A gis-based approach to watershed classification for Nebraska reservoirs

被引:12
作者
Bulley, Henry N. N.
Merchant, James W.
Marx, David B.
Holz, John C.
Holz, Aris A.
机构
[1] Univ Nebraska, Dept Geog & Geol, Omaha, NE 68182 USA
[2] Univ Nebraska, Sch Nat Resources, Ctr Adv Land Management Informat Technol, Lincoln, NE 68583 USA
[3] Univ Nebraska, Dept Stat, Lincoln, NE 68583 USA
来源
JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION | 2007年 / 43卷 / 03期
关键词
water quality; lake classification; geographic information systems; classification tree modeling; reservoirs; watershed management;
D O I
10.1111/j.1752-1688.2007.00048.x
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The U.S. Environmental Protection Agency is charged with establishing standards and criteria for assessing lake water quality. It is, however, increasingly evident that a single set of national water quality standards that do not take into account regional hydrogeologic and ecological differences will not be viable as lakes clearly have different inherent capacities to meet such standards. We demonstrate a GIS-based watershed classification strategy for identifying groups of Nebraska reservoirs that have similar potential capacity to attain a certain level of water quality standard. A preliminary cluster analysis of 78 reservoirs was performed to determine the potential number of Nebraska reservoir groups. Subsequently, a Classification Trees method was used to refine number of classes, describe the structure of reservoir watershed classes, and to develop a predictive model that relates watershed conditions to reservoir classes. Results suggest that Nebraska reservoirs can be represented by nine classes and that soil organic matter content in the watershed is the most important single variable for segregating the reservoirs. The cross-validation prediction error rate of the Classification Tree model was 26.3%. Because all geospatial data used in this work are available nationally, the method could be adopted throughout the U.S. Hence, this GIS-based watershed classification approach could provide water resources managers an effective decision-support tool in managing reservoir water quality.
引用
收藏
页码:605 / 621
页数:17
相关论文
共 68 条
[1]  
[Anonymous], 1997, Machine Learning
[2]   Establishing aquatic restoration priorities using a watershed approach [J].
Bohn, BA ;
Kershner, JL .
JOURNAL OF ENVIRONMENTAL MANAGEMENT, 2002, 64 (04) :355-363
[3]  
BULLEY HNN, 2004, THESIS U NEBRASKA LI
[4]   REGIONAL-ANALYSIS OF THE CENTRAL GREAT-PLAINS - SENSITIVITY TO CLIMATE VARIABILITY [J].
BURKE, IC ;
KITTEL, TGF ;
LAUENROTH, WK ;
SNOOK, P ;
YONKER, CM ;
PARTON, WJ .
BIOSCIENCE, 1991, 41 (10) :685-692
[5]  
Calinski T., 1974, COMMUN STAT, V3, P1, DOI DOI 10.1080/03610927408827101
[6]   TROPHIC STATE INDEX FOR LAKES [J].
CARLSON, RE .
LIMNOLOGY AND OCEANOGRAPHY, 1977, 22 (02) :361-369
[7]  
De'ath G, 2000, ECOLOGY, V81, P3178, DOI 10.2307/177409
[8]  
Eldershaw C, 1998, COMPUTATIONAL TECHNIQUES AND APPLICATIONS: CTAC 97, P201
[9]   An alternative classification method far northern Wisconsin lakes [J].
Emmons, EE ;
Jennings, MJ ;
Edwards, C .
CANADIAN JOURNAL OF FISHERIES AND AQUATIC SCIENCES, 1999, 56 (04) :661-669
[10]   Robust distance-based clustering with applications to spatial data mining [J].
Estivill-Castro, V ;
Houle, ME .
ALGORITHMICA, 2001, 30 (02) :216-242