CIVILICA We Respect the Science
Publisher of Iranian Journals and Conference Proceedings

Multiple linear regression modeling of precipitation for spatiotemporal drought assessment

Credit to Download: 1 | Page Numbers 14 | Abstract Views: 26
Year: 2018
COI code: MIWM01_073
Paper Language: English

How to Download This Paper

For Downloading the Fulltext of CIVILICA papers please visit the orginal Persian Section of website.

Authors Multiple linear regression modeling of precipitation for spatiotemporal drought assessment

zahir nikraftar - Department of Geomatics Engineering, Shahid Rajaee Teacher Training University, Tehran, Iran
abdorrahman mostafaie - Surveying Department, Faculty of Engineering, University of Zaboh, Zabol, Iran
  mohammad akbari - Department of Civil Engineering, University of Birjand, Birjand, Iran


Precipitation records from 110 stations over Iran revealed that areal mean annual precipitation decreased with various magnitudes over the country. Precipitation magnitude decreases from north-west along the west part of country by as much as 300 mm on average in 2008-2009 years. In this study elevation and longitude has been chosen as most influential parameters which have highest spatial correlation with precipitation. Results implies that during the years with minimum precipitation the precipitation shortage was greater at high elevations in the north-west and western part of Iran and the precipitation excess during the year with maximum precipitation was greater in this parts too. Spatially Normalized Standardized Precipitation Index (SN-SPI) applied to asses the spatial and temporal distribution of droughts for the period of 1990 to 2010with the aim of investigating the drought conditions of six main hydrologic basin of Iran. The results showed that severe droughts occurred around the year 2004–2009, with a duration of up to 5 year. Multiple linear regression (MLR)modeling of precipitation in conjunction with cluster analysis of drought duration exhibits the linkage between precipitation, droughts and geographical factors. This connection between spatial precipitation distribution and geographical parameters provides an important clue for the respective spatial drought pattern. The above findings on the spatiotemporal drought distribution will update the current drought management plans by developing more precise drought warning systems


Drought indices, Precipitation, Iran

Perma Link
COI code: MIWM01_073

how to cite to this paper:

If you want to refer to this article in your research, you can easily use the following in the resources and references section:
nikraftar, zahir; abdorrahman mostafaie & mohammad akbari, 2018, Multiple linear regression modeling of precipitation for spatiotemporal drought assessment, The first National Modeling Conference and New Technologies in Water Management, بيرجند, دانشگاه بيرجند, the text, wherever referred to or an achievement of this article is mentioned, after mentioning the article, inside the parental, the following specifications are written.
First Time: (nikraftar, zahir; abdorrahman mostafaie & mohammad akbari, 2018)
Second and more: (nikraftar; mostafaie & akbari, 2018)
For a complete overview of how to citation please review the following CIVILICA Guide (Citation)

Research Info Management

Export Citation info of this paper to research management softwares

New Related Papers

Iran Scientific Advertisment Netword

Share this paper


COI is a national code dedicated to all Iranian Conference and Journal Papers. the COI of each paper can be verified online.