6. Precipitación máx= ima

=

Elaborador Por: Los Autores                                           Elaborador Por: Los Autores

Viento Dirección Predominante= – velocidad 13H (m/s).

La dirección pre= dominante de la velocidad del viento registrado en el período 1900-2017 en San José d= e Payamino e V min es de 2.0 m/s, V máx 5 m/s, en Nuevo Rocafuerte Vmin. 1.2 m/s y        V máx= 3.9 m/s mediante la aplicación de SIG.

 

Mapa 4. Velocidad del vie= nto de la provincia de Orellana

=

 

 

 

 

 

 

 

                        Elaborador Por: Los Autores

La velocidad del viento en San José de Payamino tiene una tendencia baja 5.3800 m/s y en Nue= vo Rocafuerte la tendencia de la velocidad del viento es alta 16.5099 m/s, con= una tendencia a la baja de -2,74 m/s.

Figura 7. Velocidad del vie= nto Mínima m/s                   Figura 8. Velocidad del vi= ento Máxima m/s

 

 

 

 

Elaborador Por: Los Autores                                                 Elaborador Por: Los Autores

Discusión

La temperatura máxima se estudia el comportamiento de la temperatura media anual, en la figura 4 se observa una tendencia a la baja = de la temperatura, pero por los meses de agosto a diciembre la temperatura tiende= a subir 0.8 °C.  De un estudio de pro= yección de temperatura media anual 2011-2040 se observa que el cambio de temperatura estaría en un incremento en la Amazonía   0,75 – 0,9 °C incrementándose la temperatura en la región Amazónica superiores del orden 1,3 °C a 3.5 °C respectivamente (Ministerio del Ambiente, 2017). En el Ecuador, este patrón tendría un comportamiento inverso, pues en la región amazónica ecuatoriana los cambios esperados serían más fuertes que en la re= gión costera,

La precipitación máxima tiende una tendencia a la baja tal como se observa en = la figura 6, de precipitación de -2.7 mm. Según interpretación de proyecciones climáticas a escala regional periodo 2020-20= 39. El cambio climático presenta un promedio en la región amazónica el valor preci= pitaciones de -1%. El cambio climático muestra en promedio que la región interandina experimenta una tendencia positiva del valor de cambio de la precipitación = del orden del 13% (Ministerio = del Ambiente, 2017).

Conclusiones.

§  Seleccionaron los índices recomendados por el ETCCDI de los cuales fueron elegidos como básicos 27 de= una lista de 40 para un análisis de eventos climáticos extremos, considerando valores diarios de temperatura, cantidad de precipitación diaria y umbrales fijos de relevancia para aplicaciones particula= res.

§  Se realizó el análisis estadístico del comportamiento de la precipitación y temperatura máxima y mínimas, en térmicos de los índices climáticos en el software RCli= mdex  txn (T= emperatura mínima durante el día) es de 0.2 °C  y txx ( Valor mensual máximo de temperatura máxima diar= ia) 0.018 °C.

§  Las tendencias de los datos históricos de las 5 estaciones meteorológicas que se encuentran ubica= dos en la provincia de orellana, se evidencian 75 % de confianza que existirá c= ambios significativos de comportamiento del cambio de temperatura, el 25 % restant= e no se cuenta con todos los registros diarios lo que no permite obtener una información 100 % de confianza.

§  Las variaciones drásticas de precipitaciones, causan un efecto en la fisiología de las plantas, notorias básicamente en precipitaci= ones altas ya que por coincidir también con temperaturas altas las plantas se vuelven más frágiles, lo que conlleva a mayor susceptibilidad y vulnerabili= dad frente a la presencia de hongos y bacterias que en los trópicos húmedos exi= sten, por lo que las enfermedades proliferan a nivel radicular, en el tallo y en = el follaje. Esto causa grandes pérdidas en los cultivos cuyas producciones se = han mermado hasta en un 70 % como ha sido en el cultivo de la malanga en el presente año.

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PARA CITAR EL ARTÍCULO INDEXADO.=

 

 

Poma Copa, M., Jiménez Gutiérrez, M., Usca Tiuquinga, M., & Játiva Reyes, M. (2019). Determi= nación de la variabilidad climática mediante la aplicación de índices de cambio climático, provincia de Orellana. Ciencia Digital, 3(3.2.1), 239-257. h= ttps://doi.org/10.33262/cienciadigital.v3i3.2.1.816

 

 


 

 

 

El artículo que se publica es de exclusiva responsabilidad de los autores y no necesariamente reflejan el pensamiento de la Revi= sta Ciencia Digital.

 

El artículo queda en propiedad de la revista y, por tanto, su publicación parc= ial y/o total en otro medio tiene que ser autorizado por el director de la Revista Ciencia Digital.

 

 



<= ![if !supportFootnotes]>[1] Escuela Superior Politécnica de Chimborazo, Faculta de Ciencias, Facultad Recursos Naturales. Francisco de<= span style=3D'mso-spacerun:yes'>    Orellana, Ecuador. paulina.poma@espoch.edu.ec

[2= ] Escuela Superior Politécnica de Chimborazo, Faculta de Ciencias, Facultad Recursos Naturales. Francisco de Orellana, Ecuador. mirian.jimenez@espoch.edu.ec

[3= ] Escuela Superior Politécnica de Chimborazo, Faculta de Ciencias, Facultad Recursos Naturales. Francisco de Orellana, Ecuador., mario.jaitiva@espoch.e= du.ec

[4] Universidad Salburg, Departamento de Geoinformática (Z_GIS), San Francisco de Quito, Quito, Ecuador. marcousca@hotmail.com

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                                                 =                                    Vol. 3, N°3.2.1, p. 239-257, julio, 20 19

Creativ= idad & Desarrollo  =                                                                            =                                                 Página 237

 

 

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