Author Details

Home > Search > Author Details

Author Details

Scroll

Refine your search

Collections

Basic & Applied Science Collection

Co-Authors

G. T. Patle
A. Sarangi
A. Gupta
A. T. Dandekar
A. K. Singh
K. K. Singh
H. S. Negi
A. V. Kulkarni
H. S. Gusain
A. Ganju
K. Babu Govindha Raj
Santosh S. Mali
S. S. Parihar
V. D. Mishra
Shuvadeep Majumdar
Devendra Singh
R. Sarma
Mukesh Kumar
S. Sudhishri
A. R. Rao
Venkatesh Gaddikeri
K. K. Bandyopadhyay
Bidisha Chakrabarti
S. K. Sarkar

Journals

Current Science

Year

2016
2017
2018
2019
2020
2023

Authors

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

Author Finder

Singh, D. K.

Modelling of Declining Groundwater Depth in Kurukshetra District, Haryana, India

Abstract Views :208 | PDF Views:81

Authors

G. T. Patle ¹, D. K. Singh ², A. Sarangi ²

Affiliations
1 Department of Soil and Water Engineering, College of Agricultural Engineering and PHT, Ranipool 737 135, IN
2 Water Technology Centre, Indian Agricultural Research Institute, New Delhi 110 012, IN

Source

Current Science, Vol 111, No 4 (2016), Pagination: 717-723

Abstract

Changing climate of a region coupled with spatiotemporal variability of rainfall has a significant effect on groundwater recharge. An effort has been made in this study to analyse the pre- and post-monsoon average groundwater depths of different blocks in Kurukshetra district, Haryana, India. The stochastic analysis of groundwater depth was carried out using auto regressive integrated moving average (ARIMA) model. Best-fitted models ARIMA (2, 1, 1) and ARIMA (0, 1, 2) were used for prediction of pre- and post-monsoon groundwater depth fluctuations up to the year 2020. Results indicate that by the year 2020, average groundwater depth in the pre- and post-monsoon seasons in the district is expected to decline by 5.63 and 5.72 m respectively, over the base year 2010. Results of this study will be helpful in evolving strategies for groundwater development and management.

Keywords

Climatic Variability, Groundwater Depth, Irrigation, Monsoon Rainfall.

Full Text

Estimation of Crop Coefficients and Water Productivity of Mustard (Brassica juncea) under Semi-Arid Conditions

Abstract Views :255 | PDF Views:82

Authors

A. Gupta ¹, A. Sarangi ², D. K. Singh ¹

Affiliations
1 Division of Agricultural Engineering, ICAR-Indian Agricultural Research Institute, New Delhi 110 012, IN
2 Water Technology Centre, ICAR-Indian Agricultural Research Institute, New Delhi 110 012, IN

Source

Current Science, Vol 113, No 02 (2017), Pagination: 264-271

Abstract

Experiment was conducted using weighing-type field lysimeters to determine single and dual crop coefficients (K_c) and to estimate water productivity of mustard (Brassica juncea) cultivar, Pusa Vijay (NPJ-93) during rabi 2013-14 and 2014-15. It was observed that the single crop coefficient (K_c) during rabi 2013-14 was 0.39, 0.72, 1.02 and 0.5 for initial, development, mid and late stages respectively. While in dual Kc the value of K_cb (basal crop coefficient) was 0.19, 0.55, 0.91 and 0.24 for the four stages, respectively. During rabi 2014-15, the single Kc was 0.36, 0.63, 1.04 and 0.44 and for dual K_c the value of K_cb was 0.17, 0.46, 0.91 and 0.23 for four stages respectively. Relationship between K_cb and leaf area index as well as between K_cb and growing degree days was also established. Water productivity was estimated to be 14.9 kg/ha-mm corresponding to grain yield of 2.34 t ha^-1 with 157 mm of total irrigation water applied during rabi 2013-14. Whereas during rabi 2014-15, water productivity was 15.4 kg/ha-mm with grain yield of 2.89 t ha^-1 with 187 mm depth of applied irrigation. Nonetheless, the estimated crop coefficients of mustard can be used for judicious irrigation scheduling in order to enhance water productivity in semi-arid environment.

Keywords

Brassica juncea, Crop Coefficient, Evapotranspiration, Leaf Area Index, Water Productivity.

Full Text

References

Hamdy, A. and Lacirignola, D., Mediterranean water resources: major challenges toward 21st century. CIHEAM-IAM Bari, Italy, 1999, p. 570.

Katerji, N. and Rana, G., Crop evapotranspiration measurement and estimation in the Mediterranean region, INRA-CRA, Bari, Italy, 2008, p. 173; ISBN 978 8 89015 241 2.

Tyagi, N. K., Sharma, D. K. and Luthra, S. K., Determination of evapotranspiration and crop coefficients of rice and sunflower with lysimeter. Agric. Water Manage., 2000, 45, 41–54.

Kashyap, P. S. and Panda, R. K., Evaluation of evapotranspiration estimation methods and development of crop-coefficients for potato crop in a sub-humid region. Agric. Water Manage., 2001, 50, 9–25.

Irmak, S., Estimating crop evapotranspiration from reference evapotranspiration and crop coefficients. University of Nebraska-Lincoln, USA, NebGuide, 1994; http://extension.unl.edu/publications.

Martins, J. D. et al., Dual crop coefficients for maize in southern Brazil: model testing for sprinkler and drip irrigation and mulched soil. Biosyst. Eng.., 2013, 115, 291–310.

Jensen, M. E., Option by agricultural plants. In Water Deficits and Plant Growth (ed. Kozlowski, T. T.), Academic Press, New York, 1968, vol. 2, pp. 1–22.

Doorenbos, J. and Pruitt, W. O., Guidelines for predicting crop water requirements. Irrigation and Drainage Paper No. 24, Food and Agriculture Organization of United Nations (FAO-UNO), Rome, Italy, 1975.

Doorenbos, J. and Pruitt, W. O., Crop water requirements. FAO Irrigation Drainage Paper No. 24, FAO, Rome, Italy, 1977.

Burman, R. D., Nixon, P. R., Wright, J. L. and Pruitt, W. O., Water requirements, In Design of Farm Irrigation Systems (ed. Jensen, M. E.), ASAE Monograph, American Society of Agricultural Engineers, St. Joseph, MI, USA, 1980, pp. 189–232.

Allen, R. G., Pereira, L. S., Raes, D. and Smith, M., Crop evapotranspiration: guidelines for computing crop water requirements. Irrigation and Drainage Paper 56, UN-FAO, Rome, Italy, 1998.

Allen, R. G. and Pereira, L. S., Estimating crop coefficients from fraction of ground cover and height. Irrig. Sci., 2009, 28, 17–34.

Parekh, F., Crop water requirement using single and dual crop coefficient approach. Int. J. Innov. Res. Sci. Eng. Technol., 2013, 2, 4493–4499.

Shekhawat, K., Rathor, S. S., Premi, O. P., Kandpal, B. K. and Chauhan, J. S., Advances in agronomic management of Indian mustard (Brassica juncea (L.) Czernj. Cosson): an overview. Int. J. Agron., 2012, 2012, 1–14.

Parihar, S. S. and Sandhu, B. S., Irrigation of field crops: principles and practices. Indian Council of Agricultural Research, New Delhi, 1987, p. 142.

Shankar, V., Ojha, C. S. P. and Hari Prasad, K. S., Irrigation scheduling for maize and Indian-mustard based on daily crop water requirement in a semi-arid region. World Acad. Sci., Eng. Technol., 2012, 63, 563–572.

Pradhan, S., Sehgal, V. K., Das, D. K., Jain, A. K., Bandhyopadhyay, K. K., Singh, R. and Sharma, P. K., Effect of weather on seed yield and radiation and water use efficiency of mustard cultivars in a semi-arid environment. Agric. Water Manage., 2014, 139, 43–52.

Amoah, L. K., Darko, R. O. and Sekyere, J. D., Water requirement, deficit irrigation and crop coefficient of hot pepper (Capsicum frutescens var legon 18) using irrigation interval of two days. ARPN J. Agric. Biol. Sci., 2013, 8, 139–146.

Howell, T. A., Schneider, A. D. and Jensen, M. E., History of lysimeter design and use for evapotranspiration measurement. In Proceeding of International Symposium on Lysimetry, Honolulu, Hawaii, 23–25 July 1991, pp. 1–9.

Doorenbos, J. and Kassam, A. H., Yield response to water. FAO Irrigation and Drainage Paper No. 33, FAO, Rome, Italy, 1979.

Jensen, M. E., Burman, R. D. and Allen, R. G., Evapotranspiration and irrigation water requirements. ASCE Manuals and Reports on Engineering Practice, ISBN 978-0872627635, No. 70, 1990.

Majnooni-Heris, A., Sadraddini, A. A., Nazemi, A. H., Shakiba, M. R., Neyshaburi, M. R. and Tuzel, I. H., Determination of single and dual crop coefficients and ratio of transpiration to evapotranspiration for canola. Ann. Biol. Res., 2012, 3(4), 1885–1894.

Shenkut, A., Tesfaye, K. and Abegaz, F., Determination of water requirement and crop coefficient for sorghum (Sorghum bicolor L.) at Melkassa, Ethiopia. Sci., Technol. Arts Res. J., 2013, 2(3), 16–24.

Silva, V., Borges, C., Farias, C., Singh, V. P., Albuquerque, W. G. and Silva, B. B., Water requirements and single and dual crop coefficients of sugarcane grown in a tropical region. Braz. Agric. Sci., 2012, 3, 274–286.

Adak, T., Chakravarty, N. V. K., Muthukumar, M., Deshmukh, P. S., Joshi, H. C. and Katiyar, R. K., Evaluation of biomass and thermal energy utilization efficiency of oilseed Brassica (Brassica juncea) under altered microenvironments. Biomass Bioenerg., 2011, 35, 2254–2267.

Modelling Vadose Zone Processes for Assessing Groundwater Recharge in Semi-Arid Region

Abstract Views :227 | PDF Views:70

Authors

A. T. Dandekar ¹, D. K. Singh ², A. Sarangi ², A. K. Singh ³

Affiliations
1 College of Agriculture, B. Gudi, University of Agricultural Science-Raichur, Raichur 585 287, IN
2 Water Technology Centre, Indian Agricultural Research Institure, New Delhi 110 012, IN
3 Rajmata Vijayaraje Scindia Krishi Vishwavidyalaya, Gwalior 474 002, IN

Source

Current Science, Vol 114, No 03 (2018), Pagination: 608-618

Abstract

Normally groundwater recharge is estimated using methods based on water balance, water table fluctuations, fixed factor of annual rainfall and tracer movement. In many of these methods water stored in the vadose zone and evapotranspiration are not accounted properly. These factors control groundwater recharge to a large extent, particularly in arid and semi-arid regions which are normally characterized by a deep water table, thick vadose zone and high evapotranspiration. In this study, HYDRUS-1D and MODFLOW models were used to assess the recharge flux and groundwater recharge in an area under a semi-arid region giving due consideration to important vadose zone processes. Cumulative recharge flux at water table in various sub-areas varied from 20.01 cm to 23.43 cm (29.26% to 34.26% of the monsoon rainfall). The average groundwater recharge was 22.2%. Total surface runoff in various sub-areas varied from 3.39 cm to 14.36 cm (5% to 21% of the monsoon rainfall). Evapotranspiration was found to be a major recharge controlling factor. Reference evapotranspiration varied from 37.19 cm to 45 cm (54% to 66% of the monsoon rainfall). Natural recharge under the prevailing pumping rate and pumping schedule was 23.3% of the monsoon rainfall. Simulation results revealed that if all the surface runoff is retained in the area, water table will rise by 1.46 m.

Keywords

Groundwater Recharge Modelling, HYDRUS and MODLFOW, Semi-Arid Region, Vadoze Zone Processes.

Full Text

References

Scanlon, B. R. et al., Global synthesis of groundwater recharge in semiarid and arid regions. Hydrol. Process., 2006, 20, 3335–3370.

Theis, C. V., Amount of ground-water recharge in the Southern High Plains. In Proceedings of American Geophysical Union Trans 18th Annual Meeting, 1937, pp. 564–568.

Theis, C. V., Ground Water Note. American Society of Civil Engineers. Civil Engineering, 1940, pp. 277–280.

Sanford, W., Recharge and groundwater models: an overview. J. Hydrol., 2002, 10, 110–120.

Sophocleous, M., Groundwater recharge in groundwater. In Encyclopedia of Life Support Systems (EOLSS) (eds Silveira, L., Wohnlich, S. and Usunoff, E. J.), Developed under the Auspices of the UNESCO, Eolss Publishers, Oxford, UK, 2004; http://www.eolss.net

Keese, K. E., Scanlon, B. R. and Reedy, R. C., Assessing controls on diffuse groundwater recharge using unsaturated flow modelling. Water Resour. Res., 2005, 41, W06010, WR003841.

Lerner, D. N., Issar, A. S. and Simmers, I., Groundwater recharge: a guide to understanding and estimating natural recharge. Rep. 8. International Association of Hydrogeologists, Kenilworth, UK, 1990.

Cook, P. G. and Kitty, S., A helicopter-borne electromagnetic survey to delineate groundwater recharge rates. Water Resour. Res., 1992, 28, 2953–2961.

Rockhold, M. L., Fayer, M. J., Kincaid, C. T. and Gee, G. W., Estimation of natural groundwater recharge for the performance assessment of a low-level waste disposal facility at the Hanford site, Rep. PNL-10508, Pacific Northwest National Laboratory, Richland, Washington, 1995.

Kearns, A. K. and Hendrickx, J. M. H., Temporal variability of diffuse groundwater recharge in New Mexico, N.M. Water Resource Research Institute, Soccoro, Tech. Rep. No. 309, 1998, pp. 43.

Zomorodi, K., Evaluation of the response of a water table to a variable recharge rate. J. Hydrolog. Sci., 1991, 36, 67–78.

Allison, G. B., Gee, G. W. and Tyler, S. W., Vadose-zone techniques for estimating groundwater recharge in arid and semiarid regions. Soil Sci. Soc. Am. J., 1994, 58, 6–14.

Twarakavi, N. K. C., Simunek, J. and Seo, S., Evaluating interactions between groundwater and Vadose zone using the HYDRUS-based flow package for MODFLOW. Vadose Zone J., 2008, 7, 757–768.

Scanlon, B. R., Healy, R. W. and Cook, P. G., Choosing appropriate techniques for quantifying groundwater recharge. Hydrogeol. J., 2002, 10, 18–39.

Gee, G. W. and Hillel, D., Groundwater recharge in arid regions: Review and critique of estimation methods. Hydrol. Process., 1988, 2, 255–266.

De Vries, J. J. and Simmers, I., Groundwater recharge: an overview of processes and challenges. J. Hydrol., 2002, 10, pp. 5–17.

Small, E. E., Climatic controls on diffuse groundwater recharge in semi-arid environments of the southwestern United States. Water Resour. Res., 2005, W04012; doi:10.1029/2004WR003193.

Nolan, B. T., Healy, R. W., Taber, P. E., Perkins, K., Hitt, K. J. and Wolock, D. M., Factors influencing ground-water recharge in the eastern United States, J. Hydrol., 2007, 332, 187–205; doi:10.1016/j.jhydrol.2006.06.029.

Rao, G. V. V. S., Groundwater recharge process and groundwater flow modelling: examples in granitic terrain. In Proceedings of 2nd International Conference on Hydrology and Watershed Management ‘Improving Water Productivity in the Agriculture’, organized by Centre for Water Resources, JNTU Institute of Science and Technology, JNTU, Hyderabad. Key Note Paper on Groundwater Recharge and Modeling, 2006, I, 485–503.

Feddes, R., Rooij, D. E. and Van Dam. J., Unsaturated zone modelling: progress, challenges and applications, V-6. Wageningen UR Frontis Series, 2004, pp. 179–208.

Ward, S., Recharge and groundwater models: An overview. Hydrogeol. J., 2002, 10, 110–120.

Seo, H. S., Simunek, J. and Poeter, E. P., Documentation of the HYDRUS package for MODFLOW-2000, the U.S. Geological Survey modular ground-water model. GWMI 2007-01. International Ground Water Modelling Centre, Colorado School of Mines, Golden, 2007.

Harbaugh, A. W., Banta, E. R., Hill, M. C. and McDonald, M. G., MODFLOW-2000, the US Geological Survey modular groundwater model user guide to modularization concepts and the ground-water flow process. USGS, Denver, CO, 2000.

Anuraga, T. S., Ruiz, L., Mohankumar, M. S., Sekhar, M. and Leijnse, A., Estimating groundwater recharge using land use and soil data: a case study in south India. Agric. Water Manage., 2006, 84, 65–76.

G. E. C., Ground Water Estimation Methodology. Report of the Ground Water Estimation Committee, Ministry of Irrigation, Government of India, New Delhi, 1982, p. 39.

G. E. C., Groundwater Resource Estimation Methodology. Report of the Groundwater Resource Estimation Committee, Ministry of Water Resources, Government of India, New Delhi, 1997, p. 100.

Kinzelbach, W. et al., A survey of methods for groundwater recharge in arid and semi-arid regions. Early Warning and Assessment Report Series, UNEP/DEWA/RS.02-2. United Nations Environment Programme, Nairobi, Kenya, 2002.

van Genuchten, M. Th., A closed-form equation for predicting the hydraulic conductivity of unsaturated soils. Soil Sci. Soc. Am. J., 1980, 44, 892–898.

Mualem, Y., A new model predicting the hydraulic conductivity of unsaturated porous media. Water Resour. Res., 1976, 12, 513–522.

Simunek, J. and Bradford, S. A., Vadose zone modelling: introduction and importance. Vadose Zone J., 2008, 7, 581–586.

McDonald, M. G. and Harbaugh, A. W., MODFLOW, A modular three-dimensional finite difference ground-water flow model, US Geological Survey, Open-file report Chapter A1, 1988, pp. 83–875.

Vetterlein, E., Bodenphysikalische Kennwerte fur SubstratHorizont-Gruppen. In Bodenwasserregulierung (ed. Koepke, V.), Muncheberg, Germany, 1989.

INSTAAR, University of Colorado, 1 June 2009; http://instaar.colorado.edu/deltaforce

Khalil Ajdary., Singh, D. K., Singh, A. K. and Manoj Khanna, Modelling of nitrogen leaching from experimental onion field under drip fertigation. Agric. Water Manag., 2007, 89, 15–28.

Feike, J. leij W., Russell, B. and Scott, M. L., Closed form expressions for water retention and conductivity data. Ground Water, 1997, 35(5), 848–858.

Sukhija, B. S., Reddy, D. V. and Nagabhushanam, P., Groundwater recharge in semi-arid regions of India: an overview of results obtained using tracers. Hydrogeology J., 1996, 4(3), 50–71.

Rangarajan, R. and Athavale, R. N., Annual replenishable ground water potential of India–an estimate based on injected tritium studies. J. Hydrol., 2000, 234, 35–83.

Narasimha Reddy, T. et al., Water balance model and groundwater flow model in Dulapally basin, AP, GWD, A.P. Tech. Rep. Res. Series No. 9, 1991, p. 85.

Sukhija, B. S. and Rao, A. A., Environmental tritium and radiocarbon studies in the Vedavati River Basin, Karnataka and Andhra Pradesh, India. J. Hydrol., 1983, 60, 185–196.

Scanlon, B. R., Mukherjee, A., Gates, J., Reedy, R. C. and Sinha, A. K., Groundwater recharge in natural dune systems and agricultural ecosystems in the Thar Desert region, Rajasthan, India. Hydrogeol. J., 2010; doi:10.1007/s10040-009-0555-7.

Shivanna, K., Kulkarni, U. P., Joseph, T. B. and Navada, S. V., Contribution of storm to groundwater in semi-arid regions of Karnataka, India. Hydrol. Proc., 2004, 18, 473–485.

Temporal Change and Flow Velocity Estimation of Patseo Glacier, Western Himalaya, India

Abstract Views :248 | PDF Views:91

Authors

K. K. Singh ¹, D. K. Singh ¹, H. S. Negi ¹, A. V. Kulkarni ², H. S. Gusain ¹, A. Ganju ¹, K. Babu Govindha Raj ³

Affiliations
1 Snow and Avalanche Study Establishment, Chandigarh 160 036, IN
2 Divecha Centre for Climate Change, Indian Institute of Science, Bengaluru 560 012, IN
3 Indian Space Research Organization, Head Quarters, New BEL Road, Bengaluru 560 231, IN

Source

Current Science, Vol 114, No 04 (2018), Pagination: 776-784

Abstract

In the present study we estimate the velocity and thickness of the Patseo glacier, Himachal Pradesh, India. The average velocity of the glacier was estimated as ~5.47 m/year using co-registration of optically sensed images and correlation (COSI-Corr) method. The glacier thickness was found to vary between 12 and 278 m, with an average value 59 m. The total glacier ice volume was estimated as ~15.8 × 10⁷ m³, with equivalent water reservoir of ~14.5 × 10⁷ m³. Ground penetrating radar (GPR) surveys were conducted during 2004 and 2013 for validation of the estimated glacier thickness. The glacier thickness estimated using COSI-Corr method was found to be in agreement with GPR-retrieved glacier thickness (RMSE = 4.75 m; MAE = 3.74 m). The GPR profiles collected along the same geographic locations on the glacier during 2004 and 2013 showed a reduction in ice thickness of ~1.89 m, and thus resulting in an annual ice thickness decrease of ~0.21 m. The glacier area was estimated for 2004 and 2013 using LISS IV satellite data and found to be ~2.52 and ~2.30 sq. km respectively. This shows an annual reduction of ~0.024 sq. km in glacier area. The total annual loss in glacier ice volume was estimated as ~4.55 × 10⁵ m³. This loss in the glacier ice volume of the Patseo glacier is supported by the snow and meteorological observations collected at a nearby field observatory of Snow and Avalanche Study Establishment (SASE). The climate data collected at SASE meteorological observatory at Patseo (3800 m), between 1993–94 and 2014–15 showed an increasing trend in the mean annual temperature and a decreasing trend in winter precipitation.

Keywords

Glaciers, Ground Penetrating Radar Surveys, Velocity and Thickness Estimation, Winter Precipitation.

Full Text

References

Oerlemans, J., Extracting climate signals from 169 glacier records. Science, 2005, 308, 675–677.

Wagnon, P. et al., Four years of mass balance on Chhota Shigri Glacier, Himachal Pradesh, India, a new benchmark glacier in the western Himalaya. J. Glaciol., 2007, 53, 603–611.

Kaab, A., Chiarle, M., Raup, B. and Schneider, C., Climate change impacts on mountain glaciers and permafrost. Global Planet. Change, 2007, 56, vii–ix.

Tawde, S. A., Kulkarni, A. V. and Bala, G., Estimation of glacier mass balance on a basin scale: an approach based on satellitederived snowlines and a temperature index model. Curr. Sci., 2016, 111(12), 1077–1989.

Joughin, I., Ice sheet velocity mapping: a combined interferometric and speckle-tracking approach. Ann. Glaciol., 2002, 34, 195–201.

Strozzi, T., Luckman, A., Maurray, T., Wegmuller, U. and Wener, C. I., Glacier motion estimation using SAR offset-tracking procedure. IEEE Trans. Geosci. Remote Sensing, 2002, 40(11), 2384–2391.

Kimura, H., Kanamori, T., Wakabayashi, H. and Nishio, F., Ice sheet motion in inland Antarctica from JERS-1 SAR interferometry. IEEE Int. Geosci. Remote Sensing, 2004, 1–7, 3018–3020.

Scambos, T. A. et al., Application of image cross-correlation to the measurement of glacier velocity using satellite image data. Remote Sensing Environ., 1992, 42(3), 177–186.

Rolstad, C. et al., Visible and near-infrared digital images for determination of ice velocities and surface elevation during a surge on Osbornebreen, a tidewater glacier in Svalbard. Ann. Glaciol., 1997, 24, 255–261.

Herman, F., Anderson, B. and Leprince, S., Mountain glacier velocity variation during a retreat/advance cycle quantified using sub-pixel analysis of ASTER images. J. Glaciol., 2011, 57(202), 197–207.

Leprince, S. et al., Monitoring earth surface dynamics with optical imagery. EOS Trans., 2008, 89(1), 1–2.

Tiwari, R. K., Gupta, R. P. and Arora, M. K., Estimation of surface ice velocity of Chhota-Shigri glacier using sub-pixel ASTER image correlation. Curr. Sci., 2014, 106(6), 853–859.

Gantayat, P., Kulkarni, A. V. and Srinivasan, J., Estimation of ice thickness using surface velocities and slope: case study at Gangotri Glacier, India. J. Glaciol., 2014, 60(220), 277–282.

Negi, H. S., Saravana, G., Rout, R. and Snehmani, Monitoring of great Himalayan glaciers in Patsio region, India using remote sensing and climatic observations. Curr. Sci., 2013, 105(10), 1383–1392.

Leprince, S., Barbot, S., Ayoub, F. and Avouac, J. P., Automatic and precise orthorectification, coregistration, and subpixel correlation of satellite images, application to ground deformation measurements. IEEE Trans. Geosci. Remote Sensing, 2007, 45(6), 1529–1558.

Farinotti, D., Huss, M., Bauder, A., Funk, M. and Truffer, M., A method to estimate ice volume and ice-thickness distribution of alpine glaciers. J. Glaciol., 2009, 55(191), 422–430.

Haeberli, W. and Hoelzle, M., Application of inventory data for estimating characteristics of and regional climate-change effects on mountain glaciers: a pilot study with the European Alps. Ann. Glaciol., 1995, 21, 206–212.

Kamb, B. and Echelmeyer, K. A., Stress-gradient coupling in glacier flow: I. Longitudinal averaging of the influence of ice thickness and surface slope. J. Glaciol., 1986, 32(111), 267–284.

Cuffey, K. M. and Paterson, W. S. B., The Physics of Glaciers, Butterworth-Heinemann, Oxford, 2010, 4th edn.

Jiracek, G. R. and Bentley, C. R., Velocity of electromagnetic waves in Antarctic ice. Antarct. Res. Ser., 1971, 16, 199–208.

Robin, G. D. E. Q., Velocity of radio waves in ice by means of a bore-hole interferometric technique. J. Glaciol., 1975, 15(73), 151–159.

Basnett, S., Kulkarni, A. V. and Bolch, T., The influence of debris cover and glacial lakes on the recession of glaciers in Sikkim Himalaya, India. J. Glaciol., 2013, 59(218), 1–12.

Ulaby, F. T., More, R. K. and Fung, A. K., Microwave Remote Sensing: Active and Passive. Volume III from Theory to Applications, Artech House, Inc, USA, 1986.

Modelling of Climate-Induced Groundwater Recharge for Assessing Carbon Emission from Groundwater Irrigation

Abstract Views :275 | PDF Views:84

Authors

G. T. Patle ¹, D. K. Singh ², A. Sarangi ²

Affiliations
1 Department of Irrigation and Drainage Engineering, College of Agricultural Engineering and Post Harvest Technology, Central Agricultural University, Gangtok 737 135, IN
2 Water Technology Centre, Indian Agricultural Research Institute, New Delhi 110 012, IN

Source

Current Science, Vol 115, No 1 (2018), Pagination: 64-73

Abstract

In this study impact of climate change on groundwater recharge is investigated and the carbon emission from groundwater irrigation is assessed under projected climate change scenarios for Karnal district of Haryana state in India. HYDRUS-1D and MODFLOW models were used to simulate the climate change impacts on groundwater recharge for different projected climate change scenarios. Simulation results showed that groundwater recharge would increase marginally by 2030 over the baseline year of 2008 under the scenario based on ARIMA predictions, which considered the effect of all climate parameters. However, under the scenarios, which considered only rise in temperature, groundwater recharge would decrease by 0.07–0.22 m. Rise in temperature by 3.5°C and 4.3°C along with 9% and 16% increase in rainfall over the base year would increase the recharge by 0.09 m and 0.14 m respectively. The study also revealed that the effect of climate change on cumulative recharge would be more in sugarcane fields than in rice fields. Carbon emission of groundwater irrigation under the scenarios based on rise in temperature only would increase by a minimum of 12 kg CO₂/ha in pearl millet crop by the year 2030 to a maximum of 3250 kg CO₂/ha for sugarcane crop by the end of this century. Estimated total carbon emission in 2030 would be 345,857 metric tonne from groundwater irrigation in Karnal district which is 87,474 metric tonne more than the baseline emission.

Keywords

Climate Change, Carbon Emission, Groundwater Modelling, Groundwater Recharge, HYDRUS, MODFLOW.

Full Text

References

CWC, Water and related statistics. Information system organization Water planning and project wing, Central Water Commission, 2010, 1–264.

Patle, G. T., Singh, D. K. and Sarangi, A., Modelling of declining groundwater depth in Kurukshetra district, Haryana, India. Curr. Sci., 2016, 111(4), 717–723.

Mall, R. K., Bhatla, R. and Pandey, S. N., Water resources in India and impact of climate change. Jalvigyan Sameeksha (Ministry of Water Resources), 2007, 22, 157–176.

Stoll, S., Hendricks, Franssen H. J., Butts, M. and Kinzelbach, W., Analysis of the impact of climate change on groundwater related hydrological fluxes: a multi-modal approach including different downscaling methods. Hydrol. Earth Syst. Sci., 2011, 15(1), 21–38.

Brouyere, S., Carabin, G. and Dassargues, A., Climate change impacts on groundwater resources: modelled deficits in a chalky aquifer, Geer basin, Belgium. Hydrogeol. J., 2004, 12(2), 123–134.

Ranjan, S. P., Kazama, S. and Sawamoto, M., Effects of climate and land use changes on groundwater resources in coastal aquifers. J. Environ. Manage., 2006, 80(1), 25–35.

Jyrkama, M. I. and Sykes, J. F., The impact of climate change on spatially varying groundwater recharge in the Grand River watershed (Ontario). J. Hydrol., 2007, 338(3), 237–250.

Ella, V. B., Simulating the hydraulic effects of climate change on groundwater resources in a selected aquifer in the Philippines using a numerical groundwater model. SEARCA Agriculture and Development discussion paper series no. 1, 2011, pp. 1–40.

IPCC, Climate change 2007: the physical science basis. Contribution of working group I to the fourth assessment report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.

Eckhardt, K. and Ulbrich, U., Potential impacts of climate change on groundwater recharge and stream flow in a central European low mountain range. J. Hydrol., 2003, 284(1), 244–252.

Scibek, J. and Allen, D. M., Modeled impacts of predicted climate change on recharge and groundwater levels. Water Resour. Res., 2006, 42(11), 1–18.

Allen, D. M., Mackie, D. C. and Wei, M., Groundwater and climate change: a sensitivity analysis for the Grand Forks aquifer, southern British Columbia, Canada. Hydrogeol. J., 2004, 12(3), 270–290.

Thampi, S. G. and Raneesh, K. Y., Impact of anticipated climate change on direct groundwater recharge in a humid tropical basin based on a simple conceptual model. Hydrol. Process, 2012, 26(11), 1655–1671.

Herrera-Pantoja, M. and Hiscock, K. M., The effects of climate change on potential groundwater recharge in Great Britain. Hydrol. Process, 2008, 22(1), 73–86.

Dams, J., Salvadore, E., Van Daele T., Ntegeka, V., Willems, P. and Batelaan, O., Spatio-temporal impact of climate change in the groundwater system. Hydrol. Earth Syst. Sci., 2012, 16(5), 1517–1531.

Leterme, B. and Mallants, D., Climate and land use change impacts on groundwater recharge. Proceedings Model CARE 2011 held at Leipzig, Germany, 2011 (IAHS Publ. 3XX, 201X).

Leterme, B., Mallants, D. and Jacques, D., Sensitivity of groundwater recharge using climatic analogues and HYDRUS-1D. Hydrol. Earth Syst. Sci., 2012, 16(8), 2485–2497.

Karimi, P., Qureshi, A. S., Bahramloo, R. and Molden, D., Reducing carbon emissions through improved irrigation and ground-water management: A case study from Iran. Agric. Water Manage., 2012, 108, 52–60.

Wang, J., Rothausen, S. G. S. A., Conway, D., Zhang, L., Xiong, W., Holman, I. P. and Li, Y., China’s water–energy nexus: green-house-gas emissions from groundwater use for agriculture. Environ. Res. Lett., 2012, 7, 1–10.

Sugden, C., Carbon footprint of agricultural development: the potential impact of uptake of small electric and diesel pumps in five countries in Sub Saharan Africa. Stockholm Environment Institute, Working Paper, 2010, pp. 1–23.

NPC, State-wise Electricity Consumption and Conservation Potential in India: a summary report prepared by National Productivity Council (NPC) for Bureau of Energy Efficiency (BEE) Ministry of Power, Government of India, 2009, pp. 1–206; www.emtindia.net/eca2009/14Dec2009/combined summary report.pdf (assessed on 28 June 2013).

Siebert, S., Burke, J., Faures, J. M., Frenken, K., Hoogeveen, J., Doll, P. and Portmann, F. T., Groundwater use for irrigation – a global inventory. Hydrol. Earth Syst. Sci., 2010, 14, 1863–1880.

Simunek, J., van Genuchten, M Th. and Sejna, M., The HYDRUS-1D software package for simulating the movement of water, heat and multiple solutes in variably saturated media, Version 4.0. Department of Environmental Sciences, University of California Riverside, Riverside, California, USA, 2009, p. 270.

Richards, L. A., Capillary conduction of liquids through porous mediums. Physics, 1931, 1, 313.

Patle, G. T., Singh, D. K., Sarangi, A. and Sahoo, R. N., Modelling of groundwater recharge potential from irrigated paddy field under changing climate. Paddy Water Environ., 2017, 15, 413–423.

McDonald, M. C. and Harbaugh, A. W., MODFLOW, A modular three-dimensional finite difference ground-water flow model. US Geological Survey, Open-file report, 1988, pp. 83–875, Chapter A1.

Mualem, Y., A new model for predicting the hydraulic conductivity of unsaturated porous media. Water Resour. Res., 1976, 12(3), 513–522.

Hanay, A., Biiyiiksonmez, F., Kiziloglu, F. M. and Canbolat, M. Y., Reclamation of saline-sodic soils with gypsum and MSW compost. Compost. Sci. Util., 2004, 12(2), 175–179.

Belmans, C., Wesseling, J. G. and Feddes, R. A., Simulation of the water balance of cropped soil: SWATRE. J. Hydrol., 1983, 63, 271–286.

Feddes, R. A., Kowalik, P. J. and Zaradny, H., Simulation of field water use and crop yield. Center for Agricultural Publishing and Documentation, 1978.

Phogat, V., Yadav, A. K., Malik, R. S., Kumar, S. and Cox, J., Simulation of salt and water movement and estimation of water productivity of rice crop irrigated with saline water. Paddy Water Environ., 2010, 8(4), 333–346.

Ravikumar, V., Vijayakumar, G., Simunek, J., Chellamuthu, S., Santhi, R. and Appavu, K., Evaluation of fertigation scheduling for sugarcane using a vadose zone flow and transport model. Agric. Water Manage., 2011, 98(9), 1431–1440.

Wesseling, J. G., Introduction of the occurrence of high ground-water levels and surface water storage in computer program SWATRE, Nota 1636, Institute for Land and Water Management Research (ICW), Wageningen, The Netherlands, 1991.

CGWB, Ground water information booklet Karnal district, Haryana. Central Ground Water Board, Ministry of Water Resources, Chandigarh, 2007, pp. 1–19; http://cgwb.gov.in/District_Profile/Haryana/Karnal.pdf

INCCA, Climate change and India: a 4 x 4 assessment. A sectoral and regional analysis for 2030s. Ministry of Environment and Forests, Government of India, 2010, 1–64; http://www.moef.nic.in/downloads/public-information/fin-rpt-incca.pdf

Kumar, K. K., Patwardhan, S. K., Kulkarni, A., Kamala, K., Rao, K. K. and Jones, R., Simulated projections for summer monsoon climate over India by a high-resolution regional climate model (PRECIS). Curr. Sci., 2011, 101(3), 312–326.

Patle, G. T., Singh, D. K., Sarangi, A. and Khanna, M., Managing CO2 emission from groundwater pumping for irrigating major crops in trans indogangetic plains of India. Clim. Change, 2016, 136, 265–279.

Sood, J., Demand side management of India. Bureau of energy efficiency, 2010; forumofregulators.gov.in/Reference/BEE_NPTI_16.11.10.ppt.

Ficklin, D. L., Luedeling, E. and Zhang, M., Sensitivity of groundwater recharge under irrigated agriculture to changes in climate, CO₂ concentrations and canopy structure. Agric. Water Manage., 2010, 97(7), 1039–1050.

Abiye, T. A., Legesse, D. and Abate, H., Impact of climate change on groundwater recharge: a case study from the Ethiopian Rift. Groundwater and Climate in Africa, Proceedings of the Kampala Conference, IAHS Publication, 2009, 334, 174–180.

Patle, G. T., Singh, D. K., Sarangi, A., Rai, A., Khanna, M. and Sahoo, R. N., Temporal variability of climatic parameters and potential evapotranspiration. Indian J. Agric. Sci., 2013, 83(4), 518–524.

Patle, G. T., Singh, D. K., Sarangi, A., Rai, A., Khanna, M. and Sahoo, R. N., Time series analysis of groundwater levels and projection of future trend. J. Geol. Soc. India, 2015, 85, 232–242.

Assessing Water Footprints and Virtual Water Flows in Gomti River Basin of India

Abstract Views :191 | PDF Views:69

Authors

Santosh S. Mali ¹, D. K. Singh ², A. Sarangi ², S. S. Parihar ²

Affiliations
1 ICAR-Research Complex for Eastern Region, Research Centre, Ranchi 834 010, IN
2 Water Technology Centre, Indian Agricultural Research Institute, New Delhi 110 012, IN

Source

Current Science, Vol 115, No 4 (2018), Pagination: 721-728

Abstract

This article analyses the blue, green and grey water footprints and virtual water flows within the Gomti river basin (GRB) in India. Assessments were made at spatial resolution of agricultural production units (APUs). An APU is a homogeneous spatial unit delineated on the basis of soil type, agro-ecological region and district boundaries. Water footprints of crop production and consumption were compared to arrive at virtual water balance within the GRB. Results show that water footprint of GRB was 12,773 million m³ year^–1. Crop production was the largest water consumer accounting for 95.5% of water footprint within the basin. The higher proportion of blue water footprint (47.3%) indicates the dependence of GRB on irrigated agriculture. Contribution of rainfed agriculture to total water footprint was about 11.2%. Considerable portion of blue water is used in the production of low value water-intensive crops. The GRB was assessed as a net virtual water importer, indicating its dependence on the water resources of other river basins; it imports 2945 million m³ virtual water annually. This scenario can be changed if the area allocated to different water-intensive crops is optimized and limited to the extent that meets the consumption needs within the basin, leading to reduction in production surplus of these crops.

Keywords

Economic Water Productivity, River Basin, Virtual Water Flow, Water Footprint.

Full Text

References

Postel, S. L., Daily, G. C. and Ehrlich, P. R., Human appropriation of renewable freshwater. Science, 1996, 271(5250), 785–788.

Vorosmarty, C. J. et al., Global threats to human water security and river biodiversity. Nature, 2010, 467, 555–561.

UNICEF, FAO and SaciWATERs, Water in India: Situation and Prospects, 2013, p. 91.

Hoekstra, A. Y. and Chapagain, A. K., Water footprints of nations: water use by people as function of their consumption pattern. Water Res. Manage, 2007, 21, 35–48.

Liu, J. and Savenije, H. H. G., Food consumption patterns and their effect on water requirement in China. Hydrol. Earth Syst. Sci., 2008, 12(3), 887–898.

Hoekstra, A. Y., Chapagain, A. K., Aldaya, M. M. and Mekonnen, M. M., The water footprint assessment manual: setting the global standard 2011, Earthscan, London, UK.

Zeng, Z., Liu, J., Koeneman, P. H., Zarate, E. and Hoekstra, A. Y., Assessing water footprint at river basin level: a case study for the Heihe River Basin in northwest China. Hydrol. Earth Syst. Sci., 2012, 16, 2771–2781.

Aldaya, M. M., Munoz, G. and Hoekstra, A. Y., Water footprint of cotton, wheat and rice production in Central Asia. Value of Water Research Report Series No. 41, UNESCO–IHE, Delft, The Netherlands, 2010.

MOWR, Draft National Water Policy 2012, Ministry of Water Resources, Government of India (GoI), 2012; www.mowr.gov.in (accessed on 15 June 2012).

Dietzenbacher, E. and Velazquez, E., Analysing Andalusian virtual water trade in an input–output framework. Reg. Stud., 2007, 41, 185–196.

Aldaya, M. M. and Llamas, M. R., Water footprint analysis for the Guadiana river basin. Value of Water Research Report Series No. 35, UNESCO–IHE Delft, The Netherlands, 2008.

Liu, C., Carolien K., Hoekstra, A. Y. and Leenes, W. G., Past and future trends in grey water footprints of anthropogenic nitrogen and phosphorus inputs to major world rivers. Ecol. Indic., 2012, 18, 42–49.

Roy, R. and Ahmad, H., State agricultural profile of Uttar Pradesh, Agro-Economic Research Centre, University of Allahabad, 2015.

IISR, Water use efficient technologies for improving productivity and sustainability of sugarcane, Final Report of FPARP, Indian Institute of Sugarcane Research, Lucknow, 2011.

Srivastava, S. K. and Kumar Rand Singh, R. P., Extent of groundwater extraction and irrigation efficiency on farms under different water-market regimes in central Uttar Pradesh. Agric. Econ. Res. Rev., 2009, 22, 87–97.

MOA, Agricultural Statistics at a Glance-2011. Department of Economics and Statistics, Ministry of Agriculture, GoI, 2012; eands.dacnet.nic.in (accessed on July 2012).

ISRO, Bhuvan Thematic Data Services, ISRO’s Geoportal Gateway to Indian earth observation data products and Services, 2012; www.bhuvan.nrsc.gov.in (data received 8 March 2012).

IndiaStat, India’s comprehensive statistics information portal. 2013; www.indiastat.com (accessed on 5 March 2013).

Mali, S. S., Singh, D. K., Sarangi, A., Khanna, M., Parihar, S. S. and Das, D. K., Variability mapping of crop evapotranspiration for water footprint assessment at basin level. Indian J. Soil Conserv., 2015, 43(1), 255–259.

Allen, R. G., Pereira, L. S., Raes, D. and Smith, M., Crop evapotranspiration: guidelines for computing crop water requirements. Irrigation and Drainage Paper 56, Food and Agriculture Organization of the United Nations, Rome, Italy, 1998.

FAO, CROPWAT 8.0, Food and Agriculture Organization of the United Nations, Rome, Italy, 2012; www.fao.org (accessed 1 March 2012).

NICRA-ICAR, District wise daily weather data. National Initiative on Climate Resilient Agriculture, Indian Council of Agricultural Research, New Delhi; http://www.nicra-icar.in (accessed on 11 July 2012).

Doorenbos, J. and Kassam, A. H., Yield response to water. FAOIrrigation and Drainage Paper No. 33. Rome, FAO, Italy, 1979.

NSSO, Household consumption of various goods and services in India, NSS 66th Round, National Statistical Organization, National Sample Survey Office, Ministry of Statistics and Programme Implementation, GoI, Report No. 541, 2012 (66/1.0/3).

Shukla, B. D. and Patil, R. T., Post-harvest management – fights hunger with FAO. India Grains, 2002, 4(3), 20–22.

Savenije, H. H. G., Water scarcity indicators; the deception of the numbers. Phys. Chem. Earth, Part B. 2000, 25, 199–204.

Liu, J., Zehnder, A. J. B. and Yang, H., Global consumptive water use for crop production: the importance of green water and virtual water. Water Resour. Res., 2009, 45, 05428.

Kanwar, R. S., Baker, J. L. and Laflin, J. M., Nitrate movement through the soil profile in relationship to tillage system and fertilizer application method. Trans. ASAE, 1986, 31(2), 453– 460.

Chowdhary, V. M., Rao, N. H. and Sarma, P. B. S., A coupled soil water and nitrogen balance model for flooded rice fields in India. Agric. Ecosyst. Env., 2004, 103, 425–441.

Study of a Snow Avalanche Accident Along Chowkibal–Tangdhar Road in Kupwara District, Jammu and Kashmir, India

Abstract Views :258 | PDF Views:74

Authors

H. S. Gusain ¹, V. D. Mishra ¹, D. K. Singh ¹

Affiliations
1 Snow and Avalanche Study Establishment, Sector 37A, Chandigarh 160036,, IN

Source

Current Science, Vol 115, No 5 (2018), Pagination: 969-972

Abstract

An avalanche accident was occurred on 5 January 2018 on Chowkibal–Tangdhar road in Kupwara district, Jammu and Kashmir about 6 km from Chowkibal village. One light passenger vehicle was swept away in the avalanche and 10 persons lost their lives. In this communication, we study the cause of avalanche accident and simulate the snow avalanche flow using Rapid Mass MovementS model. Total snow depth recorded at the nearest observation location from the accident site was 31 cm and fresh snow of the storm was 24 cm. Avalanche condition on slope was building up and the Snow and Avalanche Study Establishment issued an avalanche warning of ‘Low Danger’ for the Chokibal–Tangdhar road axis. Maximum thickness of avalanche debris on road was observed to be 3.0 m. Flow simulation showed maximum velocity of avalanche to be ~25 ms^–1, maximum impact pressure ~9.39 × 10⁴ kg m^–1 s^–2 and maximum height of avalanche flow ~3.0 m.

Keywords

Avalanche Accident, Mountainous Terrain, Snow Storm.

Full Text

References

McClung, D. and Schaerer, P., The Avalanche Handbook, The Mountaineers Books, Seattle, WA, USA, 1993.

McClung, D. M., Avalanche character and fatalities in the high mountains of Asia. Ann. Glaciol., 2016, 57(71), 114–118.

Ganju, A., Thakur, N. K. and Rana, V., Characteristics of avalanche accidents in western Himalayan region, India. In Proceedings of the International Snow Science Workshop, Penticton, B.C., Canada, 29 September–4 October 2002, pp. 200–207.

Gusain, H. S., Chand, D., Thakur, N., Singh, A. and Ganju, A., Snow avalanche climatology of Indian Western Himalaya. In International Symposium on Snow and Avalanches, Manali, 6–10 April 2009.

Singh, A. and Ganju, A., A supplement to neares-neighbour method for avalanche forecasting. Cold Reg. Sci. Technol., 2004, 39, 105–113.

Singh, A., Srinivasan, K. and Ganju, A., Avalanche forecast using numerical weather prediction in Indian Himalaya. Cold Reg. Sci. Technol., 2005, 43, 83–92.

Joshi, J. C. and Srivastava, S., A Hidden Markov model for avalanche forecasting on Chowkibal–Tangdhar road axis in Indian Himalayas. J. Earth Syst. Sci., 2014, 123(8), 1771–1779.

Joshi, J. C. and Ganju, A., Avalanche warning on Chowkibal– Tangdhar axis (J&K): a hybrid approach. Curr. Sci., 2006, 91(11), 1558.

Gusain, H. S., Mishra, V. D., Arora, M. K., Mamgain, S. and Singh, D. K., Operational algorithm for generation of snow depth maps from discrete data in Indian Western Himalaya. Cold Reg. Sci. Technol., 2016, 126, 22–29.

Buhler, Y., Kumar, S., Veitinger, J., Christen, M., Stoffel, A. and Snehmani, Automated identification of potential snow avalanche release areas based on digital elevation models. Nat. Hazards Earth Syst. Sci., 2013, 13, 1321–1335.

Christen, M., Kowalski, J. and Bartelt, P., RAMMS: numerical simulation of dense snow avalanches in three-dimensional terrain. Cold Reg. Sci. Technol., 2010, 63, 1–14.

Udaria-A New Liverwort Genus of Lophocoleaceae from Eastern Himalaya, India

Abstract Views :252 | PDF Views:78

Authors

D. K. Singh ¹, Shuvadeep Majumdar ², Devendra Singh ²

Affiliations
1 Botanical Survey of India, Kolkata 700 064, IN
2 Botanical Survey of India, Central National Herbarium, Howrah 711 103, IN

Source

Current Science, Vol 115, No 8 (2018), Pagination: 1536-1542

Abstract

A new genus and species of liverwort, Udaria lamellicaulis gen. & sp. nov., referable to the family Lophocoleaceae is described from Arunachal Pradesh and Sikkim in Eastern Himalaya, India. The new taxon can be easily differentiated from hitherto all the known genera of the family in the presence of longitudinal, 1-12 cells high seriately arranged lamelliform strips on the surface of stem, leaves and female bracts, striolate-rugulose leaf cuticle, rhizoids arising from the lamina of underleaves, gynoecia with 1-2 subfloral innovations and gemmiparous female bracts and bracteoles.

Keywords

Bryophytes, Eastern Himalaya, Liverwort, Marchantiophyta, New Genus and Species, Udaria lamellicaulis.

Full Text

References

Pande, S. K., Some aspects of Indian Hepaticology (Presidential address). J. Indian Bot. Soc., 1958, 15, 221-233.

Singh, D. K., Liverworts. In Floristic Diversity and Conservation Strategies in India I (eds Mudgal, V. and Hajra, P. K.), Botanical Survey of India, Dehradun, 1997, pp. 235-300.

Singh, D. K., Singh, S. K. and Singh, D., Liverworts and Hornworts o f India — An Annotated Checklist, Botanical Survey of India, Bhubaneswar, 2016.

Mittermeier, R. A. et al. (eds), Hotspots Revisited: Earth's Biologically Richest and Most Endangered Terrestrial Ecoregions, Conservation International, University of Chicago Press, Chicago, 2005.

Rao, R. R., Floristic diversity of eastern Himalaya - a national heritage for conservation. In Himalayan Biodiversity: Conservation Strategies (ed. Dhar, U.), GB Pant Institute of Himalayan Environment and Development, Nainital, 1993, pp. 133-151.

Takhtajan, A., Flowering Plants, Origin and Dispersal. Oliver and Boyd, Edinburgh, 1969.

Soderstrom, L., Crandall-Stotler, B., Stotler, R. E, Vana, J., Hagborg, A. and von Konrat, M., Notes on early land plants today. 36. Generic treatment of Lophocoleaceae (Marchantiophyta). Phytotaxa, 2013, 97(2), 36-43.

Soderstrom, L. et al., World checklist of hornworts and liverworts. Phytokeys, 2016, 59, 1-828.

Hentschel, J., Feldberg, K., Zundorf, H.-J., Hellwig, F. H., Schneieder, H. and Heinrichs, J., The systematic position of Clasmatocolea and Pachyglossa (Jungermanniopsida: Lophocoleaceae) inferred from nrDNA ITS sequences and morphology. Taxon, 2007, 56(4), 1136-1142.

Srivastava, A. and Srivastava, S. C., Indian Geocalycaceae (Hepaticae) (A Taxonomic Study), Bishen Singh Mahendra Pal Singh, Dehradun, 2002.

Engel, J. J., A monograph of Clasmatocolea (Hepaticae). Fieldiana Bot., 1980, 3, 1-229.

Engel, J. J., Studies on Geocalycaceae (Hepaticae). IV. Lamellocolea, a new genus of Leptoscyphoideae from New Zealand. J. Hattori Bot. Lab., 1991, 70, 63-78.

Engel, J. J. and Glenny, D., Studies on Lophocoleaceae. XX. A new species of Lamellocolea J. J. Engel from New Zealand. Bryologist, 2011, 114(1), 23-27.

Engel, J. J., Studies on Lophocoleaceae XVII. On Leptophyllopsis R. M. Schust., with particular reference to L. laxus (Mitt.) R. M. Schust., together with a new subfamily, Lophocoleaceae subfam. Leptophyllopsoideae J. J. Engel. Nova Hedwigia, 2007, 85, 417-428.

Engel, J. J., Bardat, J. and Thouvenot, L., Studies on Lophocoleaceae XXI. Otoscyphus J. J. Engel, Bardat et Thouvenot, a new liverwort genus from New Caledonia with an unusual morphology. Cryptog., Bryol., 2012, 33(3), 279-289.

Spatio-Temporal Analysis of Drought and Aridity in Gomti Basin

Abstract Views :256 | PDF Views:81

Authors

R. Sarma ¹, D. K. Singh ²

Affiliations
1 Centre for Environment Science and Climate Resilient Agriculture, Indian Agricultural Research Institute, New Delhi 110 012, IN
2 Water Technology Centre, Indian Agricultural Research Institute, New Delhi 110 012, IN

Source

Current Science, Vol 116, No 6 (2019), Pagination: 919-925

Abstract

This study analyses the drought events for the Gomti basin in Uttar Pradesh (UP), India using the standardized precipitation index (SPI) at the spatial and temporal scales. Daily precipitation data for 14 districts in the Gomti basin for 41 years (1971–2011) were used to calculate the SPI for 1-month, 4-month, 6-month and 12-month time scales. Results for the 6-month (June–November) and 12-month time scales were similar and drought years were observed in 1972, 1979, 1987, 1993, 1994, 2002 and 2010. The 4-month SPI was analysed for the main monsoon months in the Gomti basin, i.e. from June to September. Results showed that significant drought occurred during the monsoon months of 1979, 1987, 1993, 2002, 2009 and 2010. For drought analysis at the spatial scale, the Kriging interpolation method available in ArcMap was used. The 12-month SPI showed that the frequency of severe and extreme drought was more in the upper regions of the basin during 1971–2000 whereas drought frequency was more in the central and lower regions of the basin during 2001–2011. Further, the de Martonne aridity index was calculated for the period 1971–2007 and its correlation with the 1-month SPI for the period 1971–2007 was evaluated.

Keywords

De Martonne Aridity Index, Gomti Basin, Kriging Interpolation, Spatial and Temporal Drought Analysis, Standardized Precipitation Index.

Full Text

References

Roy, R. and Ahmad, H., State Agricultural Profile of Uttar Pradesh (2011–12). Agro-Economic Research Centre, University of Allahabad, 2013.

Abeysingha, N. S., Singh, M., Sehgal, V. K., Khanna, M., Pathak, H., Jayakody, P. and Srinivasan, R., Assessment of water yield and evapotranspiration over 1985 to 2010 in the Gomti River basin in India using the SWAT Model. Curr. Sci., 2015, 108(12), 2202–2212.

Wilhite, D. A. and Glantz, M. H., Understanding the drought phenomenon: the role of definitions. Water Int., 1985, 10(3), 111– 120.

India Meteorological Department, Forecaster’s Guide. India Meteorogical Department, Pune, 2008.

Koshy, J. and Vasudeva, V., No more droughts in India, says IMD. The Hindu, 12 January 2016; retrieved from https://www.thehindu.com/ (accessed on 30 October 2018).

World Meteorological Organization, Standardized Precipitation Index User Guide (M. Svoboda, M. Hayes and D. Wood), WMONo. 1090, Geneva, 2012.

McKee, T. B., Doesken, N. J. and Kliest, J., The relationship of drought frequency and duration to time scales, in Proceedings of the 8th Conference on Applied Climatology, 17–22 January Anaheim, CA. American Meteorological Society: Boston, MA, USA, 1993, pp. 179–184.

Hayes, M., Wilhite, D. A., Svoboda, M. and Vanyarkho, O., Monitoring the 1996 drought using the Standardized Precipitation Index. B. Am. Meteorol. Soc., 1999, 80, 429–438.

Mishra, A. K. and Desai, V. R., Spatial and temporal drought analysis in the Kansabati river basin, India. Int. J. River Basin Manage., 2005, 3(1), 31–41.

Du, J., Fang, J., Xu, W. and Shi, P., Analysis of dry/wet conditions using the standardized precipitation index and its potential usefulness for drought/flood monitoring in Hunan Province, China. Stoch. Env. Res. Risk A, 2013, 27(2), 377–387.

Santos, J. P., Portela, M. M. and Pulido-Calvo, I., Regional frequency analysis of droughts in Portugal. Water Resour. Manage., 2011, 25, 3537–3558.

Pai, D. S., Sridhar, L., Guhathakurta, P. and Hatwar, H. R., Districtwide drought climatology of the southwest monsoon season over India based on standardized precipitation index (SPI). Nat. Hazards, 2011, 59(3), 1797–1813.

Ntale, H. K. and Gan, T. Y., Drought indices and their application to East Africa. Int. J. Climatol., 2003, 23, 1335–1357.

Potop, V., Turkott, L., Koznarova, V. and Mozny, M., Drought episodes in the Czech Republic and their potential effects in agriculture. Theor. Appl. Climatol., 2010, 99, 373–388.

Quan, C., Han, S., Utescher, T., Zhang, C. and Liu, Y., Validation of temperature-precipitation based aridity index: paleoclimatic implications. Palaeogeogr., Palaeoclimatol. Palaeoecol., 2013, 386, 86–95.

Maliva, R. and Missimer, T., Arid lands water evaluation and management. Environmental Science and Engineering, Springer, 2012, pp. 21–39, doi:10.1007/978-3- 642-29104-3_2.

Penck, A. Versuch einer Klimaklassifikation auf physiogeographischer Grundlage. Sitzungsberichte der Preussischen Akademie der Wissenschaften, 1910, 12, 236–246.

Beran, M. A. and Rodier, J. A., Hydrological aspects of drought, studies and reports in hydrology. UNESCO-WMO, 39, Presses Universitaires de France, Paris, 1985.

World Meteorological Organization, Drought and agriculture. WMO Note 138 Publ WMO-392 Geneva-Switzerland, 127, 1975.

Zhang, Q., Xu, C. and Zhang, Z., Observed changes of drought/ wetness episodes in the Pearl River basin, China, using the standardized precipitation index and aridity index. Theor. Appl. Climatol., 2009, 98, 89–99.

Shahid, S., Spatio-temporal variation of aridity and dry period in term of irrigation demand in Bangladesh. Am. Eurasian J. Agric. Environ. Sci., 2010, 7(4), 386–396.

Livada, I. and Assimakopoulos, V. D., Spatial and temporal analysis of drought in Greece using the Standardized Precipitation Index (SPI). Theor. Appl. Climatol., 2007, 89, 143–153.

Borcan, M., Cheval, S. and Chendes, V., Observed variability of drought and aridity and its impact on the hydrological regime in the Barlad catchment (Romania). Geophys. Res. Abstr., 2015, 17.

Lungu, M., Panaitescu, L. and Nita, S., Aridity, climatic risk phenomenon in Dobrudja. Present Environ. Sustainable Develop., 2011, 5(1), 179–189.

Mali, S., Crop water footprint assessment for sustainable agriculture in selected sub- basins of River Ganga, Ph D thesis, PostGraduate School, Indian Agricultural Research Institute, New Delhi, India, 2015.

Rai, R. K., Upadhyay, A., Sarkar, S., Upadhyay, A. M. and Singh, V. P., GIUH based transfer function for Gomti River basin of India. J. Spat. Hydrol., 2009, 9, 24–50.

de Martonne, E., Une nouvelle fanction climatologique: l’indice d’aridité. La Météorologie, 1926, 2, 449–458.

Abeysingha, N. S., Singh, M., Sehgal, V. K., Khanna, M. and Pathak, H., Analysis of rainfall and temperature trends in Gomti river basin. J. Agric. Phys., 2014, 14(1), 56–66.

Jha, S., Sehgal, V. K., Raghava, R. and Sinha, M., Trend of standardized precipitation index during Indian summer monsoon season in agroclimatic zones of India. Earth Syst. Dynam. Discuss., 2013, 4, 429–449.

Hingane, L. S., Rupa Kumar K., and Murty, V. R., Long-term trends of surface air temperature in India. Int. J. Climatol., 1985, 5, 521–528.

Indian Institute of Tropical Meteorology, Pune, Monsoon On-line. https://www.tropmet.res.in/~kolli/MOL/Monsoon/Historical/air.html (accessed on 30 October 2018).

Jamwal, N., India’s criteria for classifying drought-hit regions are causing many cases to go unreported. 27 January 2018. https://scroll.in/article/866262/indias-criteria-for-assifying-drought-hit-regions-are-causing-many-cases-to-go-unreported (accessed on 30 October 2018).

Yue, S. and Hashino, M., Long term trends of annual and monthly precipitation in Japan. J. Am. Water Resour. As., 2003, 39(3), 587–596.

Sarma, R. and Singh, D. K., Homogeneity analysis of climatic parameters for the Gomti river basin. Indian J. Soil Conserv., 2018, 46(1), 25–33.

Wheat Production Functions Under Irrigated Saline Environment and Foliar Potassium Fertigation

Abstract Views :233 | PDF Views:74

Authors

Mukesh Kumar ¹, A. Sarangi ², D. K. Singh ², S. Sudhishri ², A. R. Rao ³

Affiliations
1 Irrigation and Drainage Engineering Division, ICAR-Central Institute of Agricultural Engineering, Bhopal 462 038, IN
2 Water Technology Centre, ICAR-Indian Agricultural Research Institute, New Delhi 110 012, IN
3 ICAR-Indian Agricultural Statistics Research Institute, New Delhi 110 012, IN

Source

Current Science, Vol 118, No 12 (2020), Pagination: 1939-1945

Abstract

A field experiment was conducted for two consecutive years to develop management alternatives for wheat cultivars (salt-tolerant and salt non-tolerant) cultivated under irrigated saline environment (groundwater, 4, 8 and 12 dS m^–1) and foliar potassium fertigation. The grain yield of wheat cultivars decreased with the increase in salinity levels of irrigation water. The foliar potassium fertigation during the heading stage of wheat cultivars ameliorated the adverse effect of salinity and resulted in the increase in grain yield. In this study, empirical equations for wheat yield known as production function have been developed. The production functions were developed keeping grain yield parameter as output, besides the many input parameters pertaining to quantity and quality of the irrigation water, quantity of potassium applied as foliar spray and rainfall depth during the crop growth period. The production function with higher coefficient of determination (R²) may be used to predict grain yield of both salt-tolerant and salt non-tolerant cultivars under different saline irrigation regimes, rainfall and irrigation water depths, besides the dose of potassium sulphate (K²SO₄) for foliar spray. The production function which gave the highest R² value (i.e. 0.82 for KRL-1-4 and 0.97 for HD 2894 wheat cultivars) could be used for foliar spray under different salinity regimes with high expectation of grain yield. The predicted grain yield and estimated quantity of potassium under different salinity levels of irrigation water may prove useful to different stakeholders for enhancing the wheat yield in high saline water areas. The stakeholders can predict the grain yield under similar circumstances as explained in this experiment and estimate the appropriate potassium doses to be applied for enhancing the wheat yield.

Keywords

Foliar Potassium Fertigation, Irrigation Water, Production Function, Salt-Tolerant Cultivar, Wheat Yield.

Full Text

References

Manal, F. M., Thalooth, A. T. and Khalifa, R. K. M., Effect of foliar spraying with uniconazole and micronutrients on yield and nutrients uptake of wheat plants grown under saline condition. J. Am. Sci., 2010, 6(8), 398–404.

Anon., Annual Report 2014, Department of Agriculture and Cooperation, Ministry of Agriculture, Government of India.

Sattar, S., Hussnain, T. and Javaid, A., Effect of NaCl salinity on cotton (Gossypium arboreum L.) grown on MS medium and in hydroponic cultures. J. Anim. Plant Sci., 2010, 20(2), 87–89.

Munns, R. and James, R. A., Screening methods for salinity tolerance: a case study with tetraploid wheat. Plant Soil, 2003, 253, 201–218.

Khan, M. Z., Muhammad, S., Naeem, M. A., Akhtar, E. and Khalid, M., Response of some wheat (Triticum aestivum L.) varieties to foliar application of N&K under rainfed conditions. Pak. J. Bot., 2006, 38(4), 1027–1034.

Tabatabaei, S. J. and Fakhrzad, F., Foliar and soil application of potassium nitrate affects the tolerance of salinity and canopy growth of perennial ryegrass (Lolium perennevar Boulevard). Am. J. Agric. Biol. Sci., 2008, 3(3), 544–550.

Khan, A. and Aziz, M., Influence of foliar application of potassium on wheat (Triticum aestivum L.) under saline conditions. Sci. Technol. Dev., 2013, 32(4), 285–289.

Zheng, Y., Jia, A., Ning, T., Xu, J., Li, Z. and Jiang, G., Potassium nitrate application alleviates sodium chloride stress in winter wheat cultivars differing in salt tolerance. J. Plant Physiol., 2008, 165, 1455–1465.

Dutta, K. K., Sharma, V. P. and Sharma, D. P., Estimation of a production function for wheat under saline conditions. Agric. Water Manage., 1998, 36, 85–94.

Yang-Ren, W., Shao-ZhonglI, K., Fu-Sheng, L., Lu, Z. and Jian-Hua, Z., Saline water irrigation scheduling through a crop– water–salinity production function and a soil–water–salinity dynamic model. Pedosphere, 2007, 17(3), 303–317.

Semerci, A. et al., The production functions of wheat production in Turkey. Bulg. J. Agric. Sci., 2012, 18(2), 240–253.

Zheng, Y., Xu, X., Simmons, M., Zhang, C., Gao, F. and Li, Z., Responses of physiological parameters, grain yield, and grain quality to foliar application of potassium nitrate in two contrasting winter wheat cultivars under salinity stress. J. Plant Nutr. Soil Sci., 2010, 173, 444–452.

Kumar, M., Sarangi, A., Singh, D. K. and Rao, A. R., Modelling the grain yield of wheat in irrigated saline environment with foliar potassium fertilization. Agric. Res., 2018, 7(3), 321–337.

Rosenzweig, C., Iglesias, A., Fischer, G., Liu, Y., Baethgen, W. and Jones, J. W., Wheat yield functions for analysis of land-use change in China. Environ. Model. Assess., 1999, 4, 115–132.

Kumar, M., Sarangi, A., Singh, D. K., Rao, A. R. and Sudhishri, S., Response of wheat cultivars to foliar potassium fertilization under irrigated saline environment. J. Appl. Nat. Sci., 2016, 8(1), 429–436.

Devlin, R. M. and Witham, F. H., Plant Physiology, CBS Publizers and Distributors, New Delhi, 1986, pp. 80–85.

Sairam, R. K. and Tyagi, A., Physiology and molecular biology of salinity stress tolerance in plants. Curr. Sci., 2004, 86, 407–421.

Mesbah, E. A. E., Effect of irrigation regimes and foliar spraying of potassium on yield, yield component and water use efficiency of wheat (Triticum aestivum L.) in sandy soils. World J. Agric. Sci., 2009, 5(6), 662–669.

Sawan, Z. M., Fahmy, A. H. and Yousef, S. E., Direct and residual effects of nitrogen fertilization, foliar application of potassium and plant growth retardant on Egyptian cotton growth, seed yield, seed viability and seedling vigor. Acta Ecol. Sin., 2009, 29,116–123.

Raza, M. A. S., Saleem, M. F., Shah, G. M., Jamil, M. and Khan, I. H., Potassium applied under drought improves physiological and nutrient uptake performances of wheat (Triticum aestivum L.). J. Soil Sci. Plant Nutr., 2013, 13(1), 175–185.

Comparative Evaluation of Reference Evapotranspiration Estimation Models In New Bhupania Minor Command, Jhajjar, Haryana, India

Abstract Views :94 | PDF Views:60

Authors

Venkatesh Gaddikeri ¹, A. Sarangi ², D. K. Singh ¹, K. K. Bandyopadhyay ³, Bidisha Chakrabarti ⁴, S. K. Sarkar ⁵

Affiliations
1 Division of Agricultural Engineering, ICAR-Indian Agricultural Research Institute, New Delhi 110 012, India., IN
2 Water Science and Technology, ICAR-Indian Agricultural Research Institute, New Delhi 110 012, India., IN
3 Division of Agricultural Physics, ICAR-Indian Agricultural Research Institute, New Delhi 110 012, India., IN
4 Centre for Environment Science and Climate Resilient Agriculture, ICAR-Indian Agricultural Research Institute, New Delhi 110 012, India., IN
5 ICAR-Indian Agricultural Statistics Research Institute, New Delhi 110 012, India., IN

Source

Current Science, Vol 124, No 10 (2023), Pagination: 1181-1187

Abstract

Accurate quantification of reference crop evapotran-spiration (ETo) plays a significant role in determining crop water requirements in irrigated agriculture. A plethora of methods for the estimation of ETo are available. However, the regional suitability of these methods needs to be assessed given the limited availa-bility of meteorological data. In this study, daily estimates of 11 ETo models were selected and compared with the FAO-Penman–Monteith equation (FAO-PM). The select-ed methods were Blaney–Criddle (BC), Jaisen–Haise (JH), Hargreaves method (HM), McGuinness–Borndne (MB), Chapman (CM), Abtew model (AM), Turc method (TM), FAO-PM equation, Penman equation (PM), Prie-stley–Taylor (PT) and Matt–Shuttleworth (MS). Evalua-tion of these models was carried out during 2016–20 in the New Bhupania Minor Command of the Dulhera dis-tributary, Western Yamuna Canal Command (WYCC), Haryana, India. The selected models were evaluated to find a substitute for the FAO-PM equation based on different statistical indices. It was observed that the PT method performed best and was in line with the FAO-PM equation with correlation coefficient, root mean square error, mean absolute error, Nash–Sutcliffe co-efficient and mean bias error as 0.92, 0.74, 0.48, 0.83, 0.171 respectively. Based on this study and statistical error indices values, the models can be ranked as PT > CM > TM > JH > AM > PM > MS > HM > BC > MB. Thus, we recommend using the PT model for the esti-mation of ETo in the study area with available meteoro-logical parameters for irrigation scheduling.

Keywords

Canal Command, Climatological Data, Comparative Evaluation, Evapotranspiration Estimation Models, Irrigated Agriculture.

Full Text

References

Pandey, P. K., Dabral, P. P. and Pandey, V., Evaluation of reference evapotranspiration methods for the northeastern region of India. Int. Soil Water Conserv. Res., 2016, 4, 52–63.

Shirmohammadi-Aliakbarkhani, Z. and Saberali, S. F., Evaluating of eight evapotranspiration estimation methods in arid regions of Iran. Agric. Water Manage., 2020, 239, 106243.

Djaman, K., Koudahe, K., Akinbile, C. O. and Irmak, S., Evaluation of eleven reference evapotranspiration models in semiarid conditions. J. Water Resour. Prot., 2017, 9, 1469–1490.

Saggi, M. K. and Jain, S., Reference evapotranspiration estimation and modeling of the Punjab, Northern India using deep learning. Comput. Electron. Agric., 2019, 156, 387–398.

Song, X., Lu, F., Xiao, W., Zhu, K., Zhou, Y. and Xie, Z., Performance of 12 reference evapotranspiration estimation methods compared with the Penman–Monteith method and the potential influences in Northeast China. Meteorol. Appl., 2019, 26, 83–96.

Allen, R. G. et al., Crop evapotranspiration – guidelines for compu-ting crop water requirements FAO Irrigation and Drainage paper 56. FAO, Rome, Italy, 1998, vol. 300(9), pp. 65–79.

Zhao, L. B., Zhao, Y. L. and Jiang, Z. D., Design and fabrication of a piezoresistive pressure sensor for ultra high temperature environ-ment. J. Phys. Conf. Ser., 2006, 48, 178–183.

Lang, D. et al., A comparative study of potential evapotranspiration estimation by eight methods with FAO Penman–Monteith method in southwestern China. Water, 2017, 9, 734.

Todorovic, M., Karic, B. and Pereira, L. S., Reference evapo-transpiration estimate with limited weather data across a range of Mediterranean climates. J. Hydrol., 2013, 481, 166–176.

Gupta, R. and Misra, A. K., Groundwater quality analysis of qua-ternary aquifers in Jhajjar district, Haryana, India: focus on ground-water fluoride and health implications. Alexandria Eng. J., 2018, 57, 375–381.

NABARD, District Project Plan. PLP – 2016–17, Jhajjar district, Haryana, 2016; https://www.nabard.org/demo/auth/writereaddata/ tender/2110161208Haryana-StateFocusPaper-2016-17.split-and-mer-ged.pdf

Doorenbos, J. and Pruitt, W. O., Guidelines for predicting crop water requirements. FAO Irrigation Drainage Paper, 1977, no. 24, pp. 1–144.

Abtew, W., Evapotranspiration measurements and modeling for three wetland systems in South Florida. J. Am. Water Resour. Assoc., 1996, 32, 465–473; https://doi.org/10.1111/k.1752-1688.1996.tb0-4044.x.

Jensen, M. E. and Haise, H. R., Estimating evapotranspiration from solar radiation. J. Irrig. Drain. Div., 1963, 89, 15–41.

Hargreaves, G. H. and Samani, Z. A., Reference crop evapotrans-piration from temperature. Appl. Eng. Agric., 1985, 1, 96–99.

Turc, L., Water requirements assessment of irrigation, potential evapotranspiration: simplified and updated climatic formula. Ann. Agronom., 1961, 12, 13–49.

Penman, H. L., Natural evaporation from open water, bare soil and grass. Proc. R. Soc. London, Ser. A, 1948, 193, 120–145.

Feddes, R. A. and Lenselink, K. J., Evaporation from Open Water: The Penman Method. Drainage Principles and Application (ed. Ritzema, H. P.), International Institute for Land Reclamation and Improvement, The Netherlands, pp. 145–172.

Bapuji Rao, B., Sandeep, V. M., Rao, V. U. M. and Venkateswarlu, B., Potential Evapotranspiration estimation for Indian conditions: Improving accuracy through calibration coefficients. Tech. Bull. No 1/2012. All India Co-ordinated Research Project on Agromete-orology, Central Research Institute for Dryland Agriculture, Hy-derabad, 2012, p. 60.

Allen, R. G. and Pruitt, W. O., FAO-24 reference evapotranspira-tion factors. J. Irrig. Drain. Eng., 1991, 117, 758–773.

Chapman, T. G., Estimation of evaporation in rainfall-runoff mod-els. In Proceedings MODSIM 2003. International Congress on Modelling and Simulation, Modelling and Simulation Society of Australia, 2003, vol. 1, pp. 148–153.

Shuttleworth, W. J. and Wallace, J. S., Calculating the water requi-rements of irrigated crops in Australia using the Matt–Shuttleworth approach. Trans. ASABE, 2009, 52(6), 1895–1906.

Khan, R., Ali, I., Asif Suryani, M., Ahmad, M. and Zakarya, M., Wireless sensor network based irrigation management system for container grown crops in Pakistan. World Appl. Sci. J., 2013, 24, 1111–1118.

Lhomme, J. P., Boudhina, N. and Masmoudi, M. M., Technical note: on the Matt–Shuttleworth approach to estimate crop water requi-rements. Hydrol. Earth Syst. Sci., 2014, 18, 4341–4348.

Oudin, L. et al., Which potential evapotranspiration input for a lumped rainfall-runoff model? Part 2 – towards a simple and effi-cient potential evapotranspiration model for rainfall-runoff modelling. J. Hydrol., 2005, 303, 290–306.

McGuinness, J. L. and Bordne, E. F., A Comparison of Lysimeter-derived Potential Evapotranspiration with Computed Values, US Department of Agriculture, 1972.

Singh, P., Sarangi, A., Singh, D. K., Sehegal, V. K., Dash, S. and Chakrabarti, B., Performance evaluation of evapotranspiration esti-mation methods in Sultanpur, Uttar Pradesh, India. Indian J. Agric. Sci., 2021, 91, 421–425.

Borah, R. S. M. K., Comparative evaluation of different reference evapotranspiration estimation methods for Lakhimpur district of Assam, India. Int. J. Sci. Res., 2017, 6, 2162–2168.

Heydari, M. M., Aghamajidi, R., Beygipoor, G. and Heydari, M., Comparison and evaluation of 38 equations for estimating reference evapotranspiration in an arid region. Fresenius Environ. Bull., 2014, 23, 1985–1996.

Xu, C. Y. and Chen, D., Comparison of seven models for estimation of evapotranspiration and groundwater recharge using lysimeter measurement data in Germany. Hydrol. Process., 2005, 19, 3717– 3734.

Patle, G. T. and Singh, D. K., Sensitivity of annual and seasonal reference crop evapotranspiration to principal climatic variables. J. Earth Syst. Sci., 2015, 124(4), 819–828.

Efthimiou, N., Alexandris, S., Karavitis, C. and Mamassis, N., Comparative analysis of reference evapotranspiration estimation between various methods and the FAO-56 Penman–Monteith procedure. Eur. Water, 2013, 42, 19–34.

Chowdhury, A., Gupta, D., Das, D. P. and Bhowmick, A., Compari-son of different evapotranspiration estimation techniques for Mohan-pur, Nadia District, West Bengal. Int. J. Comput. Eng. Res., 2017, 7(4), 33–39.

Zheng, H. et al., Assessing the ability of potential evapotranspi-ration models in capturing dynamics of evaporative demand across various biomes and climatic regimes with ChinaFLUX measure-ments. J. Hydrol., 2017, 551, 70–80.

Liu, X., Xu, C., Zhong, X., Li, Y., Yuan, X. and Cao, J., Comparison of 16 models for reference crop evapotranspiration against weighing lysimeter measurement. Agric. Water Manage., 2017, 184, 145–155.

Username
Password
Remember me