東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Assessing the impacts of climate cha...

Reinl, Kaitlin L.

FindBook

Google Book

Amazon

博客來

Assessing the impacts of climate change on the surface temperature of inland lakes in Michigan.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Assessing the impacts of climate change on the surface temperature of inland lakes in Michigan./
作者:	Reinl, Kaitlin L.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2016,
面頁冊數:	87 p.
附註:	Source: Masters Abstracts International, Volume: 55-05.
Contained By:	Masters Abstracts International55-05(E).
標題:	Limnology. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10120305
ISBN:	9781339814889

Assessing the impacts of climate change on the surface temperature of inland lakes in Michigan.
Reinl, Kaitlin L.

Assessing the impacts of climate change on the surface temperature of inland lakes in Michigan. - Ann Arbor : ProQuest Dissertations & Theses, 2016 - 87 p.

Source: Masters Abstracts International, Volume: 55-05.

Thesis (M.S.)--Michigan Technological University, 2016.

The aim of this study was to validate and apply a lake model for predicting the susceptibility of small inland lakes in Michigan to changes in thermal regime and increased cyanobacteria growth as a result of future climate conditions. The Freshwater Lake Model was selected, tested for sensitivity to various inputs, and validated through comparison to observed conditions. The sensitivity analysis showed that the lake model was most sensitive to solar radiation, air temperature, and air humidity. Comparison of predicted climate data with observed conditions revealed highly variable climate model error. The lake model validation was conducted using 10 lakes in Wisconsin with observed and modeled meteorological data from 1998 through 1999. The model was valid for predicting surface water temperature, but not for mean temperature, and modeling proceeded with only surface water temperature. The lake model validation resulted in over-prediction when using modeled climate data inputs, which is likely due to inaccuracy in the climate model.

ISBN: 9781339814889Subjects--Topical Terms:

545788
Limnology.

Assessing the impacts of climate change on the surface temperature of inland lakes in Michigan.
LDR:04378nmm a2200337 4500 001 2154272
005 20180330125240.5
008 190424s2016 ||||||||||||||||| ||eng d
020 $a 9781339814889
035 $a (MiAaPQ)AAI10120305
035 $a (MiAaPQ)michigantech:11090
035 $a AAI10120305
040 $a MiAaPQ $c MiAaPQ
100 1 $a Reinl, Kaitlin L. $3 3341998
245 1 0 $a Assessing the impacts of climate change on the surface temperature of inland lakes in Michigan.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2016
300 $a 87 p.
500 $a Source: Masters Abstracts International, Volume: 55-05.
500 $a Includes supplementary digital materials.
500 $a Adviser: Joseph Wagenbrenner.
502 $a Thesis (M.S.)--Michigan Technological University, 2016.
520 $a The aim of this study was to validate and apply a lake model for predicting the susceptibility of small inland lakes in Michigan to changes in thermal regime and increased cyanobacteria growth as a result of future climate conditions. The Freshwater Lake Model was selected, tested for sensitivity to various inputs, and validated through comparison to observed conditions. The sensitivity analysis showed that the lake model was most sensitive to solar radiation, air temperature, and air humidity. Comparison of predicted climate data with observed conditions revealed highly variable climate model error. The lake model validation was conducted using 10 lakes in Wisconsin with observed and modeled meteorological data from 1998 through 1999. The model was valid for predicting surface water temperature, but not for mean temperature, and modeling proceeded with only surface water temperature. The lake model validation resulted in over-prediction when using modeled climate data inputs, which is likely due to inaccuracy in the climate model.
520 $a The study area included 517 inland lakes in Michigan. These lakes were divided into 27 groups based on climate, size, and trophic state. Thirteen lake groups were modeled on a daily time step from 2020 to 2099 using prototype lakes and regionally downscaled, modeled climate data. The climate parameters forcing the lake model predictions were analyzed for long-term trends and differences across climates, lake size, and trophic state. The trends in surface water temperature for the entire period and each season from 2020 to 2099 were significant for all modeled lake groups, and lake model surface temperature predictions closely followed modeled air temperature. For all lake groups, the largest increases in surface temperature were observed in spring while the smallest increases occurred in winter. No statistical differences in long-term trends of surface temperature were found between any of the groups regardless of location, size, or trophic state. We analyzed the relationship between changes in periods of minimum and optimum algal growth conditions and climate, lake size, and trophic state. The largest increase in the period with surface temperature above minimum growth temperatures was predicted for small, oligotrophic lakes in the southern Lower Peninsula. This result can mainly be attributed to inherently warmer temperature earlier in the year in more southern latitude positions and the quicker response of small lakes to warming temperatures in comparison to larger lakes. The largest increase in the period with surface temperature above optimal growth temperatures was predicted for large, oligotrophic lakes in the Upper Peninsula. The predicted increase in the number of days the surface temperatures exceeded the optimum growing temperature in the colder Upper Peninsula was greater because of the relatively low number of days at the onset of the modeling period in comparison to lakes in more southern latitudes, and large lakes are able to uptake more heat for longer periods of time. The results of this study illustrated the future trends in surface water temperature and the potential implications for cyanobacteria growth, and can be used to develop plans to prevent and mitigate the spread of cyanobacteria as a result of climate change.
590 $a School code: 0129.
650 4 $a Limnology. $3 545788
650 4 $a Water resources management. $3 794747
650 4 $a Aquatic sciences. $3 3174300
690 $a 0793
690 $a 0595
690 $a 0792
710 2 $a Michigan Technological University. $b Forest Resources and Environmental Science. $3 3281640
773 0 $t Masters Abstracts International $g 55-05(E).
790 $a 0129
791 $a M.S.
792 $a 2016
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10120305