{"id":"https://openalex.org/W7225244157","doi":"https://doi.org/10.3390/app162110934","title":"Inversion of Non-Optically Active Water Quality Parameters in Karst Mountain Reservoirs Based on Multi-Source Data: A Case Study of Pingzhai Reservoir","display_name":"Inversion of Non-Optically Active Water Quality Parameters in Karst Mountain Reservoirs Based on Multi-Source Data: A Case Study of Pingzhai Reservoir","publication_year":2026,"publication_date":"2026-11-04","ids":{"openalex":"https://openalex.org/W7225244157","doi":"https://doi.org/10.3390/app162110934"},"language":"en","primary_location":{"id":"doi:10.3390/app162110934","doi":"https://doi.org/10.3390/app162110934","is_oa":true,"landing_page_url":"https://doi.org/10.3390/app162110934","pdf_url":null,"source":{"id":"https://openalex.org/S4210205812","display_name":"Applied Sciences","issn_l":"2076-3417","issn":["2076-3417"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","norway-1","oarl","poland-100","russia-white-list-2","vabb-shw"],"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Sciences","raw_type":"journal-article"},"volume":null,"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.3390/app162110934","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5160604258","display_name":"Rui Li","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I154893126","display_name":"Guizhou Normal University","ror":"https://ror.org/02x1pa065","country_code":"CN","type":"education","lineage":["https://openalex.org/I154893126"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rui Li","raw_affiliation_strings":["Guizhou Provincial Key Laboratory of Intelligent Processing and Application of Remote Sensing Big Data, Guiyang 550001, China","School of Karst Science, Guizhou Normal University, Guiyang 550001, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guizhou Provincial Key Laboratory of Intelligent Processing and Application of Remote Sensing Big Data, Guiyang 550001, China","institution_ids":[]},{"raw_affiliation_string":"School of Karst Science, Guizhou Normal University, Guiyang 550001, China","institution_ids":["https://openalex.org/I154893126"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5115693115","display_name":"Zhongfa Zhou","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I154893126","display_name":"Guizhou Normal University","ror":"https://ror.org/02x1pa065","country_code":"CN","type":"education","lineage":["https://openalex.org/I154893126"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhongfa Zhou","raw_affiliation_strings":["Guizhou Provincial Key Laboratory of Intelligent Processing and Application of Remote Sensing Big Data, Guiyang 550001, China","School of Geography & Environmental Science, Guizhou Normal University, Guiyang 550001, China","School of Karst Science, Guizhou Normal University, Guiyang 550001, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guizhou Provincial Key Laboratory of Intelligent Processing and Application of Remote Sensing Big Data, Guiyang 550001, China","institution_ids":[]},{"raw_affiliation_string":"School of Geography & Environmental Science, Guizhou Normal University, Guiyang 550001, China","institution_ids":["https://openalex.org/I154893126"]},{"raw_affiliation_string":"School of Karst Science, Guizhou Normal University, Guiyang 550001, China","institution_ids":["https://openalex.org/I154893126"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102832413","display_name":"Xinyue Zhang","orcid":"https://orcid.org/0000-0002-3397-7200","observed_orcids":["https://orcid.org/0000-0002-3397-7200"]},"institutions":[{"id":"https://openalex.org/I154893126","display_name":"Guizhou Normal University","ror":"https://ror.org/02x1pa065","country_code":"CN","type":"education","lineage":["https://openalex.org/I154893126"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinyue Zhang","raw_affiliation_strings":["School of Geography & Environmental Science, Guizhou Normal University, Guiyang 550001, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Geography & Environmental Science, Guizhou Normal University, Guiyang 550001, China","institution_ids":["https://openalex.org/I154893126"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5160620806","display_name":"Yusen Zhong","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I154893126","display_name":"Guizhou Normal University","ror":"https://ror.org/02x1pa065","country_code":"CN","type":"education","lineage":["https://openalex.org/I154893126"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yusen Zhong","raw_affiliation_strings":["School of Karst Science, Guizhou Normal University, Guiyang 550001, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Karst Science, Guizhou Normal University, Guiyang 550001, China","institution_ids":["https://openalex.org/I154893126"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5160684634","display_name":"Sisi Yang","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I154893126","display_name":"Guizhou Normal University","ror":"https://ror.org/02x1pa065","country_code":"CN","type":"education","lineage":["https://openalex.org/I154893126"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sisi Yang","raw_affiliation_strings":["School of Geography & Environmental Science, Guizhou Normal University, Guiyang 550001, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Geography & Environmental Science, Guizhou Normal University, Guiyang 550001, China","institution_ids":["https://openalex.org/I154893126"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5115693115"],"corresponding_institution_ids":["https://openalex.org/I154893126"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2896},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2896},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.73397039,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"16","issue":"21","first_page":"10934","last_page":"10934"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12697","display_name":"Water Quality Monitoring Technologies","score":0.836899995803833,"subfield":{"id":"https://openalex.org/subfields/2312","display_name":"Water Science and Technology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12697","display_name":"Water Quality Monitoring Technologies","score":0.836899995803833,"subfield":{"id":"https://openalex.org/subfields/2312","display_name":"Water Science and Technology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T14249","display_name":"Water Quality Monitoring and Analysis","score":0.11540000140666962,"subfield":{"id":"https://openalex.org/subfields/2311","display_name":"Waste Management and Disposal"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11634","display_name":"Water Quality and Pollution Assessment","score":0.025299999862909317,"subfield":{"id":"https://openalex.org/subfields/2312","display_name":"Water Science and Technology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[],"concepts":[{"id":"https://openalex.org/C1893757","wikidata":"https://www.wikidata.org/wiki/Q3653001","display_name":"Inversion (geology)","level":3,"score":0.7720000147819519},{"id":"https://openalex.org/C182348080","wikidata":"https://www.wikidata.org/wiki/Q16817","display_name":"Karst","level":2,"score":0.617900013923645},{"id":"https://openalex.org/C173163844","wikidata":"https://www.wikidata.org/wiki/Q1761440","display_name":"Multispectral image","level":2,"score":0.58160001039505},{"id":"https://openalex.org/C2780797713","wikidata":"https://www.wikidata.org/wiki/Q625376","display_name":"Water quality","level":2,"score":0.5418999791145325},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.49239999055862427},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.491100013256073},{"id":"https://openalex.org/C108597893","wikidata":"https://www.wikidata.org/wiki/Q663650","display_name":"Reflectivity","level":2,"score":0.36890000104904175},{"id":"https://openalex.org/C153823671","wikidata":"https://www.wikidata.org/wiki/Q1049799","display_name":"Water resources","level":2,"score":0.3650999963283539},{"id":"https://openalex.org/C76886044","wikidata":"https://www.wikidata.org/wiki/Q2883300","display_name":"Hydrology (agriculture)","level":2,"score":0.3296999931335449},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.32510000467300415},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.29319998621940613},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.2842000126838684},{"id":"https://openalex.org/C206345919","wikidata":"https://www.wikidata.org/wiki/Q20380951","display_name":"Resource (disambiguation)","level":2,"score":0.26249998807907104},{"id":"https://openalex.org/C104541649","wikidata":"https://www.wikidata.org/wiki/Q6935090","display_name":"Multispectral pattern recognition","level":3,"score":0.25099998712539673}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3390/app162110934","doi":"https://doi.org/10.3390/app162110934","is_oa":true,"landing_page_url":"https://doi.org/10.3390/app162110934","pdf_url":null,"source":{"id":"https://openalex.org/S4210205812","display_name":"Applied Sciences","issn_l":"2076-3417","issn":["2076-3417"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","norway-1","oarl","poland-100","russia-white-list-2","vabb-shw"],"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Sciences","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.3390/app162110934","doi":"https://doi.org/10.3390/app162110934","is_oa":true,"landing_page_url":"https://doi.org/10.3390/app162110934","pdf_url":null,"source":{"id":"https://openalex.org/S4210205812","display_name":"Applied Sciences","issn_l":"2076-3417","issn":["2076-3417"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","norway-1","oarl","poland-100","russia-white-list-2","vabb-shw"],"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Sciences","raw_type":"journal-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W1991846291","https://openalex.org/W2036887984","https://openalex.org/W2145979309","https://openalex.org/W2295598076","https://openalex.org/W2748127925","https://openalex.org/W2911964244","https://openalex.org/W2971897573","https://openalex.org/W2998681661","https://openalex.org/W3042832640","https://openalex.org/W3114738320","https://openalex.org/W3166273387","https://openalex.org/W4205436153","https://openalex.org/W4210256416","https://openalex.org/W4223437889","https://openalex.org/W4283077289","https://openalex.org/W4284958113","https://openalex.org/W4293078909","https://openalex.org/W4293116366","https://openalex.org/W4301431040","https://openalex.org/W4311365868","https://openalex.org/W4317036038","https://openalex.org/W4386688915","https://openalex.org/W4386865177","https://openalex.org/W4389206140","https://openalex.org/W4391275875","https://openalex.org/W4392240689","https://openalex.org/W4394903918","https://openalex.org/W4399685852","https://openalex.org/W4403001361","https://openalex.org/W4404645931","https://openalex.org/W4406328136","https://openalex.org/W4408129686","https://openalex.org/W4409147147","https://openalex.org/W4411327712","https://openalex.org/W4412694843","https://openalex.org/W4412860780","https://openalex.org/W4413027442","https://openalex.org/W4413122250"],"related_works":[],"abstract_inverted_index":{"Accurate":[0],"monitoring":[1,195],"of":[2,41,120,155],"water":[3,18,176,193],"quality":[4,177,194],"in":[5,196],"karst":[6,197],"mountainous":[7],"reservoirs,":[8],"where":[9],"the":[10,38,97,118,145,149],"ecosystems":[11],"are":[12],"fragile,":[13],"is":[14,71,113,135],"central":[15],"to":[16,116,124,137],"sustainable":[17],"resource":[19],"management":[20],"and":[21,78,84,110,123,141,159,165],"risk":[22],"mitigation.":[23],"Existing":[24],"remote":[25],"sensing":[26],"inversion":[27,67,139,183],"studies,":[28],"however,":[29],"have":[30],"mostly":[31],"relied":[32],"on":[33,96],"spectral":[34],"reflectance":[35],"alone,":[36],"overlooking":[37],"synergistic":[39],"effects":[40],"meteorological":[42,92],"variables,":[43],"while":[44],"machine":[45,65],"learning":[46,66],"models":[47],"remain":[48],"too":[49],"opaque":[50],"for":[51,161,174,192],"meaningful":[52],"interpretation.":[53],"Taking":[54],"Pingzhai":[55,186],"Reservoir":[56],"as":[57],"a":[58],"case":[59],"study,":[60],"this":[61],"study":[62],"develops":[63],"two":[64],"frameworks.":[68],"The":[69,86,179],"first":[70],"driven":[72],"solely":[73],"by":[74],"Sentinel-2":[75],"multispectral":[76,89],"imagery":[77],"compares":[79],"Random":[80,142],"Forest,":[81],"LightGBM,":[82],"XGBoost,":[83],"CatBoost.":[85],"second":[87],"couples":[88],"data":[90,133],"with":[91,152],"variables":[93],"and,":[94],"based":[95],"optimal":[98],"model,":[99],"predicts":[100],"dissolved":[101],"oxygen":[102],"(DO),":[103],"ammonia":[104],"nitrogen":[105,108],"(NH3-N),":[106],"total":[107],"(TN),":[109],"pH.":[111],"SHAP":[112,168],"subsequently":[114],"used":[115],"quantify":[117],"contribution":[119],"each":[121],"input":[122],"analyze":[125],"how":[126],"different":[127,175],"features":[128],"influence":[129],"model":[130],"predictions.":[131],"Multisource":[132],"fusion":[134],"found":[136],"improve":[138],"accuracy,":[140],"Forest":[143],"yields":[144],"best":[146],"performance":[147],"among":[148],"four":[150],"models,":[151],"R2":[153],"values":[154],"0.88,":[156],"0.68,":[157],"0.62,":[158],"0.89":[160],"DO,":[162],"NH3-N,":[163],"TN,":[164],"pH,":[166],"respectively.":[167],"analysis":[169],"revealed":[170],"distinct":[171],"dominant":[172],"drivers":[173],"parameters.":[178],"framework":[180],"produced":[181],"good":[182],"results":[184],"at":[185],"Reservoir,":[187],"offering":[188],"an":[189],"interpretable":[190],"method":[191],"mountain":[198],"reservoirs.":[199]},"counts_by_year":[],"updated_date":"2026-11-05T12:25:35.769452","created_date":"2026-11-05T00:00:00"}