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  1. NTU Theses and Dissertations Repository
  2. 生物資源暨農學院
  3. 農藝學系
請用此 Handle URI 來引用此文件: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/84326
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dc.contributor.advisor劉力瑜(Li-Yu Liu)
dc.contributor.authorTing-Zhen Huangen
dc.contributor.author黃亭禎zh_TW
dc.date.accessioned2023-03-19T22:08:37Z-
dc.date.copyright2022-07-07
dc.date.issued2022
dc.date.submitted2022-06-01
dc.identifier.citationBasak, J. K., Ali, M. A., Islam, M. N., & Rashid, M. A. (2010). Assessment of the effect of climate change on boro rice production in Bangladesh using DSSAT model. Journal of Civil Engineering, 38(2), 95-108. Bruinsma, J. (2009). The resource outlook to 2050: by how much do land, water and crop yields need to increase by 2050? Paper presented at Expert Meeting on How to Feed the World in 2050, Rome, Italy. Ewert, F., Rötter, R. P., Bindi, M., Webber, H., Trnka, M., Kersebaum, K. C., …Asseng, S. (2015). Crop modelling for integrated assessment of risk to food production from climate change. Environmental Modelling & Software, 72, 287-303. Jiang, Y., Zhang, L., Zhang, B., He, C., Jin, X., & Bai, X. (2016). Modeling irrigation management for water conservation by DSSAT-maize model in arid northwestern China. Agricultural Water Management, 177, 37-45. Jones, J. W., Hoogenboom, G., Porter, C. H., Boote, K. J., Batchelor, W. D., Hunt, L. A., …Ritchie, J.T. (2003). The DSSAT cropping system model. European Journal of Agronomy, 18(3-4), 235-265. Korres, N. E., Norsworthy, J. K., Burgos, N. R., & Oosterhuis, D.M. (2017). Temperature and drought impacts on rice production: An agronomic perspective regarding short- and long-term adaptation measures. Water Resources and Rural Development, 9, 12-27. Malik, W., & Dechmi, F. (2019). DSSAT modelling for best irrigation management practices assessment under Mediterranean conditions. Agricultural Water Management, 216, 27-43. Pandey, S., Bhandari, H., Ding, S., Prapertchob, P., Sharan, R., Naik, D., Taunk, S. K., & Sastri, A. (2007). Coping with drought in rice farming in Asia: insights from a cross-country comparative study. Agricultural Economics, 37(1), 213-224. Paola, A. D., Valentini R., & Santini M. (2016). An overview of available crop growth and yield models for studies and assessments in agriculture. Journal of the Science of Food and Agriculture, 102(6), 709-714. Rugira, P., Ma, J., Zheng, L., Wu, C., & Liu, E. (2021). Application of DSSAT CERES-Maize to Identify the Optimum Irrigation Management and Sowing Dates on Improving Maize Yield in Northern China. Agronomy, 11(4), 674. Rosegrant, M. W., Ringler, C., & Zhu, T. (2009). Water for Agriculture: Maintaining Food Security under Growing Scarcity. Annual Review of Environment and Resources, 34, 205-222. Thornton, P. K., Ericksen, P. J., Herrero, M., & Challinor, A. J. (2014). Climate variability and vulnerability to climate change: a review. Global Change Biology, 20(11), 3313-3328. Thorp, K. R., DeJonge, K. C., Kaleita, A. L., Batchelor, W. D., & Paz, J. O. (2008). Methodology for the use of DSSAT models for precision agriculture decision support. Computers and Electronics in Agriculture, 64(2), 276-285. Velasco-Muñoz, J. F., Aznar-Sánchez, J. A., Belmonte-Ureña, L. J., & Román-Sánchez, I. M. (2018). Sustainable Water Use in Agriculture: A Review of Worldwide Research. Sustainability, 10(4), 1084. Ventrella, D., Charfeddine, M., Giglio, L., & Castellini, M. (2012). Application of DSSAT models for an agronomic adaptation strategy under climate change in Southern of Italy: optimum sowing and transplanting time for winter durum wheat and tomato. Italian Journal of Agronomy, 7(1), 109-115. 行政院農業委員會 (2021)。110年3-5月高溫乾旱農業災情報告。取自: https://www.coa.gov.tw/theme_data.php?theme=news&sub_theme=agri&id=8415 行政院農業委員會農糧署 (2021)。稻米生產量調查報告稻民國110年第1期作。 呂奇峰、羅正宗 (2014)。節水栽培對水稻產量及品質之影響。臺南區農業改良場研究彙報(64),10-19。 林羿汝、邱儀婷、陳清田、李振誥 (2017)。灌溉管理操作對水稻生長期距及灌溉用水效能影響之研究。農業工程學報,63(2),35-48。 林國清 (2004)。水稻新品種台南11號之育成。台南區農業改良場研究彙報(45),1-25。 施愷哲 (2021)。DSSAT 模式結合網格化土壤資訊預測水稻產量之可行性評估。臺灣大學農藝學研究所學位論文。 姚銘輝、盧虎生、朱鈞、蔡金川 (2000)。DSSAT模式在預測水稻產量及氣候變遷衝擊評估之適用性探討。中華農業研究,49(4),16-28。 姚銘輝、鍾昀軒、徐永衡 (2015)。利用未來統計降尺度氣候資料評估臺灣水稻生產潛勢。作物、環境與生物資訊,12(3),142-154。 楊嘉凌、鄭佳綺、王柏蓉、吳以健 (2016)。臺灣多樣化的水稻品種及硬秈稻米生產現況。臺中區農業專訊(94),4-11。 臺灣氣候變遷推估資訊與調適知識平台,https://tccip.ncdr.nat.gov.tw/ 劉玫婷、李欣輯、徐永衡、陳永明 (2021)。2021年乾旱事件農作物損失調查紀實。國家災害防救科技中心災害防救電子報(194)。 劉麗飛 (1999)。缺水及鹽分對水稻生產之影響。環境與稻作生產,87-103。 羅秋雄、張金城 (2005)。作物施肥手冊。行政院農業委員會農糧署。
dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/84326-
dc.description.abstract近年來,隨著氣候變遷加劇,農業為首當其衝、受到影響的產業之一,尤其面臨乾旱逆境時,灌溉水的供給若出現問題,勢必會對糧食產量造成負面影響,除了調整栽種期、加強引水蓄水設施、研發耐旱品種等相關策略外,農民也須依賴更精準的災害預警系統,再加上動態性地調整田間栽培管理方式,在天然災害造成大規模損失前做出因應措施,盡可能降低生產損失。本研究使用DSSAT作物模式模擬水稻第1期作在不同灌溉情境下的生產情境,並將節水栽培所會造成的減產百分比繪製水稻生產之風險地圖,此模擬將結合2019年的歷史氣候重建資料、涵蓋全臺農用地之土壤檔和水稻品種臺農67號之作物基因參數。本研究所要模擬的灌溉情境有3種如下:首先分別針對「自動灌溉」和「無灌溉」2種情境進行模擬,透過比較各生育期所需之水量及風險程度,找出對於灌溉水最為敏感的生育期,接著模擬第3種情境-僅於缺水敏感期進行灌溉。為了探討節水栽培的可行性,本研究將全臺所有的試驗地分成了12個區域,接著透過成對t檢定將各小區在不同灌溉情境下的產量進行比較,研究結果發現中彰投、宜蘭、花東等地區若行節水栽培、僅在敏感期進行灌溉,的確可在不影響產量的前提下,達到節省用水量的成效,其省水量約為37.8%至76.4%。本研究結合程式語言及作物模式,進行更有效率之模擬並建立繪製風險地圖之系統性方法,未來若能將氣候預測資料結合校正過後的作物模式,相信能夠針對氣候變遷對產量造成的影響進行預測,以利決策者制定相關的調適策略。zh_TW
dc.description.abstractWith the intensification of climate change in recent year, agriculture is one of the industries that are most affected. Especially when suffering from drought stress, if there are problems of supplying irrigation water, it will have a negative impact on grain production. In addition to adjusting the planting period, strengthening water storage facilities and development of drought-tolerant varieties, farmers must also rely on a more accurate disaster warning system, coupled with dynamic adjustment of field management methods. Also, they need to take measures before the disasters cause large-scale losses, so as to minimize the loss of production. This study uses the DSSAT crop model to simulate the production of rice under different irrigation scenarios, and draws the risk map of rice production based on the percentage of yield reduction caused by saving water cultivation. The simulation will integrate Taiwan ReAnalysis Downscaling data of 2019, soil data of agricultural land, the crop genetic parameters of the rice variety Tainung 67. There are three kinds of irrigation scenarios to be simulated in this study as follows: First, simulate the two scenarios of 'automatic irrigation' and 'non-irrigation', and find out the growth stages that are sensitive to irrigation water by comparing the amount of water required and the degree of risk in each growth stage. And then simulate the third scenario – 'irrigation only during the water-scarcity-sensitive period'. In order to explore the feasibility of water-saving cultivation, this study divided all the experimental fields in Taiwan into 12 regions, and then compared the rice yield under different irrigation scenarios through paired t-test. The result shows that if take water-saving cultivation (that means only irrigate in sensitive growth stage) in central Taiwan and eastern Taiwan, it is possible to achieve the goal that saving water consumption without affecting the yield. The water saving rate is about 37.8% to 76.4%. This study combines programming language and crop models to conduct more efficient simulations and establish a systematic method for drawing risk maps. In the future, if we can combine predictive climate data with corrected crop models, it is believed that the we can forecast the impact of climate change on yield. Thus, decision makers can formulate relevant adaptation strategies to help reducing the production loss.en
dc.description.provenanceMade available in DSpace on 2023-03-19T22:08:37Z (GMT). No. of bitstreams: 1
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Previous issue date: 2022
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dc.description.tableofcontents口試委員審定書 i 謝辭 ii 摘要 iii Abstract iv 一、前言 1 1.1 水資源對農業的重要性 1 1.2 臺灣水稻生產 2 1.3 乾旱對水稻的影響及應變措施 2 1.4 DSSAT作物模式 3 1.5 研究流程 4 二、材料與方法 6 2.1 氣候資料 6 2.2 土壤資料 6 2.3 作物遺傳參數 7 2.4 試驗地的選擇及命名 8 2.5 模擬不同灌溉策略下的產量 8 2.5.1 DSSAT灌溉管理參數設置 9 2.5.2 產量地圖及風險地圖繪製 9 2.5.3 生育敏感期分析及生育敏感期灌溉 10 2.6 試驗檔其他參數設置 11 2.7 檢定各區域不同灌溉策略下的產量差異 12 三、結果 13 3.1 試驗地篩選結果及插秧日分布 13 3.2 生育敏感期分析結果 15 3.3 產量地圖及各區域產量模擬結果 18 3.4 風險地圖及各區域風險程度 22 3.5 灌溉水地圖及各區域灌溉水量 24 3.6 產量差異檢定 27 四、討論 30 4.1 DSSAT建構風險地圖 30 4.2 本研究可精進之方向 30 4.3 節水栽培之可行性 31 4.4 未來可應用之方向 32 五、結論 34 參考文獻 35 附錄 38 一、DSSAT模擬生育敏感期灌溉 38
dc.language.isozh-TW
dc.titleDSSAT模擬灌溉對臺灣水稻產量影響及風險地圖繪製zh_TW
dc.titleUsing DSSAT to Simulate the Impact of Irrigation Scenario on Rice Yield and Produce Risk Map in Taiwanen
dc.typeThesis
dc.date.schoolyear110-2
dc.description.degree碩士
dc.contributor.oralexamcommittee許少瑜(Shao-Yiu Hsu),楊志維(Zhi-Wei Yang)
dc.subject.keyword氣候變遷,風險地圖,DSSAT,作物模式,水稻產量,zh_TW
dc.subject.keywordClimate Change,Risk Maps,DSSAT,Crop Model,Rice Yield,en
dc.relation.page39
dc.identifier.doi10.6342/NTU202200842
dc.rights.note同意授權(限校園內公開)
dc.date.accepted2022-06-02
dc.contributor.author-college生物資源暨農學院zh_TW
dc.contributor.author-dept農藝學研究所zh_TW
dc.date.embargo-lift2024-07-01-
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