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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
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dc.contributor.advisor | 鄭克聲(Ke-Sheng Cheng) | |
dc.contributor.author | Teng-Wei Lin | en |
dc.contributor.author | 林登瑋 | zh_TW |
dc.date.accessioned | 2021-06-16T03:56:51Z | - |
dc.date.available | 2021-08-01 | |
dc.date.copyright | 2020-08-06 | |
dc.date.issued | 2020 | |
dc.date.submitted | 2020-07-30 | |
dc.identifier.citation | Cinlar, E. (1975). Introduction to Stochastic Processes. NJ:Prentice-Hall: Englewood Cliffs. Genz, A., Bretz, F. (2009). Computation of Multivariate Normal and t Probabilities, series Lecture Notes in Statistics. Heidelberg: Springer-Verlag. Genz, A., Bretz, F., Miwa, T., Mi, X., Leisch, F., Scheipl, F., Hothorn, T. (2020). mvtnorm: Multivariate Normal and t Distributions. Retrieved from R package version 1.1-1: https://CRAN.R-project.org/package=mvtnorm Hao, Z., Hao, F., Singh, V. P. (2016, May 11). A general framework for multivariate multi-index drought prediction based on Multivariate Ensemble Streamflow Prediction (MESP). Journal of Hydrology, pp. 1-10. Hao, Z., Hong, Y., Xia, Y., Singh, V. P., Hao, F., Cheng, H. (2016, February 17). Probabilistic drought characterization in the categorical form using ordinal regression. Journal of Hydrology, pp. 331-339. Hsieh, H.-I., Su, M.-D., Cheng, K.-S. (2014, April). Multisite Spatiotemporal Streamflow Simulation - With an Application to Irrigation Water Shortage Risk Assessment. Terrestrial, Atmospheric and Oceanic Sciences, pp. 255-266. Hsieh, H.‐I., Su, M.‐D., Wu, Y.‐C., Cheng, K.‐S. (2016). Water shortage risk assessment using spatiotemporal flow simulation. Geoscience Letters. Kavianpour, M., Seyedabadi, M., Moazami, S. (2018, November 21). Spatial and temporal analysis of drought based on a combined index using copula. Environmental Earth Sciences. Khadr, M. (2015, December 10). Forecasting of meteorological drought using Hidden Markov Model (case study: The upper Blue Nile river basin, Ethiopia). Ain Shams Engineering Journal, pp. 47-56. Matheron, G. (1963). Principles of geostatistics. Economic Geology, pp. 1246–1266. McKee, T., Doesken, N., Kleist, J. (1993, January). The relationship of drought frequency and duration to time scale. In: Proceedings of the Eighth Conference on Applied Climatology, Anaheim, California. American Meteorological Society, pp. 179-184. Mishra, A. K., Singh, V. P. (2011, April). Drought modeling – A review. Journal of Hydrology, pp. 157-175. Mlenga, D. H., Jordaan, A. J. (2019, Octorber 24). Monitoring droughts in Eswatini: A spatiotemporal variability analysis using the Standard Precipitation Index. Journal of Disaster Risk Studies. Moreira, E., Russo, A., Trigo, R. M. (2018, January 12). Monthly Prediction of Drought Classes Using Log-Linear Models under the Influence of NAO for Early-Warning of Drought and Water Management . Water. Ndehedehe, C. E., Agutu, N. O., Okwuashi, O., Ferreira, V. G. (2016, June 4). Spatio-temporal variability of droughts and terrestrial water storage over Lake Chad Basin using independent component analysis. Journal of Hydrology, pp. 106-128. Palmer, W. C. (1965, February). Meteorological Drought. U.S. department of commerce Weather Bureau, research paper no. 45. Paulo, A. A., Pereira, L. S. (2007, January 6). Prediction of SPI Drought Class Transitions Using Markov Chains. Water Resour Manage, pp. 1813–1827. Paulo, A. A., Ferreira, E., Coelho, C., Pereira, L. S. (2005, March 28). Drought class transition analysis through Markov and Loglinear models, an approach to early warning. Agricultural Water Management, pp. 59-81. Rahmat, S. N., Jayasuriya, N., Bhuiyan, M. A. (2016, April 6). Short-term droughts forecast using Markov chain model in Victoria, Australia. Theoretical and Applied Climatology, pp. 445–457. Rao, A., Hamed, K. (2002). Flood Frequency Analysis. New York: CRC Publications. Richard, R., Heim, J. (2002, August). A review of Twentieth- Century Drought Indices Used in the United States. American Meteorological Society, pp. 1149-1165. Ripley, B. (1987). Stochastic Simulation. New York: Wiley. Svoboda, M., Hayes, M., Wood, D. (2012). Standardized Precipitation Index User Guide. World Meteorological Organization. Vicente-Serrano, S. M., Begueri'a, S., Lo ́pez-moreno, J. I. (2009, October 6). A Multiscalar Drought Index Sensitive to Global Warming: The Standardized Precipitation Evapotranspiration Index. Journal of Climate, pp. 1696-1781. 朱容練, 黃柏誠, 吳宜昭, 陳淡容, 林欣弘, 林冠伶, 于宜強. (2018). 2018年台灣乾旱事件分析. 107年天氣分析與預報研討會. 國家災害防救科技中心. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/55328 | - |
dc.description.abstract | 在台灣,由於人口密度高、水庫面積小,以及降雨分布不均等問題,乾旱仍是棘手的議題。為了確保供水無虞,需持續監測乾旱的情形並於水資源管理進行調整。標準化降雨指標(Standardized Precipitation Index; SPI)已被廣泛用於描述與監測乾旱事件,然而,由於SPI固定的記憶長度,使得乾旱可能太晚被偵測、或太早被判定結束。本研究基於原有SPI的架構,發展出變動尺度SPI,令乾旱事件的選取能與事實相符。此外,亦從SPI建構馬可夫模型(Markov model),以評估乾旱持續的可能性。為了建構馬可夫模型,歷史雨量資料過小的樣本量需要被擴大,增加的樣本量仍須保持與歷史資料相同的統計特性。因此,將以半變異元(Semi-variogram)建立時間、空間的相關性,再依此相關性以序率模擬產生大量樣本。上述方法將以歷史乾旱事件進行驗證,並提供未來乾旱監測上的建議,政府單位亦可依此研究結果於水資源管理制定相應之措施。 | zh_TW |
dc.description.abstract | Because of the high population density, small area of reservoirs, and uneven precipitation, drought remains a serious issue in Taiwan. To ensure uninterrupted water supply, the drought situation should be monitored all year round, and adjustments should be made to water management measures. The Standardized Precipitation Index (SPI) has been commonly applied to monitor and describe the process of drought events. However, the SPI may delay detecting or prematurely end a drought event owing to its constant memory. Therefore, based on the original SPI structure, a variable-scale SPI is proposed in this study to capture drought events that corresponds to reality. In addition, a Markov model is developed based on the SPI to evaluate the possibility of drought continuation. To construct the Markov model, a small sample of historical rainfall data should be expanded into a large sample while maintaining the same statistical characteristics. Thus, a semivariogram was applied to build spatial and temporal correlations. From these correlations, several simulated samples were generated through stochastic simulation. These methods were examined using several past drought events, and suggestions about drought monitoring are provided. The government or policymakers can apply these results to water management procedures. | en |
dc.description.provenance | Made available in DSpace on 2021-06-16T03:56:51Z (GMT). No. of bitstreams: 1 U0001-3007202014492300.pdf: 5244934 bytes, checksum: 5c5bd989ec9b1b928941e3c37f97368e (MD5) Previous issue date: 2020 | en |
dc.description.tableofcontents | Abstract i 摘要 ii List of Figures iv List of Tables vi Introduction 1 Precipitation Data 8 Standardized Precipitation Index 10 Stochastic Simulation 15 Regional Analysis 44 Variable-scale Standardized Precipitation Index 45 Fixed-scale Standardized Precipitation Index 49 Discrete Time Markov Train 51 Result and Discussion 56 Conclusion 66 Reference 69 Appendix 72 | |
dc.language.iso | en | |
dc.title | 變動尺度標準化降雨指標及降雨量序率模擬於乾旱監測與早期預警之應用 | zh_TW |
dc.title | Drought Monitoring and Early Warning Using Variable-Scale Standardized Precipitation Index and Stochastic Rainfall Simulation | en |
dc.type | Thesis | |
dc.date.schoolyear | 108-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 溫在弘(Tzai-Hung Wen),黃文政(Wen-Cheng Huang),葉惠中(Hui-Chung Yeh),王藝峰(Yi-Feng Wang) | |
dc.subject.keyword | 標準化降雨指標,變動尺度標準化降雨指標,馬可夫模型,序率模擬,半變異元, | zh_TW |
dc.subject.keyword | Standardized Precipitation Index,Variable-scale SPI,Markov model,Stochastic simulation,Semivariogram, | en |
dc.relation.page | 80 | |
dc.identifier.doi | 10.6342/NTU202002104 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2020-07-31 | |
dc.contributor.author-college | 生物資源暨農學院 | zh_TW |
dc.contributor.author-dept | 生物環境系統工程學研究所 | zh_TW |
顯示於系所單位: | 生物環境系統工程學系 |
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