Impact of Time Resolution of Rainfall Measurement on Erosivity Factor in Arid Region of India: RESEARCH PAPER

Deepesh Machiwal; Priyabrata Santra; H.M. Meena; Akath Singh

doi:10.56093/aaz.v64i4.168282

Authors

Deepesh Machiwal Division of Natural Resources, ICAR-Central Arid Zone Research Institute, Jodhpur - 342 003, INDIA
Priyabrata Santra Division of Natural Resources, ICAR-Central Arid Zone Research Institute, Jodhpur – 342003, India
H.M. Meena Division of Natural Resources, ICAR-Central Arid Zone Research Institute, Jodhpur – 342003, India
Akath Singh Division of Post Harvest Management, Central Institute of Subtropical Horticulture, Lucknow – 226101, India

https://doi.org/10.56093/aaz.v64i4.168282

Keywords:

high temporal resolution, kinetic energy, maximum 30-min rainfall intensity, arid region, conversion factor

Abstract

Rainfall erosivity is considered as a vital factor in computing soil loss through erosion prediction models such as original and derived versions of the universal soil loss equation model. The accurate estimates of the rainfall erosivity require high-resolution rainfall measurements, which are still not widely available for many parts of the world. In this study, a set of conversion factors was developed to adjust rainfall erosivity estimates derived from rainfall data recorded at various temporal resolutions to those based on 1 min interval rainfall measurements. For the first time in the western arid region of India, 1 min interval rainfall data for two years (2020 and 2024) were utilized to compute the total kinetic energy (E), maximum 30 minute rainfall intensity (I30), and rainfall erosivity factor (R-factor) for individual rainfall events using the EI30 index method. Results of the study indicated that I30 values were severe for 5% to 10% of the total rainy storms, and high to very high for 75% to 80% storms. It is further revealed that as rainfall measurement interval decreases, the peaks of I30 are easily captured, which ultimately leads to enhanced erosive energy of the rainfall. The conversion factors obtained for the arid region in this study are relatively less as compared to that reported for humid and semi-arid regions in earlier studies. Also, underestimations of the E are evidenced on increasing the time interval from 5 min to 60 min with relative error within -10% whereas, the R-factors showed -4.5, -8.0, -9.6, -5.8 and -96.7% underestimations at 5, 15, 30 and 60 min and 24 h, respectively. The relationships developed for computing the precise and accurate E, I30 and R-factors for high-resolution (1 min) data based on coarser data at different time intervals (5 min, 15 min, 30 min, 60 min and 24 h) can be used adequately as the estimations involves a strong interactions confirmed among the factors.

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Author Biography

Deepesh Machiwal, Division of Natural Resources, ICAR-Central Arid Zone Research Institute, Jodhpur - 342 003, INDIA

Principal Scientist

ICAR-CAZRI, Jodhpur

References

Agnese, C., Bagarello, V., Corrao, C., D’Agostino, L. and D’Asaro, F. (2006). Influence of the rainfall measurement interval on the erosivity determinations in the Mediterranean area. Journal of Hydrology 329(1-2): 39-48. https://doi.org/10.1016/j.jhydrol.2006.02.002

Beguería, S., Serrano-Notivoli, R. and Tomas- Burguera, M. 2018. Computation of rainfall erosivity from daily precipitation amounts. Science of the Total Environment 637: 359-373. https://doi.org/10.1016/j.scitotenv.2018.04.400

Bhattacharyya, R., Ghosh, B.N., Mishra, P.K., Mandal, B., Rao, C.S., Sarkar, D., Das, K., Anil, K.S., Lalitha, M., Hati, K.M., et al. 2015. Soil degradation in India: Challenges and potential. Sustainability 7: 3528-3570. https://doi.org/10.3390/su7043528

Diodato, N., Borrelli, P., Fiener, P., Bellocchi, G. and Romano, N. 2017. Discovering historical rainfall erosivity with a parsimonious approach: A case study in Western Germany. Journal of Hydrology 544: 1-9. https://doi.org/10.1016/j.jhydrol.2016.11.023

Dunkerley, D. 2019. How does sub-hourly rainfall intermittency bias the climatology of hourly and daily rainfalls? Examples from arid and wet tropical Australia. International Journal of Climatology 39(4): 2412-2421. https://doi.org/10.1002/joc.5961

Fiener, P., Neuhaus, P. and Botschek, J. 2013. Long-term trends in rainfall erosivity-analysis of high-resolution precipitation time series (1937-2007) from Western Germany. Agricultural and Forest Meteorology 171-172(8): 115-123. https://doi.org/10.1016/j.agrformet.2012.11.011

Foster, G.R., McCool, D.K., Renard, K.G. and Moldenhauer, W.C. 1981. Conversion of the universal soil loss equation to SI metric units. Journal Soil and Water Conservation 36(6): 355-359. https://doi.org/10.1080/00224561.1981.12436140

Hanel, M., M_aca, P., Ba_sta, P., Vlnas, R. and Pech, P. 2016. The rainfall erosivity factor in the Czech Republic and its uncertainty. Hydrology and Earth System Sciences 20: 4307-4322. https://doi.org/10.5194/hess-20-4307-2016

ICAR and NAAS 2010. Degraded and Wastelands of India - Status and Spatial Distribution. Indian Council of Agricultural Research (ICAR) and National Academy of Agricultural Sciences (NAAS), New Delhi, India, 158 p.

IPCC 2001. Climate Change 2001: The Scientific Basis. Working Group I, 2001, Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change (IPCC), Cambridge University Press, Cambridge, United Kingdom.

IPCC 2007. Climate Change 2007: Impacts, Adaptation, and Vulnerability. In: Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) (Eds. M. Parry, M.L. Parry, O. Canziani, J. Palutikof, P. Van der Linden and C. Hanson), pp. 470-506. Cambridge University Press, Cambridge, United Kingdom, pp. 470-506.

IPCC 2012. Seneviratne, S.I., Nicholls, N., Easterling, D., Goodess, C.M., Kanae, S., Kossin, J., Luo, Y., Marengo, J., McInnes, K., Rahimi, M., Reichstein, M., Sorteberg, A., Vera, C. and Zhang, X. Changes in climate extremes and their impacts on the natural physical environment. In: Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation, A Special Report of Working Groups I and II of the Intergovernmental Panel on Climate Change (IPCC) (Eds. Field, C.B. Field, V. Barros, T.F. Stocker, D., Qin, D.J. Dokken, K.L. Ebi, M.D. Mastrandrea, K.J. Mach, G.-K. Plattner, S.K. Allen, M. Tignor and P.M. Midgley), pp. 109-230. Cambridge University Press, Cambridge, United Kingdom, and New York, NY, USA.

Istok, J., McCool, D., King, L. and Boersma, L. 1986. Effect of rainfall measurement interval on EI calculation. Transactions of the American Society of Agricultural Engineers 29(3): 730-734. https://doi.org/10.1016/j.catena.2022.106714

Katsir, S., Biswas, A.K., Urs, K., Lenka, N.K., Jha, P. and Arora, K. 2024. Governing soils sustainably in India: Establishing policies and implementing strategies through local governance. Soil Security 14: 100132. https://doi.org/10.1016/j.soisec.2024.100132

Kinnell, P.I.A. 2010. Event soil loss, runoff and the universal soil loss equation family of models: A review. Journal of Hydrology 385: 384-397. https://doi.org/10.1016/j.jhydrol.2010.01.024

Klik, A., Haas, K., Dvorackova, A. and Fuller, I.C. 2015. Spatial and temporal distribution of rainfall erosivity in New Zealand. Soil Research 40(6): 887-901. http://dx.doi.org/10.1071/SR14363

Lal, R. 2012. Land degradation and pedological processes in a changing climate. Pedologist 55(3): 315-325. https://doi.org/10.18920/pedologist.55.3_315

Machiwal, D., Dayal, D. and Kumar, S. 2015. Assessment of reservoir sedimentation in arid region watershed of Gujarat. Journal of Agricultural Engineering, ISAE 52(4): 40-49. https://doi.org/10.52151/jae2015524.1590

Machiwal, D., Kumar, S. and Dayal, D. 2016. Characterizing rainfall of hot arid region by using time series modeling and sustainability approaches: A case study from Gujarat, India. Theoretical and Applied Climatology 124: 593-607. https://doi.org/10.1007/s00704-015-1435-9

Machiwal, D., Kumar, S., Dayal, D. and Mangalassery, S. 2017. Identifying abrupt changes and detecting gradual trends of annual rainfall in an Indian arid region under heightened rainfall rise regime. International Journal of Climatology 37(5): 2719-2733. https://doi.org/10.1002/joc.4875

Machiwal, D., Patel, A., Kumar, S. and Naorem, A. 2022. Status and challenges of monitoring soil erosion in croplands of arid regions. In: Soil Health and Environmental Sustainability (Eds. P.K. Shit, P.P. Adhikary, G.S. Bhunia, D. Sengupta),. Environmental Science and Engineering. Springer, Cham. https://doi.org/10.1007/978-3-031-09270-1_8

Mannaerts, C.M. and Gabriels, D. 2000. Rainfall erosivity in Cape Verde. Soil and Tillage Research 55(3): 207-212. http://dx.doi.org/10.1016/j.geoderma.2013.10.026

Martins, S.G., Avanzi, J.C., Silva, M.L.N., Curi, N., Norton, L.D. and Fonseca, S. 2010. Rainfall erosivity and rainfall return period in the experimental watershed of Aracruz, in the coastal plain of Espirito Santo, Brazil. Revista Brasileira de Ciência do Solo 34(3): 999-1004. http://dx.doi.org/10.1590/S0100-06832010000300042

McFarlane, D.J., Davies, R.J. and Westcott, T. 1986. Rainfall erosivity in Western Australia. In: Proceedings of the Hydrology and Water Resources Symposium, Griffith University, Brisbane. Institution of Engineers, Australia, Barton, ACT, pp. 350-354.

Meena, H.M., Machiwal, D., Santra, P., Moharana, P.C. and Singh, D.V. 2019. Trends and homogeneity of monthly, seasonal, and annual rainfall over arid region of Rajasthan, India. Theoretical and Applied Climatology 136: 795-811. https://doi.org/10.1007/s00704-018-2510-9

Meusburger, K., Steel, A., Panagos, P., Montanarella, L. and Alewell, C. 2012. Spatial and temporal variability of rainfall erosivity factor for Switzerland. Hydrology and Earth System Sciences 16: 167-177. https://doi.org/10.5194/hess-16- 167-2012

NAAS 2012. Management of Crop Residues in the Context of Conservation Agriculture. Policy Paper No. 58, National Academy of Agricultural Sciences (NAAS), New Delhi, India, 12p.

Panagos, P., Ballabio, C., Borrelli, P., Meusburger, K., Klik, A., Rousseva, S., et al. 2015. Rainfall erosivity in Europe. Science of the Total Environment, 511: 801-814. https://doi.org/10.1016/j.scitotenv.2015.01.008

Panagos, P., Borrelli, P., Spinoni, J., Ballabio, C., Meusburger, K., Beguería, S., Rousseva, S., et al. 2016. Monthly rainfall erosivity: Conversion factors for different time resolutions and regional assessments. Water 8(4): 119. https://doi.org/10.3390/w8040119

Porto, P. 2016. Exploring the effect of different time resolutions to calculate the rainfall erosivity factor R in Calabria, southern Italy. Hydrological Processes 30(10): 1551-1562. https://doi.org/10.1002/hyp.10737

Renard, K.G. 1997. Predicting soil erosion by water: A guide to conservation planning with the Revised Universal Soil Loss Equation (RUSLE), United States Government Printing.

Renard, K.G. and Freimund, J.R. 1994. Using monthly precipitation data to estimate the R-factor in the revised USLE. Journal of Hydrology 157(1-4): 287-306. https://doi.org/10.1016/0022-1694(94)90110-4

Robinson, A., Lehmann, J., Barriopedro, D., Rahmstorf, S. and Coumou, D. 2021. Increasing heat and rainfall extremes now far outside the historical climate. npj Climate and Atmospheric Science 4 (45). https://doi.org/10.1038/s41612-021-00202-w

Santosa, P.B., Mitani, Y. and Ikemi, H. 2010. Estimation of RUSLE EI30 based on 10 min interval rainfall data and GIS-based development of rainfall erosivity maps for Hitotsuse basin in Kyushu Japan. In: 18th International Conference on Geoinformatics, Beijing, China, 2010, pp. 1-6, https://doi.org/10.1109/GEOINFORMATICS.2010.5568195

Santra, P., Goyal, R.K., Tewari, J.C., Roy, M.M. and Singh, J.P. 2014. Assessment of potential soil loss rate by wind and water erosion in Jodhpur region of western Rajasthan, India. In: Global Soil Map - Basis of the Global Spatial Soil Information System (Eds. D. Arrouays, N. McKenzie, J. Hempel, A.R. de Forges and A. McBratney), pp. 139-143. CRC Press, Taylor & Francis Group, London, https://doi.org/10.1201/b16500-28

Sartori, M., Philippidis, G., Ferrari, E., Borrelli, P., Lugato, E., Montanarella, L. and Panagos, P. 2019. A linkage between the biophysical and the economic: Assessing the global market impacts of soil erosion. Land Use Policy 86: 299-312. https://doi.org/10.1016/j.landusepol.2019.05.014

Schmidt, S., Alewell, C., Panagos, P. and Meusburger, K. 2016. Regionalization of monthly rainfall erosivity patterns in Switzerland. Hydrology and Earth System Sciences 20(10): 4359-4373. https:// doi.org/10.5194/hess-20-4359-2016

Shamshad, A., Azhari, M.N., Isa, M.H. al, Hussin, W.M.A.W. and Parida, B.P. 2008. Development of an appropriate procedure for estimation of RUSLE EI30 index and preparation of erosivity maps for Pulau Penang in Peninsular Malaysia. Catena 72(3): 423-432. https://doi.org/10.1016/j. catena.2007.08.002

Singh, J. and Singh, O. 2020. Assessing rainfall erosivity and erosivity density over a western Himalayan catchment, India. Journal of Earth System Science 129(1): 97. https://doi.org/10.1007/s12040-020-1362-8

Striffler, W.D., Tejwani, K.G. and Babu, R. 1979. A note on rainfall intensity classes for tropical countries like India. Indian Journal of Soil Conservation 7(1): 60-61.

Tu, A., Xie, S., Li, Y., Liu, Z. and Shen, F. 2023. Effect of fixed time interval of rainfall data on calculation of rainfall erosivity in the humid area of south China. Catena 220: 106714. https://doi.org/10.1016/j.catena.2022.106714

Verstraeten, G., Poesen, J., Demarée, G. and Salles, C. 2006. Long-term (105 years) variability in rain erosivity as derived from 10 min rainfall depth data for Ukkel (Brussels, Belgium): Implications for assessing soil erosion rates. Journal of Geophysical Research Atmospheres 111(D22). https://doi.org/10.1029/2006JD007169

Williams, J.R. and Berndt, H.D. 1972. Sediment yield computed with universal equation. Journal of Hydraulics Division 98(12): 2087-2098. https://doi.org/10.1061/JYCEAJ.0003498

Williams, R.G. and Sheridan, J.M. 1991. Effect of rainfall measurement time and depth resolution on EI calculation. Transactions of the American Society of Agricultural Engineers 34(2): 402-406. https://doi.org/10.13031/2013.31675

Wischmeier, W.H. and Smith, D.D. 1978. Predicting rainfall erosion losses: A guide to conservation planning. Agriculture Handbook, Volume 537, United States Department of Agriculture, Washington DC, USA.

Xie, Y., Yin, S.Q., Liu, B.Y., Nearing, M.A. and Zhao, Y. 2016. Models for estimating daily rainfall erosivity in China. Journal of Hydrology 535: 547-558. https://doi.org/10.1016/j.jhydrol.2016.02.020

Yin, S., Xie, Y., Nearing, M.A. and Wang, C. 2007. Estimation of rainfall erosivity using 5- to 60 minute fixed-interval rainfall data from China. Catena 70(3): 306-312. https://doi.org/10.1016/j.catena.2006.10.011

Yin, S.-Q., Xie, Y., Liu, B. and Nearing, M.A. 2015. Rainfall erosivity estimation based on rainfall data collected over a range of temporal resolutions. Hydrology and Earth System Sciences 19(10): 4113-4126. https://doi.org/10.5194/hess-19-4113-2015

Yu, B. 1998. Rainfall erosivity and its estimation for Australia’s tropics. Australian Journal of Soil Research 36(1): 143-166. https://doi.org/10.1071/S97025

Yu, B. and Rosewell, C.J. 1996. Rainfall erosivity estimation using daily rainfall amounts for South Australia. Australian Journal of Soil Research 34(5): 721-733. https://doi.org/10.1071/SR9960721

Yue, T., Xie, Y., Yin, S., Yu, B., Miao, C. and Wang, W. 2020. Effect of time resolution of rainfall measurements on the erosivity factor in the USLE in China. International Soil and Water Conservation Research 8: 373-382. https://doi.org/10.1016/j.iswcr.2020.06.001

Zhang, W., Zhou, J., Feng, G., Weindorf, D.C., Hu, G. and Sheng, J. 2015. Characteristics of water erosion and conservation practice in arid regions of Central Asia: Xinjiang, China as an example. International Soil and Water Conservation Research 3(2): 97-111. http://dx.doi.org/10.1016/j. iswcr.2015.06.002