بررسی عوامل مؤثر بر تغییرپذیری داده های کرت های فرسایش و امکان سنجی تعمیم به سطح دامنه

The main factors that control the variability of water erosion could be classified into physical and
management parameters. The physical factorsincludeslope geometry (length, steepness and shape
of slope and distance from drainage), surface properties (soil properties, roughness and cover of
surface and etc.), and environmental factors (climate condition, water table depth, and soil moisture
and precipitation regime) andmain management factors include vegetation and land use parameters.
Somesubstantivedifferencesthatcontrolerosion processes in plot surface comparing hillslope surface,arising
from limited dimension of plot and kind of its exploitation. These encountergeneralizeability ofthe
plotsize data to hillslope scale withuncertainty. However, erosion measurement in plot scale,because of
the easeandpossibility ofmonitoringthe long-termerosion, possibility of dynamic tracing of erosion and
erosion models development, is very important. In addition,a wide range ofsimulationerosion models,
bothempiricalandprocess based models, were developed based on plot size data. Therefore,in this article,
methodology and challengeshillslope erosionestimates using erosion plot data explored.Studyofthe
world'sbackgroundresearches indicatethat these efforts can be classified in threecategories including
multivariate parametric analysis, scaling generalization or up scaling and multi-scale modeling techniques.
Multi-scale modeling techniques are relatively youngandin existed in developing stage.Therefore, have less
diversity comparing statistical and up scaling methods. The use ofpattern recognitiontechniques, based on
data mining techniques including nonlinear non parametric analysis and intelligent methods, for finding
optimum model for generalized point based erosion data to hillslope and wider scales are the options that
fewerhave beenevaluated.