000			02861nam a22002537a 4500
003			ZW-GwMSU
005			20230530155256.0
008			230530b |||||||| |||| 00| 0 eng d
040			_aMSU _cMSU _erda
100			_aZHANG, Tao
245			_aPredicting nitrogen loading with land-cover composition _bHow can watershed size affect model performance?
264			_aNew York _bSpringer _c2013
336			_2rdacontent _atext _btxt
337			_2rdamedia _aunmediated _bn
338			_2rdacarrier _avolume _bnc
440			_a Environmental Management _vVolume , number ,
520			_aWatershed-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			_awatershed size
650			_aland-cover composition-based regression model
650			_anon-point source nutient loading
700			_aYANG, Xiaojun
856			_uhttps://doi.org/10.1007/s00267-012-9897-3
942			_2lcc _cJA
999			_c162462 _d162462