{"id":"https://openalex.org/W4405994635","doi":"https://doi.org/10.22214/ijraset.2024.66196","title":"An Overview of the Methodologies in Drought Forecasting","display_name":"An Overview of the Methodologies in Drought Forecasting","publication_year":2024,"publication_date":"2024-12-31","ids":{"openalex":"https://openalex.org/W4405994635","doi":"https://doi.org/10.22214/ijraset.2024.66196"},"language":"en","primary_location":{"id":"doi:10.22214/ijraset.2024.66196","doi":"https://doi.org/10.22214/ijraset.2024.66196","is_oa":true,"landing_page_url":"https://doi.org/10.22214/ijraset.2024.66196","pdf_url":"https://doi.org/10.22214/ijraset.2024.66196","source":{"id":"https://openalex.org/S2764566388","display_name":"International Journal for Research in Applied Science and Engineering Technology","issn_l":"2321-9653","issn":["2321-9653"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/P4322614460","host_organization_name":"International Journal for Research in Applied Science and Engineering Technology (IJRASET)","host_organization_lineage":["https://openalex.org/P4322614460"],"host_organization_lineage_names":["International Journal for Research in Applied Science and Engineering Technology (IJRASET)"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal for Research in Applied Science and Engineering Technology","raw_type":"journal-article"},"volume":null,"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.22214/ijraset.2024.66196","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5115745221","display_name":"R Angel","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Angel R","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5115745221"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.16034548,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"12","issue":"12","first_page":"2270","last_page":"2274"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11186","display_name":"Hydrology and Drought Analysis","score":0.9911999702453613,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"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/T11186","display_name":"Hydrology and Drought Analysis","score":0.9911999702453613,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"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/T11490","display_name":"Hydrological Forecasting Using AI","score":0.00839999970048666,"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/T11326","display_name":"Stock Market Forecasting Methods","score":0.0,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/drought-forecasting","display_name":"drought forecasting","score":1.0},{"id":"https://openalex.org/keywords/machine-learning","display_name":"machine learning","score":0.7179999947547913},{"id":"https://openalex.org/keywords/arima","display_name":"ARIMA","score":0.9990000128746033},{"id":"https://openalex.org/keywords/lstm","display_name":"LSTM","score":0.6470000147819519},{"id":"https://openalex.org/keywords/random-forest","display_name":"random forest","score":0.9760000109672546},{"id":"https://openalex.org/keywords/drought-indices","display_name":"drought indices","score":0.8299999833106995},{"id":"https://openalex.org/keywords/standardized-precipitation-index","display_name":"Standardized Precipitation Index","score":0.9739999771118164},{"id":"https://openalex.org/keywords/standardized-precipitation-evapotranspiration-index","display_name":"Standardized Precipitation Evapotranspiration Index","score":0.9649999737739563},{"id":"https://openalex.org/keywords/hybrid-forecasting-model","display_name":"hybrid forecasting model","score":0.8050000071525574},{"id":"https://openalex.org/keywords/water-stress","display_name":"water stress","score":0.8640000224113464}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3482816219329834}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.22214/ijraset.2024.66196","doi":"https://doi.org/10.22214/ijraset.2024.66196","is_oa":true,"landing_page_url":"https://doi.org/10.22214/ijraset.2024.66196","pdf_url":"https://doi.org/10.22214/ijraset.2024.66196","source":{"id":"https://openalex.org/S2764566388","display_name":"International Journal for Research in Applied Science and Engineering Technology","issn_l":"2321-9653","issn":["2321-9653"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/P4322614460","host_organization_name":"International Journal for Research in Applied Science and Engineering Technology (IJRASET)","host_organization_lineage":["https://openalex.org/P4322614460"],"host_organization_lineage_names":["International Journal for Research in Applied Science and Engineering Technology (IJRASET)"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal for Research in Applied Science and Engineering Technology","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.22214/ijraset.2024.66196","doi":"https://doi.org/10.22214/ijraset.2024.66196","is_oa":true,"landing_page_url":"https://doi.org/10.22214/ijraset.2024.66196","pdf_url":"https://doi.org/10.22214/ijraset.2024.66196","source":{"id":"https://openalex.org/S2764566388","display_name":"International Journal for Research in Applied Science and Engineering Technology","issn_l":"2321-9653","issn":["2321-9653"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/P4322614460","host_organization_name":"International Journal for Research in Applied Science and Engineering Technology (IJRASET)","host_organization_lineage":["https://openalex.org/P4322614460"],"host_organization_lineage_names":["International Journal for Research in Applied Science and Engineering Technology (IJRASET)"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal for Research in Applied Science and Engineering Technology","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/13","display_name":"Climate action","score":0.7892000079154968},{"id":"https://metadata.un.org/sdg/2","display_name":"Zero hunger","score":0.4359000027179718}],"sustainable_development_goals_aurora":[{"id":"https://metadata.un.org/sdg/13","display_name":"Climate action","score":0.4099999964237213}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4405994635.pdf","grobid_xml":"https://content.openalex.org/works/W4405994635.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Drought":[0],"has":[1,56,77],"resulted":[2],"in":[3,30,41,71,82,118,160,181,192],"the":[4,16,19,33,47,50,63,66,69,72,83,88,123,130,143,147,150,161,179,182,190,193,199,202],"massive":[5],"destruction":[6],"of":[7,32,49,65,85,87,90,95,149,201],"lives,":[8],"livestock":[9],"and":[10,13,61,135,171],"economy,":[11],"locally":[12],"globally.":[14],"Under":[15],"current":[17],"circumstances,":[18],"dry":[20,37],"weather":[21,38],"conditions":[22],"are":[23,156],"prevalent":[24],"leading":[25],"to":[26,59,99],"water":[27],"stress":[28],"resulting":[29],"imbalance":[31],"ecosystem.":[34],"The":[35,93],"persistent":[36],"eventually":[39],"results":[40],"drought":[42,91,120,126,154],"conditions,":[43],"which":[44,196],"indirectly":[45],"affects":[46],"economy":[48],"country.":[51],"As":[52],"a":[53,79],"result,":[54],"it":[55],"become":[57],"imperative":[58],"assess":[60],"mitigate":[62],"effects":[64],"droughts.":[67,177],"With":[68],"advancements":[70],"machine":[73,102],"learning":[74,103],"techniques,":[75],"there":[76],"been":[78,185],"substantial":[80],"improvement":[81],"level":[84],"accuracy":[86],"prediction":[89],"events.":[92,121],"motivation":[94],"this":[96],"paper":[97],"is":[98],"review":[100,168],"those":[101],"techniques":[104],"such":[105],"as":[106],"Extreme":[107],"Gradient":[108],"Boost,":[109],"ARIMA,":[110],"Long":[111],"ShortTerm":[112],"Memory":[113],"(LSTM),":[114],"Random":[115],"Forest":[116],"used":[117,125,174],"forecasting":[119,176],"Considering":[122],"extensively":[124],"indices,":[127],"that":[128],"is,":[129],"Standard":[131],"Precipitation":[132,137],"Index":[133,139],"(SPI)":[134],"Standardized":[136],"Evaporation":[138],"(SPEI)":[140],"together":[141],"with":[142],"various":[144],"meteorological":[145],"parameters,":[146],"influence":[148],"climate":[151],"variables":[152],"on":[153,169],"forecasts":[155],"given":[157],"more":[158],"importance":[159],"present":[162],"study.":[163],"This":[164],"study":[165],"also":[166],"includes":[167],"single":[170],"hybrid":[172],"models":[173],"for":[175],"Further":[178],"gaps":[180],"reviews":[183],"have":[184],"identified":[186],"by":[187],"critically":[188],"observing":[189],"studies":[191],"research":[194],"articles":[195],"will":[197],"enhance":[198],"efficiency":[200],"predictive":[203],"models.":[204]},"counts_by_year":[],"updated_date":"2026-09-11T09:22:31.653822","created_date":"2025-10-10T00:00:00"}