{"id":"https://openalex.org/W7225910698","doi":"https://doi.org/10.21203/rs.3.rs-11693497/v1","title":"A Review of Image-Based and AI-Driven Water Level Monitoring: Methods, Datasets, and Deployment Considerations","display_name":"A Review of Image-Based and AI-Driven Water Level Monitoring: Methods, Datasets, and Deployment Considerations","publication_year":2026,"publication_date":"2026-11-12","ids":{"openalex":"https://openalex.org/W7225910698","doi":"https://doi.org/10.21203/rs.3.rs-11693497/v1"},"language":"en","primary_location":{"id":"doi:10.21203/rs.3.rs-11693497/v1","doi":"https://doi.org/10.21203/rs.3.rs-11693497/v1","is_oa":true,"landing_page_url":"https://doi.org/10.21203/rs.3.rs-11693497/v1","pdf_url":"https://www.researchsquare.com/article/rs-11693497/latest.pdf","source":{"id":"https://openalex.org/S4306525896","display_name":"Research Square","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Research Square","raw_type":"posted-content"},"parent_works":[],"lineage":["https://openalex.org/W7225910698"],"child_works_count":0,"type":"preprint","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://www.researchsquare.com/article/rs-11693497/latest.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103178226","display_name":"Atif Latif","orcid":"https://orcid.org/0009-0007-8384-7272","observed_orcids":["https://orcid.org/0009-0007-8384-7272"]},"institutions":[{"id":"https://openalex.org/I121980950","display_name":"Utah State University","ror":"https://ror.org/00h6set76","country_code":"US","type":"education","lineage":["https://openalex.org/I121980950"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Atif Latif","raw_affiliation_strings":["Utah State University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Utah State University","institution_ids":["https://openalex.org/I121980950"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005747820","display_name":"Masoumeh Hashemi","orcid":"https://orcid.org/0000-0001-8649-5208","observed_orcids":["https://orcid.org/0000-0001-8649-5208"]},"institutions":[{"id":"https://openalex.org/I121980950","display_name":"Utah State University","ror":"https://ror.org/00h6set76","country_code":"US","type":"education","lineage":["https://openalex.org/I121980950"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Masoumeh Hashemi","raw_affiliation_strings":["Utah State University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Utah State University","institution_ids":["https://openalex.org/I121980950"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072781337","display_name":"Matt A. Yost","orcid":"https://orcid.org/0000-0001-5012-8481","observed_orcids":["https://orcid.org/0000-0001-5012-8481"]},"institutions":[{"id":"https://openalex.org/I121980950","display_name":"Utah State University","ror":"https://ror.org/00h6set76","country_code":"US","type":"education","lineage":["https://openalex.org/I121980950"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Matt Yost","raw_affiliation_strings":["Utah State University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Utah State University","institution_ids":["https://openalex.org/I121980950"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5124820952","display_name":"Safran Khan","orcid":"https://orcid.org/0009-0002-4354-5572","observed_orcids":["https://orcid.org/0009-0002-4354-5572"]},"institutions":[{"id":"https://openalex.org/I121980950","display_name":"Utah State University","ror":"https://ror.org/00h6set76","country_code":"US","type":"education","lineage":["https://openalex.org/I121980950"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Safran Khan","raw_affiliation_strings":["Utah State University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Utah State University","institution_ids":["https://openalex.org/I121980950"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5005747820","https://openalex.org/A5103178226"],"corresponding_institution_ids":["https://openalex.org/I121980950"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11490","display_name":"Hydrological Forecasting Using AI","score":0.26899999380111694,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"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/T11490","display_name":"Hydrological Forecasting Using AI","score":0.26899999380111694,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"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/T14427","display_name":"Environmental Monitoring and Data Management","score":0.21619999408721924,"subfield":{"id":"https://openalex.org/subfields/2308","display_name":"Management, Monitoring, Policy and Law"},"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/T12697","display_name":"Water Quality Monitoring Technologies","score":0.1696999967098236,"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":[{"id":"https://openalex.org/keywords/water-level-monitoring","display_name":"water level monitoring","score":0.9490000009536743},{"id":"https://openalex.org/keywords/computer-vision","display_name":"computer vision","score":0.6800000071525574},{"id":"https://openalex.org/keywords/deep-learning","display_name":"deep learning","score":0.6309999823570251},{"id":"https://openalex.org/keywords/object-detection","display_name":"object detection","score":0.7250000238418579},{"id":"https://openalex.org/keywords/semantic-segmentation","display_name":"semantic segmentation","score":1.0},{"id":"https://openalex.org/keywords/transformer","display_name":"transformer models","score":0.8159999847412109},{"id":"https://openalex.org/keywords/unmanned-aerial-vehicles","display_name":"unmanned aerial vehicles","score":0.765999972820282},{"id":"https://openalex.org/keywords/satellite-imagery","display_name":"satellite imagery","score":0.8999999761581421},{"id":"https://openalex.org/keywords/ungauged-rivers","display_name":"ungauged rivers","score":0.7870000004768372},{"id":"https://openalex.org/keywords/agricultural-canals","display_name":"agricultural canals","score":0.9629999995231628},{"id":"https://openalex.org/keywords/water-resources","display_name":"water resources","score":0.39899998903274536},{"id":"https://openalex.org/keywords/water-banking","display_name":"water banking","score":0.4560000002384186},{"id":"https://openalex.org/keywords/evaluation-dataset","display_name":"evaluation dataset","score":0.5360000133514404},{"id":"https://openalex.org/keywords/model-generalization","display_name":"model generalization","score":0.6930000185966492},{"id":"https://openalex.org/keywords/illumination-robustness","display_name":"illumination robustness","score":0.5460000038146973}],"concepts":[{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.6732000112533569},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6557000279426575},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5981000065803528},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.49410000443458557},{"id":"https://openalex.org/C188198153","wikidata":"https://www.wikidata.org/wiki/Q1613840","display_name":"Limiting","level":2,"score":0.37459999322891235},{"id":"https://openalex.org/C74256435","wikidata":"https://www.wikidata.org/wiki/Q134052","display_name":"Flood myth","level":2,"score":0.3682999908924103},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35190001130104065},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.35030001401901245},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.3449000120162964},{"id":"https://openalex.org/C153823671","wikidata":"https://www.wikidata.org/wiki/Q1049799","display_name":"Water resources","level":2,"score":0.3321000039577484},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.33059999346733093},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3183000087738037},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.3140000104904175},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2987000048160553},{"id":"https://openalex.org/C107826830","wikidata":"https://www.wikidata.org/wiki/Q929380","display_name":"Environmental resource management","level":1,"score":0.29159998893737793},{"id":"https://openalex.org/C1284942","wikidata":"https://www.wikidata.org/wiki/Q1929501","display_name":"Water level","level":2,"score":0.28130000829696655},{"id":"https://openalex.org/C117455697","wikidata":"https://www.wikidata.org/wiki/Q190149","display_name":"Photogrammetry","level":2,"score":0.27639999985694885},{"id":"https://openalex.org/C112930515","wikidata":"https://www.wikidata.org/wiki/Q4389547","display_name":"Risk analysis (engineering)","level":1,"score":0.26829999685287476},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.26739999651908875},{"id":"https://openalex.org/C3019973339","wikidata":"https://www.wikidata.org/wiki/Q899523","display_name":"Object based","level":3,"score":0.260699987411499}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.21203/rs.3.rs-11693497/v1","doi":"https://doi.org/10.21203/rs.3.rs-11693497/v1","is_oa":true,"landing_page_url":"https://doi.org/10.21203/rs.3.rs-11693497/v1","pdf_url":"https://www.researchsquare.com/article/rs-11693497/latest.pdf","source":{"id":"https://openalex.org/S4306525896","display_name":"Research Square","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Research Square","raw_type":"posted-content"}],"best_oa_location":{"id":"doi:10.21203/rs.3.rs-11693497/v1","doi":"https://doi.org/10.21203/rs.3.rs-11693497/v1","is_oa":true,"landing_page_url":"https://doi.org/10.21203/rs.3.rs-11693497/v1","pdf_url":"https://www.researchsquare.com/article/rs-11693497/latest.pdf","source":{"id":"https://openalex.org/S4306525896","display_name":"Research Square","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Research Square","raw_type":"posted-content"},"sustainable_development_goals":[{"score":0.9090999960899353,"display_name":"Clean water and sanitation","id":"https://metadata.un.org/sdg/6"}],"study_designs":[{"display_name":"Systematic Review","id":"https://openalex.org/study-designs/systematic-review"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7225910698.pdf","grobid_xml":"https://content.openalex.org/works/W7225910698.grobid-xml"},"referenced_works_count":12,"referenced_works":["https://openalex.org/W1581517233","https://openalex.org/W1983958735","https://openalex.org/W2043185941","https://openalex.org/W2568967893","https://openalex.org/W3007088614","https://openalex.org/W3047566904","https://openalex.org/W3118615836","https://openalex.org/W4225726656","https://openalex.org/W4312126458","https://openalex.org/W4313408697","https://openalex.org/W4382322597","https://openalex.org/W4388204062"],"related_works":[],"abstract_inverted_index":{"Abstract":[0],"Accurate":[1],"and":[2,12,19,32,38,45,59,89,93,105,113,122,135,162,173,181,184,190,196,212,215],"continuous":[3],"water-level":[4,50],"monitoring":[5],"is":[6,28],"essential":[7],"for":[8],"agriculture,":[9],"flood":[10],"management,":[11],"water":[13,36,43],"resources":[14],"planning.":[15],"However,":[16,148],"many":[17],"rivers":[18],"agricultural":[20],"canals":[21],"remain":[22],"ungauged":[23],"because":[24,155],"conventional":[25,67],"sensing":[26,91],"infrastructure":[27],"costly":[29],"to":[30,66,192],"install":[31],"maintain,":[33],"limiting":[34],"basin-scale":[35],"accounting":[37],"conservation":[39],"policies":[40],"such":[41],"as":[42],"banking":[44],"leasing.":[46],"Computer":[47],"vision":[48],"enables":[49],"estimation":[51],"from":[52,75,79],"ground-based":[53],"cameras,":[54],"unmanned":[55],"aerial":[56],"vehicles":[57],"(UAVs),":[58],"satellites,":[60],"offering":[61],"a":[62],"low-cost,":[63],"non-contact":[64,90],"alternative":[65],"sensors.":[68],"This":[69],"review":[70],"synthesizes":[71],"93":[72],"studies":[73,140,156],"selected":[74],"168":[76],"articles":[77],"retrieved":[78],"five":[80],"databases,":[81],"following":[82],"PRISMA":[83],"2020":[84],"guidelines.":[85],"We":[86],"summarize":[87],"contact-based":[88],"methods":[92],"examine":[94],"image-based":[95],"approaches,":[96],"including":[97],"traditional":[98],"image":[99],"processing,":[100],"classical":[101],"machine":[102],"learning":[103,107],"(ML),":[104],"deep":[106],"(DL),":[108],"alongside":[109],"their":[110],"imaging":[111],"modalities":[112],"datasets.":[114],"DL":[115],"methods,":[116],"particularly":[117],"object":[118],"detection,":[119],"semantic":[120],"segmentation,":[121],"transformer-based":[123],"models,":[124],"are":[125,151],"more":[126],"robust":[127],"than":[128],"earlier":[129],"approaches":[130],"under":[131,221],"low":[132],"light,":[133],"reflections,":[134,195],"cluttered":[136],"backgrounds,":[137],"with":[138],"several":[139],"reporting":[141],"field":[142,188,223],"errors":[143],"of":[144],"approximately":[145],"1\u20133":[146],"cm.":[147],"these":[149],"results":[150],"not":[152],"directly":[153],"comparable":[154],"differ":[157],"in":[158],"datasets,":[159,207],"reference":[160],"measurements,":[161],"evaluation":[163,175,189,209],"metrics.":[164],"Three":[165],"major":[166],"research":[167,200],"gaps":[168],"emerge:":[169],"(1)":[170],"fragmented":[171],"datasets":[172],"inconsistent":[174],"protocols;":[176],"(2)":[177],"limited":[178],"cross-site":[179,211],"validation":[180],"model":[182],"generalization;":[183],"(3)":[185],"insufficient":[186],"long-term":[187],"robustness":[191],"illumination":[193],"changes,":[194],"camera":[197],"displacement.":[198],"Future":[199],"should":[201],"prioritize":[202],"standardized,":[203],"publicly":[204],"available":[205],"multi-site":[206],"common":[208],"protocols,":[210],"seasonal":[213],"testing,":[214],"adaptive":[216],"models":[217],"that":[218],"maintain":[219],"reliability":[220],"changing":[222],"conditions.":[224]},"counts_by_year":[],"updated_date":"2026-11-14T11:04:58.165337","created_date":"2026-11-13T00:00:00"}
