Rainfall Indices for MCDM models in ArcGIS: how and Why? Promo скачать в хорошем качестве

Rainfall Indices for MCDM models in ArcGIS: how and Why? Promo

Just click on Links to Get Discount https://www.udemy.com/course/rainfall... In this course, I have shown complete process about how to download rainfall data, processing data, convert daily to monthly rainfall data, step by step guide of 10 important rainfall indices such as long term average annual rainfall (High resolution 0.04 X 0.04), Rainfall Intensity Index (by MFI), Rainfall Erosivity factor (R), Rainfall deviation Index ( RDI), Precipitation concentration Index (PCI), Rainfall seasonality Index (RSI), Rainfall Anomaly Index (RAI), Rainfall variability index (RVI), Co-efficient of variability of Rainfall (CVR), Percent of normal precipitation index (PNPI) in excel and produced map for MCDM models using ArcGIS. The Rainfall intensity is one of the main factors due to its significant impact on the flood magnitude, flash flood, desertification, Bank erosion, Gully Erosion, land degradation, sediment flux, soil erosion etc. Rainfall Erosivity factor (R) is developed by Wischmeier and Smith (1978) and modified by Arnoldus (1980). It is determined as a function of the volume, intensity and duration of rainfall and can be computed from a single storm, or a series of storms to include cumulative erosivity from any time period The Precipitation Concentration Index (PCI) developed by Oliver (1980) to quantify the periodic variation of the rainfall, concentration of rainfall and rainfall erosivity. Rainfall seasonality Index (RSI) developed by Walsh and Lawler (1981), refers to the degree of variability in monthly rainfall through the year; it assesses seasonal contrasts in rainfall amounts rather than whether months are ‘dry’ or ‘wet’ in an absolute sense. Rainfall Anomaly Index (RAI) developed by van Rooy (1965) is used in depicting periods of dryness and wetness in the area. Rainfall variability index (RVI) is the ratio between anomalies over the standard deviation of long period of rainfall data. The coefficient of variation (CV) is a statistical measure of the dispersion of data points in a data series around the mean. The PNPI is one of the most straightforward measures of rainfall deviation from its long-term mean. ‘Normal’ may be and is usually set to a long-term mean precipitation value at a location. After completing this course, you will be efficiently able to prepare these parameters for MCDM models using Excel and ArcMap. ******************************************************************************************************* International Workshop on An Integrated MCDM approach for Drought Vulnerability Assessments in ArcGIS Whatsapp: +91 94751 72399 The workshop will be started on 12th February 2012. After completing this course, you will be efficiently able to process, predict, and validate any data related to hazard, vulnerability, risk, and suitability assessment using the CRITIC, WASPAS, and SAW models. Live WhatsApp Chatting e-Certificate will be provided Publication support from SCOPUS Index Journal 1:1 Sessions with experts Provide supporting resources like ppt, code, research articles Access recorded class videos any times Brochure https://drive.google.com/file/d/1dZ5k... SUBSCRIBE to the YouTube channel Dr. Jayanta Das, to get notification about our recent lecture uploads on Advances in Geographical Research.    / drjayantadas   ALL RIGHTS RESERVED. #DrJayantaDas