Digital soil mapping of Maniyari Basin using Geospatial Techniques
الموضوعات :Dipak Bej 1 , Naresh Kumar Baghmar 2
1 - Ph.D. Scholar, Pt. Ravishankar Shukla University, Raipur, India
2 - Professor, Pt. Ravishankar Shukla University, Raipur, India
الکلمات المفتاحية: Soil nutrients, geographical information system, Digital soil map, IDW interpolation,
ملخص المقالة :
Background and objective:Remote sensing image data are often used as input in digital soil mapping (DSM). DSM nowadays is very popular rather than conventional soil maps it is an important tool in soil survey and sustainable agriculture planning. Spatial distribution of soil information in each pixel using laboratory observation data of soil samples plays an important role. The purpose of this study is to prepare a digital soil map using remote sensing.Materials and methods:Ninety soil samples were collected at a depth of up to 50 cm from various Physiography land units made with the help of the basis of slope and Land use Land cover (LULC) as well as physiography. Sentinel 2 satellite data (10 m.) and Aster DEM (30 m.) have been used to prepare the digital soil map. Soil samples were analyzed to determine the Macro (N, P, and K) Micro (Fe, Zn, Cu, Mn, S, and Br) Nutrients and Some Physico (Texture, Bulk density, depth) Chemical Properties (pH, EC, and OC).Results and conclusion:Six textural classes identified were sandy clay loam and sandy clay, clay, clay loam, loam, and sandy loam. The bulk density, and the depth varied from 1.08 to 1.8 Mg m-3, and 14 to 90 cm. respectively. The pH, EC, and OC are varied from 5 to 8.36, 0.1 to 1.2 ds/m, and 0.03 to 1.47 respectively. Nitrogen (N), Phosphorus (P), and Potassium(K) varied from 125 to 476 kg/ha., 4.44 to 77.78 kg/ha, and 79.6 to 504 kg/ha respectively. The digital soil database along with all its properties called a physiographic soil map which has been prepared with the help of the inverse distance weightage (IDW) interpolation method, which will help to select crops and get the best sustainable cultivation.
Arianpour, M., & Jamali, A. A. (2014). Locating flood spreading suitable sites for groundwater recharging through multi criteria modeling in GIS (case study: Omidieh-Khuzestan). Journal of Biodiversity and Environmental Sciences, 5, 119-127.
Bouma, J., Jongmans, A. G., Stein, A., & Peek, G. (1989). Characterizing spatially variable hydraulic properties of a boulder clay deposit in the Netherlands. Geoderma, 45(1), 19-29. https://doi.org/10.1016/0016-7061(89)90054-2
Carré, F., McBratney, A. B., Mayr, T., & Montanarella, L. (2007). Digital soil assessments: Beyond DSM. Geoderma, 142(1-2), 69-79. https://doi.org/10.1016/j.geoderma.2007.08.015
Dharumarajan, S., Hegde, R., Janani, N., & Singh, S. K. (2019). The need for digital soil mapping in India. Geoderma Regional, 16, e00204. https://doi.org/10.1016/j.geodrs.2019.e00204
Ghane Ezabadi, N., Azhdar, S., & Jamali, A. A. (2021). Analysis of dust changes using satellite images in Giovanni NASA and Sentinel in Google Earth Engine in western Iran. Journal of Nature and Spatial Sciences (JONASS), 1(1), 17-26. https://doi.org/10.30495/jonass.2021.680327
He, S., Wang, D., Zhao, P., Li, Y., Lan, H., Chen, W., & Jamali, A. A. (2020). A review and prospects of debris flow waste-shoal land use in typical debris flow areas, China. Land Use Policy, 99, 105064. https://doi.org/10.1016/j.landusepol.2020.105064
He, S., Wang, D., Li, Y., Zhao, P., Lan, H., Chen, W., ... & Chen, X. (2021). Social-ecological system resilience of debris flow alluvial fans in the Awang basin, China. Journal of Environmental Management, 286, 112230. https://doi.org/10.1016/j.jenvman.2021.112230
Masoumi, H., Jamali, A. A., & Khabazi, M. (2014). Investigation of role of slope, aspect and geological formations of landslide occurrence using statistical methods and GIS in some watersheds in Chahar Mahal and Bakhtiari Province. J. Appl. Environ. Biol. Sci, 4(9), 121-129.
McBratney, A. B., Santos, M. M., & Minasny, B. (2003). On digital soil mapping. Geoderma, 117(1-2), 3-52. https://doi.org/10.1016/S0016-7061(03)00223-4
Minasny, B., & McBratney, A. B. (2016). Digital soil mapping: A brief history and some lessons. Geoderma, 264, 301-311. https://doi.org/10.1016/j.geoderma.2015.07.017
Mohanty, B. P., & Mousli, Z. (2000). Saturated hydraulic conductivity and soil water retention properties across a soil‐slope transition. Water Resources Research, 36(11), 3311-3324. https://doi.org/10.1029/2000WR900216
Parsasyrat, L., & Jamali, A. A. (2015). The effects of impermeable surfaces on the flooding possibility in Zarrin-Shahr, Isfahan Municipal Watershed. J Appl Environ Biol Sci, 5(1), 28-38.
Qanbari, V., & Jamali, A. A. (2015). The relationship between elevation, soil properties and vegetation cover in the Shorb-Ol-Ain watershed of Yazd. J Biodivers Environ Sci (JBES), l.
Zhu, A. X., Hudson, B., Burt, J., Lubich, K., & Simonson, D. (2001). Soil mapping using GIS, expert knowledge, and fuzzy logic. Soil Science Society of America Journal, 65(5), 1463-1472. https://doi.org/10.2136/sssaj2001.6551463x