Skip to main content
Log in

Geo-spatial analysis for horizontal and vertical variability of bulk density, particle-size distribution and soil moisture content in Tripura, Northeastern India

  • Original Paper
  • Published:
Arabian Journal of Geosciences Aims and scope Submit manuscript

Abstract

The bulk density (BD), particle-size distribution and soil moisture content (SMC) are important properties that govern the physical and mechanical behaviours of the soil and also provide crucial information on the pedogenesis of soils. A total of 153 soil profiles were randomly selected and studied from part of Sepahijala district, Tripura, Northeastern India. The horizon-wise soil property data were converted to fixed-depth data for 0–20, 20–40, 40–60, 60 − 80 and 80–100 cm of soil depth. The result showed that the mean values of BD 1.51, 1.60, 1.59, 1.55 and 1.55 Mg m−3; sand 37.7, 38.1, 36.9, 36.0, and 37.3%; silt 29.1, 26.8, 28.0, 28.3 and 27.2%; clay 33.2, 35.1, 35.1, 35.7 and 35.5%; and SMC 21.4, 20.2, 21.2, 21.3 and 19.4% in the 0 − 20, 20 − 40, 40 − 60, 60 − 80 and 80 − 100 cm depths, respectively. The values of CV for soil variables ranged from 9.4 to 70.0% for all the depths. The CVs indicated that BD had lowest variability, while sand and SMC showed high variability in all the depths. Stein, circular, spherical, exponential and Gaussian models were found to be the best fit for semivariograms of different physical properties for different soil depths. The nugget to sill ratios of the empirical semivariograms for all the layers of BD, clay and SMC indicated moderate spatial dependence, except the 80 − 100 cm of BD and clay and 20 − 40 and 60 − 80 cm of SMC, which showed strong spatial dependence. Soil physical properties exhibited different distribution pattern. Spatial distribution maps of BD showed that except surface layer, the BD is lower in the southern part of the study area, and decreasing towards the northern parts in all the depths may be due to higher clay content in this region. The spatial distribution of SMC closely followed the distribution pattern of sand and clay contents. The developed maps prepared in this study may be useful to farmers, planners and decision-makers for improving soil–water management.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  • Adhikari K, Kheir RB, Greve MB, Bocher PK, Malone BP, Minasny B, McBratney AB, Greve MH (2013) High-resolution 3-D mapping of soil texture in Denmark. Soil Sci Soc Am J 77:860–876

    Article  Google Scholar 

  • Akpa SIC, Odeh IOA, Bishop TFA, Hartemink AE (2014) Digital mapping of soil particle-size fractions for Nigeria. Soil Sci Soc Am J 78:1953–1966

    Article  Google Scholar 

  • Azadmard B, Mosaddeghi MR, Ayoubi S, Chavosh E, Raoof M (2018) Spatial variability of near-saturated soil hydraulic properties in Moghan plain, North-Western Iran. Arab J Geosci 11:452

    Article  Google Scholar 

  • Bhattacharyya T, Pal DK, Mandal C, Chandran P, Ray SK, Sarkar D, Velmourougane K, Srivastava A, Sidhu GS, Singh RS, Sahoo AK, Dutta D, Nair KM, Srivastava R, Tiwary P, Nagar AP, Nimkhedkar SS (2013) Soils of India: historical perspective, classification and recent advances. Curr Sci 104:1308–1323

    Google Scholar 

  • Bhattacharyya T, Sarkar D, Pal DK, Mandal C, Baruah U, Telpandey B, Vaidya PH (2010) Soil information system for resource management-Tripura as a case study. Curr Sci 99:1208–1217

    Google Scholar 

  • Bhattacharyya T, Sehgal JL, Sarkar D (1996) Soils of Tripura for optimizing land use: their kinds, distribution and suitability for major field crops and rubber. NBSS Publication No. 65, Nagpur, pp 154

  • Bishop TFA, McBratney AB, Laslett GM (1999) Modelling soil attribute depth functions with equal-area quadratic smoothing splines. Geoderma 91:27–45

    Article  Google Scholar 

  • Blake GR, Hartge KH (1986) Bulk density. In: Klute A (ed) Methods of soil analysis, Part 1-physical and mineralogical methods. Agronomy Monograph 9, American Society of Agronomy-Soil Science Society of America, Madison, pp 363−382

  • Brejda JJ, Moorman TB, Smith JL, Karlen DL, Allan DL, Dao TH (2000) Distribution and variability of surface soil properties at a regional scale. Soil Sci Soc Am J 64:974–982

    Article  Google Scholar 

  • Cambardella CA, Moorman TB, Parkin TB, Karlen DL, Turco RF, Konopka AE (1994) Field scale variability of soil properties in Central Iowa soils. Soil Sci Soc Am J 58:1501–1511

    Article  Google Scholar 

  • Castro-Franco M, Domenech MB, Borda MR, Costa JL (2018) A spatial dataset of topsoil texture for the southern Argentine Pampas. Geoderma Reg 12:18–27

    Article  Google Scholar 

  • Chaudhari PR, Dodha Ahire V, Vidya Ahire D, Chkravarty M, Maity S (2013) Soil bulk density as related to soil texture, organic matter content and available total nutrients of Coimbatore soil. Int J Sci Res Pub 3:2250–3153

    Google Scholar 

  • Deka B, Baruah TC, Dutta M, Karmakar RM (2009) Landscape soil relationships and pedonegic evaluation of soils in Ghiladhari watershed of the Brahmaputra valleys of Assam. J Indian Soc Soil Sci 57:245–252

    Google Scholar 

  • Deshmukh KK, Aher SP (2014) Particle size analysis of soils and its interpolation using GIS technique from Sangamner Area, Maharashtra, India. Int Res J Environ Sci 3:32–37

    Google Scholar 

  • Dobarco MR, Arrouays D, Lagacherie P, Ciampalini R, Saby NPA (2017) Prediction of topsoil texture for Region Centre (France) applying model ensemble methods. Geoderma 298:67–77

    Article  Google Scholar 

  • Dörner J, Dec D, Peng X, Horn R (2009) Change of shrinkage behavior of an Andisol in southern Chile: effects of land use and wetting/drying cycles. Soil till Res 106:45–53

    Article  Google Scholar 

  • Goovaerts P (1998) Geostatistical tools for characterizing the spatial variability of microbiological and physio-chemical soil properties. Biol Fertil Soils 27:315–334

    Article  Google Scholar 

  • Grunwald S (2009) Multi-criteria characterization of recent digital soil mapping and modeling approaches. Geoderma 152:195–207

    Article  Google Scholar 

  • GSI (Geological Survey of India), (1998) 1:2 million scale geological map of north-east. Geological Survey of India, Kolkata

    Google Scholar 

  • Gülser C, Ekberli I, Candemir F, Demir Z (2016) Spatial variability of soil physical properties in a cultivated field. Eurasian J Soil Sci 5:192–200

    Google Scholar 

  • Guo X, Fu Q, Hang Y, Lu H, Gao F, Si J (2020) Spatial variability of soil moisture in relation to land use types and topographic features on hillslopes in the black soil (Mollisols) area of Northeast China. Sustainability 12:3552

    Article  Google Scholar 

  • Hengl T (2020) GSIF: global soil information facilities. R package version 0.5–5.1. https://CRAN.R-project.org/package=GSIF

  • Iqbal J, Thomasson JA, Jenkins JN, Owens PR, Whisler FD (2005) Spatial variability analysis of soil physical properties of alluvial soils. Soil Sci Soc Am J 69:1338–1350

    Article  Google Scholar 

  • Jabro JD, Stevens WB, Evans RG, Iversen WM (2010) Spatial variability and correlation of selected soil properties in the Ap horizon of a CRP grassland. Appl Eng Agric 26:419–428

    Article  Google Scholar 

  • Jacobs JM, Mohanty BP, Hsu EC, Miller D (2004) SMEX02: field scale variability, time stability and similarity of soil moisture. Remote Sens Environ 92:436–446

    Article  Google Scholar 

  • Kenney JF, Keeping ES (1962) Root mean square. Mathematics of Statistics, Part 1, 3rd Edition. Van Nostrand, Princeton, pp 59–60

    Google Scholar 

  • Kome G, Enang R, Tabi F, Yerima B (2019) Influence of clay minerals on some soil fertility attributes: a review. Open J Soil Sci 9:155–188

    Article  Google Scholar 

  • Kong X, Dao TH, Qin J, Qin H, Li C, Zhang F (2009) Effects of soil texture and land use interactions on organic carbon in soils in North China cities’ urban fringe. Geoderma 154:86–92

    Article  Google Scholar 

  • Krümmelbein J, Peth S, Zhao Y, Horn R (2009) Grazing-induced alterations of soil hydraulic properties and functions in Inner Mongolia, PR China. J Plant Nutr Soil Sci 172:769–776

    Article  Google Scholar 

  • Li J, Heap AD (2011) A review of comparative studies of spatial interpolation methods in environmental sciences: performance and impact factors. Ecol Inform 6:228–241

    Article  Google Scholar 

  • Liao K, Xu S, Wu J, Zhu Q (2013) Spatial estimation of surface soil texture using remote sensing data. Soil Sci Plant Nutr 59:488–500

    Article  Google Scholar 

  • Lin LI (1989) A concordance correlation coefficient to evaluate reproducibility. Biometrics 45:255–268

    Article  Google Scholar 

  • Lopez-Granados F, Jurado-Exposito M, Atenciano S, Gracia-Ferrer A, De La Orden MS, Gracia-Toreres L (2002) Spatial variability of agricultural soil parameters in Southern Spain. Plant Soil 246:97–105

    Article  Google Scholar 

  • Mabit L, Bernard C (2007) Assessment of spatial distribution of fallout radionuclides through geostatistics concept. J Environ Radioact 97:206–219

    Article  Google Scholar 

  • Malone BP, McBratney AB, Minasny B, Laslett GM (2009) Mapping continuous depth functions of soil carbon storage and available water capacity. Geoderma 154:138–152

    Article  Google Scholar 

  • Marc P, Jacques G (2011) Handbook of soil analysis. Springer International Edition, pp 15−17

  • Mashalaba L, Galleguillos M, Seguel O, Poblete-Olivares J (2020) Predicting spatial variability of selected soil properties using digital soil mapping in a rainfed vineyard of central Chile. Geoderma Reg 22:e00289

    Article  Google Scholar 

  • Mikhailova EA, Post CJ, Schlautman MA, Galbraith JM, Zurqani HA (2018) Usability of soil survey soil texture data for soil health indicator scoring. Comm Soil Sci Plant Anal 49:1826–1834

    Article  Google Scholar 

  • Mueller TG, Pierce FJ (2003) Soil carbon maps: enhancing spatial estimates with simple terrain attributes at multiple scales. Soil Sci Soc Am J 67:258–267

    Google Scholar 

  • Nagy NM, Konia J (2010) Interfacial chemistry of rocks and soil. Taylor & Francis Group, Boca Raton, FL: CRC Press

  • Nebo GI, Manyevere A, Araya T, van Tol J (2020) Short-term impact of conservation agriculture on soil strength and saturated hydraulic conductivity in the South African semiarid areas. Agriculture 10:414

    Article  Google Scholar 

  • Owji A, Boroujeni IE, Kamali A, Hosseinifard SJ, Bodaghabadi MB (2014) The effects of hydrometer reading times on the spatial variability of soil textures in southeast Iran. Arab J Geosci 7:1491–1499

    Article  Google Scholar 

  • Özgöz E, Günal H, Önen H, Bayram M, Acir N (2012) Effect of management on spatial and temporal distribution of soil physical properties. J Agric Sci 18:77–91

    Google Scholar 

  • Pearson K (1895) Notes on regression and inheritance in the case of two parents. Proc Royal Soc London 58:240–242

    Article  Google Scholar 

  • Pebesma EJ (1997) Gstat user’s manual: Program manual (http://www.gstat.org/)

  • Pebesma EJ, Wesseling CG (1998) Gstat, a program for geostatistical modelling, prediction and simulation. Comput Geosci 24:17–31

    Article  Google Scholar 

  • Piper CS (1966) Soil and plant analysis. Hans Publishers, Bombay, India

    Google Scholar 

  • Reynolds WD, Drury CF, Yang XM, Fox CA, Tan CS, Zhang TQ (2007) Land management effects on the near-surface physical quality of a clay loam soil. Soil till Res 96:316–330

    Article  Google Scholar 

  • Reza SK, Baruah U, Nayak DC, Dutta D, Singh SK (2018) Effects of land-use on soil physical, chemical and microbial properties in humid subtropical northeastern India. Natl Acad Sci Lett 41:141–145

    Article  Google Scholar 

  • Reza SK, Baruah U, Sarkar D, Dutta DP (2011) Influence of slope positions on soil fertility index, soil evaluation factor and microbial indices in acid soil of Humid Subtropical India. Ind J Soil Cons 39:44–49

    Google Scholar 

  • Reza SK, Baruah U, Sarkar D (2013) Hazard assessment of heavy metal contamination by the paper industry, northeastern India. Int J Environ Studies 70:23–32

    Article  Google Scholar 

  • Reza SK, Baruah U, Singh SK, Das TH (2015) Geostatistical and multivariate analysis of soil heavy metal contamination near coal mining area, northeastern India. Environ Earth Sci 73:5425–5433

    Article  Google Scholar 

  • Reza SK, Dutta D, Bandyopadhyay S, Singh SK (2019a) Spatial variability analysis of soil properties of Tinsukia district, Assam, India, using geostatistics. Agric Res 8:231–238

    Article  Google Scholar 

  • Reza SK, Nayak DC, Chattopadhyay T, Mukhopadhyay S, Singh SK, Srinivasan R (2016) Spatial distribution of soil physical properties of alluvial soils: a geostatistical approach. Arch Agron Soil Sci 62:972–981

    Article  Google Scholar 

  • Reza SK, Nayak DC, Mukhopadhyay S, Chattopadhyay T, Singh SK (2017) Characterizing spatial variability of soil properties in alluvial soils of India using geostatistics and geographical information system. Arch Agron Soil Sci 63:1489–1498

    Article  Google Scholar 

  • Reza SK, Ray P, Ramachandran S, Bandyopadhyay S, Mukhopadhyay S, Sah KD, Nayak DC, Singh SK, Ray SK (2019b) Spatial distribution of soil nitrogen, phosphorus and potassium contents and stocks in humid subtropical North-eastern India. J Indian Soc Soil Sci 67:12–20

    Article  Google Scholar 

  • Reza SK, Ray P, Ramachandran S, Bandyopadhyay S, Mukhopadhyay S, Sah KD, Nayak DC, Singh SK, Ray SK (2019c) Profile distribution of soil organic carbon in major land use systems in Bishalgarh block, Tripura. J Indian Soc Soil Sci 67:236–239

    Article  Google Scholar 

  • Reza SK, Sarkar D, Baruah U, Das TH (2010) Evaluation and comparison of ordinary kriging and inverse distance weighting methods for prediction of spatial variability of some chemical parameters of Dhalai district, Tripura. Agropedology 20:38–48

    Google Scholar 

  • Safari Y, Boroujeni IE, Kamali A, Salehi MH, Bodaghabadi MB (2013) Mapping of the soil texture using geostatistical method (a case study of the Shahrekord plain, central Iran). Arab J Geosci 6:3331–3339

    Article  Google Scholar 

  • Saglam M, Dengiz O (2012) Influence of selected land use types and soil texture interactions on some soil physical characteristics in an alluvial land. Int J Agron Plant Prod 3:508–513

    Google Scholar 

  • Saleh AM (2018) Spatial variability mapping of some soil properties in Jadwal Al_Amir Project/Babylon/Iraq. J Indian Soc Remote Sens 46:1481–1495

    Article  Google Scholar 

  • Santra P, Chopra UK, Chakraborty D (2008) Spatial variability of soil properties and its application in predicting surface map of hydraulic parameters in an agricultural farm. Curr Sci 95:937–945

    Google Scholar 

  • Santra P, Kumar M, Panwar N (2017) Digital soil mapping of sand content in arid western India through geostatistical approaches. Geoderma Reg 9:56–72

    Article  Google Scholar 

  • Seyedmohammadi J, Navidi MN, Esmaeelnejad L (2019) Geospatial modeling of surface soil texture of agricultural land using fuzzy logic, geostatistics and GIS techniques. Comm Soil Sci Plant Anal 50:1452–1464

    Article  Google Scholar 

  • Shi J, Wang H, Xu J, Wu J, Liu X, Zhu H, Yu C (2007) Spatial distribution of heavy metals in soils: a case study of Changxing, China. Environ Geol 52:1–10

    Article  Google Scholar 

  • Silva Cruz J, de Assis Júnior RN, Rocha Matias SS, Camacho-Tamayo JH (2011) Spatial variability of an Alfisol cultivated with sugarcane. Ciencia e Investigación Agraria 38:155–164

    Article  Google Scholar 

  • Soil Survey Staff (1995) Soil Survey Manual, USDA, Agricultural handbook No. 18, New Revised Edition, Scientific Publishers, Jodhpur

  • Soil Survey Staff (2014) Keys to soil taxonomy, 12th edition. USDA, National Soil Survey Center, Natural Resources Conservation Service, Washington DC

  • Some’e BS, Hassanpour F, Ezani A, Miremadi SR, Tabari H (2011) Investigation of spatial variability and pattern analysis of soil properties in the northwest of Iran. Environ Earth Sci 64:1849–1864

    Article  Google Scholar 

  • Tesfahunegn GB, Tamene L, Vlek PLG (2011) Catchment scale spatial variability of soil properties and implications on site-specific soil management in northern Ethiopia. Soil till Res 117:124–139

    Article  Google Scholar 

  • Tripathi R, Nayak AK, Shahid M, Raja R, Panda BB, Mohanty S, Kumar A, Lal B, Gautam P, Sahoo RN (2015) Characterizing spatial variability of soil properties in salt affected coastal India using geostatistics and kriging. Arab J Geosci 8:10693–10703

    Article  Google Scholar 

  • Van der Meij WM, Temme AJAM, Wallinga J, Sommer M (2020) Modelling soil and landscape evolution−the effect of rainfall and land use change on soil and landscape patterns. Soils 6:337–358

    Article  Google Scholar 

  • Varma S, Simon R (2006) Bias in error estimation when using cross-validation for model selection. BMC Bioinformatics 7:91

    Article  Google Scholar 

  • Voltz M, Webster R (1990) A comparison of kriging, cubic splines and classification for predicting soil properties from sample information. J Soil Sci 41:473–490

    Article  Google Scholar 

  • Wani MA, Shaista N, Wani ZM (2017) Spatial variability of some chemical and physical soil properties in Bandipora district of lesser Himalayas. J Indian Soc Remote Sens 45:611–620

    Article  Google Scholar 

  • Wani MA, Wani JA, Bhat MA, Kirmani NA, Wani ZM, Bhat SN (2013) Mapping of soil micronutrients in Kashmir agricultural landscape using ordinary kriging and indicator approach. J Indian Soc Remote Sens 41:319–329

    Article  Google Scholar 

  • Webster R, Oliver MA (2001) Local estimation or prediction: kriging. Geostatistics for environmental scientists. Wiley, Chichester, pp 149–191

    Google Scholar 

  • Webster R, Oliver MA (2007) Geostatistics for environmental scientists. John Wiley & Sons, pp 315

  • Western AW, Grayson RB, Blöschl G, Wilson DJ (2003) Spatial variability of soil moisture and its implication for scaling. In: Pachepsky Y, Radcliffe DE, Selim HM (eds) Scaling methods in soil physics. CRC Press, Boca Raton, pp 119–142

    Google Scholar 

  • Wilding LP (1985) Spatial variability: its documentation, accommodation, and implication to soil surveys. In Nielsen DR, Bouma J, (eds) Soil spatial variability. Pudoc, Wageningen, Netherlands, pp 166−194

  • Xing-Yi SYY, Zhang XD, Meng K, Herbert SJ (2007) Spatial variability of nutrient properties in black soil of Northeastz China. Pedosphere 17:19–29

    Article  Google Scholar 

  • Yao LX, Zhou XC, Cai YF, Chen WZ (2004) Spatial variability of soil properties at different sampling intensities and accuracy of their estimation. Soils 36:538–542

    Google Scholar 

  • Zhang Y, Ji W, Saurette DD, Easher TH, Li H, Shi Z, Adamchuk VI, Biswas A (2020) Three-dimensional digital soil mapping of multiple soil properties at a field scale using regression kriging. Geoderma 366:114–253

    Article  Google Scholar 

  • Zhou H, Chen Y, Li W (2010) Soil properties and their spatial pattern in an oasis on the lower reaches of the Tarim River, Northwest China. Agric Water Manage 97:1915–1922

    Article  Google Scholar 

  • Zhu XH, Yang XC, Cai YL (2005) Fractal and fractal dimension of spatial distribution of China soil system. Acta Pedol Sinica 42:881–888

    Google Scholar 

Download references

Acknowledgements

We acknowledge all of our colleagues who helped directly or indirectly in carrying out the study.

Funding

This research was financially supported by the Indian Council of Agricultural Research (ICAR), New Delhi, India.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Sah Kausar Reza.

Ethics declarations

Conflict of interest

The authors declare that they have no competing interests.

Additional information

Responsible Editor: Biswajeet Pradhan

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Reza, S.K., Kumar, N., Ramachandran, S. et al. Geo-spatial analysis for horizontal and vertical variability of bulk density, particle-size distribution and soil moisture content in Tripura, Northeastern India. Arab J Geosci 14, 2734 (2021). https://doi.org/10.1007/s12517-021-09151-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s12517-021-09151-3

Keywords

Navigation