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Hillslope elements and soil–landscape analysis in Himalayas for characterizing soil quality parameters using digital terrain model and remote-sensing data

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Abstract

Hillslope elements and land cover types are primarily determining the spatial variability of soils in the hilly and mountainous landscape. Among the soil forming factors, topography strongly influences pedogenic process and governs the variability of soils in hilly and mountainous landscape. This study mainly focusses on characterizing soil quality parameters distribution based on the hillslope elements and soil–landscape units in the watershed. Digital terrain model (DTM)-derived topographic position index was used to delineate various hillslope elements. Land use/land cover map was generated using random forest machine learning technique. Hillslope elements, land use/land cover types and aspects were integrated in GIS environment to generate soil–landscape unit map of the watershed. Soil samples were collected based on various soil–landscape units to characterize soil quality parameters such as total carbon (TC) soil organic matter (SOM), total nitrogen (TN), aggregate stability (SAS) in the watershed. SOM ranged from 1.6% to 10.05% and higher estimated in shoulder (forest) followed by valley (agriculture) and toe slope (forest). TC and TN contents ranged from 0.93% to 5.84% and 0.11% to 0.38%, respectively. The C:N ratio ranged from 7.96% to 18.31% and high value was found in shoulder (forest) followed by valley (agriculture) and toe slope (forest). SAS under different hillslope elements in the area ranged from 0.0.552 to 0.615 indicating large spatial variation of soil quality parameters. The study indicates that in hilly and mountainous landscape, topography and land cover types have major role in determining soil quality. DTM-based soil–landscape units’ delineation can be helpful to study soil quality variability and can be used to generate soil map for the hilly and mountainous watershed. The significance of this study lies in its potential to make substantial contributions to land use planning, sustainable land management and environmental conservation planning in the challenging and ecologically fragile and sensitive Himalayan region.

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References

  • Ahmed R, Ahmad ST, Wani GF, Ahmed P, Mir AA, Singh A (2021) Analysis of landuse and landcover changes in Kashmir valley, India—a review. GeoJournal 87(5):4391–4403

  • Alem S, Pavlis J (2014) Conversion of grazing land into Grevillea robusta plantation and exclosure: impacts on soil nutrients and soil organic carbon. Environ Monit Assess 186(7):4331–4341

    Article  Google Scholar 

  • Alemayehu K (2007) Effects of different land use systems and topography on selected soil properties at Delbo watershed, Wolaita zone, southern Ethiopia. Msc thesis, Hawassa University, Hawassa, Ethiopia

  • Alemayehu D, Tadesse M, AS MAA (2019) Application of TPI for analysis of landforms and LULC of Adama Wereda, Ethiopia. J Geograph Stud 2:100–109

  • Amézketa E (1999) Soil aggregate stability: a review. J Sustain Agric 14(2–3):83–151

    Article  Google Scholar 

  • An S, Mentler A, Mayer H, Blum WE (2010) Soil aggregation, aggregate stability, organic carbon and nitrogen in different soil aggregate fractions under forest and shrub vegetation on the Loess Plateau, China. CATENA 81(3):226–233

    Article  Google Scholar 

  • Arnold J, Corre MD, Veldkamp E (2009) Soil N cycling in old-growth forests across an Andosol toposequence in Ecuador. For Ecol Manag 257(10):2079–2087

    Article  Google Scholar 

  • Austin AT, Vivanco L (2006) Plant litter decomposition in a semi-arid ecosystem controlled by photodegradation. Nature 442(7102):555–558

    Article  Google Scholar 

  • Ayalew DM, Kassahun DW (2016) Monitoring land use/land cover change impacts on soils in data scarce environments: a case of south-central Ethiopia. J Land Use Sci 11(1):96–112. https://doi.org/10.1080/1747423X.2014.927011

    Article  Google Scholar 

  • Bauer M, Loeffelholz B, Wilson B (2005) Estimation, mapping and change analysis of impervious surface area by Landsat remote sensing. In: Proceedings, Pecora 16 conference, pp 23–27

  • Belgiu M, Drăguţ L (2016) Random forest in remote sensing: a review of applications and future directions. ISPRS J Photogramm Remote Sens 114:24–31

    Article  Google Scholar 

  • Blaszczynski JS (1997) Landform characterization with geographic information systems. Photogrammetric Eng Remote Sens 63:183–191.

  • Brabyn L (1998) GIS analysis of macro landform. The 10th Colloquium of the Spatial Information Research Centre: University of Otago, Dunedin, pp 35–48

  • Bronick CJ, Lal R (2005) Manuring and rotation effects on soil organic carbon concentration for different aggregate size fractions on two soils in northeastern Ohio, USA. Soil Tillage Res 81(2):239–252

    Article  Google Scholar 

  • Brubaker SC, Jones AJ, Frank K, Lewis DT (1994) Regression models for estimating soil properties by landscape position. Soil Sci Soc Am J 58:1763–1767

    Article  Google Scholar 

  • Butler DR, Marston RA (2017) Landforms and physiography. In: Richardson D, Castree N, Goodchild MF, Kobayash A, Liu W, Marston RA (eds), The international encyclopedia of geography. ohn Wiley & Sons, Ltd. https://doi.org/10.1002/9781118786352.wbieg1144

  • Cerdà A (1996) Soil aggregate stability in three Mediterranean environments. Soil Technol 9(3):133–140

    Article  Google Scholar 

  • Chauniyal DD, Dutta S (2018) Application of topographic position index for classification of landforms in Dudhatoli Region of Garhwal Himalaya, Uttarakhand. J Indian Geomorphol 6:28–41

    Google Scholar 

  • Chendes V, Dumitru S, Simota C (2008) Analyzing the landforms-agricultural land-use types relationship using a DTM-based indicator. Sci Pap USAMV Ser A Agron 52:135140

    Google Scholar 

  • De Reu J, Bourgeois J, Bats M, Zwertvaegher A, Gelorini V, De Smedt P et al (2013) Application of the topographic position index to heterogeneous landscapes. Geomorphology 186:39–49

    Article  Google Scholar 

  • Dikau R (1989) The application of a digital relief model to landform analysis in geomorphology. In: Raper J (ed) Three dimensional application in geographic information systems. Taylor & Francis, London, pp 51–77

    Google Scholar 

  • Evans DA, Williard KW, Schoonover JE (2016) Comparison of terrain indices and landform classification procedures in low-relief agricultural fields. J Geospat Appl Nat Resour 1(1):1

    Google Scholar 

  • Fang X, Xue Z, Li B, An S (2012) Soil organic carbon distribution in relation to land use and its storage in a small watershed of the Loess Plateau, China. CATENA 88(1):6–13

    Article  Google Scholar 

  • FAO (2015) Understanding mountain soils: a contribution from mountain areas to the International Year of Soils 2015, by Romeo, R., Vita, A., Manuelli, S., Zanini, E., Freppaz, M. & Stanchi, S. Rome, Italy

  • Fernández-Ugalde O, Barré P, Hubert F, Virto I, Girardin C, Ferrage E et al (2013) Clay mineralogy differs qualitatively in aggregate-size classes: clay-mineral-based evidence for aggregate hierarchy in temperate soils. Eur J Soil Sci 64(4):410–422

    Article  Google Scholar 

  • Florinsky IV, Eilers RG, Manning G, Fuller LG (2002) Prediction of soil properties by digital terrain modelling. Environ Model Softw 17:295–311

    Article  Google Scholar 

  • Fu BJ, Liu SL, Chen LD, Lü YH, Qiu J (2004) Soil quality regime in relation to land cover and slope position across a highly modified slope landscape. Ecol Res 19:111–118

    Article  Google Scholar 

  • Gee GW, Bauder JW (1979) Particle size analysis by hydrometer: a simplified method for routine textural analysis and a sensitivity test of measurement parameters. Soil Sci Soc Am J 43:1004–1007

    Article  Google Scholar 

  • Gorelick N, Hancher M, Dixon M, Ilyushchenko S, Thau D, Moore R (2017) Google Earth Engine: planetary-scale geospatial analysis for everyone. Remote Sens Environ 202:18–27

    Article  Google Scholar 

  • Grandy AS, Robertson GP (2006) Aggregation and organic matter protection following tillage of a previously uncultivated soil. Soil Sci Soc Am J 70(4):1398–1406

    Article  Google Scholar 

  • Greenland DJ, Lindstrom GR, Quirk JP (1962) Organic materials which stabilize natural soil aggregates. Soil Sci Soc Am J 26(4):366–371

    Article  Google Scholar 

  • Gruber FE, Baruck J, Geitner C (2017) Algorithms vs. surveyors: a comparison of automated landform delineations and surveyed topographic positions from soil mapping in an Alpine environment. Geoderma 308:9–25

    Article  Google Scholar 

  • Gu C, Zhang Y, Liu L, Li L, Li S, Zhang B et al (2021) Qualifying land use and land cover dynamics and their impacts on ecosystem service in central Himalaya transboundary landscape based on Google Earth Engine. Land 10(2):173

    Article  Google Scholar 

  • Guzmán G, Cabezas JM, Sánchez-Cuesta R, Lora Á, Bauer T, Strauss P et al (2019) A field evaluation of the impact of temporary cover crops on soil properties and vegetation communities in southern Spain vineyards. Agric Ecosyst Environ 272:135–145

    Article  Google Scholar 

  • Hansen AJ, DeFries RS, Turner W (2004) Land use change and biodiversity: a synthesis of rates and consequences during the period of satellite imagery. In: Land change science: Observing, monitoring and understanding trajectories of change on the Earth’s surface, pp 277–299

  • India Meteorological Department (2014) “Climate of Uttarakhand” scientific publication climatological summaries of states series-no. 21. Additional Director General of Meteorology (Research) India Meteorological Department, Pune, India

  • Jenness J (2006) TPI documentation. Topographic position index (TPI) v. 1.2 16(3):1–42. http://www.jennessent.com/downloads/tpi_documentation_online.pdf

  • Jenny H (1941) Factors of soil formation—a system of quantitative pedology. McGraw-Hill, New York, p 281

    Google Scholar 

  • Jien SH, Wu SP, Chen ZS, Chen TH, Chiu CY (2010) Characteristics and pedogenesis of podzolic forest soils along a toposequence near a subalpine lake in northern Taiwan. Bot Stud 51(2):223–236

    Google Scholar 

  • Karlen DL, Ditzler CA, Andrews SS (2003) Soil quality: why and how? Geoderma 114(3–4):145–156

    Article  Google Scholar 

  • Kemper WD, Rosenau RC (1986) Aggregate stability and size distribution. In: Klute A (eds) Methods of soil analysis: part 1. Physical and mineralogical methods, 2nd edn. ASA and SSSA, Madison, WI, pp 425–442

  • Khalili-Rad M, Nourbakhsh F, Jalalian A, Eghbal MK (2011) The effects of slope position on soil biological properties in an eroded toposequence. Arid Land Res Manag 25(3):308–312

    Article  Google Scholar 

  • Koné B, Touré A, Amadji GL, Yao-Kouamé A, Angui PT, Huat J (2013) Soil characteristics and Cyperus spp. occurrence along a toposequence. Afr J Ecol 51(3):402–408

    Article  Google Scholar 

  • Kumar L, Mutanga O (2018) Google Earth Engine applications since inception: usage, trends, and potential. Remote Sens 10(10):1509

    Article  Google Scholar 

  • Kumar S, Singh RP (2016) Spatial distribution of soil nutrients in a watershed of Himalayan landscape using terrain attributes and geostatistical methods. Environ Earth Sci 75(6):1–11

    Article  Google Scholar 

  • Leh M, Bajwa S, Chaubey I (2013) Impact of land use change on erosion risk: an integrated remote sensing, geographic information system and modeling methodology. Land Degrad Dev 24(5):409–421

    Google Scholar 

  • Liu S, Bliss N, Sundquist E, Huntington TG (2003) Modeling carbon dynamics in vegetation and soil under the impact of soil erosion and deposition. Glob Biogeochem Cycles 17(2)

  • Liu Z, Yao Z, Huang H, Wu S, Liu G (2014) Land use and climate changes and their impacts on runoff in the Yarlung Zangbo river basin, China. Land Degrad Dev 25(3):203–215

    Article  Google Scholar 

  • Lu D, Weng Q (2007) A survey of image classification methods and techniques for improving classification performance. Int J Remote Sens 28(5):823–870

    Article  Google Scholar 

  • Ma Y, Minasny B, Malone PB, Mcbratney A (2019) Pedology and digital soil mapping (DSM). Eur J Soil Sci 70:216–235

    Article  Google Scholar 

  • Maitra S (1999) Landforms and geomorphological classification of part of the upper Baitarani River Basin. J Indian Soc Remote Sens 27(3):175–184

    Article  Google Scholar 

  • McBratney AB, Mendonca Santos ML, Minasny B (2003) On digital soil mapping. Geoderma 117:3–52

    Article  Google Scholar 

  • McKenzie NJ, Gallant JC (2006) Digital soil mapping with improved environmental predictors and models of pedogenesis. In: Lagacherie P, McBratney AB, Voltz M (eds) Digital soil mapping: an introductory perspective. Elsevier, Amsterdam, pp 327–349

    Chapter  Google Scholar 

  • Mishra VN, Prasad R, Rai PK, Vishwakarma AK, Arora A (2019) Performance evaluation of textural features in improving land use/land cover classification accuracy of heterogeneous landscape using multi-sensor remote sensing data. Earth Sci Inf 12(1):71–86

    Article  Google Scholar 

  • Mohajane M, Essahlaoui A, Oudija F, Hafyani ME, Hmaidi AE, Ouali AE et al (2018) Land use/land cover (LULC) using landsat data series (MSS, TM, ETM+ and OLI) in Azrou Forest, in the Central Middle Atlas of Morocco. Environments 5(12):131

    Article  Google Scholar 

  • Mokarram M, Seif A, Sathyamoorthy D (2015) Landform classification of Zagros Mountains using multiscale analysis of digital elevation models. Creating a vibrant space industry for Malaysia: the need for a space act 30

  • Monger HC, Bestelmeyer BT (2006) The soil-geomorphic template and biotic change in arid and semi-arid ecosystems. J Arid Environ 65(2):207–218

    Article  Google Scholar 

  • Moore ID, Grayson RB, Ladson AR (1991) Digital terrain modeling: a review of hydrological, geomorphological, and biological applications. Hydrol Process 5:3–30

    Article  Google Scholar 

  • Nosrati K (2013) Assessing soil quality indicator under different land use and soil erosion using multivariate statistical techniques. Environ Monit Assess 185(4):2895–2907

    Article  Google Scholar 

  • Nyaupane GP, Chhetri N (2009) Vulnerability to climate change of nature-based tourism in the Nepalese Himalayas. Tour Geogr 11(1):95–119

    Article  Google Scholar 

  • Pal M (2005) Random forest classifier for remote sensing classification. Int J Remote Sens 26(1):217–222. https://doi.org/10.1080/01431160412331269698

    Article  Google Scholar 

  • Partap T (2011) Hill agriculture: challenges and opportunities. Indian J Agric Econ 66(1):33–52

    Google Scholar 

  • Pennock DJ, Zebarth BJ, De Jong E (1987) Landform classification and soil distribution in hummocky terrain, Saskatchewan, Canada. Geoderma 40(3–4):297–315

    Article  Google Scholar 

  • Pierson FB, Mulla DJ (1990) Aggregate stability in the Palouse region of Washington: effect of landscape position. Soil Sci Soc Am J 54(5):1407–1412

  • Rezaei SA, Gilkes RJ (2005) The effects of landscape attributes and plant community on soil chemical properties in rangelands. Geoderma 125(1–2):167–176

    Article  Google Scholar 

  • Scherr SJ, Yadav S (1996) Land degradation in the developing world: implications for food, agriculture, and the environment to 2020 (no. 584-2016-39743). International Food Policy Research Institute, Washington, DC

  • Schwanghart W, Jarmer T (2011) Linking spatial patterns of soil organic carbon to topography—a case study from south-eastern Spain. Geomorphology 126(1–2):252–263

    Article  Google Scholar 

  • Seif A (2014) Using topography position index for landform classification (case study: Grain Mountain). Bull Environ Pharmacol Life Sci 3(11):1808–2277

  • Shary PA, Rukhovich OV, Sharaya LS, Mitusov AV (2002a) Soils and topography: accumulation zones and non-local approaches. In: Transactions of the 17th world congress of soil science, 14_21 August 2002, Bangkok, Thailand, Symposium 48 (paper # 2310). Bangkok: ISSS (CD ROM)

  • Shary PA, Sharaya LS, Mitusov AV (2002b) Fundamental quantitative methods of land surface analysis. Geoderma 107:1–32

    Article  Google Scholar 

  • Shaver TM, Peterson GA, Ahuja LR, Westfall DG, Sherrod LA, Dunn G (2002) Surface soil physical properties after twelve years of dryland no-till management. Soil Sci Soc Am J 66(4):1296–1303

    Article  Google Scholar 

  • Singh AK, Bordoloi LJ, Kumar M, Hazarika S, Parmar B (2014) Land use impact on soil quality in eastern Himalayan region of India. Environ Monit Assess 186(4):2013–2024

    Article  Google Scholar 

  • Singh AK, Kumar S, Kalambukattu JG (2019) Assessing aggregate stability of soils under various land use/land cover in a watershed of Mid-Himalayan Landscape. Eurasian J Soil Sci 8(2):131–143

    Google Scholar 

  • Sinha RK, Eldho TI, Subimal G (2020) Assessing the impacts of historical and future land use and climate change on the streamflow and sediment yield of a tropical mountainous river basin in South India. Environ Monit Assess 192(11):1–21

    Article  Google Scholar 

  • Six J, Elliott ET, Paustian K (1999) Aggregate and soil organic matter dynamics under conventional and no-tillage systems. Soil Sci Soc Am J 63(5):1350–1358

    Article  Google Scholar 

  • Six J, Paustian K, Elliott ET, Combrink C (2000) Soil structure and organic matter I. Distribution of aggregate-size classes and aggregate-associated carbon. Soil Sci Soc Am J 64(2):681–689

    Article  Google Scholar 

  • Six J, Bossuyt H, Degryze S, Denef K (2004) A history of research on the link between (micro) aggregates, soil biota, and soil organic matter dynamics. Soil Tillage Res 79(1):7–31

    Article  Google Scholar 

  • Skentos A, Ourania A (2017) Landform analysis using terrain attributes. A GIS application on the Island of Ikaria (Aegean Sea, Greece). Ann Valahia Univ Targoviste Geogr Ser 17:90–97

    Article  Google Scholar 

  • Smith MP, Zhu AX, Burt JE, Stiles C (2006) The effects of DEM resolution and neighborhood size on digital soil survey. Geoderma 137(1–2):58–69

    Article  Google Scholar 

  • Sreenivas K, Dadhwal VK, Kumar S, Harsha GS, Mitran T, Sujatha G et al (2016) Digital mapping of soil organic and inorganic carbon status in India. Geoderma 269:160–173

    Article  Google Scholar 

  • Stanchi S, Falsone G, Bonifacio E (2015) Soil aggregation, erodibility, and erosion rates in mountain soils (NW Alps, Italy). Solid Earth 6:403–414. https://doi.org/10.5194/se-6-403-2015

    Article  Google Scholar 

  • Stehman SV (1997) Selecting and interpreting measures of thematic classification accuracy. Remote Sens Environ 62(1):77–89

    Article  Google Scholar 

  • Summerfield MA (1991) Sub-aerial denudation of passive margins: regional elevation versus local relief models. Earth Planet Sci Lett 102(3–4):460–469

    Article  Google Scholar 

  • Tagil S, Jenness J (2008) GIS-based automated classification and topographic, landcover and geologic attributes of landforms around the Yazoren Polje, Turkey. J Appl Sci 8(6):910–921. https://doi.org/10.3923/jas.2008.910.921

  • Tsai YH, Stow D, Chen HL, Lewison R, An L, Shi L (2018) Mapping vegetation and land use types in Fanjingshan National Nature Reserve using google earth engine. Remote Sens 10(6):927

    Article  Google Scholar 

  • UNDP/FAO (1988) Land resources appraisal of Bangladesh for agricultural development, report 2, Agroecological Regions of Bangladesh, food and agriculture organization of the United Nations, Rome

  • Verma VK, Setia RK, Sharma PK, Singh CHARANJIT, Kumar ASHOK (2005) Pedospheric variations in distribution of DTPA-extractable micronutrients in soils developed on different physiographic units in central parts of Punjab, India. Int J Agric Biol 7(2):243–246

    Google Scholar 

  • Walkley A, Black IA (1934) An examination of the Degtjareff method for determining soil organic matter, and a proposed modification of the chromic acid titration method. Soil Sci 37(1):29–38

    Article  Google Scholar 

  • Wang J, Fu B, Qiu Y, Chen L (2001) Soil nutrients in relation to land use and landscape position in the semi-arid small catchment on the loess plateau in China. J Arid Environ 48(4):537–550

    Article  Google Scholar 

  • Weiss A (2001) Topographic position and landforms analysis. In: Poster presentation, ESRI user conference, San Diego, CA, vol 200

  • White DA II, Welty-Bernard A, Rasmussen C, Schwartz E (2009) Vegetation controls on soil organic carbon dynamics in an arid, hyperthermic ecosystem. Geoderma 150(1–2):214–223

    Article  Google Scholar 

  • Wolde M, Veldkamp E, Mitiku H, Nyssen J, Muys B, Kindeya G (2007) Effectiveness of exclosures to restore degraded soils as a result of overgrazing in Tigray, Ethiopia. J Arid Environ 69(2):270–284

    Article  Google Scholar 

  • Wubie MA, Assen M (2020) Effects of land cover changes and slope gradient on soil quality in the Gumara watershed, Lake Tana basin of North-West Ethiopia. Model Earth Syst Environ 6:85–97

    Article  Google Scholar 

  • Yu W, Zhou W, Qian Y, Yan J (2016) A new approach for land cover classification and change analysis: Integrating backdating and an object-based method. Remote Sens Environ 177:37–47

    Article  Google Scholar 

  • Zhang JJ, Fu MC, Zeng H, Geng YH, Hassani FP (2013) Variations in ecosystem service values and local economy in response to land use: a case study of Wu’an, China. Land Degrad Dev 24(3):236–249

    Article  Google Scholar 

  • Zhang Z, Sheng L, Yang J, Chen XA, Kong L, Wagan B (2015) Effects of land use and slope gradient on soil erosion in a red soil hilly watershed of southern China. Sustainability 7(10):14309–14325

    Article  Google Scholar 

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Acknowledgements

Authors are thankful to Indian Space Research Organization (ISRO) for providing financial support under Earth Observation Applications Mission (EOAM) Project (ISRO/DOS) on “Mountain Ecosystem Processes and Services-Phase-II” to carry out the research work. We are thankful to the Director, Indian Institute of Remote Sensing (IIRS) for providing necessary facilities to carry out the research work.

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The financial support for this study is provided by Indian Space Research Organization (ISRO), Departement of Space (DOS).

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SK—conceptualization; NM and ADR—investigation; SK, NM and ADR—methodology; SK—project administration; SK and JGK—supervision; NM and ADR—data collection: SK, and ADR—validation; ADR and NM—visualization; SK, ADR and NM—original draft; SK, NM and ADR—writing; SK, ADR, JGK—review and editing. All authors discussed the results, commented and approved the manuscript.

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Correspondence to Suresh Kumar.

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Kumar, S., Murugan, N., David Raj, A. et al. Hillslope elements and soil–landscape analysis in Himalayas for characterizing soil quality parameters using digital terrain model and remote-sensing data. Environ Earth Sci 82, 469 (2023). https://doi.org/10.1007/s12665-023-11166-w

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