Yilan River Flood Flow Persistent Analysis
碩士 === 國立臺灣大學 === 生物環境系統工程學研究所 === 105 === Flood forecasting is an essential issue in hydrological studies. In the literature, many flood forecasting models were shown to perform well. However, it has also been recognized that, due to flood flow persistence, even simple models could also achieve goo...
Main Authors: | , |
---|---|
Other Authors: | |
Format: | Others |
Language: | zh-TW |
Published: |
2017
|
Online Access: | http://ndltd.ncl.edu.tw/handle/cgmx54 |
id |
ndltd-TW-105NTU05404019 |
---|---|
record_format |
oai_dc |
spelling |
ndltd-TW-105NTU054040192019-05-15T23:39:39Z http://ndltd.ncl.edu.tw/handle/cgmx54 Yilan River Flood Flow Persistent Analysis 宜蘭河洪水流量持續性分析 Guang-Ying Shih 石廣英 碩士 國立臺灣大學 生物環境系統工程學研究所 105 Flood forecasting is an essential issue in hydrological studies. In the literature, many flood forecasting models were shown to perform well. However, it has also been recognized that, due to flood flow persistence, even simple models could also achieve good performance. In this study, two model performance criteria, namely the coefficient of efficiency (CE) and coefficient of persistence (CP) were used to evaluate performance of flood forecasting models. Flood flow data at three stations in the Yilan River Basin were represented by autoregressive (AR) models. An asymptotic theoretical relationship between CE and CP, which is dependent on the lag-k autocorrelation coefficient, was derived and used to demonstrate why the simple naïve forecasting model could achieve good performance, in certain cases, even outperform more complicated models. 鄭克聲 2017 學位論文 ; thesis 44 zh-TW |
collection |
NDLTD |
language |
zh-TW |
format |
Others
|
sources |
NDLTD |
description |
碩士 === 國立臺灣大學 === 生物環境系統工程學研究所 === 105 === Flood forecasting is an essential issue in hydrological studies. In the literature, many flood forecasting models were shown to perform well. However, it has also been recognized that, due to flood flow persistence, even simple models could also achieve good performance. In this study, two model performance criteria, namely the coefficient of efficiency (CE) and coefficient of persistence (CP) were used to evaluate performance of flood forecasting models. Flood flow data at three stations in the Yilan River Basin were represented by autoregressive (AR) models. An asymptotic theoretical relationship between CE and CP, which is dependent on the lag-k autocorrelation coefficient, was derived and used to demonstrate why the simple naïve forecasting model could achieve good performance, in certain cases, even outperform more complicated models.
|
author2 |
鄭克聲 |
author_facet |
鄭克聲 Guang-Ying Shih 石廣英 |
author |
Guang-Ying Shih 石廣英 |
spellingShingle |
Guang-Ying Shih 石廣英 Yilan River Flood Flow Persistent Analysis |
author_sort |
Guang-Ying Shih |
title |
Yilan River Flood Flow Persistent Analysis |
title_short |
Yilan River Flood Flow Persistent Analysis |
title_full |
Yilan River Flood Flow Persistent Analysis |
title_fullStr |
Yilan River Flood Flow Persistent Analysis |
title_full_unstemmed |
Yilan River Flood Flow Persistent Analysis |
title_sort |
yilan river flood flow persistent analysis |
publishDate |
2017 |
url |
http://ndltd.ncl.edu.tw/handle/cgmx54 |
work_keys_str_mv |
AT guangyingshih yilanriverfloodflowpersistentanalysis AT shíguǎngyīng yilanriverfloodflowpersistentanalysis AT guangyingshih yílánhéhóngshuǐliúliàngchíxùxìngfēnxī AT shíguǎngyīng yílánhéhóngshuǐliúliàngchíxùxìngfēnxī |
_version_ |
1719151791889711104 |