簡易檢索 / 詳目顯示

回結果列表
研究生： 阮氏邵
THAO, NGUYEN THI PHUONG
論文名稱： 應用乾旱嚴重-延時-頻率曲線評估氣候變遷下農業經濟衝擊
Assessment of agricultural economic impacts under climate change through drought Severity- Duration - Frequency curves
指導教授： 游保杉
Yu, Pao-Shan
學位類別： 碩士
Master
系所名稱： 工學院 - 水利及海洋工程學系
Department of Hydraulic & Ocean Engineering
論文出版年： 2019
畢業學年度： 107
語文別： 英文
論文頁數： 118
外文關鍵詞： Threshold level, Severity-duration-frequency (SDF) curves, AR4, GCMs, climate change, agriculture.
相關次數： 點閱：136  下載：6 
分享至:
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報

    • A drought is a natural disaster of not receiving rain or snow over a period of time, resulting in prolonged shortages in the water supply, whether atmospheric, surface water or groundwater. A quantitative estimate of the probability of occurrence and the predicted severity, duration of drought is important for the development of strategies in the water resources management. This study aims to develop a streamflow drought severity – duration- frequency (SDF) curves to estimate the long-term financial impact due to lack of certainties in climate change and agriculture projections. Severity was identified as the total water deficit volume to target threshold for a given drought duration. Furthermore, this study compared the SDF curves of two threshold level methods: fixed and monthly as well as evaluate the impacts of climate change on the SDF curves for the fixed threshold level. The scenarios climate is focused on AR4 (A2, AB1, B2) from the general climate model. Time series of the annual maxima values of duration and volume deficit indicated a similar trend of increasing and decreasing in different threshold level. The fixed threshold level is the 70th percentile value (Q70) of the flow duration curves (FDC) which is compiled using all available daily streamflow. The monthly threshold level in this study is the monthly varying Q70 values that was obtained from antecedent 12 months streamflow. SDF curves were prepared and fitting statistical distribution to each one.
    The approach continues with the impacts of climate change on the SDF curves for the fixed threshold level. Likewise, the methodology defines a water tariff price delimited by the drought duration and calculate the revenue loss scenarios in agriculture. As a case study, the approach is applied to the Kaoping River in Taiwan, the main water supply source for agriculture, industry but this study concentrates on the profit loss in agriculture. The results show that the SDF curves from the fixed threshold level increase value of the volume deficit than the monthly threshold level in each period. Drought deficit volume increasing rate was different in each class of duration–interval. Similarly, the SDF curves were varied under climate change, the duration and severities from GFDL_CM2_1 GCMs of each scenario is higher than baseline and increasing of duration resulted to the increased value of the volume deficit with a non–linear trend. Additionally, the severity-duration-frequency- profit loss under the historical data is resulted to estimate the baseline scenario of damage cost in the water utility company. In addition, the anticipated profit loss the long term would serve as the initial estimate for financial contingency plan or community contingency funds. In general, the development of SDF curves can be proposed as a planning tool to mitigating and real-time management of drought effects in water resource management.

    ABSTRACT I ACKNOWLEDGEMENTS III TABLE OF CONTENTS V LIST OF TABLE X LIST OF FIGURES XII CHAPTER ONE INTRODUCTION 1 1.1. Background 1 1.2. Research Questions 2 1.3. The aims of study 3 1.4 Outline of the Thesis 3 CHAPTER TWO LITERATURE REVIEW 5 2.1. Introduction 5 2.2. Historical drought in Taiwan 8 2.3. Threshold level method 10 2.2.1. The inter-event time method (IT-method) 14 2.2.2 Moving-average procedure (MA-procedure) 14 2.2.3. The sequent peak algorithm (SPA) 15 2.4. Frequency analysis 16 2.5. Climate Change scenarios 18 2.6. Summary 19 CHAPTER THREE STUDY AREA AND DEVELOPMENT OF DROUGHT SEVERITY – DURATION – FREQUENCY (SDF) CURVES 20 3.1. Description of study area 20 3.1.1. Study area 20 3.1.2. Data collection 22 3.2. Frequency analysis 23 3.2.1. The threshold level and drought characteristics 23 3.2.2 Calculations of the streamflow drought severity and duration 25 3.2.3 Determination of the Probability Distribution Functions 29 3.3. Development of SDF curves 31 3.4. Summary 33 CHAPTER FOUR THE IMPACT OF CLIMATE CHANGE ON THE SDF CURVE 34 4.1. The climate change scenarios 34 4.2. The threshold level method 36 4.3. Identifying of SDF curves 37 4.3.1. Calculating water deficit for time resolution 38 4.3.2. Determine of probability distribution function 40 4.3.3. Development of streamflow drought SDFs curves 41 4.4. Summary 45 CHAPTER FIVE AGRICULTURE IMPACTS OF DROUGHT UNDER CLIMATE CHANGE 46 5.1 Introduction 46 5.2. Water price and hydrological drought relationship 47 5.3. Severity – Duration – frequency – profit loss under climate change 49 5.3.1 SDF curves 50 5.3.2. Development of Severity-duration-frequency-economic loss curves 54 CHAPTER SIX CONCLUSIONS AND RECOMMENDATIONS 58 6.1. Conclusions 58 6.2. Recommendation 59 REFERENCE 61 APPENDICES 66 Appendix 1: Annual maximum deficit and duration for two threshold level 66 Appendix 2: Maximum deficit volume (million m3/s) for different duration of fixed threshold level 68 Appendix 3: Maximum deficit volume (million m3/s) for different duration of monthly threshold level 69 Appendix 4: Maximum deficit volume (million m3/s) for different duration of monthly threshold level - CSIRO_MK_5 projection – A1B scenario 71 Appendix 5: Maximum deficit volume (million m3/s) for different duration of monthly threshold level - GFDL_CM2_1 projection – A1B scenario 73 Appendix 6: Maximum deficit volume (million m3/s) for different duration of monthly threshold level - MICRO 3_2 projection – A1B scenario 74 Appendix 7: Maximum deficit volume (million m3/s) for different duration of monthly threshold level - MPI_ECHAM 5 projection – A1B scenario 76 Appendix 8: Maximum deficit volume (million m3/s) for different duration of monthly threshold level - MRI_CGCM2_3_2A projection – A1B scenario 77 Appendix 9: Maximum deficit volume (million m3/s) for different duration of monthly threshold level - CSIRO_MK_5 projection – A2 scenario 79 Appendix 10: Maximum deficit volume (million m3/s) for different duration of monthly threshold level - GFDL_CM2_1 projection – A2 scenario 80 Appendix 11: Maximum deficit volume (million m3/s) for different duration of monthly threshold level - MICRO 3_2 projection – A2 scenario 82 Appendix 12: Maximum deficit volume (million m3/s) for different duration of monthly threshold level - MPI_ECHAM 5 projection – A2 scenario 84 Appendix 13: Maximum deficit volume (million m3/s) for different duration of monthly threshold level - MRI_CGCM2_3_2A projection – A2 scenario 85 Appendix 14: Maximum deficit volume (million m3/s) for different duration of monthly threshold level - CSIRO_MK_5 projection – B1 scenario 87 Appendix 15: Maximum deficit volume (million m3/s) for different duration of monthly threshold level - GFDL_CM2_1 projection – B1 scenario 88 Appendix 16: Maximum deficit volume (million m3/s) for different duration of monthly threshold level - MICRO 3_2 projection – B1 scenario 90 Appendix 17: Maximum deficit volume (million m3/s) for different duration of monthly threshold level - MPI_ECHAM 5 projection – B1 scenario 92 Appendix 18: Maximum deficit volume (million m3/s) for different duration of monthly threshold level - MRI_CGCM2_3_2A projection – B1 scenario 93 Appendix 19: Maximum deficit volume (million m3/s) for different duration of monthly threshold level (agriculture use) - CSIRO_MK_5 projection – A1B scenario 95 Appendix 20: Maximum deficit volume (million m3/s) for different duration of monthly threshold level (agriculture use) - GFDL_CM2_1 projection – A1B scenario 96 Appendix 21: Maximum deficit volume (million m3/s) for different duration of monthly threshold level (agriculture use) - MICRO 3_2 projection – A1B scenario 98 Appendix 22: Maximum deficit volume (million m3/s) for different duration of monthly threshold level (agriculture use) - MPI_ECHAM 5 projection – A1B scenario 99 Appendix 23: Maximum deficit volume (million m3/s) for different duration of monthly threshold level (agriculture use) - MRI_CGCM2_3_2A projection – A1B scenario 101 Appendix 24: Maximum deficit volume (million m3/s) for different duration of monthly threshold level (agriculture use) - CSIRO_MK_5 projection – A2 103 Appendix 25: Maximum deficit volume (million m3/s) for different duration of monthly threshold level (agriculture use) - GFDL_CM2_1 projection – A2 scenario 104 Appendix 26: Maximum deficit volume (million m3/s) for different duration of monthly threshold level (agriculture use) - MICRO 3_2 projection – A2 scenario 106 Appendix 27: Maximum deficit volume (million m3/s) for different duration of monthly threshold level (agriculture use) - MPI_ECHAM 5 projection – A2 scenario 107 Appendix 28: Maximum deficit volume (million m3/s) for different duration of monthly threshold level (agriculture use) - MRI_CGCM2_3_2A projection – A2 scenario 109 Appendix 29: Maximum deficit volume (million m3/s) for different duration of monthly threshold level (agriculture use) - CSIRO_MK_5 projection – B1 scenario 111 Appendix 30: Maximum deficit volume (million m3/s) for different duration of monthly threshold level (agriculture use)- GFDL_CM2_1 projection – B1 scenario 112 Appendix 31: Maximum deficit volume (million m3/s) for different duration of monthly threshold level (agriculture use)- MICRO 3_2 projection – B1 scenario 114 Appendix 32: Maximum deficit volume (million m3/s) for different duration of monthly threshold level (agriculture use) - MPI_ECHAM 5 projection – B1 scenario 115 Appendix 33: Maximum deficit volume (million m3/s) for different duration of monthly threshold level (agriculture use) - MRI_CGCM2_3_2A projection – B1 scenario 117

    Agresti, A. (1990). Categorical data analysis. John Wiley & Sons, New York, USA.
    Akhtari, R., Bandarabadi, S. R. and Saghafian, B. (2008). Spatio-temporal pattern of drought in Northeast of Iran. International Conference on Drought management: Scientific and technological innovations, Zaragoza,Spain. 80: 71-77.
    Alexander, L. V., Tapper, N., Zhang, X., Fowler, H. J., Tebaldi, C. and Lynch, A. (2009). "Climate extremes: progress and future directions." International Journal of Climatology 29(3): 317-319.
    Allen, R. G., Pereira, L. S., Raes, D. and Smith, M. (1998) "Crop evapotranspiration: Guidelines for computing crop water requirements." FAO Irrigation and Drainage Paper No. 56. Online at: http://www.fao.org/docrep/X0490E/X0490E00.htm
    Chow, V., Maidment, D. and Mays, L. (1988). Applied Hydrology. Mc Graw Hill Book Company, New York.
    Dalezios, N. R., Loukas, A., Vasiliades, L. and Liakopoulos, E. (2001). "Severity-duration frequency analysis of droughts and wet periods in Greece." Hydrol. Sci. J. 45(5): 751-768
    Dogan, S., Berktay, A. and Singh, V. P. (2012). "Comparison of multi-monthly rainfall-based drought severity indices, with application to semi-arid Konya closed basin, Turkey." Journal of Hydrology 470–471(0): 255-268.
    Intergovernmental Panel on Climate Change (IPCC) (2007). Climate change 2007: Synthesis report. Valencia, Spain
    American Meteorological Society: Meteorological drought – Policy statement, B. Am. Meteorol. Soc., 78, 847–849, 1997.
    Bonaccorso, B., Cancelliere, A., and Rossi, G.: An analytical formulation of return period of drought severity, Stoch. Environ. Res. Risk A., 17, 157–174, 2003.
    Byun, H.-R. and Wilhite, D. A.: Objective quantification of drought severity and duration, J. Climate, 12, 747–756, 1999.
    Chowdhury, J. U., Stedinger, J. R., and Lu, L.-H.: Goodness-of-fit tests for regional generalized extreme value flood distributions, Water Resour. Res., 27, 1765–1776, 1991. Dalezios, N., Loukas, A., Vasiliades, L., and Liakopolos, E.:
    Severity-duration-frequency analysis of droughts and wet periods in Greece, Hydrolog. Sci. J., 45, 751–769, 2000.
    De Michele, C., Salvadori, G., Vezzoli, R., and Pecora, S.: Multivariate assessment of droughts: Frequency analysis and dynamic return period, Water Resour. Res., 49, 6985–6994, 2013.
    Dracup, J. A., Lee, K. S., and Paulson Jr., E. G.: On the statistical characteristics of drought events, Water Resour. Res., 16, 289– 296, 1980.
    Fleig, A. K., Tallaksen, L. M., Hisdal, H., and Demuth, S.: A global evaluation of streamflow drought characteristics, Hydrol. Earth Syst. Sci., 10, 535–552, doi:10.5194/hess-10-535-2006, 2006.
    González, J. and Valdés, J. B.: Bivariate drought recurrence analysis using tree ring reconstructions, J. Hydrol. Eng., 8, 247–258, 2003.
    Heim Jr., R. R.: A review of twentieth-century drought indices used in the United States, B. Am. Meteorol. Soc., 83, 1149–1165, 2002.
    Hisdal, H. and Tallaksen, L. M.: Estimation of regional meteorological and hydrological drought characteristics: A case study for Denmark, J. Hydrol., 281, 230–247, 2003.
    Hisdal, H., Tallaksen, L. M., Clausen, B., and Alan, E. P.: Ch. 5 Hydrological drought characteristics, in: Hydrological Droughts:
    Processes and Estimation Methods for Streamflow and Groundwater, Developments in Water Science, Elsevier, Amsterdam, 139–198, 2004.
    Hosking, J. R. M.: L-moments: Analysis and estimation of distributions using linear combinations of order statistics, J. Roy. Stat. Soc. Ser. B, 52, 105–124, 1990.
    Hosking, J. R. M. and Wallis, J. R.: Regional Frequency Analysis: An Approach Based on L-Moments, Cambridge Univ. Press, New York, 1997.
    Kjeldsen, T. R., Lundorf, A., and Dan, R.: Use of two component exponential distribution in partial duration modeling of hydrological droughts in Zimbabwean rivers, Hydrolog. Sci. J., 45, 285–298, 2000.
    McKee, T. B., Doesken, N. J., and Kleist, J.: The relationship of drought frequency and duration to time scales, Proc. 8th Conf. Appl. Climatol., American Meteor. Soc., Boston, 179–184, 1993.
    Mishra, A. K. and Singh, V. P.: Analysis of drought severity.area.frequency curves using a general circulation model and scenario uncertainty, J. Geophys. Res., 114, D06120, doi:10.1029/2008JD010986, 2009.
    Nalbantis, I. and Tsakiris, G.: Assessment of hydrological drought revisited, Water Resour. Manage., 23, 881–897, 2009.
    https://english.water.gov.taipei/cp.aspx?n=315869EEDF0D4401
    Yu, P.-S., Yang, T.-C., Kuo, C.-M., Tseng, H.-W., & Chen, S.-T. (2014). Climate change impacts on streamflow drought: a case study in Tseng-Wen reservoir catchment in southern Taiwan. Climate, 3(1), 42-62.
    Tabari, H., Nikbakht, J., and Talaee, P. H.: Hydrological drought assessment in Northwestern Iran based on streamflow drought index (SDI), Water Resour. Manage., 27, 137–151, 2013.
    Tallaksen, L. M. and van Lanen, H. A. J.: Hydrological drought: and estimation methods for streamflow and groundwater, Developments in Water Science, Elsevier Science B. V., Amsterdam, 2004.
    Tallaksen, L. M., Madsen, H., and Clusen, B.: On the definition and modeling of streamflow drought duration and deficit volume, Hydrolog. Sci. J., 42, 15–33, 1997.
    Tallaksen, L. M., Hisdal, H., and van Lanen, H. A. J.: Space-time modelling of catchment scale drought characteristics, J. Hydrol., 375, 363–372, 2009.
    Razmkhah H (2016a) Comparing performance of different loss methods in rainfall-runoff modeling. Water Resour 43(1):207–224
    Razmkhah H (2016b) Preparing stream flow drought severity-duration-frequency curves using threshold level method. Arab J Geosci 9(7):513
    Sung JH, Chung E-S (2014) Development of stream flow drought severity-duration-frequency curves using the threshold level method. Hydrol Earth Syst Sci 18:3341–3351
    Asadieh, B., Krakauer, N.Y., 2017. Global change in flood and drought intensities under climate change in the 21st century. Hydrol. Earth Syst. Sci. 1–22.
    Jeo-Heon Lee, Chang Joo Kim (2013). Amultimodel Assessment of the Climated Change Effect on the Drought Severity – Duration – Frequency ralationship. Hydrol. Processes, doi: 10.1002/hyp.9390
    Diego A. Guzman, Guilherme S. Mohor, Denise Taffarello and Eduardo M.Mendiondo (2018), Economic impacts of drought risks for water utilities through Severity-Duration-Frequency assessment under climate change scenario (disscuss paper) Hydrol. Processes
    Elain Barrow & GeYu 2005. A Report Prepared for the Prairie Adaptation Research Collaborative (PARC) in co-operation with Alberta Environment
    Climate change in Taiwan: Scientific report 2011 (summary) https://tccip.ncdr.nat.gov.tw/v2/upload/book_en/20150907164600.pdf
    Huang-Hsiung Hsu, Cheng- Ta- Chen, 2002. Observed and projected climate change in taiwan. Meteorology and Atmospheric Physics. DOI: 10.1007/s703-002 8230-x
    Shien-Tsung Chen, Chun- Chao Kuo, Pao-Shan Yu (2009). Historical trends and variability of meteorological droughts in Taiwan. Hydrological Sciences Journal, 54:3, 430-441, DOI: 10.1623/hysj.54.3.430

    下載圖示 校內：立即公開
    校外：立即公開
    QR CODE