Loading…

Watershed Grouping Based on Suspended Sediment Yield Using Morphological Criteria: A Comparison of Hierarchical and Nonhierarchical Techniques

Regional sediment analysis methods have traditionally been used to reliably estimate sediment yield in ungauged watersheds with adequate hydrometric stations. Watershed‐grouping techniques are a suitable approach for estimating sediment load, which can be used to assess erosion processes, and surfac...

Full description

Saved in:
Bibliographic Details
Published in:River research and applications 2024-11
Main Authors: Adhami, Maryam, Hamdami, Ghasem, Najafinejad, Ali, Sadoddin, Amir, Abghari, Hirad
Format: Article
Language:English
Citations: Items that this one cites
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by
cites cdi_FETCH-LOGICAL-c118t-7a768b19d7cde6c454db9026b71f8bca128e9ead9ff36b2846aa88bb009c49793
container_end_page
container_issue
container_start_page
container_title River research and applications
container_volume
creator Adhami, Maryam
Hamdami, Ghasem
Najafinejad, Ali
Sadoddin, Amir
Abghari, Hirad
description Regional sediment analysis methods have traditionally been used to reliably estimate sediment yield in ungauged watersheds with adequate hydrometric stations. Watershed‐grouping techniques are a suitable approach for estimating sediment load, which can be used to assess erosion processes, and surface water quality, and plan soil and water conservation measures. Additionally, the relationship between sediment yield and watershed characteristics can be used to identify different stages of erosion evolution and prioritize watersheds for conservation efforts. To this end, this study aimed to assess the applicability of various analytical hierarchy process (AHP) methods, including Ward's, Single linkage, and β‐flexible methods, as well as the nonhierarchical fuzzy C‐means (FCM) method in the Gorganroud and Qareh‐Sou watersheds of northern Iran based on hydrological, geological, climatic, physiographical, and land‐use characteristics. Furthermore, the study evaluated clustering methods to determine the optimal number of subwatershed clusters. The AHP methods identified two, three, or four clusters, while the FCM method identified three clusters as the best number of clusters. The results indicated that the FCM method had a well‐regionalized estimation in the study area with the maximum amount of validation indices (The highest Dunn coefficient 0.31–0.65, the lowest TESS 16.62–36.8, and acceptable Pseudo‐ F coefficient 8.1–10.4). Notably, the fuzzy clustering methods associated each input sample with two or more clusters, which reduced the uncertainty of sediment yield estimation. The recommended clustering method can be used for regional sediment analysis in ungauged watersheds and evaluated against other hydrological variables in the study area.
doi_str_mv 10.1002/rra.4400
format article
fullrecord <record><control><sourceid>crossref</sourceid><recordid>TN_cdi_crossref_primary_10_1002_rra_4400</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>10_1002_rra_4400</sourcerecordid><originalsourceid>FETCH-LOGICAL-c118t-7a768b19d7cde6c454db9026b71f8bca128e9ead9ff36b2846aa88bb009c49793</originalsourceid><addsrcrecordid>eNpNkL1OwzAUhS0EEqUg8QgeWVLsxIltthJBi1RgaCvEFF3_pDFK42C3Ay_BM5MCQkz3nqOjb_gQuqRkQglJr0OACWOEHKERzbM8oazgx39_Lk_RWYxvhFAupBihzxfY2RAba_As-H3vug2-hThE3-HlPva2M0NYWuO2ttvhV2dbg9fxsHv0oW986zdOQ4vL4AaSgxs8xaXf9hBcHBi-xnNnAwTdfM-gM_jJd83_bmV107n3vY3n6KSGNtqL3ztG6_u7VTlPFs-zh3K6SDSlYpdw4IVQVBqujS00y5lRkqSF4rQWSgNNhZUWjKzrrFCpYAWAEEoRIjWTXGZjdPXD1cHHGGxd9cFtIXxUlFQHj9XgsTp4zL4A4r9pGg</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype></control><display><type>article</type><title>Watershed Grouping Based on Suspended Sediment Yield Using Morphological Criteria: A Comparison of Hierarchical and Nonhierarchical Techniques</title><source>Wiley</source><creator>Adhami, Maryam ; Hamdami, Ghasem ; Najafinejad, Ali ; Sadoddin, Amir ; Abghari, Hirad</creator><creatorcontrib>Adhami, Maryam ; Hamdami, Ghasem ; Najafinejad, Ali ; Sadoddin, Amir ; Abghari, Hirad</creatorcontrib><description>Regional sediment analysis methods have traditionally been used to reliably estimate sediment yield in ungauged watersheds with adequate hydrometric stations. Watershed‐grouping techniques are a suitable approach for estimating sediment load, which can be used to assess erosion processes, and surface water quality, and plan soil and water conservation measures. Additionally, the relationship between sediment yield and watershed characteristics can be used to identify different stages of erosion evolution and prioritize watersheds for conservation efforts. To this end, this study aimed to assess the applicability of various analytical hierarchy process (AHP) methods, including Ward's, Single linkage, and β‐flexible methods, as well as the nonhierarchical fuzzy C‐means (FCM) method in the Gorganroud and Qareh‐Sou watersheds of northern Iran based on hydrological, geological, climatic, physiographical, and land‐use characteristics. Furthermore, the study evaluated clustering methods to determine the optimal number of subwatershed clusters. The AHP methods identified two, three, or four clusters, while the FCM method identified three clusters as the best number of clusters. The results indicated that the FCM method had a well‐regionalized estimation in the study area with the maximum amount of validation indices (The highest Dunn coefficient 0.31–0.65, the lowest TESS 16.62–36.8, and acceptable Pseudo‐ F coefficient 8.1–10.4). Notably, the fuzzy clustering methods associated each input sample with two or more clusters, which reduced the uncertainty of sediment yield estimation. The recommended clustering method can be used for regional sediment analysis in ungauged watersheds and evaluated against other hydrological variables in the study area.</description><identifier>ISSN: 1535-1459</identifier><identifier>EISSN: 1535-1467</identifier><identifier>DOI: 10.1002/rra.4400</identifier><language>eng</language><ispartof>River research and applications, 2024-11</ispartof><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c118t-7a768b19d7cde6c454db9026b71f8bca128e9ead9ff36b2846aa88bb009c49793</cites><orcidid>0000-0003-1238-9239</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids></links><search><creatorcontrib>Adhami, Maryam</creatorcontrib><creatorcontrib>Hamdami, Ghasem</creatorcontrib><creatorcontrib>Najafinejad, Ali</creatorcontrib><creatorcontrib>Sadoddin, Amir</creatorcontrib><creatorcontrib>Abghari, Hirad</creatorcontrib><title>Watershed Grouping Based on Suspended Sediment Yield Using Morphological Criteria: A Comparison of Hierarchical and Nonhierarchical Techniques</title><title>River research and applications</title><description>Regional sediment analysis methods have traditionally been used to reliably estimate sediment yield in ungauged watersheds with adequate hydrometric stations. Watershed‐grouping techniques are a suitable approach for estimating sediment load, which can be used to assess erosion processes, and surface water quality, and plan soil and water conservation measures. Additionally, the relationship between sediment yield and watershed characteristics can be used to identify different stages of erosion evolution and prioritize watersheds for conservation efforts. To this end, this study aimed to assess the applicability of various analytical hierarchy process (AHP) methods, including Ward's, Single linkage, and β‐flexible methods, as well as the nonhierarchical fuzzy C‐means (FCM) method in the Gorganroud and Qareh‐Sou watersheds of northern Iran based on hydrological, geological, climatic, physiographical, and land‐use characteristics. Furthermore, the study evaluated clustering methods to determine the optimal number of subwatershed clusters. The AHP methods identified two, three, or four clusters, while the FCM method identified three clusters as the best number of clusters. The results indicated that the FCM method had a well‐regionalized estimation in the study area with the maximum amount of validation indices (The highest Dunn coefficient 0.31–0.65, the lowest TESS 16.62–36.8, and acceptable Pseudo‐ F coefficient 8.1–10.4). Notably, the fuzzy clustering methods associated each input sample with two or more clusters, which reduced the uncertainty of sediment yield estimation. The recommended clustering method can be used for regional sediment analysis in ungauged watersheds and evaluated against other hydrological variables in the study area.</description><issn>1535-1459</issn><issn>1535-1467</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><recordid>eNpNkL1OwzAUhS0EEqUg8QgeWVLsxIltthJBi1RgaCvEFF3_pDFK42C3Ay_BM5MCQkz3nqOjb_gQuqRkQglJr0OACWOEHKERzbM8oazgx39_Lk_RWYxvhFAupBihzxfY2RAba_As-H3vug2-hThE3-HlPva2M0NYWuO2ttvhV2dbg9fxsHv0oW986zdOQ4vL4AaSgxs8xaXf9hBcHBi-xnNnAwTdfM-gM_jJd83_bmV107n3vY3n6KSGNtqL3ztG6_u7VTlPFs-zh3K6SDSlYpdw4IVQVBqujS00y5lRkqSF4rQWSgNNhZUWjKzrrFCpYAWAEEoRIjWTXGZjdPXD1cHHGGxd9cFtIXxUlFQHj9XgsTp4zL4A4r9pGg</recordid><startdate>20241106</startdate><enddate>20241106</enddate><creator>Adhami, Maryam</creator><creator>Hamdami, Ghasem</creator><creator>Najafinejad, Ali</creator><creator>Sadoddin, Amir</creator><creator>Abghari, Hirad</creator><scope>AAYXX</scope><scope>CITATION</scope><orcidid>https://orcid.org/0000-0003-1238-9239</orcidid></search><sort><creationdate>20241106</creationdate><title>Watershed Grouping Based on Suspended Sediment Yield Using Morphological Criteria: A Comparison of Hierarchical and Nonhierarchical Techniques</title><author>Adhami, Maryam ; Hamdami, Ghasem ; Najafinejad, Ali ; Sadoddin, Amir ; Abghari, Hirad</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c118t-7a768b19d7cde6c454db9026b71f8bca128e9ead9ff36b2846aa88bb009c49793</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Adhami, Maryam</creatorcontrib><creatorcontrib>Hamdami, Ghasem</creatorcontrib><creatorcontrib>Najafinejad, Ali</creatorcontrib><creatorcontrib>Sadoddin, Amir</creatorcontrib><creatorcontrib>Abghari, Hirad</creatorcontrib><collection>CrossRef</collection><jtitle>River research and applications</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Adhami, Maryam</au><au>Hamdami, Ghasem</au><au>Najafinejad, Ali</au><au>Sadoddin, Amir</au><au>Abghari, Hirad</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Watershed Grouping Based on Suspended Sediment Yield Using Morphological Criteria: A Comparison of Hierarchical and Nonhierarchical Techniques</atitle><jtitle>River research and applications</jtitle><date>2024-11-06</date><risdate>2024</risdate><issn>1535-1459</issn><eissn>1535-1467</eissn><abstract>Regional sediment analysis methods have traditionally been used to reliably estimate sediment yield in ungauged watersheds with adequate hydrometric stations. Watershed‐grouping techniques are a suitable approach for estimating sediment load, which can be used to assess erosion processes, and surface water quality, and plan soil and water conservation measures. Additionally, the relationship between sediment yield and watershed characteristics can be used to identify different stages of erosion evolution and prioritize watersheds for conservation efforts. To this end, this study aimed to assess the applicability of various analytical hierarchy process (AHP) methods, including Ward's, Single linkage, and β‐flexible methods, as well as the nonhierarchical fuzzy C‐means (FCM) method in the Gorganroud and Qareh‐Sou watersheds of northern Iran based on hydrological, geological, climatic, physiographical, and land‐use characteristics. Furthermore, the study evaluated clustering methods to determine the optimal number of subwatershed clusters. The AHP methods identified two, three, or four clusters, while the FCM method identified three clusters as the best number of clusters. The results indicated that the FCM method had a well‐regionalized estimation in the study area with the maximum amount of validation indices (The highest Dunn coefficient 0.31–0.65, the lowest TESS 16.62–36.8, and acceptable Pseudo‐ F coefficient 8.1–10.4). Notably, the fuzzy clustering methods associated each input sample with two or more clusters, which reduced the uncertainty of sediment yield estimation. The recommended clustering method can be used for regional sediment analysis in ungauged watersheds and evaluated against other hydrological variables in the study area.</abstract><doi>10.1002/rra.4400</doi><orcidid>https://orcid.org/0000-0003-1238-9239</orcidid></addata></record>
fulltext fulltext
identifier ISSN: 1535-1459
ispartof River research and applications, 2024-11
issn 1535-1459
1535-1467
language eng
recordid cdi_crossref_primary_10_1002_rra_4400
source Wiley
title Watershed Grouping Based on Suspended Sediment Yield Using Morphological Criteria: A Comparison of Hierarchical and Nonhierarchical Techniques
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-04T16%3A04%3A18IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-crossref&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Watershed%20Grouping%20Based%20on%20Suspended%20Sediment%20Yield%20Using%20Morphological%20Criteria:%20A%20Comparison%20of%20Hierarchical%20and%20Nonhierarchical%20Techniques&rft.jtitle=River%20research%20and%20applications&rft.au=Adhami,%20Maryam&rft.date=2024-11-06&rft.issn=1535-1459&rft.eissn=1535-1467&rft_id=info:doi/10.1002/rra.4400&rft_dat=%3Ccrossref%3E10_1002_rra_4400%3C/crossref%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c118t-7a768b19d7cde6c454db9026b71f8bca128e9ead9ff36b2846aa88bb009c49793%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