Erosion hidrica del suelo - USLE - Parte 2 de 5 - FACTOR R - ArcGIS ONLINE

Erosión Hídrica del Suelo: Parte 2

Introducción a la Ecuación Universal de Pérdida de Suelos

• Se presenta la segunda parte del tutorial sobre erosión hídrica del suelo, enfocándose en la determinación del factor R y su cálculo.

Insumos Necesarios para el Cálculo

• Para estimar el parámetro R se requieren tres insumos fundamentales:

• Modelo digital de elevación de la cuenca.

• Polígono del área de estudio.

• Precipitaciones mensuales durante al menos 20 años.

Revisión de Conceptos Previos

• Se recuerda que en la sesión anterior se presentó la ecuación universal de pérdida de suelo: A = R * K * L * S * C * P.

• El enfoque actual es el coeficiente R, que tiene unidades (mega julios por milímetro por hectárea), mientras que otros parámetros son adimensionales.

Cálculo del Factor R

• El factor R aglutina toda la energía erosiva de las lluvias. Para calcularlo mensualmente, se suman todas las energías asociadas a los eventos de lluvia y se multiplican por su intensidad en intervalos específicos.

Ejemplo Práctico y Consideraciones

• Se explica cómo calcular el factor mensual sumando las energías individuales obtenidas durante diferentes eventos pluviales dentro del mes.

• La dificultad radica en obtener datos precisos sobre lluvias parciales; generalmente, solo están disponibles datos mensuales.

Método para Calcular Energía Pluvial

• La energía de lluvia se calcula mediante una fórmula establecida por varios autores, incluyendo Mich en 1978. Esta fórmula considera logaritmos basados en la intensidad pluvial.

Ejercicio Aplicado

• Se presenta un ejercicio práctico donde se analizan eventos pluviales específicos con sus respectivas intensidades y tiempos entre ellos para ilustrar el cálculo del factor R.

• Las lluvias menores a 13 mm no son consideradas, y hay criterios sobre el tiempo entre eventos para incluirlos en los cálculos.

Este formato proporciona un resumen claro y estructurado que facilita el estudio y comprensión del contenido presentado en el tutorial sobre erosión hídrica del suelo.

Energy Calculation and Rainfall Analysis

Energy Unit Calculation

• The precipitation is divided by a specific value and then by 60 to convert units, resulting in an intensity of 20 millimeters per hour.

• To estimate the unit energy in megajoules per hectare hours, a formula involving logarithmic calculations based on the previously calculated intensity is applied.

• Effective energy is derived by multiplying unit energy with the initial precipitation value, yielding a total of 15.12 megajoules per millimeter per hectare.

Event R Factor Determination

• To find the R factor for rainfall events, it’s necessary to multiply by a defined intensity (e.g., 60 mm/hour).

• The calculated R factor for this event amounts to 906 megajoules per millimeter per hectare.

Monthly Rainfall Data Analysis

• Monthly rainfall records from various stations in Manabí province are utilized for potential erosion estimation.

• After analyzing 51 years of data, results are compiled but not shown due to complexity; focus remains on average annual precipitation.

Precipitation Distribution Methodology

• Annual precipitation must be transformed into daily values using monthly distribution percentages obtained from multi-year analysis.

• Percentages indicating monthly rainfall distribution are multiplied by annual totals to derive monthly figures.

Daily and Intensity Calculations

• Monthly precipitation is divided by an estimated number of rain events (15), providing daily averages.

• For calculating rainfall intensity over 30 minutes, daily distributions are analyzed; significant contributions occur within the first two hours.

Final Calculations and Results Compilation

• A regression analysis yields a formula that determines the percentage contribution of half-hourly rainfall.

• By multiplying intensity values with corresponding energies, total erosivity factors (R values) for each event are computed and summed up for overall assessment.

Summary of Erosivity Factors

• The final R total reflects cumulative data across multiple days; these figures inform annual erosivity factors used in further analyses.

Understanding the Calculation of Precipitation and Energy

Methodology for Calculating Energy from Precipitation

• The energy is calculated using a specific methodology applied to annual precipitation events, which will be used to generate a raster for the factor R.

• Monthly precipitation values are provided (e.g., 22.13, 21.68), with a total monthly precipitation of 30.54 mm being noted for analysis across various stations.

• Daily precipitation data is referenced, emphasizing the need to distribute this data accurately across different timeframes and copy relevant rows into calculations.

Generating Raster Data

• The calculated energy values are organized in a table format, which is essential for generating the raster representation of rainfall over specified intervals (e.g., every 30 minutes).

• A comprehensive table is exported containing all necessary attributes related to rainfall data collected from 37 weather stations in Manabí.

Interpolation and Raster Creation Process

• The process involves utilizing interpolation tools within software to create a raster based on the rainfall stations' data and their corresponding parameters.

• Steps include selecting appropriate parameters in the analysis toolbox, ensuring that the generated raster reflects accurate interpolated values.

Finalizing Raster Output

• Upon completion, an interpolated raster is generated showing specific values at various points; these can be reviewed for accuracy against known benchmarks.

• A clipping process follows where only relevant areas within defined boundaries (Manabí demarcation) are retained in the final output.

Adjusting Visualization Parameters

• The newly created raster's name is modified for clarity, indicating it represents factor R; visual properties such as color classification are adjusted for better interpretation.

• Units of measurement are clarified as megajoules per millimeter per hectare; adjustments ensure that numerical outputs reflect two decimal places for precision in reporting results.

Implications of Results on Erosion Potential

• Areas exceeding certain thresholds (e.g., R value over 2000 indicates high erosion potential); negative values resulting from interpolation errors must be corrected to zero before final analysis.

• This concludes part two of the tutorial series focused on calculating potential water erosion through derived factors, setting up future discussions on further calculations involving multiple parameters.