The Effect of Topography on Surface Sliding of the COMPLEX HILLSLOPES of Watersheds Using SINMAP and TOPMODEL Models

Subject Areas : Optimal management of water and soil resources

Farid Bahmani ¹ , Mohammad Hadi Fattahi ² , Touraj Sabzevari ³ , Ali Talebi ⁴ , Ali Torabi haghighi ⁵

1 - Department of civil engineering, Marvdasht Branch, Islamic Azad University, Marvdasht, Iran.
2 - Department of civil engineering, Marvdasht Branch, Islamic Azad University, Marvdasht, Iran.
3 - partment of civil engineering, Estahban Branch, Islamic Azad University, Estahban, Iran.
4 - Faculty of Natural Resources, Yazd University, Yazd, Iran.
5 - Water, Energy and Environmental Engineering Research Unit, University of Oulu, Finland.

Received: 2023-04-14 Accepted : 2023-11-13 Published : 2023-11-22

Keywords: SINMAP, Topography, TOPMODE, Landslide, complex hillslopes,

Abstract :

Background and Aim: The slopes of watersheds in nature have three converging, divergent and parallel shapes in terms of plan shape and three convex, concave and flat shapes in terms of floor curvature. In general, there are 9 shapes and geometries for hillslopes, which are called complex hillslopes. Past researches have shown that the topography and geometry of the complex hillslopes have an effect on many hydrological characteristics of the domains, such as the degree of saturation. The degree of saturation of the domain points depends on the concentration of subsurface flow at each point, which is influenced by the shape of the design and topography of the domain. The purpose of this research is the effect of topography on the surface sliding of the complex hillslopes of the watersheds using SINMAP and TOPMODEL models. Method: In this research, the TOPMODEL model was used to check the degree of saturation of the complex hillslopes, and the equations of this model were modified so that it could consider the topography of the domains, and the results of the saturation in the TOPMODEL model were transferred to a sliding model called SINMAP. And the effect of domain topography on the stability of complex domains was investigated and compared with MATLAB coding and drawing shapes. It should be noted that the aforementioned models are used based on hydrological and topographical data. The methods used in this research are generally applicable to all geographical and climatic regions.  Results:Considering that in this research, the saturation index was calculated from TOPMODEL, which indicates the degree of concentration of subsurface flow at any point of the domain and determines the saturation of different points of the domain and has a significant effect on the stability of compex hillslopes and based on the average the stability coefficient of the slopes, on average, convex slopes have more stability than flat and concave slopes, and divergent slopes have more stability than convergent slopes, and the higher the saturation layer thickness and soil hydraulic transfer coefficient, the more stable the slope is. and as the amount of effective rainfall increases and as a result the soil moisture increases, the stability of the slopes decreases. Conclusion: Based on the results obtained in this research, in the downstream parts, the concave slopes are more stable than the upstream part of the slope, while it is the opposite in the convex slopes. Compared to the saturation index, the local slope of the domain points is a much more important factor in determining the stability of the domains. Based on the average saturation index, convex domains are more stable than concave and divergent domains are more stable than convergent domains. It should be noted that in flat slopes with different plan shapes, the slope value is constant, but the degree of saturation of flat-convergent slopes is more than that of smooth-divergent slopes, and it has made some points of the flat-convergent slope more unstable, and the stability value is from top to side. The bottom becomes less and the end parts of the smooth-convergent domain are in an unstable state, but the entire smooth-parallel and smooth-divergent domains are in a stable state. 

References:

Ardekani, A. A., & Sabzevari, T. (2020). Effects of hillslope geometry on soil moisture deficit and base flow using an excess saturation model. Acta Geophysica, 68(3), 773-782. [in Persian]

Aryal, S. K., O’Loughlin, E. M., & Mein, R. G. (2005). A similarity approach to determine response times to steady-state saturation in landscapes. Advances in Water Resources, 28(2), 99-115.

Arnone, E., Noto, L. V., Lepore, C., & Bras, R. L. (2011). Physically-based and distributed approach to analyze rainfall-triggered landslides at watershed scale. Geomorphology, 133(3-4), 121-131.

Bahmani, F., hadi Fattahi, M., Sabzevari, T., Haghighi, A. T., & Talebi, A. (2021). Shallow Landslide Modeling in Complex Hillslope by Using TOPMODEL and SINMAP Models. [in Persian]

Berne, A., Uijlenhoet, R., & Troch, P. A. (2005). Similarity analysis of subsurface flow response of hillslopes with complex geometry. Water Resources Research, 41(9).

Bishop, A. W. (1959). The principle of effective stress. Teknisk ukeblad, 39, 859-863.

Borga, M., Dalla Fontana, G., & Cazorzi, F. (2002). Analysis of topographic and climatic control on rainfall-triggered shallow landsliding using a quasi-dynamic wetness index. Journal of Hydrology, 268(1-4), 56-71.

Beven, K., Quinn, P., Romanowicz, R., Freer, J., Fisher, J. and Lamb,R., 1995, TOPMODEL and GRIDATB: a users’ guide to the distributionversions (95.02) - CRES Technical Report TR110, 2^ndEd., Lancaster University, UK.

Beven, K., and M. Kirkby (1979), A physically based, variable contributing area model of basin hydrology/un mode`le a base physique de zone d’appel variable de l’hydrologie du bassin versant, Hydrol. Sci. J., 24(1), 43–69.

Beven, K. (2012), Rainfall-Runoff Modelling: The Primer, John Wiley, Hoboken, N. J.

Beven, K., 1997. TOPMODEL: a critque. Hydrol. Process 11 (9), 1069e1085.

Cardozo, C. P., Lopes, E. S. S., & Monteiro, A. M. V. (2018). Shallow landslide susceptibility assessment using SINMAP in Nova Friburgo (Rio de Janeiro, Brazil). Revista Brasileira de Cartografia, 70(4), 1206-1230

Cascini L, Cuomo S, Pastor M, Sorbino G (2010) Modeling of rainfall induced shallow landslides of the flow-type. J Geotech Geoenviron 136(1):85–98. https://doi.org/10.1061/(ASCE)GT.1943-5606. 0000182.

Campos, T. M. P., Andrade, M. H. N., Gerscovich, D. M. S., & Vargas Jr, E. A. (1994). Analysis of the failure of an unsaturated gneissic residual soil slope in Rio de Janeiro, Brazil. In 1st Panamerican Symposium On Landslides (pp. 201-213).

Dilley, M. (2005). Natural disaster hotspots: a global risk analysis (Vol. 5). World Bank Publications.

Dunne, T., and R. D. Black (1970), An experimental investigation of runoff production in permeable soils, Water Resour. Res., 6, 478 – 490.

Dietrich WE, Montgomery DR(1998)SHALSTAB: a digital terrain model for mapping shallow landslide potential.

Evans IS. (1980). An integrated system of terrain analysis and slope mapping. Zeitschrift fur Geomorphologie, Supplementband 36: 274-295.

Fariborzi, H., Sabzevari, T., Noroozpour, S., & Mohammadpour, R. (2019). Prediction of the subsurface flow of hillslopes using a subsurface time-area model. Hydrogeology Journal, 27(4), 1401-1417. [in Persian]

Goodwin, J., Jasper, J. M., & Khattra, J. (1999, March). Caught in a winding, snarling vine: The structural bias of political process theory. In Sociological forum (pp. 27-54). Eastern Sociological Society.

Godt, J. W., Baum, R. L., & Lu, N. (2009). Using soil suction and moisture content measurements for landslide prediction. Geophysical Research Letters, 36, L02403.

Kim MS, Onda Y, Uchida T, Kim JK, Song YS (2018) Effect of seepage on shallow landslides in consideration of changes in topography: case study including an experimental sandy slope with artificial rainfall. CATENA 161:50–62.

Kaspar, R. B., Letterio, M. P., Wittkopf, J. A., Gong, K., Gu, S., & Yan, Y. (2015). Manipulating water in high-performance hydroxide exchange membrane fuel cells through asymmetric humidification and wetproofing. Journal of the Electrochemical Society, 162(6), F483.

Lamb, R., & Beven, K. (1997). Using interactive recession curve analysis to specify a general catchment storage model. Hydrology and Earth System Sciences, 1(1), 101-113.

Liang, W. L., & Chan, M. C. (2017). Spatial and temporal variations in the effects of soil depth and topographic wetness index of bedrock topography on subsurface saturation generation in a steep natural forested headwater catchment. Journal of Hydrology, 546, 405-418.

Lane, S. N., Brookes, C. J., Kirkby, M. J., & Holden, J. (2004). A network‐index‐based version of TOPMODEL for use with high‐resolution digital topographic data. Hydrological processes, 18(1), 191-201.

Norbiato, D., & Borga, M. (2008). Analysis of hysteretic behaviour of a hillslope-storage kinematic wave model for subsurface flow. Advances in Water Resources, 31(1), 118-131.

Nachabe, M. H. (2006). Equivalence between TOPMODEL and the NRCS curve number method in predicting variable runoff source areas 1. JAWRA Journal of the American Water Resources Association, 42(1), 225-235.

O'loughlin, E. M. (1986). Prediction of surface saturation zones in natural catchments by topographic analysis. Water Resources Research, 22(5), 794-804.

Okura, Y., Kitahara, H., Ochiai, H., Sammori, T., & Kawanami, A. (2002). Landslide fluidization process by flume experiments. Engineering Geology, 66(1-2), 65-78.

Ogden, F. L., & Watts, B. A. (2000). Saturated area formation on nonconvergent hillslope topography with shallow soils: A numerical investigation. Water Resources Research, 36(7), 1795-1804.

Pack, R. T., Tarboton, D. G., & Goodwin, C. N. (2001). Assessing terrain stability in a GIS using SINMAP.

Park HJ, Lee JH, Woo I (2013) Assessment of rainfall-induced shallow landslide susceptibility using a GIS-based probabilistic approach. Eng Geol 161:1–15. https://doi.org/10.1016/j.enggeo.2013.04.011.

Pack, R. T., Tarboton, D. G., & Goodwin, C. N. (1999). GIS-based landslide susceptibility mapping with SINMAP.

Rabonza, M. L., Felix, R. P., Lagmay, A. M. F. A., Eco, R. N. C., Ortiz, I. J. G., & Aquino, D. T. (2016). Shallow landslide susceptibility mapping using high-resolution topography for areas devastated by super typhoon Haiyan. Landslides, 13, 201-210.

Sabzevari, Toraj, Karimi, Ramtin, Karmi Moghadam, Mehdi. (2018). "Estimating the length of the saturated zone and subsurface navigation time of the domains based on three simulations of the saturation of the composite domains", Scientific Quarterly of Water Resources Engineering, 12(43), pp. 49-63. [in Persian]

Sabzevari, T., Talebi, A., Ardakanian, R., & Shamsai, A. (2010). A steady-state saturation model to determine the subsurface travel time (STT) in complex hillslopes. Hydrology and Earth System Sciences, 14(6), 891-900. [in Persian]

Sabzevari, T., & Noroozpour, S. (2014). Effects of hillslope geometry on surface and subsurface flows. Hydrogeology journal, 22(7), 1593-1604. [in Persian]

Sabzevari, T., & Talebi, A. (2021). Landslide hazard zonation of catchments by using TOPMODEL and SINMAP models. Watershed Engineering and Management, 13(1), 222-234. [in Persian]

Sabzevari T, Talebi A, Ardakanian R, Shamsai A (2010) A steady state saturation model to determine the subsurface travel time (STT) in complex hillslopes. Hydrol Earth Syst Sci 14:891–900. doi:10.5194/hess-14-891-2010. [in Persian]

TAROLLI, P.; TARBOTON, D. G. A new method for determination of most likely landslide initiation points and the evaluation of digital terrain model scale in terrain stability mapping. Hydrology and Earth System Science, vol. 10, 2006. pp. 663-677.

Tarboton, D. G. (1997). A new method for the determination of flow directions and upslope areas in grid digital elevation models. Water resources research, 33(2), 309-319.

Talebi, A., Troch, P. A. A., & Uijlenhoet, R. (2006). A steady-state analytical hillslope stability model.

Troch PA, van Loon AH, Hilberts AGJ (2002) Analytical solutions to a hillslope storage kinematic wave equation for subsurface flow. Adv Water Resour 25(6):637–649.

Wu, W., & Sidle, R. C. (1995). A distributed slope stability model for steep forested basins. Water resources research, 31(8), 2097-2110.

Zhou, C., Yin, K., Cao, Y., & Ahmed, B. (2016). Application of time series analysis and PSO–SVM model in predicting the Bazimen landslide in the Three Gorges Reservoir, China. Engineering geology, 204, 108-120.