國立虎尾科技大學 |

Dynamics of Seasonal Crop Yield Prediction Under Weather and Climate Extremes.

紀錄類型:	書目-語言資料,手稿 : Monograph/item
正題名/作者:	Dynamics of Seasonal Crop Yield Prediction Under Weather and Climate Extremes./
作者:	Abhishek, Abhijeet.
面頁冊數:	1 online resource (184 pages)
附註:	Source: Dissertations Abstracts International, Volume: 85-06, Section: B.
Contained By:	Dissertations Abstracts International85-06B.
標題:	Agricultural engineering. -
電子資源:	click for full text (PQDT)
ISBN:	9798381171006

Dynamics of Seasonal Crop Yield Prediction Under Weather and Climate Extremes.
Abhishek, Abhijeet.

Dynamics of Seasonal Crop Yield Prediction Under Weather and Climate Extremes. - 1 online resource (184 pages)

Source: Dissertations Abstracts International, Volume: 85-06, Section: B.

Thesis (Ph.D.)--Michigan State University, 2023.

Includes bibliographical references

The challenges of predicting seasonal crop yields amidst fluctuating weather and climate extremes is a pressing concern, given the increasing unpredictability brought on by global climate shifts and their socio-economic implications. This research delves into the multifaceted dynamics surrounding this challenge, placing focus on the profound implications of droughts, especially in vulnerable regions like Cambodia. Droughts, characterized by extended periods of scant precipitation, have historically been disruptors of agricultural systems. Their ripple effects often cascade through economies, underpinning socio-economic upheavals that stretch beyond agricultural boundaries. In the study's initial phase, Cambodia's agricultural patterns from 2000 to 2016 were closely examined. The results were notable: despite the recurrent and debilitating droughts, rice yields consistently rose. This anomaly was traced back to shifts in agricultural practices, particularly the heightened application rates of chemical fertilizers post-2008. This finding is both encouraging and cautionary, hinting at adaptive resilience in the face of adversity but also flagging the potential environmental implications of intensified chemical usage. The research then transitioned to an evaluation of the efficacy of seasonal climate forecasts in predicting interannual crop yields. The inherent uncertainties of such forecasts, their potential pitfalls, and their pivotal importance were all evaluated. By integrating hydrologic models with probabilistic forecasts, a novel methodology was formulated, aiming to bridge the gulf between historical data sets and real-time climatic shifts. This approach was tested across Cambodia, offering a comparative perspective that enriched the research's findings. In regions heavily reliant on rainfed agricultural systems, the value of precise, timely forecasting cannot be overstated. The unpredictability of rainfall patterns, exacerbated by climate change, places immense strain on these systems, making accurate forecasting a backbone for effective agricultural planning. However, forecasting, no matter how advanced, is still beset with challenges. Additionally, the study revealed that among the myriad variables affecting crop yields, minimum air temperature and dry spells wielded the most significant impact, underscoring their critical role in agricultural yield dynamics. The subsequent phase of the research, therefore, ventured into data assimilation, exploring its potential in refining crop yield predictions. In essence, this comprehensive study not only sheds light on the intricate interplay between climate extremes and crop yield predictions but also charts a potential way forward. By blending traditional research methodologies with advanced technologies, it underscores the need for proactive, informed, and adaptable agricultural strategies. The findings from this research are expected to aid efforts aimed at achieving agricultural sustainability and bolstering food security in an era characterized by climatic uncertainties and evolving challenges.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2024

Mode of access: World Wide Web

ISBN: 9798381171006Subjects--Topical Terms:

1148660
Agricultural engineering.
Subjects--Index Terms:

Crop yieldsIndex Terms--Genre/Form:

554714
Electronic books.

Dynamics of Seasonal Crop Yield Prediction Under Weather and Climate Extremes.
LDR:04493ntm a2200409K 4500 001 1141654
005 20240318062708.5
006 m o d
007 cr mn ---uuuuu
008 250605s2023 xx obm 000 0 eng d
020 $a 9798381171006
035 $a (MiAaPQ)AAI30813853
035 $a AAI30813853
040 $a MiAaPQ $b eng $c MiAaPQ $d NTU
100 1 $a Abhishek, Abhijeet. $3 1465569
245 1 0 $a Dynamics of Seasonal Crop Yield Prediction Under Weather and Climate Extremes.
264 0 $c 2023
300 $a 1 online resource (184 pages)
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
500 $a Source: Dissertations Abstracts International, Volume: 85-06, Section: B.
500 $a Advisor: Phanikumar, Mantha S.
502 $a Thesis (Ph.D.)--Michigan State University, 2023.
504 $a Includes bibliographical references
520 $a The challenges of predicting seasonal crop yields amidst fluctuating weather and climate extremes is a pressing concern, given the increasing unpredictability brought on by global climate shifts and their socio-economic implications. This research delves into the multifaceted dynamics surrounding this challenge, placing focus on the profound implications of droughts, especially in vulnerable regions like Cambodia. Droughts, characterized by extended periods of scant precipitation, have historically been disruptors of agricultural systems. Their ripple effects often cascade through economies, underpinning socio-economic upheavals that stretch beyond agricultural boundaries. In the study's initial phase, Cambodia's agricultural patterns from 2000 to 2016 were closely examined. The results were notable: despite the recurrent and debilitating droughts, rice yields consistently rose. This anomaly was traced back to shifts in agricultural practices, particularly the heightened application rates of chemical fertilizers post-2008. This finding is both encouraging and cautionary, hinting at adaptive resilience in the face of adversity but also flagging the potential environmental implications of intensified chemical usage. The research then transitioned to an evaluation of the efficacy of seasonal climate forecasts in predicting interannual crop yields. The inherent uncertainties of such forecasts, their potential pitfalls, and their pivotal importance were all evaluated. By integrating hydrologic models with probabilistic forecasts, a novel methodology was formulated, aiming to bridge the gulf between historical data sets and real-time climatic shifts. This approach was tested across Cambodia, offering a comparative perspective that enriched the research's findings. In regions heavily reliant on rainfed agricultural systems, the value of precise, timely forecasting cannot be overstated. The unpredictability of rainfall patterns, exacerbated by climate change, places immense strain on these systems, making accurate forecasting a backbone for effective agricultural planning. However, forecasting, no matter how advanced, is still beset with challenges. Additionally, the study revealed that among the myriad variables affecting crop yields, minimum air temperature and dry spells wielded the most significant impact, underscoring their critical role in agricultural yield dynamics. The subsequent phase of the research, therefore, ventured into data assimilation, exploring its potential in refining crop yield predictions. In essence, this comprehensive study not only sheds light on the intricate interplay between climate extremes and crop yield predictions but also charts a potential way forward. By blending traditional research methodologies with advanced technologies, it underscores the need for proactive, informed, and adaptable agricultural strategies. The findings from this research are expected to aid efforts aimed at achieving agricultural sustainability and bolstering food security in an era characterized by climatic uncertainties and evolving challenges.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2024
538 $a Mode of access: World Wide Web
650 4 $a Agricultural engineering. $3 1148660
650 4 $a Environmental engineering. $3 557376
650 4 $a Water resources management. $3 1178858
653 $a Crop yields
653 $a Climate forecasts
653 $a Crop modeling
653 $a Droughts
653 $a Water resources
655 7 $a Electronic books. $2 local $3 554714
690 $a 0595
690 $a 0775
690 $a 0539
690 $a 0543
710 2 $a Michigan State University. $b Civil Engineering - Doctor of Philosophy. $3 1465368
710 2 $a ProQuest Information and Learning Co. $3 1178819
773 0 $t Dissertations Abstracts International $g 85-06B.
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30813853 $z click for full text (PQDT)