Abstract
Rill erosion is under the influence of several parameters which their recognitions and optimal combination will be necessary in modeling. One of the soil degradation reasons on hills of Mashhad vicinity is rill erosion that makes recognition of the behavior and control essential. So in this research, by establishing 50-m transects in each different slope length, effective parameters in shaping rills, including canopy cover, ground cover, gravel, sand, silt, clay, slope, and mutual effects between length and degree of slope have been measured. Surface area of rills has been calculated by measuring width and depth of each rill and their geometric sections. Gamma test has been applied in order to find optimal combination of input parameters. Whereas the statistical tests including gamma, VRatio, gradient, and standard error were different, combined statistics index of Modified Ideal Point Error (MIPE) has been employed. This statistic criterion shows that parameters composition including surface gravel, silt, slope and mutual effects between length and degree of slope is the optimal model. Ground cover, amount of silt, and gravel surface, respectively, play more important role when the priority of their effect is being considered.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Ahmadi A, Han D, Karamouz M, Remesan R (2009) Input data selection for solar radiation estimation. J Hydrol Process 23:2754–2764
Bayati Khatibi M (2010) Role of changes in physical and chemical properties of soils during the slopes in erodibility of soils in the mountains (with emphasis on Gully Erosion): (northwest slopes Sabalan from ahar to Meshkinshahr). J Hum Sci MODARES 14(1):33–56
Elshorbagy A, Corzo G, Srinivasulu S, Solomatine D (2009) Experimental investigation of the predictive capabilities of soft computing techniques in hydrology. Centre for Advanced Numerical Simulation (CANSIM), Department of Civil & Geological Engineering, University of Saskatchewan, Saskatoon
Ghabaei sough M, Mosaedi A, Hesam M, Hezarjaribi A (2010) Evaluation effect of input parameters pre-processing in artificial neural networks (ANNs) by using stepwise regression and gamma test techniques for fast estimation of daily evapotranspiration. J Water Soil 24(3):610–624
Gimenez R, Govers G (2007) Effects of freshly incorporated straw residue on rill erosion and hydraulics. J Catena 72:214–223
Jones A.J, Evans D, Margetts S, Durrant P (2002) Chapter IX: the gamma test. Heuristic and Optimization for Knowledge Discovery. Ruhul Sarker, Hussein Abbass and Charles Newton, editors. Idea Group Publishing, Hershey, PA
Kang S, Zhang L, Song X, Zhang S, Liu X, Liang Y, Zheng S (2001) Runoff and sediment loss responses to rainfall and land use in two agricultural catchments on the Loess Plateau of China. J Hydrol Process 15:977–988
Koncar N (1997) Optimisation Methodologies for direct inverse neurocontrol. PhD thesis, Department of Computing, Imperial College of Science, Technology and Medicine, University of London
Li XY (2003) Gravel-sand mulch for soil and water conservation in the semiarid loess region of northwest China. J Catena 52:105–127
Meyer LD, Harmon WC (1984) Susceptibility of agricultural soils to interrill erosion. J Soil Sci Soc Am 48:1152–1157
Misra RK, Rose CW (1996) Application and sensitivity analysis of process-based erosion model GUEST. J Soil Sci 47:593–604
Moghaddamnia A, Ghafari Gousheh M, Piri J, Amin S, Han D (2008) Evaporation estimation using artificial neural networks and adaptive neuro-fuzzy inference system techniques. J Adv Water Resour 32:88–97
Noori R, Karbassi AR, Moghaddamnia A, Han D, Zokaei-Ashtiani MH, Farokhnia A, Ghafari Gousheh M (2011) Assessment of input variables determination on the SVM model performance using PCA, gamma test, and forward selection techniques for monthly stream flow prediction. J Hydrol 401:177–189
Poesen J, Ingelmo-Sanchez F (1992) Runoff and sediment yield from topsoil with different porosity and affected by rock fragment cover and position. J Catena 19:451–474
Rafahi H Gh. (2007) Water erosion and conservation, Tehran
Rejman J, Brodowski R (2005) Rill characteristics and sediment transport as a function of slope length during a storm event on loess soil. J Earth Surf Process Landf 30:231–239
Remesan R, Shamim MA, Han D (2008) Model data selection using gamma test for daily solar radiation estimation. J Hydrol Process 22:4301–4309
Veihe A, Rey J, Quinton JN, Strauss P, Sancho FM, Somarriba M (2001) Modeling pf event-based soil erosion in Costa Rica, Nicaragua and Mexico. Catena 44:187–203
Zahiri A, Ghabaei-Sough M, Mosaedi A (2012) Determination of influence parameters and its optimal combination in order to model flood rivers discharge. J Water Soil 25(6):1480–1493
Zangiabadi M, Rangavar A, Gh RH, Shorafa M, Bihamta MR (2010) Investigation of the most important factors affecting on soil erosion in Kalat semi-arid rangelands. J Water Soil 24:4,737–744
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Mosaedi, A., Hosseini, S.M. Determining the effective parameters and their optimal combination in rill erosion modeling. Arab J Geosci 8, 3045–3053 (2015). https://doi.org/10.1007/s12517-014-1363-5
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12517-014-1363-5