Loading…
Evaluation of remotely sensed precipitation estimates using PERSIANN-CDR and MSWEP for spatio-temporal drought assessment over Iran
•Performance of SREs was evaluated for spatio-temporal drought analysis.•SREs may not perform adequately for extreme drought events.•Drought frequency curves can vary based on the climatic zones.•Performance of SREs can vary with temporal resolution of drought indices. Satellite Rainfall Estimates (...
Saved in:
Published in: | Journal of hydrology (Amsterdam) 2019-12, Vol.579, p.124189, Article 124189 |
---|---|
Main Authors: | , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
cited_by | cdi_FETCH-LOGICAL-c309t-a6087acaec501c40350b0eba1159e2439844919afa9a84d94e3eb206d54bd3943 |
---|---|
cites | cdi_FETCH-LOGICAL-c309t-a6087acaec501c40350b0eba1159e2439844919afa9a84d94e3eb206d54bd3943 |
container_end_page | |
container_issue | |
container_start_page | 124189 |
container_title | Journal of hydrology (Amsterdam) |
container_volume | 579 |
creator | Alijanian, Mohammadali Rakhshandehroo, Gholam Reza Mishra, Ashok Dehghani, Maryam |
description | •Performance of SREs was evaluated for spatio-temporal drought analysis.•SREs may not perform adequately for extreme drought events.•Drought frequency curves can vary based on the climatic zones.•Performance of SREs can vary with temporal resolution of drought indices.
Satellite Rainfall Estimates (SREs) can provide rainfall information at finer spatial and temporal resolutions, however their performance varies with respect to gauged precipitation data in different climatic regions. A limited number of studies investigated the performance of SREs for spatio-temporal (regional) drought analysis, which is a key component for developing tools for regional drought planning and management. In this study, the performance of two recent SREs (data length > 30 years), which includes Artificial Neural Networks Climate Data Record (PERSIANN-CDR) and the Multi-Source Weighted-Ensemble Precipitation (MSWEP) are selected for spatio-temporal drought assessment over different climatic regions located in Iran. Firstly, the accuracy of SREs was evaluated for deriving standardized precipitation index (SPI) at different time scales (1, 3, 6, 9 and 12 months) for four climatic regions during the period of 1983–2012. Secondly, the performance of SREs was evaluated for regional drought assessment based on the concept of the Severity-Areal-Frequency (SAF) curves. It was observed that the performance of SREs can be different with respect to gauge data in terms of quantifying drought characteristics (e.g., severity, duration, and frequency), identification of major historical droughts, and a significant difference can be observed based on the SAF analysis. For example, the number of drought events based on shorter time scales (SPI-1 and 3) found to be greater for SREs in comparison to gauge information for all climatic regions. While investigating the major historical droughts, discrepancies can be observed between these two types of data sets. For example, gauge data suggests wetness (i.e., SPI-3 > 0.5) near southern Iran, whereas, SREs show droughts (SPI |
doi_str_mv | 10.1016/j.jhydrol.2019.124189 |
format | article |
fullrecord | <record><control><sourceid>elsevier_cross</sourceid><recordid>TN_cdi_crossref_primary_10_1016_j_jhydrol_2019_124189</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S0022169419309242</els_id><sourcerecordid>S0022169419309242</sourcerecordid><originalsourceid>FETCH-LOGICAL-c309t-a6087acaec501c40350b0eba1159e2439844919afa9a84d94e3eb206d54bd3943</originalsourceid><addsrcrecordid>eNqFkMtOwzAQRS0EEqXwCUj-gQQ7cR5eoaoEqFRK1YJYWk4yaR0lcWS7lbrmx0mV7pnNbOZc3TkIPVLiU0Ljp9qv96fS6MYPCOU-DRhN-RWa0DThXpCQ5BpNCAkCj8ac3aI7a2syTBiyCfrNjrI5SKd0h3WFDbTaQXPCFjoLJe4NFKpXbjwA61QrHVh8sKrb4XW22S5mq5U3f9lg2ZX4Y_uTrXGlDbb9GfEctL02ssFDvcNu77C0FqxtoXNYH8HghZHdPbqpZGPh4bKn6Ps1-5q_e8vPt8V8tvSKkHDnyZikiSwkFBGhBSNhRHICuaQ04hCwkKeMccplJblMWckZhJAHJC4jlpchZ-EURWNuYbS1BirRm-EfcxKUiLNJUYuLSXE2KUaTA_c8cjCUOyowwhYKugJKNehxotTqn4Q_tkqBfA</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype></control><display><type>article</type><title>Evaluation of remotely sensed precipitation estimates using PERSIANN-CDR and MSWEP for spatio-temporal drought assessment over Iran</title><source>ScienceDirect Freedom Collection</source><creator>Alijanian, Mohammadali ; Rakhshandehroo, Gholam Reza ; Mishra, Ashok ; Dehghani, Maryam</creator><creatorcontrib>Alijanian, Mohammadali ; Rakhshandehroo, Gholam Reza ; Mishra, Ashok ; Dehghani, Maryam</creatorcontrib><description>•Performance of SREs was evaluated for spatio-temporal drought analysis.•SREs may not perform adequately for extreme drought events.•Drought frequency curves can vary based on the climatic zones.•Performance of SREs can vary with temporal resolution of drought indices.
Satellite Rainfall Estimates (SREs) can provide rainfall information at finer spatial and temporal resolutions, however their performance varies with respect to gauged precipitation data in different climatic regions. A limited number of studies investigated the performance of SREs for spatio-temporal (regional) drought analysis, which is a key component for developing tools for regional drought planning and management. In this study, the performance of two recent SREs (data length > 30 years), which includes Artificial Neural Networks Climate Data Record (PERSIANN-CDR) and the Multi-Source Weighted-Ensemble Precipitation (MSWEP) are selected for spatio-temporal drought assessment over different climatic regions located in Iran. Firstly, the accuracy of SREs was evaluated for deriving standardized precipitation index (SPI) at different time scales (1, 3, 6, 9 and 12 months) for four climatic regions during the period of 1983–2012. Secondly, the performance of SREs was evaluated for regional drought assessment based on the concept of the Severity-Areal-Frequency (SAF) curves. It was observed that the performance of SREs can be different with respect to gauge data in terms of quantifying drought characteristics (e.g., severity, duration, and frequency), identification of major historical droughts, and a significant difference can be observed based on the SAF analysis. For example, the number of drought events based on shorter time scales (SPI-1 and 3) found to be greater for SREs in comparison to gauge information for all climatic regions. While investigating the major historical droughts, discrepancies can be observed between these two types of data sets. For example, gauge data suggests wetness (i.e., SPI-3 > 0.5) near southern Iran, whereas, SREs show droughts (SPI < -1.0) in the same spatial domain. The performance of SREs with respect to gauge data varies largely in terms of quantifying the frequency component embedded in the SAF curves for selected climatic regions located in Iran. Our research findings can be useful for drought assessment in ungagged basins, as well as to develop regional drought management plans to improve water security by integrating multivariate nature of drought events.</description><identifier>ISSN: 0022-1694</identifier><identifier>EISSN: 1879-2707</identifier><identifier>DOI: 10.1016/j.jhydrol.2019.124189</identifier><language>eng</language><publisher>Elsevier B.V</publisher><subject>Regional drought assessment ; Satellite rainfall estimates (SREs) ; Severity-area-frequency (SAF) curves</subject><ispartof>Journal of hydrology (Amsterdam), 2019-12, Vol.579, p.124189, Article 124189</ispartof><rights>2019 Elsevier B.V.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c309t-a6087acaec501c40350b0eba1159e2439844919afa9a84d94e3eb206d54bd3943</citedby><cites>FETCH-LOGICAL-c309t-a6087acaec501c40350b0eba1159e2439844919afa9a84d94e3eb206d54bd3943</cites><orcidid>0000-0002-4702-9375</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,777,781,27905,27906</link.rule.ids></links><search><creatorcontrib>Alijanian, Mohammadali</creatorcontrib><creatorcontrib>Rakhshandehroo, Gholam Reza</creatorcontrib><creatorcontrib>Mishra, Ashok</creatorcontrib><creatorcontrib>Dehghani, Maryam</creatorcontrib><title>Evaluation of remotely sensed precipitation estimates using PERSIANN-CDR and MSWEP for spatio-temporal drought assessment over Iran</title><title>Journal of hydrology (Amsterdam)</title><description>•Performance of SREs was evaluated for spatio-temporal drought analysis.•SREs may not perform adequately for extreme drought events.•Drought frequency curves can vary based on the climatic zones.•Performance of SREs can vary with temporal resolution of drought indices.
Satellite Rainfall Estimates (SREs) can provide rainfall information at finer spatial and temporal resolutions, however their performance varies with respect to gauged precipitation data in different climatic regions. A limited number of studies investigated the performance of SREs for spatio-temporal (regional) drought analysis, which is a key component for developing tools for regional drought planning and management. In this study, the performance of two recent SREs (data length > 30 years), which includes Artificial Neural Networks Climate Data Record (PERSIANN-CDR) and the Multi-Source Weighted-Ensemble Precipitation (MSWEP) are selected for spatio-temporal drought assessment over different climatic regions located in Iran. Firstly, the accuracy of SREs was evaluated for deriving standardized precipitation index (SPI) at different time scales (1, 3, 6, 9 and 12 months) for four climatic regions during the period of 1983–2012. Secondly, the performance of SREs was evaluated for regional drought assessment based on the concept of the Severity-Areal-Frequency (SAF) curves. It was observed that the performance of SREs can be different with respect to gauge data in terms of quantifying drought characteristics (e.g., severity, duration, and frequency), identification of major historical droughts, and a significant difference can be observed based on the SAF analysis. For example, the number of drought events based on shorter time scales (SPI-1 and 3) found to be greater for SREs in comparison to gauge information for all climatic regions. While investigating the major historical droughts, discrepancies can be observed between these two types of data sets. For example, gauge data suggests wetness (i.e., SPI-3 > 0.5) near southern Iran, whereas, SREs show droughts (SPI < -1.0) in the same spatial domain. The performance of SREs with respect to gauge data varies largely in terms of quantifying the frequency component embedded in the SAF curves for selected climatic regions located in Iran. Our research findings can be useful for drought assessment in ungagged basins, as well as to develop regional drought management plans to improve water security by integrating multivariate nature of drought events.</description><subject>Regional drought assessment</subject><subject>Satellite rainfall estimates (SREs)</subject><subject>Severity-area-frequency (SAF) curves</subject><issn>0022-1694</issn><issn>1879-2707</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><recordid>eNqFkMtOwzAQRS0EEqXwCUj-gQQ7cR5eoaoEqFRK1YJYWk4yaR0lcWS7lbrmx0mV7pnNbOZc3TkIPVLiU0Ljp9qv96fS6MYPCOU-DRhN-RWa0DThXpCQ5BpNCAkCj8ac3aI7a2syTBiyCfrNjrI5SKd0h3WFDbTaQXPCFjoLJe4NFKpXbjwA61QrHVh8sKrb4XW22S5mq5U3f9lg2ZX4Y_uTrXGlDbb9GfEctL02ssFDvcNu77C0FqxtoXNYH8HghZHdPbqpZGPh4bKn6Ps1-5q_e8vPt8V8tvSKkHDnyZikiSwkFBGhBSNhRHICuaQ04hCwkKeMccplJblMWckZhJAHJC4jlpchZ-EURWNuYbS1BirRm-EfcxKUiLNJUYuLSXE2KUaTA_c8cjCUOyowwhYKugJKNehxotTqn4Q_tkqBfA</recordid><startdate>201912</startdate><enddate>201912</enddate><creator>Alijanian, Mohammadali</creator><creator>Rakhshandehroo, Gholam Reza</creator><creator>Mishra, Ashok</creator><creator>Dehghani, Maryam</creator><general>Elsevier B.V</general><scope>AAYXX</scope><scope>CITATION</scope><orcidid>https://orcid.org/0000-0002-4702-9375</orcidid></search><sort><creationdate>201912</creationdate><title>Evaluation of remotely sensed precipitation estimates using PERSIANN-CDR and MSWEP for spatio-temporal drought assessment over Iran</title><author>Alijanian, Mohammadali ; Rakhshandehroo, Gholam Reza ; Mishra, Ashok ; Dehghani, Maryam</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c309t-a6087acaec501c40350b0eba1159e2439844919afa9a84d94e3eb206d54bd3943</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Regional drought assessment</topic><topic>Satellite rainfall estimates (SREs)</topic><topic>Severity-area-frequency (SAF) curves</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Alijanian, Mohammadali</creatorcontrib><creatorcontrib>Rakhshandehroo, Gholam Reza</creatorcontrib><creatorcontrib>Mishra, Ashok</creatorcontrib><creatorcontrib>Dehghani, Maryam</creatorcontrib><collection>CrossRef</collection><jtitle>Journal of hydrology (Amsterdam)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Alijanian, Mohammadali</au><au>Rakhshandehroo, Gholam Reza</au><au>Mishra, Ashok</au><au>Dehghani, Maryam</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Evaluation of remotely sensed precipitation estimates using PERSIANN-CDR and MSWEP for spatio-temporal drought assessment over Iran</atitle><jtitle>Journal of hydrology (Amsterdam)</jtitle><date>2019-12</date><risdate>2019</risdate><volume>579</volume><spage>124189</spage><pages>124189-</pages><artnum>124189</artnum><issn>0022-1694</issn><eissn>1879-2707</eissn><abstract>•Performance of SREs was evaluated for spatio-temporal drought analysis.•SREs may not perform adequately for extreme drought events.•Drought frequency curves can vary based on the climatic zones.•Performance of SREs can vary with temporal resolution of drought indices.
Satellite Rainfall Estimates (SREs) can provide rainfall information at finer spatial and temporal resolutions, however their performance varies with respect to gauged precipitation data in different climatic regions. A limited number of studies investigated the performance of SREs for spatio-temporal (regional) drought analysis, which is a key component for developing tools for regional drought planning and management. In this study, the performance of two recent SREs (data length > 30 years), which includes Artificial Neural Networks Climate Data Record (PERSIANN-CDR) and the Multi-Source Weighted-Ensemble Precipitation (MSWEP) are selected for spatio-temporal drought assessment over different climatic regions located in Iran. Firstly, the accuracy of SREs was evaluated for deriving standardized precipitation index (SPI) at different time scales (1, 3, 6, 9 and 12 months) for four climatic regions during the period of 1983–2012. Secondly, the performance of SREs was evaluated for regional drought assessment based on the concept of the Severity-Areal-Frequency (SAF) curves. It was observed that the performance of SREs can be different with respect to gauge data in terms of quantifying drought characteristics (e.g., severity, duration, and frequency), identification of major historical droughts, and a significant difference can be observed based on the SAF analysis. For example, the number of drought events based on shorter time scales (SPI-1 and 3) found to be greater for SREs in comparison to gauge information for all climatic regions. While investigating the major historical droughts, discrepancies can be observed between these two types of data sets. For example, gauge data suggests wetness (i.e., SPI-3 > 0.5) near southern Iran, whereas, SREs show droughts (SPI < -1.0) in the same spatial domain. The performance of SREs with respect to gauge data varies largely in terms of quantifying the frequency component embedded in the SAF curves for selected climatic regions located in Iran. Our research findings can be useful for drought assessment in ungagged basins, as well as to develop regional drought management plans to improve water security by integrating multivariate nature of drought events.</abstract><pub>Elsevier B.V</pub><doi>10.1016/j.jhydrol.2019.124189</doi><orcidid>https://orcid.org/0000-0002-4702-9375</orcidid></addata></record> |
fulltext | fulltext |
identifier | ISSN: 0022-1694 |
ispartof | Journal of hydrology (Amsterdam), 2019-12, Vol.579, p.124189, Article 124189 |
issn | 0022-1694 1879-2707 |
language | eng |
recordid | cdi_crossref_primary_10_1016_j_jhydrol_2019_124189 |
source | ScienceDirect Freedom Collection |
subjects | Regional drought assessment Satellite rainfall estimates (SREs) Severity-area-frequency (SAF) curves |
title | Evaluation of remotely sensed precipitation estimates using PERSIANN-CDR and MSWEP for spatio-temporal drought assessment over Iran |
url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-19T15%3A10%3A55IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-elsevier_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Evaluation%20of%20remotely%20sensed%20precipitation%20estimates%20using%20PERSIANN-CDR%20and%20MSWEP%20for%20spatio-temporal%20drought%20assessment%20over%20Iran&rft.jtitle=Journal%20of%20hydrology%20(Amsterdam)&rft.au=Alijanian,%20Mohammadali&rft.date=2019-12&rft.volume=579&rft.spage=124189&rft.pages=124189-&rft.artnum=124189&rft.issn=0022-1694&rft.eissn=1879-2707&rft_id=info:doi/10.1016/j.jhydrol.2019.124189&rft_dat=%3Celsevier_cross%3ES0022169419309242%3C/elsevier_cross%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c309t-a6087acaec501c40350b0eba1159e2439844919afa9a84d94e3eb206d54bd3943%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true |