Multiwater Index Synergistic Monitoring of Typical Wetland Water Bodies in the Arid Regions of West-Central Ningxia over 30 Years
The Shapotou National Nature Reserve in the Ningxia Hui Autonomous Region is a typical arid region in China. There is an exceptionally serious problem of surface water resource conservation, and dynamic monitoring of surface water with the help of water indices can help to elucidate its change patte...
Gespeichert in:
Veröffentlicht in: | Water (Basel) 2023-01, Vol.15 (1), p.20 |
---|---|
Hauptverfasser: | , , , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | |
---|---|
container_issue | 1 |
container_start_page | 20 |
container_title | Water (Basel) |
container_volume | 15 |
creator | Pang, Haiwei Wang, Xinwei Hou, Ruiping You, Wanxue Bian, Zhen Sang, Guoqing |
description | The Shapotou National Nature Reserve in the Ningxia Hui Autonomous Region is a typical arid region in China. There is an exceptionally serious problem of surface water resource conservation, and dynamic monitoring of surface water with the help of water indices can help to elucidate its change patterns and impact mechanisms. Here, we analysed the characteristics of interannual variation in surface water area in the study area from 1992–2021. The correlation coefficients of the surface water area in the previous year and the contemporaneous water bodies of the Yellow River with the total surface water area (TSWA) were calculated. The results show the following: ① In terms of the classification accuracy of the two methods, water indices and support vector machine classification, water indices are more suitable for water body extraction in the study area. In particular, the three water indices, NDWI, MNDWI and AWEIsh, were more effective, with average overall accuracies of 90.38%, 90.33% and 90.36% over the 30-year period, respectively. ② From the TSWA extraction results from the last 30 years, the TSWA showed an increasing trend with an increase of 368.28 hm2. Among the areas, Tenggeli Lake contributed the most to the increase in TSWA. ③ The highest correlation between the TSWA and the previous year’s TSWA was 0.89, indicating that the better way to protect the water body is to maintain water surface stability year-round. The surface water area of the Yellow River and TSWA also showed a strong correlation, indicating that the rational use of Yellow River water is also an important direction for the future conservation of water resources in the study area. |
doi_str_mv | 10.3390/w15010020 |
format | Article |
fullrecord | <record><control><sourceid>gale_proqu</sourceid><recordid>TN_cdi_proquest_journals_2761200971</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A791352863</galeid><sourcerecordid>A791352863</sourcerecordid><originalsourceid>FETCH-LOGICAL-c331t-a2c00261a7438848a8f77409722bd94534adf1a10b0c7563821718d9ef39cf503</originalsourceid><addsrcrecordid>eNpNkU1LAzEQhhdRsNQe_AcBTx5W87Wb7LEWPwqtglaKpyXNJjVlm9Qkte3Rf25qRZw5zDDM884Mk2XnCF4RUsHrDSogghDDo6yDISM5pRQd_8tPs14IC5iMVpwXsJN9jddtNBsRlQdD26gteNlZ5ecmRCPB2FkTnTd2DpwGk93KSNGCqYqtsA2Y_lA3rjEqAGNBfFeg700DntXcOBv2zFSFmA-UjT6Bj0loawRwn4kjELwp4cNZdqJFG1TvN3az17vbyeAhHz3dDwf9US4JQTEXWKbLSiQYJZxTLrhmjMKKYTxrKloQKhqNBIIzKFlREo4RQ7yplCaV1AUk3ezioLvy7mOd1qoXbu1tGlljViIMkxZKXVeHrrloVW2sdmlzmbxRSyOdVdqkep9ViBSYlyQBlwdAeheCV7peebMUflcjWO-_Uv99hXwD5yJ9Ew</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2761200971</pqid></control><display><type>article</type><title>Multiwater Index Synergistic Monitoring of Typical Wetland Water Bodies in the Arid Regions of West-Central Ningxia over 30 Years</title><source>MDPI - Multidisciplinary Digital Publishing Institute</source><source>EZB-FREE-00999 freely available EZB journals</source><creator>Pang, Haiwei ; Wang, Xinwei ; Hou, Ruiping ; You, Wanxue ; Bian, Zhen ; Sang, Guoqing</creator><creatorcontrib>Pang, Haiwei ; Wang, Xinwei ; Hou, Ruiping ; You, Wanxue ; Bian, Zhen ; Sang, Guoqing</creatorcontrib><description>The Shapotou National Nature Reserve in the Ningxia Hui Autonomous Region is a typical arid region in China. There is an exceptionally serious problem of surface water resource conservation, and dynamic monitoring of surface water with the help of water indices can help to elucidate its change patterns and impact mechanisms. Here, we analysed the characteristics of interannual variation in surface water area in the study area from 1992–2021. The correlation coefficients of the surface water area in the previous year and the contemporaneous water bodies of the Yellow River with the total surface water area (TSWA) were calculated. The results show the following: ① In terms of the classification accuracy of the two methods, water indices and support vector machine classification, water indices are more suitable for water body extraction in the study area. In particular, the three water indices, NDWI, MNDWI and AWEIsh, were more effective, with average overall accuracies of 90.38%, 90.33% and 90.36% over the 30-year period, respectively. ② From the TSWA extraction results from the last 30 years, the TSWA showed an increasing trend with an increase of 368.28 hm2. Among the areas, Tenggeli Lake contributed the most to the increase in TSWA. ③ The highest correlation between the TSWA and the previous year’s TSWA was 0.89, indicating that the better way to protect the water body is to maintain water surface stability year-round. The surface water area of the Yellow River and TSWA also showed a strong correlation, indicating that the rational use of Yellow River water is also an important direction for the future conservation of water resources in the study area.</description><identifier>ISSN: 2073-4441</identifier><identifier>EISSN: 2073-4441</identifier><identifier>DOI: 10.3390/w15010020</identifier><language>eng</language><publisher>Basel: MDPI AG</publisher><subject>Annual variations ; Aquatic resources ; Arid regions ; Arid zones ; China ; Classification ; Conservation ; Correlation coefficient ; Correlation coefficients ; Impact analysis ; Lakes ; Landsat satellites ; Monitoring ; Nature reserves ; Precipitation ; Remote sensing ; Resource conservation ; Rivers ; Support vector machines ; Surface water ; Water area ; Water bodies ; Water conservation ; Water resources ; Wetlands</subject><ispartof>Water (Basel), 2023-01, Vol.15 (1), p.20</ispartof><rights>COPYRIGHT 2023 MDPI AG</rights><rights>2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c331t-a2c00261a7438848a8f77409722bd94534adf1a10b0c7563821718d9ef39cf503</citedby><cites>FETCH-LOGICAL-c331t-a2c00261a7438848a8f77409722bd94534adf1a10b0c7563821718d9ef39cf503</cites><orcidid>0000-0002-4993-4766</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>315,781,785,27929,27930</link.rule.ids></links><search><creatorcontrib>Pang, Haiwei</creatorcontrib><creatorcontrib>Wang, Xinwei</creatorcontrib><creatorcontrib>Hou, Ruiping</creatorcontrib><creatorcontrib>You, Wanxue</creatorcontrib><creatorcontrib>Bian, Zhen</creatorcontrib><creatorcontrib>Sang, Guoqing</creatorcontrib><title>Multiwater Index Synergistic Monitoring of Typical Wetland Water Bodies in the Arid Regions of West-Central Ningxia over 30 Years</title><title>Water (Basel)</title><description>The Shapotou National Nature Reserve in the Ningxia Hui Autonomous Region is a typical arid region in China. There is an exceptionally serious problem of surface water resource conservation, and dynamic monitoring of surface water with the help of water indices can help to elucidate its change patterns and impact mechanisms. Here, we analysed the characteristics of interannual variation in surface water area in the study area from 1992–2021. The correlation coefficients of the surface water area in the previous year and the contemporaneous water bodies of the Yellow River with the total surface water area (TSWA) were calculated. The results show the following: ① In terms of the classification accuracy of the two methods, water indices and support vector machine classification, water indices are more suitable for water body extraction in the study area. In particular, the three water indices, NDWI, MNDWI and AWEIsh, were more effective, with average overall accuracies of 90.38%, 90.33% and 90.36% over the 30-year period, respectively. ② From the TSWA extraction results from the last 30 years, the TSWA showed an increasing trend with an increase of 368.28 hm2. Among the areas, Tenggeli Lake contributed the most to the increase in TSWA. ③ The highest correlation between the TSWA and the previous year’s TSWA was 0.89, indicating that the better way to protect the water body is to maintain water surface stability year-round. The surface water area of the Yellow River and TSWA also showed a strong correlation, indicating that the rational use of Yellow River water is also an important direction for the future conservation of water resources in the study area.</description><subject>Annual variations</subject><subject>Aquatic resources</subject><subject>Arid regions</subject><subject>Arid zones</subject><subject>China</subject><subject>Classification</subject><subject>Conservation</subject><subject>Correlation coefficient</subject><subject>Correlation coefficients</subject><subject>Impact analysis</subject><subject>Lakes</subject><subject>Landsat satellites</subject><subject>Monitoring</subject><subject>Nature reserves</subject><subject>Precipitation</subject><subject>Remote sensing</subject><subject>Resource conservation</subject><subject>Rivers</subject><subject>Support vector machines</subject><subject>Surface water</subject><subject>Water area</subject><subject>Water bodies</subject><subject>Water conservation</subject><subject>Water resources</subject><subject>Wetlands</subject><issn>2073-4441</issn><issn>2073-4441</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><recordid>eNpNkU1LAzEQhhdRsNQe_AcBTx5W87Wb7LEWPwqtglaKpyXNJjVlm9Qkte3Rf25qRZw5zDDM884Mk2XnCF4RUsHrDSogghDDo6yDISM5pRQd_8tPs14IC5iMVpwXsJN9jddtNBsRlQdD26gteNlZ5ecmRCPB2FkTnTd2DpwGk93KSNGCqYqtsA2Y_lA3rjEqAGNBfFeg700DntXcOBv2zFSFmA-UjT6Bj0loawRwn4kjELwp4cNZdqJFG1TvN3az17vbyeAhHz3dDwf9US4JQTEXWKbLSiQYJZxTLrhmjMKKYTxrKloQKhqNBIIzKFlREo4RQ7yplCaV1AUk3ezioLvy7mOd1qoXbu1tGlljViIMkxZKXVeHrrloVW2sdmlzmbxRSyOdVdqkep9ViBSYlyQBlwdAeheCV7peebMUflcjWO-_Uv99hXwD5yJ9Ew</recordid><startdate>20230101</startdate><enddate>20230101</enddate><creator>Pang, Haiwei</creator><creator>Wang, Xinwei</creator><creator>Hou, Ruiping</creator><creator>You, Wanxue</creator><creator>Bian, Zhen</creator><creator>Sang, Guoqing</creator><general>MDPI AG</general><scope>AAYXX</scope><scope>CITATION</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><orcidid>https://orcid.org/0000-0002-4993-4766</orcidid></search><sort><creationdate>20230101</creationdate><title>Multiwater Index Synergistic Monitoring of Typical Wetland Water Bodies in the Arid Regions of West-Central Ningxia over 30 Years</title><author>Pang, Haiwei ; Wang, Xinwei ; Hou, Ruiping ; You, Wanxue ; Bian, Zhen ; Sang, Guoqing</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c331t-a2c00261a7438848a8f77409722bd94534adf1a10b0c7563821718d9ef39cf503</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Annual variations</topic><topic>Aquatic resources</topic><topic>Arid regions</topic><topic>Arid zones</topic><topic>China</topic><topic>Classification</topic><topic>Conservation</topic><topic>Correlation coefficient</topic><topic>Correlation coefficients</topic><topic>Impact analysis</topic><topic>Lakes</topic><topic>Landsat satellites</topic><topic>Monitoring</topic><topic>Nature reserves</topic><topic>Precipitation</topic><topic>Remote sensing</topic><topic>Resource conservation</topic><topic>Rivers</topic><topic>Support vector machines</topic><topic>Surface water</topic><topic>Water area</topic><topic>Water bodies</topic><topic>Water conservation</topic><topic>Water resources</topic><topic>Wetlands</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Pang, Haiwei</creatorcontrib><creatorcontrib>Wang, Xinwei</creatorcontrib><creatorcontrib>Hou, Ruiping</creatorcontrib><creatorcontrib>You, Wanxue</creatorcontrib><creatorcontrib>Bian, Zhen</creatorcontrib><creatorcontrib>Sang, Guoqing</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Access via ProQuest (Open Access)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><jtitle>Water (Basel)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Pang, Haiwei</au><au>Wang, Xinwei</au><au>Hou, Ruiping</au><au>You, Wanxue</au><au>Bian, Zhen</au><au>Sang, Guoqing</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Multiwater Index Synergistic Monitoring of Typical Wetland Water Bodies in the Arid Regions of West-Central Ningxia over 30 Years</atitle><jtitle>Water (Basel)</jtitle><date>2023-01-01</date><risdate>2023</risdate><volume>15</volume><issue>1</issue><spage>20</spage><pages>20-</pages><issn>2073-4441</issn><eissn>2073-4441</eissn><abstract>The Shapotou National Nature Reserve in the Ningxia Hui Autonomous Region is a typical arid region in China. There is an exceptionally serious problem of surface water resource conservation, and dynamic monitoring of surface water with the help of water indices can help to elucidate its change patterns and impact mechanisms. Here, we analysed the characteristics of interannual variation in surface water area in the study area from 1992–2021. The correlation coefficients of the surface water area in the previous year and the contemporaneous water bodies of the Yellow River with the total surface water area (TSWA) were calculated. The results show the following: ① In terms of the classification accuracy of the two methods, water indices and support vector machine classification, water indices are more suitable for water body extraction in the study area. In particular, the three water indices, NDWI, MNDWI and AWEIsh, were more effective, with average overall accuracies of 90.38%, 90.33% and 90.36% over the 30-year period, respectively. ② From the TSWA extraction results from the last 30 years, the TSWA showed an increasing trend with an increase of 368.28 hm2. Among the areas, Tenggeli Lake contributed the most to the increase in TSWA. ③ The highest correlation between the TSWA and the previous year’s TSWA was 0.89, indicating that the better way to protect the water body is to maintain water surface stability year-round. The surface water area of the Yellow River and TSWA also showed a strong correlation, indicating that the rational use of Yellow River water is also an important direction for the future conservation of water resources in the study area.</abstract><cop>Basel</cop><pub>MDPI AG</pub><doi>10.3390/w15010020</doi><orcidid>https://orcid.org/0000-0002-4993-4766</orcidid><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 2073-4441 |
ispartof | Water (Basel), 2023-01, Vol.15 (1), p.20 |
issn | 2073-4441 2073-4441 |
language | eng |
recordid | cdi_proquest_journals_2761200971 |
source | MDPI - Multidisciplinary Digital Publishing Institute; EZB-FREE-00999 freely available EZB journals |
subjects | Annual variations Aquatic resources Arid regions Arid zones China Classification Conservation Correlation coefficient Correlation coefficients Impact analysis Lakes Landsat satellites Monitoring Nature reserves Precipitation Remote sensing Resource conservation Rivers Support vector machines Surface water Water area Water bodies Water conservation Water resources Wetlands |
title | Multiwater Index Synergistic Monitoring of Typical Wetland Water Bodies in the Arid Regions of West-Central Ningxia over 30 Years |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-12T05%3A59%3A36IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_proqu&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Multiwater%20Index%20Synergistic%20Monitoring%20of%20Typical%20Wetland%20Water%20Bodies%20in%20the%20Arid%20Regions%20of%20West-Central%20Ningxia%20over%2030%20Years&rft.jtitle=Water%20(Basel)&rft.au=Pang,%20Haiwei&rft.date=2023-01-01&rft.volume=15&rft.issue=1&rft.spage=20&rft.pages=20-&rft.issn=2073-4441&rft.eissn=2073-4441&rft_id=info:doi/10.3390/w15010020&rft_dat=%3Cgale_proqu%3EA791352863%3C/gale_proqu%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2761200971&rft_id=info:pmid/&rft_galeid=A791352863&rfr_iscdi=true |