Midlands State University Library

Predicting nitrogen loading with land-cover composition (Record no. 162462)

MARC details
000 -LEADER
fixed length control field 02861nam a22002537a 4500
003 - CONTROL NUMBER IDENTIFIER
control field ZW-GwMSU
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20230530155256.0
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fixed length control field 230530b |||||||| |||| 00| 0 eng d
040 ## - CATALOGING SOURCE
Original cataloging agency MSU
Transcribing agency MSU
Description conventions rda
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name ZHANG, Tao
245 ## - TITLE STATEMENT
Title Predicting nitrogen loading with land-cover composition
Remainder of title How can watershed size affect model performance?
264 ## - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Place of production, publication, distribution, manufacture New York
Name of producer, publisher, distributor, manufacturer Springer
Date of production, publication, distribution, manufacture, or copyright notice 2013
336 ## - CONTENT TYPE
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Content type term text
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337 ## - MEDIA TYPE
Source rdamedia
Media type term unmediated
Media type code n
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440 ## - SERIES STATEMENT/ADDED ENTRY--TITLE
Title Environmental Management
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520 ## - SUMMARY, ETC.
Summary, etc. Watershed-wide land-cover proportions can be used to predict the in-stream non–point source pollutant loadings through regression modeling. However, the model performance can vary greatly across different study sites and among various watersheds. Existing literature has shown that this type of regression modeling tends to perform better for large watersheds than for small ones, and that such a performance variation has been largely linked with different interwatershed landscape heterogeneity levels. The purpose of this study is to further examine the previously mentioned empirical observation based on a set of watersheds in the northern part of Georgia (USA) to explore the underlying causes of the variation in model performance. Through the combined use of the neutral landscape modeling approach and a spatially explicit nutrient loading model, we tested whether the regression model performance variation over the watershed groups ranging in size is due to the different watershed landscape heterogeneity levels. We adopted three neutral landscape modeling criteria that were tied with different similarity levels in watershed landscape properties and used the nutrient loading model to estimate the nitrogen loads for these neutral watersheds. Then we compared the regression model performance for the real and neutral landscape scenarios, respectively. We found that watershed size can affect the regression model performance both directly and indirectly. Along with the indirect effect through interwatershed heterogeneity, watershed size can directly affect the model performance over the watersheds varying in size. We also found that the regression model performance can be more significantly affected by other physiographic properties shaping nitrogen delivery effectiveness than the watershed land-cover heterogeneity. This study contrasts with many existing studies because it goes beyond hypothesis formulation based on empirical observations and into hypothesis testing to explore the fundamental mechanism.
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element watershed size
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element land-cover composition-based regression model
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element non-point source nutient loading
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name YANG, Xiaojun
856 ## - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://doi.org/10.1007/s00267-012-9897-3
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Library of Congress Classification
Koha item type Journal Article
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Home library Current library Shelving location Date acquired Serial Enumeration / chronology Total Checkouts Full call number Date last seen Price effective from Koha item type Public note
    Library of Congress Classification     Main Library Main Library - Special Collections 30/05/2023 Vol.51 , No.1 (Jan 2013)   GE300 ENV 30/05/2023 30/05/2023 Journal Article For In House Use Only