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! 1#           def, H: @L ARIMA=>) GMS ghijklmn&&o                                            2 7

                 ÈD, a:µcñ¼{ RMSEî3–ƒ 0.40                     ÖC,NSEîµ2¦ 0.71~0.96|Î,RMSEîµ
            m, Œ¦cñ¼ J6 ÿ,GMS ž ML ij{ RMSEîµ                  2¦ 0.05~0.45m|Î, ijß~•é。
            T 0.45 ž 0.40m, ÌVWu;ƒijîôÈ©                          (2)ARIMAiº‚ø\íê{ðñS0•»,
            ªd 4、10 Â4BZZ¦{–fÒîl¡。xï J6                        ÂTu‚ƒ8íê{ðñ{«»ƒÊZíê, ðñ
            ÿ{ NSEî•a, g/¬k)#•Ý{ij{                           îcaÖíêj/[Ý。
            «。‚ƒcñ¼ J14、J8, I RMSEî3d×&L                           ( 3) ° ARIMAiºðñ{ø\íê®/d
            0.40m{¨Qccñ¼ J6 ’Ò。                                GMS iº4ÆÇ4BZZ¦ij, ˆ{§¯2†
                 ./ GMS ž MLiº{ NSEc RMSEü†Î                   iº‚ôÎíêéÞÑà{ª³Ñ, u€‡ˆ›
            ], ‹Òcñ¼{ij{«b¦67, ˆ{cñ¼¢                          ÇÑc›KÑ, ȍv55Kðñ4BZZ¦–—
            >/Ǖ GMS iºÆÇij, ïˆ{N¢>/Ǖ                         #0éê, š›5K4BZ]^œ„c½¾–—
            ML iº。                                             ?Wq1。
                 ­/ïó,GMS ž MLiº¦ij4BZZ¦
            €r3S0#•Ý{ÑÈ, ȯˆ{dŒcñî{                            opFG:
            ú¼Z[, Xïq¯° ARIMAiºc GMS ®/                       [1]…,M, ùúú, ûüý, :. SÐZB{–·EJK4B
            {›ÇÑ。ît}–{u,Zhao :             [29] eL¿/ EE          ZZ¦ú¼ÆÊ[J]. 0Þ4Ÿ,2023,37(4):986993.
            MD-LSTM-ARIMAiº‚ó¯œÊZÆÇðñ,                         [2]TAYLORRG,SCANLONB,D?LLP,etal.Groundwa
                                                                  terandclimatechange [J].NatureClimateChange,2013,
            +t¯•é{ðñtú~。òœ¿/Ü.p€0
                                                                  3(4):322329.
            ¹È¯*t•ìà{ðñ®«, ñp€0i
                                                               [3]þâK. %ƒCD„ècp€0{þE4BZZ¦ð
            ºqôѰ̈́‰Š, ­¦Üúðñ×íîij
                                                                  ñAB[D]. ÿ`: ÿ`a0,2018.
            LD4üWacÖ*+{íê。QÈ, YõôÎ
                                                               [4]ƒ Œ. 5K4BZíîij[D].  F: Ç~a0,2005.
            AB›Æ}ÉÊ.p€0€cíîiº{®/                             [5]9 ”, x ‹, ¹4. %ƒ VisualModFlow{‡Ïœ4
            Õ, Ö»¼4BZZ¦{ðñ{«。                                    BZ&Ç5Z¦ðñ[J]. 4BZ,2022,44(4):5358.
                 qABlXY{XEJK4BZiºö>ƒ–                          [6]x9+, z–,, ( W. EF òP±c44BZ 4S
            ·EJK, –·EJK¦¾÷ZßÖ¬{5Ka:                               Zd“”•ij\L+;<AB[J]. ZbZq÷n,
            µÇ5, 4I`›•a, T¡¦4BZZ¦ijL                             2022,43(12):8187.
            D4j÷#0aÄ({µï0\。QÈ, qAB?                            [7]•––.EnKF €¦pUœìh54BZíîij4
                                                                  {ÕAB[D]. pU: 4!4Ÿa0,2021.
            ¸Ç5, ÖÇÎ쨍AB‚\, u€ò›ôÎÆ
                                                               [8]MIROM E,GROVESD,TINCHERB,etal.Adaptive
            Ça5KÇ54BZZ¦ij–—q1。ÈD, q
                                                                  watermanagementinthefaceofuncertainty:integrating
            AB^õ¯ ARIMAiº, îxuiº¦ÆÇ p、q
                                                                  machinelearning,groundwatermodelingandrobustdeci
            ( òw’stí) ·Fχˆ}·{VcÑ, ñIð
                                                                  sionmaking [J].ClimateRiskManagement,2021,34
            ñ®«•ìà。¦P¢{AB4, ¸¯ ARIMAi                            (3):100383.
            º, <›ÖæÃs•IQÏÎ@<µ¶€, H                            [9]¯ !. %ƒaÖaíêžp€0€{4BZ]^
            LSTM、 øÌµŸ¶· ôЩ³´NC µ Ÿ ¶ ·                         %³´iºAB[D]. "`: {¡a0,2020.
            (convolutionalneuralnetwork-longshorttermmemo    [10]ZHUSenlin,HRNJICAB,PTAKM,etal.Forecasting
            ry,CNN-LSTM) :, ‹³ƒ‚ÊZcƒ8íê{ð                          ofwaterlevelinmultipletemperatelakesusingmachine
            ñ, <›‚IQ’síêÆÇçèžðñ。                                   learningmodels [J].JournalofHydrology,2020,585:
                                                                   124819.
            6 @ c                                              [11]HRNJICAB,BONACCIO.Lakelevelpredictionusing
                                                                   feedforwardandrecurrentneuralnetworks [J].Water
                 qABG‚2†4BZíîiº‚ôÎÊZc
                                                                   ResourcesManagement ,2019,33(7):24712484.
            ƒ8íêéÞÑà­íêcÖ*+{=>, –#¯
                                                               [12]DERBELAM,NOUIRII.Intelligentapproachtopredict
            }.®/ ARIMAiºc GMS iº{4BZZ¦ð
                                                                   futuregroundwaterlevelbasedonartificialneuralnetworks
            ñ€, ֖éðñß~ž>•Ñ。                                      (ANN)[J].EuroMediterraneanJournalforEnvironmen
                 ( 1)GMS iºÈ¯ˆ{ijXEJK4BZ                           talIntegration,2020,5(3):51.
            Z¦{%ú¼, a:µcñ¼{ijÐ6¦0.5m                          [13]z #. p€0¹\IÕAB [D]. ô$: ±Fa
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