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  1. 50 大学院生物資源学研究科・生物資源学部
  2. 50D 学位論文
  3. 修士論文
  4. 2018年度

Hydrological Modelling for the Conservation of the Niger Inner Delta in Mali

http://hdl.handle.net/10076/00018552
http://hdl.handle.net/10076/00018552
cefc02b3-225a-4fed-864a-157a95c53263
名前 / ファイル ライセンス アクション
2018MB0040.pdf 2018MB0040.pdf (2.6 MB)
Item type 学位論文 / Thesis or Dissertation(1)
公開日 2019-11-06
タイトル
タイトル Hydrological Modelling for the Conservation of the Niger Inner Delta in Mali
言語 en
言語
言語 eng
資源タイプ
資源タイプ識別子 http://purl.org/coar/resource_type/c_46ec
資源タイプ thesis
著者 KASSAMBARA, BARRY

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en KASSAMBARA, BARRY

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著者(ヨミ)
識別子Scheme WEKO
識別子 41832
姓名 カッサンバラ, バリ
言語 ja
抄録
内容記述タイプ Abstract
内容記述 The Niger Inner Delta (NID), a wetland that was selected as an International Important Wetland under the Ramsar Convention (on February 1st, 2004) still can be considered a hotspot of biodiversity in the Sahel. The Niger River as the main source of water for the NID is also used for urban life and irrigation. Therefore, the sustainable use of water to ensure the environmental flow in the NID is under discussion. Owing to climate change and population increase over the past three decades with a very large expansion of irrigated land upstream, the inhabitants have witnessed that their ecosystem is under threat (Cisse, 2009), and a significant reduction of its resources has occurred.
The main objective of this study is to develop different models to forecast efficiently the water-level in the Niger Inner Delta, based on the climate condition and the changing river flow.
We evaluate the performance of different models established with empirical (Artificial Neural Network and Regressions) or Conceptual Variable Source Area (Water Balance Method WBM) approaches. The results of evaluation and validation based on determination coefficient (R2), Root Mean Squared Error (RMSE) and Nash-Sutcliffe Efficiency (NSE) show that all the models have good results however the Lavenberg-Marqardt Artificial Neural Network (ANN) with 15 hidden layers has the best fitting for the validation and the Bayesian Regularization ANN with 80 in testing periods.
Therefore, although the WBM using Variable Source Area concept doesn’t fit as well as the other models, it has the merit to estimate and forecast the wet area surrounding the water body of the delta and the monthly outflow (Qout) from the NID.
内容記述
内容記述タイプ Other
内容記述 GRADUATE SCHOOL OF BIORESOURCES, MIE UNIVERSITY
内容記述
内容記述タイプ Other
内容記述 110p
書誌情報
発行日 2019-03
フォーマット
内容記述タイプ Other
内容記述 application/pdf
著者版フラグ
出版タイプ VoR
出版タイプResource http://purl.org/coar/version/c_970fb48d4fbd8a85
その他の言語のタイトル
その他のタイトル マリ国ニジェールインナーデルタ保全のための水文モデリング
言語 ja
出版者
出版者 三重大学
出版者(ヨミ)
値 ミエダイガク
修士論文指導教員
寄与者識別子Scheme WEKO
寄与者識別子 41833
姓名 加治佐, 隆光
言語 ja
資源タイプ(三重大)
値 Master's Thesis / 修士論文
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