東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Characterizing ecologically relevant...

Chinnayakanahalli, Kiran J.

Linked to FindBook

Google Book

Amazon

博客來

Characterizing ecologically relevant variations in streamflow regimes.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Characterizing ecologically relevant variations in streamflow regimes./
Author:	Chinnayakanahalli, Kiran J.
Description:	226 p.
Notes:	Source: Dissertation Abstracts International, Volume: 71-04, Section: B, page: 2563.
Contained By:	Dissertation Abstracts International71-04B.
Subject:	Biology, Ecology. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3397138
ISBN:	9781109680010

Characterizing ecologically relevant variations in streamflow regimes.
Chinnayakanahalli, Kiran J.

Characterizing ecologically relevant variations in streamflow regimes. - 226 p.

Source: Dissertation Abstracts International, Volume: 71-04, Section: B, page: 2563.

Thesis (Ph.D.)--Utah State University, 2010.

Maintaining the ecological health of streams is vital for sustainable water resources management. Streamflow is a primary factor influencing the structure and function of ecological communities. A quantitative understanding of how stream biota respond to variation in streamflow is required for stream bioassessment. This dissertation focuses on quantifying relationships between streamflow regime and stream macroinvertebrate richness and composition. The contribution comprises statistical models that predict stream macroinvertebrate class from streamflow regime and predict streamflow regime from watershed attributes, and a tool that helps derive watershed attribute variables used in these models.

ISBN: 9781109680010Subjects--Topical Terms:

1017726
Biology, Ecology.

Characterizing ecologically relevant variations in streamflow regimes.
LDR:03549nam 2200373 4500 001 1396380
005 20110603092115.5
008 130515s2010 ||||||||||||||||| ||eng d
020 $a 9781109680010
035 $a (UMI)AAI3397138
035 $a AAI3397138
040 $a UMI $c UMI
100 1 $a Chinnayakanahalli, Kiran J. $3 1675164
245 1 0 $a Characterizing ecologically relevant variations in streamflow regimes.
300 $a 226 p.
500 $a Source: Dissertation Abstracts International, Volume: 71-04, Section: B, page: 2563.
500 $a Adviser: David G. Tarboton.
502 $a Thesis (Ph.D.)--Utah State University, 2010.
520 $a Maintaining the ecological health of streams is vital for sustainable water resources management. Streamflow is a primary factor influencing the structure and function of ecological communities. A quantitative understanding of how stream biota respond to variation in streamflow is required for stream bioassessment. This dissertation focuses on quantifying relationships between streamflow regime and stream macroinvertebrate richness and composition. The contribution comprises statistical models that predict stream macroinvertebrate class from streamflow regime and predict streamflow regime from watershed attributes, and a tool that helps derive watershed attribute variables used in these models.
520 $a The dissertation is a collection of three papers. In the first paper 12 variables were used to represent streamflow regime at 543 sites in the western US. Principal component analysis (PCA) and K-means clustering were used to obtain statistically independent factors and streamflow regime classes. We examined the relationship between these characterizations of streamflow and macroinvertebrate richness and composition at 63 of the 543 sites where there was also biological data. This analysis identified specific aspects of the streamflow regime that were useful in predicting macroinvertebrate richness and composition and that have potential application in classification-based bioassessment and management.
520 $a A regional-scale study such as this requires tools for efficiently delineating watersheds and deriving their attributes. Paper two presents a multiple watershed delineation tool that addresses issues such as (a) incorrectly positioned outlets and (b) large Digital Elevation Models. This tool has capabilities to delineate stream networks with the threshold that determines drainage density being objectively determined so that the resulting networks adhere to geomorphological stream network laws. It also derives a suite of geomorphological watershed attributes that were used in prediction models in paper three.
520 $a In paper three, we developed statistical models to predict streamflow regime class from watershed attributes. Four popular statistical methods were used and the uncertainty associated with class predictions for each method was quantified. Paper three also identified the watershed attributes that were most important for discriminating streamflow regime classes.
590 $a School code: 0241.
650 4 $a Biology, Ecology. $3 1017726
650 4 $a Engineering, Civil. $3 783781
650 4 $a Water Resource Management. $3 1669219
690 $a 0329
690 $a 0543
690 $a 0595
710 2 $a Utah State University. $b Civil and Environmental. $3 1023746
773 0 $t Dissertation Abstracts International $g 71-04B.
790 1 0 $a Tarboton, David G., $e advisor
790 1 0 $a Hawkins, Charles P. $e committee member
790 1 0 $a McKee, Mac $e committee member
790 1 0 $a Schmidt, Jack C. $e committee member
790 1 0 $a Hardy, Thomas B. $e committee member
790 $a 0241
791 $a Ph.D.
792 $a 2010
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3397138