Refine your search
Collections
Co-Authors
Journals
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Dharumarajan, S.
- Status of Desertification in South India – Assessment, Mapping and Change Detection Analysis
Abstract Views :207 |
PDF Views:82
Authors
S. Dharumarajan
1,
M. Lalitha
1,
Rajendra Hegde
1,
N. Janani
1,
A. S. Rajawat
2,
K. L. N. Sastry
2,
S. K. Singh
3
Affiliations
1 ICAR-National Bureau of Soil Survey and Land Use Planning, Hebbal, Bengaluru - 560 024, IN
2 ISRO-Space Applications Centre, Ahmedabad - 380 015, IN
3 ICAR-National Bureau of Soil Survey and Land Use Planning, Amaravati Road, Nagpur - 440 033, IN
1 ICAR-National Bureau of Soil Survey and Land Use Planning, Hebbal, Bengaluru - 560 024, IN
2 ISRO-Space Applications Centre, Ahmedabad - 380 015, IN
3 ICAR-National Bureau of Soil Survey and Land Use Planning, Amaravati Road, Nagpur - 440 033, IN
Source
Current Science, Vol 115, No 2 (2018), Pagination: 331-338Abstract
Desertification is the transformation of productive land into a non-productive one due to poor resource management, and unfavourable biophysical and economical factors. Periodical assessment of desertification status is imperative for a suitable comprehensive and combating plan. In the present study, desertification status maps of Andhra Pradesh (AP), Karnataka and Telangana in South India have been prepared using remote sensing data for two time-frames (2003– 2005 and 2011–2013) and change detection analysis has been carried out. The results reveal that 14.35%, 36.24% and 31.40% of the total geographical area in Andhra Pradesh, Karnataka and Telangana were affected by desertification processes respectively, in 2011–2013. Among the desertification processes, vegetal degradation contributes 7.27% of total area in AP, followed by water erosion (4.93%) and waterlogging (0.83%), whereas in Karnataka water erosion (26.29%) is dominant followed by vegetal degradation (8.93%) and salinization (0.45%). Change detection analysis shows that desertification processes of AP and Karnataka have increased by 0.19% and 0.05% respectively, whereas in Telangana it has decreased by about 0.52% from 2003 to 2005 data. The present database will help the scientists, planners and stakeholders to prepare appropriate land reclamation measures to control the increasing trend of desertification.Keywords
Change Detection Analysis, Desertification, Salinization, Vegetal Degradation, Waterlogging.References
- Dharumarajan, S., Bishop, T. F. A., Hegde, R. and Singh, S. K., Desertification vulnerability index – an effective approach to assess desertification processes: a case study in Anantapur district, Andhra Pradesh, India. Land Degra. Dev., 2018, 29, 150–161; doi:10.1002/ldr.2850.
- Middleton, L. and Thomas, D. (eds), World Atlas of Desertification, United Nations Environment Programme (UNEP), Arnold, London, 1997, 2nd edn, p. 182.
- United Nations Convention for Combating Desertification (UNCCD), Desertification, the invisible frontline, 2014; http://www.unccd.int/Lists/SiteDocumentLibrary/Publications
- Reynolds, J. F., Smith, D. M. S. and Lambin, E. F., Global desertification: building a science for dryland development. Science, 2007, 316, 847–851; doi:10.1126/science.1131634.
- UNCCD, Max Planck Yearbook of United Nations Law, 2008, vol. 12, pp. 287–300; http://www.unccd.int/convention/ratif/doeif.php
- Okin, G. S., Murray, B. and Schlesinger, W. H., Degradation of sandy arid shrubland environments: observations, process modelling, and management implications. J. Arid Environ., 2001, 47(2), 123–144; doi:10.1006/jare.2000.0711.
- Land desertification, 2005; http://www.biox.cn/content/20050414/10407.htm
- Duanyang, X., Kang, X., Qiu, D., Zhuang, D. and Pan, J., Quantitative assessment of desertification using Landsat data on a regional scale – a case study in the Ordos Plateau, China. Sensors, 2009, 9(3), 1738–1753; doi:10.3390/s90301738.
- Hill, H., Stellmes, M., Udelhoven, Th., Roder, A. and Sommer. S., Mediterranean desertification and land degradation. Mapping related land use change syndromes based on satellite observations. Global Planet. Change, 2008, 64(3–4), 146–157; doi:10.1016/j.gloplacha.2008.10.005.
- Kundu, A., Patel, N. R., Saha, S. K. and Dutta, D., Desertification in western Rajasthan (India): an assessment using remote sensing derived rain-use efficiency and residual trend methods. Nat. Hazards, 2017, 86, 297–313; doi:10.1007/s11069-016-2689y.
- Dhargawe, S. D., Sastry, K. L. N., Gahlod, N. S. and Arya, V. S., Desertification change analysis study using multi-temporal Awifs data: Uttarakhand State. Universal J. Environ. Res. Technol., 2016, 6(2), 73–81.
- Sharma, K. D., The hydrological indicators of desertification. J. Arid Environ., 1998, 39(2), 121–132; doi:10.1006/jare.1998.0403.
- Jain, S. K., Kumar, S. and Varghese. J., Estimation of soil erosion for a Himalayan watershed using GIS technique. Water Resour. Manage., 2001, 15, 41–54; doi:10.1023/A:1012246029263.
- Mouat, D., Lancaster, J., Wade, T., Wickham, J., Fox, C., Kepner, W. and Ball, T., Desertification evaluated using an integrated environmental assessment model. Environ. Monit. Assess., 1997, 48(2), 139–156; doi:10.1023/A:1005748402798.
- Geist, H. J. and Lambin. E. F., Dynamic causal patterns of desertification. BioScience, 2004, 54(9), 817–829; doi:10.1641/00063568.
- Tripathy, G. K., Ghosh, T. K. and Shah, S. D., Monitoring of desertification process in Karnataka state of India using multitemporal remote sensing and ancillary information using GIS. Int. J. Remote Sensing, 1996, 17, 2243–2257; doi:10.1080/ 01431169608948771.
- Kosmas, C., Gerontidis, S., Detsis, V., Zafiriou, T. and Marathianou, M., Application of the proposed methodology for defining ESAs: the island of Lesvos (Greece). In Manual on Key Indicators of Desertification and Mapping Environmentally Sensitive Areas to Desertification (eds Kosmas, C., Kirkby, M. J. and Geeson, N.), European Commission Publication 18882, 1999, pp. 66–73.
- Lin, M.-L. et al., Fuzzy model-based assessment and monitoring of desertification using MODIS satellite imagery. Eng. Comput., 2009, 26(7), 745–760; doi:10.1108/02644400910985152.
- Dhinwa, P. S., Dasgupta, A. and Ajai, Monitoring and assessment of desertification using satellite remote sensing. J. Geomat., 2016, 10(2), 210–216.
- Salvati, L., Bajocco, S., Ceccarelli, T., Zitti, M. and Perini, L., Towards a process-based evaluation of land vulnerability to soil degradation in Italy. Ecol. Indic., 2011, 11, 1216–1227; doi:10.1016/j.ecolind.2010.12.024.
- Elias, S., Karathanasis, N., Koukoulas, S. and Panagopoulos, G., Monitoring sensitivity to land degradation and desertification with the environmentally sensitive area index: the case of Lesvos Island. Land Degrad. Dev., 2016, 27, 1562–1573; doi:10.1002/ldr.2285.
- Sehgal, J. and Abrol, I. P., Soil Degradation in India: Status and Impact, Oxford and IBH, New Delhi, 1994, p. 80.
- Ajai, Arya, A. S., Dhinwa, P. S., Pathan, S. K. and Ganesh Raj, K., Desertification/land degradation status mapping of India. Curr. Sci., 2009, 97, 1478–1483.
- Singh, G., Salinity-related desertification and management strategies: Indian experience. Land Degrad. Dev., 2009, 20(4), 367–385; doi:10.1002/ldr.933.
- Maji, A. K., Reddy, G. P. O. and Sarkar, D., Degraded and wastelands of India: status and spatial distribution. Directorate of Information and Publications of Agriculture, Indian Council of Agricultural Research, New Delhi and National Academy of Agricultural Sciences, New Delhi, 2010, p. 158.
- Budihal, S. L. et al., Assessment and mapping of desertification status in Bellary district, Karnataka State, using IRS data. In ISPRS Commission IV International Symposium on Geospatial Databases for Sustainable Development, Goa, 25–30 September 2006.
- Reddy, R. S., Nalatwadmath, S. K. and Krishnan, P., Soil erosion in Andhra Pradesh. National Bureau of Soil Survey and Land Use Planning, Publication No. 114, NBSSLUP, Nagpur, 2005, p. 76.
- Naidu, L. G. K. et al., Evaluation of soil and climatic characteristics for identifying constraints and potentials for forest development in Andhra Pradesh, India. Indian J. Dryland Agric. Res. Dev., 2017, 32(1), 63–70; doi:10.5958/2231-6701.2017.00011.2.
- Pedotransfer Functions for Predicting Soil Hydraulic Properties in Semi-Arid Regions of Karnataka Plateau, India
Abstract Views :182 |
PDF Views:78
Authors
Affiliations
1 ICAR-National Bureau of Soil Survey and Land Use Planning, Regional Centre, Hebbal, Bengaluru 560 024, IN
2 ICAR-National Bureau of Soil Survey and Land Use Planning, Amaravati Road, Nagpur 440 033, IN
1 ICAR-National Bureau of Soil Survey and Land Use Planning, Regional Centre, Hebbal, Bengaluru 560 024, IN
2 ICAR-National Bureau of Soil Survey and Land Use Planning, Amaravati Road, Nagpur 440 033, IN
Source
Current Science, Vol 116, No 7 (2019), Pagination: 1237-1246Abstract
Soil hydraulic properties are important for irrigation scheduling and proper land-use planning. Field capacity, permanent wilting point and infiltration rate are the three vital hydraulic properties which determine the availability and retention of water for crop growth. These properties are difficult to measure and time-consuming, but can be easily predicted from the available information like soil texture, bulk density, organic carbon content, etc. through pedotransfer functions (PTFs). PTFs were developed for field capacity and permanent wilting point for two different regions of Karnataka, viz. Northern Karnataka Plateau (512 soil samples) and Southern Karnataka Plateau (228 soil samples), separately. PTF for infiltration rate was developed using 100 soil samples for the entire Karnataka. Cross-validation techniques were used to validate the PTFs, and the results are satisfactory with low RMSE and higher R2. The developed PTFs are useful in determining soil hydraulic properties of the semi-arid regions of southern India.Keywords
Pedotransfer Functions, Field Capacity, Permanent Wilting Point, Infiltration Rate, Semi-Arid Regions.References
- Santra, P., Mahesh Kumar, Kumawat, R. N., Painuli, D. K., Hati, K. M., Heuvelink, G. B. M. and Batjes, N. H., Pedotransfer functions to estimate water content at field capacity and permanent wilting point in hot arid western India. J. Earth Syst. Sci., 2018, 127, 35.
- Simpson, J. A. and Weiner, E. S. C., The Oxford English Dictionary, Clarendon Press, Oxford University Press, Oxford, UK, 1989, 2nd edn.
- Ferré, T. P. A. and Warrick, A. W., Infiltration. In Encyclopedia of Soils in the Environment, 2005, pp. 254–260.
- Romano, N. and Palladino, M., Prediction of soil water retention using soil physical data and terrain attributes, J Hydrol., 2002, 265, 56–75.
- Parasuraman, K., Elshorbagy, A. and Bing, C. S., Estimating saturated hydraulic conductivity using genetic programming, Soil Sci. Soc. Am. J., 2007, 71, 1676–1684.
- Vereecken, H., Weynants, M., Javaux, M., Pachepsky, Y., Schaap, M. G. and van Genuchten, M. Th., Using pedotransfer functions to estimate the van Genuchten–Mualem soil hydraulic properties: a review. Soil Sci. Soc. Am. J., 2010, 9, 795–820; doi:10.2136/ vzj2010.0045.
- Dharumarajan, S., Singh, S. K., Bannerjee, T. and Sarkar, D., Water retention characteristics and available water capacity in three cropping system of lower Indo Gangetic alluvial plain. Commun. Soil Sci. Plant Anal., 2001, 4, 2734–2745.
- Bouma, J., Using soil survey data for quantitative land evaluation, Adv. Soil Sci., 1989, 9, 177–213.
- Rawls, W. J., Pachepsky, Y. A., Ritchie, J. C., Sobecki, T. M. and Bloodworth, H., Effect of soil organic carbon on soil water retention. Geoderma, 2003, 116, 61–76.
- Tóth, B., Makó, A., Guadagnini, A. and Tóth, G., Water retention of salt affected soils: quantitative estimation using soil survey information. Arid Land Res. Manage., 2012, 26, 103–121.
- Keshavarzi, A., Sarmadian, F. and Labbafi, R., Developing pedotransfer functions for estimating field capacity and permanent wilting point using fuzzy table look up scheme. Comput. Inf. Sci., 2011, 4(1), 130–141.
- Santra, P. and Das, B. S., Pedotransfer functions for soil hydraulic properties developed from a hilly watershed of eastern India. Geoderma, 2008, 146, 439–448.
- Chakraborty, D., Mazumdar, S. P., Garg, R. N., Banerjee, S., Santra, P., Singh, R. and Tomar, R. K., Pedotransfer functions for predicting points on the moisture retention curve of Indian soils. Indian J. Agric. Sci., 2011, 81, 1030–1036.
- Patil, N. G. and Chaturvedi, A., Pedotransfer functions based on nearest neighbour and neural networks approach to estimate available water capacity of shrink–swell soils. Indian J. Agric. Sci., 2012, 82, 35–38.
- Cornelis, W. M., Ronsyn, J., van Meirvenne, M. and Hartmann, R., Evaluation of pedotransfer functions for predicting the soil moisture retention curve. Soil Sci. Soc. Am. J., 2001, 65, 638–648.
- Kaur, R., Kumar, S., Gurung, R. P., Rawat, J. S., Singh, A. K., Prasad, S. and Rawat, G., Evaluation of pedotransfer functions for predicting field capacity and wilting point moisture content from routinely surveyed soil texture and organic carbon data. J. Indian Soc. Soil Sci., 2002, 50, 205–208.
- Patil, N. et al., Soil water retention characteristics of black soils of India and pedotransfer functions using different approaches. J. Irrig. Drain Eng., 2013, 139, 313–324.
- Tiwary, P. et al., Pedotransfer functions: a tool for estimating hydraulic properties of two major soil types of India. Curr. Sci., 2014, 107, 1431–1439.
- NBSS Publication, Soils of Karnataka. In Soils of Karnataka for Optimizing Land Use, ICAR-NBSS&LUP, Nagpur, Maharashtra, Publ. No. 47, 1998.
- Hegde, R., Niranjana, K. V., Srinivas, S., Danorkar, B. A. and Singh. S. K., Site-specific land resource inventory for scientific planning of Sujala watersheds in Karnataka. Curr. Sci., 2018, 115(4), 645–652.
- ASTM, D3385-03 Standard test method for infiltration rate of soils in field using double-ring infiltrometer. In Annual Book of ASTM Standards 04.08, American Society of Testing Materials, West Conshohocken, PA, USA, 2003.
- Liaw, A. and Wiener, M., Classification and regression by randomForest. R News, 2002, 2, 18–21.
- Breiman, L., Random forests, Machine Learn, 2001; doi:10.1023/ A:1010933404324.
- Dharumarajan, S., Bishop, T. F. A., Hegde, R. and Singh, S. K., Desertification vulnerability index – an effective approach to assess desertification processes: a case study in Anantapur District, Andhra Pradesh, India. Land Degrad. Dev., 2018, 29, 150–161; https://doi.org/10.1002/ldr.2850.
- Dharumarajan, S. et al., Biophysical and socio-economic causes for increasing fallow lands in Tamil Nadu. Soil Use Manage., 2017, 33, 487–498.
- Adhikary, P. P. et al., Pedotransfer functions for predicting the hydraulic properties of Indian soils. Aust. J. Soil Res., 2008, 46, 476–484.
- Mohanty, M., Sinha, N. K., Painuli, D. K., Bandyopadhyay, K. K., Hati, K. M., Reddy, K. S. and Chaudhary, R. S., Pedotransfer functions for estimating water content at field capacity and wilting point of Indian soils using particle size distribution and bulk density. J. Agric. Phys., 2014, 14(1), 1–9.
- Dabral, P. P. and Pandey, P. K., Models to estimate soil moisture retention limits and saturated hydraulic conductivity. J. Indian Water Resour. Soc., 2016, 36(1), 50–55.
- Shwetha, P. and Varija, K., Soil water-retention prediction from pedotransfer functions for some Indian soils. Arch. Agron. Soil Sci., 2013, 59(11), 1529–1543.
- Mahdian, M. H., Oskoee, R. S., Kamali, K., Angoshtari, H. and Kadkhodapoor, M. A., Developing pedotransfer functions to predict infiltration rate in flood spreading stations of Iran. Res. J. Environ. Sci., 2009, 3(6), 697–704.