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      水門資料 品質管理에 따른 洪水豫測正確度의 影響 評價와 改善 = Evaluation and improvement of flood forecasting accuracy based on hydrological data quality control

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      https://www.riss.kr/link?id=T13542456

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      다국어 초록 (Multilingual Abstract) kakao i 다국어 번역

      This study examined the effect of the flood forecasting accuracy based on hydrological data quality control. Initially, several improvement methods suggested for the hydrological data quality based on the investigation of the status and problems of hydrological survey facilitation, data transmission and process. All of the rainfall and water level stations of the Han River were chosen and a 10-year data was collected to analyze the effect of the improvement methods. Each station data were analyzed, during the flood season, monthly and yearly. Consequently, hydrological data quality improved significantly after applying the suggested methods.
      Moreover, there is a direct correlation between estimation results of the basin or precipitation and data quality control of each rainfall station by analysis of quantitative traits. The Storage Function and FLDWAV model are applied to simulate the flood events which occurred in the Han River basin. The parameter calibration are minimized to evaluate the effect of hydrological data quality control. The case studies are divided before and after the establishment of hydrological data quality control improvement. This study carefully analyzes the forecasting results of rainfall data quality control between raw data and calibration data respectively. Furthermore, the accuracy of flood forecasting based on water level data quality control compares with upstream and downstream water level station.
      This research provides the ways of improving hydrological data quality control such as the installation of dual measurement and upgrading the transmission system. In addition, those contribute not only to the good quality of data production but also accuracy of model performance. Therefore, it is necessary to obtain a high quality of hydrological data for accurate flood forecasting result instead of concentrating on forecast model’s development and parameter calibration.
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      This study examined the effect of the flood forecasting accuracy based on hydrological data quality control. Initially, several improvement methods suggested for the hydrological data quality based on the investigation of the status and problems of ...

      This study examined the effect of the flood forecasting accuracy based on hydrological data quality control. Initially, several improvement methods suggested for the hydrological data quality based on the investigation of the status and problems of hydrological survey facilitation, data transmission and process. All of the rainfall and water level stations of the Han River were chosen and a 10-year data was collected to analyze the effect of the improvement methods. Each station data were analyzed, during the flood season, monthly and yearly. Consequently, hydrological data quality improved significantly after applying the suggested methods.
      Moreover, there is a direct correlation between estimation results of the basin or precipitation and data quality control of each rainfall station by analysis of quantitative traits. The Storage Function and FLDWAV model are applied to simulate the flood events which occurred in the Han River basin. The parameter calibration are minimized to evaluate the effect of hydrological data quality control. The case studies are divided before and after the establishment of hydrological data quality control improvement. This study carefully analyzes the forecasting results of rainfall data quality control between raw data and calibration data respectively. Furthermore, the accuracy of flood forecasting based on water level data quality control compares with upstream and downstream water level station.
      This research provides the ways of improving hydrological data quality control such as the installation of dual measurement and upgrading the transmission system. In addition, those contribute not only to the good quality of data production but also accuracy of model performance. Therefore, it is necessary to obtain a high quality of hydrological data for accurate flood forecasting result instead of concentrating on forecast model’s development and parameter calibration.

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      목차 (Table of Contents)

      • 제1장 서론 1
      • 1.1. 연구 배경 및 목적 1
      • 1.2. 연구동향 4
      • 1.2.1. 수문자료 품질관리 4
      • 1.2.2. 홍수예측 정확도 향상 6
      • 제1장 서론 1
      • 1.1. 연구 배경 및 목적 1
      • 1.2. 연구동향 4
      • 1.2.1. 수문자료 품질관리 4
      • 1.2.2. 홍수예측 정확도 향상 6
      • 1.3. 연구 범위 및 내용 8
      • 제2장 홍수예측을 위한 저류함수와 FLDWAV 모형 및 대상지점 현황 11
      • 2.1. 홍수예측을 위한 저류함수와 FLDWAV모형 11
      • 2.1.1. 유역 유출량 산정을 위한 저류함수법 14
      • 2.1.2. 하도 유출량 산정을 위한 저류함수법 18
      • 2.1.3. 하도홍수위 산정을 위한 FLDWAV 모형 21
      • 2.2. 한강수계 특성 및 대상지점 현황 26
      • 2.2.1 한강수계 특성 26
      • 2.2.2. 한강수계 수문관측소 및 홍수예보지점 현황 33
      • 2.2.3. 대상지점 및 기간 선정 37
      • 제3장 강우량 자료 품질관리에 따른 홍수예측 정확도의 영향 평가 및 개선 38
      • 3.1. 강우량 자료의 품질관리 분석 39
      • 3.1.1. 현장 품질관리 분석 39
      • 3.1.2. 자료 품질관리 분석 42
      • 3.2. 강우량 자료의 품질관리 개선방안 및 효과분석 44
      • 3.2.1. 현장 품질관리 개선방안 및 적용 44
      • 3.2.2. 자료 품질관리 개선방안 및 적용 46
      • 3.2.3. 강우량 자료 품질관리 개선 효과 분석 50
      • 3.3. 강우량 자료의 품질관리가 홍수예측 정확도에 미치는 영향 평가 71
      • 3.3.1. 지점강우량 품질관리가 유역평균강우량 산정에 미치는 영향 분석 71
      • 3.3.2. 강우량 자료의 품질관리에 따른 홍수예측 정확도 평가 79
      • 3.4. 결과 고찰 97
      • 제4장 수위 자료 품질관리에 따른 홍수예측 정확도 개선 100
      • 4.1. 수위 자료의 품질관리 분석 101
      • 4.1.1. 현장 품질관리 분석 101
      • 4.1.2. 자료 품질관리 분석 103
      • 4.2. 수위 자료의 품질관리 개선방안 및 효과분석 105
      • 4.2.1. 현장 품질관리 개선방안 및 적용 105
      • 4.2.2. 자료 품질관리 개선방안 및 적용 110
      • 4.2.3. 수위 자료 품질관리 개선 효과 분석 119
      • 4.3. 수위 자료의 품질관리에 따른 홍수예측 정확도 개선 분석 138
      • 4.4. 결과 고찰 151
      • 제5장 결론 153
      • 참고문헌 156
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