PEST++IES 繰り返し実行する回数
Trent J Farnum, Andrew T Leaf1, Michael N Fienen1
1U.S. Geologic Survey, Upper Midwest Water Science Center, Madison, WI.
Ground water
|September 4, 2025
まとめ
地下水のモデリングには,PEST++IES (連続テストによる人口推定) が最適のアンサンブルサイズを必要とします. 一般的に,正確な履歴マッチングと不確実性分析のために100〜250の実現と2つの繰り返しで十分です.
科学分野:
- 地下水の水学
- 計算モデリング
- 地政学
背景:
- PEST++IESは,地下水モデルの校正と不確実性分析のための一般的なツールです.
- このアンサンブル・スムーズなアプローチは,高度にパラメータ化されたモデルに有効です.
- 効率化のために最適の数のエンサンブル実現と反復を決定することは極めて重要です.
研究 の 目的:
- PEST++IESのアンサンブル実現とイテレーションの最適な数を調査する.
- 地下水のモデリングにおけるモデル性能に対するアンサンブルサイズの影響を評価する.
- 計算コストと履歴マッチングの精度とのトレードオフを評価する.
主な方法:
- 改造されたフレイバーグモデルがシミュレーションに使用されました.
- 10から2000までのアンサンブルサイズで4回の繰り返しが行われました.
- 水力伝導性,リチャージ,川の伝導性,井戸の流れ率を調整しました.
- 結果は,リスクベースの井戸捕獲ゾーンと水力伝導性フィールドを使用した"真実"モデルと比較されました.
主要な成果:
- 100〜250の完成のアンサンブルサイズは,一般的に良い結果をもたらしました.
- PEST++IESの2回の繰り返しは,ほとんどのシナリオでは十分であることが判明しました.
- より小さなアンサンブルサイズ (例えば10〜50) は性能が低下した.
- より大きなアンサンブルサイズ (例えば,500以上) は,最小限の追加改善を提供しました.
結論:
- 100〜250の実現と2つのイテレーションのアンサンブルサイズは,PEST++IESの効率的で効果的な構成を表します.
- この発見は地下水のモデリングにおける 計算リソースの最適化に役立ちます
- この研究は,PEST++IESの利用者向けに,履歴のマッチングと不確実性分析のための実践的なガイドラインを提供します.
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