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Monitoring seasonal and phenological variability of cover management factor for wheat cropping systems under semi-arid climate conditions

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Abstract

In modeling studies, the use of spatial data derived from geographic information systems and remote sensing applications to simulate the impact of phenological and seasonal changes on soil loss has a promising effect on the accuracy of predictions. The objective of this work was to estimate the C-factor (cover management) as a dynamic-factor RUSLE (revised universal soil loss equation) model based on an NDVI (Normalized Difference Vegetation Index) approach derived from high-resolution Landsat 8 and Landsat ETM7 satellite images for 140 different rain-fed wheat parcels in terms of seasonal and phenological-based by the integrated use of remote sensing and GIS. Overall, it was found that the highest C values, an average of 0.70, were estimated for the emergence period of the wheat, while the lowest value of 0.06 was found in the booting period. Seasonally, the estimated average C values in these parcels were 0.69, 0.63, 0.13, and 0.44 for the autumn, winter, spring, and summer, respectively. Corresponding soil losses for those seasons were 1.70, 1.55, 0.28, and 1.13 t ha−1 year−1 respectively. Comparatively, without considering the phenological growing periods of wheat, the annual predicted soil loss rate was 11.5% higher than the conditions considered. The present study concluded that an assessment of seasonal and phenological changes in the C-factor for fragile ecosystems with weak crop-cover development could significantly improve the accuracy of the RUSLE model predictions and effectively manage limited soil and water resources.

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Data availability

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

References

  • Akgöz, R., Ince, K., & Erpul, G. (2020). Determination of roughness parameter of national dynamic wind erosion model and monitoring system. Anadolu Tarim Bilimleri Dergisi, 35(1), 124–132. https://doi.org/10.7161/omuanajas.632156

    Article  Google Scholar 

  • Alexandridis, T. K., Sotiropoulou, A. M., Bilas, G., Karapetsas, N., & Silleos, N. G. (2015). The effects of seasonality in estimating the C-factor of soil erosion studies. Land Degradation & Development, 26(6), 596–603. https://doi.org/10.1002/ldr.2223

    Article  Google Scholar 

  • Anonymous. (2018). Turkish State Meteorological Service, Republic of Turkey Ministry of Agriculture and Forestry (TR). Meteorological data information sales and presentation system. (In Turkish) Accessed online on April, 2021. https://mevbis.mgm.gov.tr/mevbis/ui/index.html#/Workspace

  • Anonymous. (2019). Turkish State Meteorological Service, Republic of Turkey Ministry of Agriculture and Forestry (TR). Climate classification. (In Turkish) Accessed online on April, 2021. https://www.mgm.gov.tr/iklim/iklim-siniflandirmalari.aspx

  • Anonymous. (2020). Food and Agriculture Organization of United Nations. Food and Agricultural Data. http://faostat.fao.org. Accessed online on April, 2021.

  • Behera, M., Sena, D. R., Mandal, U., Kashyap, P. S., & Dash, S. S. (2020). Integrated GIS-based RUSLE approach for quantification of potential soil erosion under future climate change scenarios. Environmental Monitoring and Assessment, 192(11), 1–18. https://doi.org/10.1007/s10661-020-08688-2

    Article  Google Scholar 

  • Brown, L. C., & Foster, G. R. (1987). Storm erosivity using idealized intensity distributions. Transactions of the ASAE, 30(2), 379–0386. https://doi.org/10.13031/2013.31957

  • Bruinsma, J. (2017). World agriculture: Towards 2015/2030: An FAO study. Routledge.

    Book  Google Scholar 

  • Cox, C., & Madramootoo, C. (1998). Application of geographic information systems in watershed management planning in St. Lucia. Computers and Electronics in Agriculture, 20(3), 229–250. https://doi.org/10.1016/S0168-1699(98)00021-0

    Article  Google Scholar 

  • Durigon, V. L., Carvalho, D. F., Antunes, M. A. H., Oliveira, P. T. S., & Fernandes, M. M. (2014). NDVI time series for monitoring RUSLE cover management factor in a tropical watershed. International Journal of Remote Sensing, 35(2), 441–453. https://doi.org/10.1080/01431161.2013.871081

    Article  Google Scholar 

  • Duru, U., Wohl, E., & Ahmadi, M. (2017). Factors controlling sediment load in the Central Anatolia Region of Turkey: Ankara River basin. Environmental Management, 59(5), 826–841. https://doi.org/10.1007/s00267-016-0818-8

    Article  Google Scholar 

  • Erdogan, E. H., Erpul, G., & Bayramin, İ. (2007). Use of USLE/GIS methodology for predicting soil loss in a semiarid agricultural watershed. Environmental Monitoring and Assessment, 131(1), 153–161. https://doi.org/10.1007/s10661-006-9464-6

    Article  Google Scholar 

  • Erpul, G., Şahin, S., İnce, K., Küçümen, A., Akdağ, M. A., Demirtaş, İ., & Çetin, E. (2018). Water erosion map of Turkey, General Directorate of Combating Desertification and Erosion Publications, Ankara, Turkey, ISBN No:978-605-9550-23-9 (In Turkish)

  • Erpul, G., İnce, K., Demirhan, A., Küçümen, A., Akdağ, M. A., Demirtaş, İ., Sarıhan, B., Çetin, E., & Şahin, S. (2020). Water erosion provincial statistics - Soil erosion control strategies (sustainable land/soil management practices and approaches). General Directorate of Combating Desertification and Erosion Publications, Ankara, Turkey ISBN No: 978-605-7599-36-0 (In Turkish)

  • FAO. (2017). Voluntary Guidelines for Sustainable Soil Management, Food and Agriculture Organization of the United Nations Rome, Italy.

  • FAO & ITPS. (2015). Status of the world’s soil resources (SWSR) – Main report. Rome, Italy: Food and Agriculture Organization of the United Nations and Intergovernmental Technical Panel on Soils. ISBN: 978–92–5–109004–6

  • Feng, Q., Zhao, W., Ding, J., Fang, X., & Zhang, X. (2018). Estimation of the cover and management factor based on stratified coverage and remote sensing indices: A case study in the Loess Plateau of China. Journal of Soils and Sediments, 18(3), 775–790. https://doi.org/10.1007/s11368-017-1783-4

    Article  Google Scholar 

  • Foster, G. R., Toy, T. E., & Renard, K. G. (2003). Comparison of the USLE, RUSLE1. 06c, and RUSLE2 for application to highly disturbed lands. In First Interagency Conference on Research in Watersheds, 27(30), 154–160. Washington, DC: US Department of Agriculture, Agricultural Research Service.

  • Hamza, M. A., & Anderson, W. K. (2005). Soil compaction in cropping systems: A review of the nature, causes and possible solutions. Soil and Tillage Research, 82(2), 121–145. https://doi.org/10.1016/j.still.2004.08.009

    Article  Google Scholar 

  • Huang, J. (2018). Assessment of potential changes in soil erosion using remote sensing and GIS: A case study of Dacaozi Watershed. China. Environmental Monitoring and Assessment, 190(12), 1–11. https://doi.org/10.1007/s10661-018-7120-6

    Article  Google Scholar 

  • Kadioglu, S. (2008). Photographing layer thicknesses and discontinuities in a marble quarry with 3D GPR visualisation. Journal of Applied Geophysics, 64(3–4), 109–114. https://doi.org/10.1016/j.jappgeo.2008.01.001

    Article  Google Scholar 

  • Kaya, Y. (2021). Winter wheat adaptation to climate change in Turkey. Agronomy, 11(4), 689. https://doi.org/10.3390/agronomy11040689

    Article  Google Scholar 

  • Kouli, M., Soupios, P., & Vallianatos, F. (2009). Soil erosion prediction using the revised universal soil loss equation (RUSLE) in a GIS framework, Chania, Northwestern Crete. Greece. Environmental Geology, 57(3), 483–497. https://doi.org/10.1007/s00254-008-1318-9

    Article  Google Scholar 

  • Lagacherie, P., Álvaro-Fuentes, J., Annabi, M., Bernoux, M., Bouarfa, S., Douaoui, A., & Raclot, D. (2018). Managing Mediterranean soil resources under global change: Expected trends and mitigation strategies. Regional Environmental Change, 18(3), 663–675. https://doi.org/10.1007/s10113-017-1239-9

    Article  Google Scholar 

  • Moore, I. D., & Wilson, J. P. (1992). Length-slope factors for the Revised Universal Soil Loss Equation: Simplified method of estimation. Journal of Soil and Water Conservation, 47(5), 423–428.

    Google Scholar 

  • Möller, M., Gerstmann, H., Gao, F., Dahms, T. C., & Förster, M. (2017). Coupling of phenological information and simulated vegetation index time series: Limitations and potentials for the assessment and monitoring of soil erosion risk. CATENA, 150, 192–205. https://doi.org/10.1016/j.catena.2016.11.016

    Article  Google Scholar 

  • Oliveira, P. T. S., Wendland, E., & Nearing, M. A. (2013). Rainfall erosivity in Brazil: A review. CATENA, 100, 139–147. https://doi.org/10.1016/j.catena.2012.08.006

    Article  Google Scholar 

  • Panagos, P., Borrelli, P., Meusburger, K., Alewell, C., Lugato, E., & Montanarella, L. (2015). Estimating the soil erosion cover-management factor at the European scale. Land Use Policy, 48, 38–50. https://doi.org/10.1016/j.landusepol.2015.05.021

    Article  Google Scholar 

  • Peel, M. C., Finlayson, B. L., & McMahon, T. A. (2007). Updated world map of the Köppen-Geiger climate classification. Hydrology and Earth System Sciences, 11(5), 1633–1644. https://doi.org/10.5194/hess-11-1633-2007

    Article  Google Scholar 

  • Raclot, D., Le Bissonnais, Y., Annabi, M., Sabir, M., & Smetanova, A. (2018). Main issues for preserving Mediterranean soil resources from water erosion under global change. Land Degradation & Development, 29(3), 789–799. https://doi.org/10.1002/ldr.2774

    Article  Google Scholar 

  • Rawat, K. S., & Singh, S. K. (2018). Appraisal of soil conservation capacity using NDVI model-based C factor of RUSLE model for a semi arid ungauged watershed: A case study. Water Conservation Science and Engineering, 3(1), 47–58. https://doi.org/10.1007/s41101-018-0042-x

    Article  Google Scholar 

  • Renard, K., Foster, G., Weesies, G., McDool, D., Yoder, D. (1997). Predicting soil erosion by water: A guide to conservation planning with the revised universal soil loss equation (RUSLE). Agricultural Handbook 703, USDA-ARS.

  • Saygın, S. D., Basaran, M., Ozcan, A. U., Dolarslan, M., Timur, O. B., Yilman, F. E., & Erpul, G. (2011). Land degradation assessment by geo-spatially modeling different soil erodibility equations in a semi-arid catchment. Environmental Monitoring and Assessment, 180(1), 201–215. https://doi.org/10.1007/s10661-010-1782-z

    Article  Google Scholar 

  • Saygın, S. D., Ozcan, A. U., Basaran, M., Timur, O. B., Dolarslan, M., Yılman, F. E., & Erpul, G. (2014). The combined RUSLE/SDR approach integrated with GIS and geostatistics to estimate annual sediment flux rates in the semi-arid catchment. Turkey. Environmental Earth Sciences, 71(4), 1605–1618. https://doi.org/10.1007/s12665-013-2565-y

    Article  Google Scholar 

  • Saygin, S. D. (2021). Effects of season and phenology-based changes on soil erodibility and other dynamic RUSLE factors for semi-arid winter wheat fields. Journal of Agricultural Sciences-Tarım Bilimleri Dergisi, 27(4), 1–7. https://doi.org/10.15832/ankutbd.749181

  • Schmidt, S., Tresch, S., & Meusburger, K. (2019). Modification of the RUSLE slope length and steepness factor (LS-factor) based on rainfall experiments at steep alpine grasslands. MethodsX, 6, 219–229. https://doi.org/10.1016/j.mex.2019.01.004

    Article  Google Scholar 

  • Shi, Z. H., Cai, C. F., Ding, S. W., Wang, T. W., & Chow, T. L. (2004). Soil conservation planning at the small watershed level using RUSLE with GIS: A case study in the Three Gorge Area of China. CATENA, 55(1), 33–48. https://doi.org/10.1016/S0341-8162(03)00088-2

    Article  Google Scholar 

  • Shirazi, M. A., & Boersma, L. (1984). A unifying quantitative analysis of soil texture. Soil Science Society of America Journal, 48(1), 142–147. https://doi.org/10.2136/sssaj1984.03615995004800010026x

    Article  Google Scholar 

  • Shoshany, M., Goldshleger, N., & Chudnovsky, A. (2013). Monitoring of agricultural soil degradation by remote-sensing methods: A review. International Journal of Remote Sensing, 34(17), 6152–6181. https://doi.org/10.1080/01431161.2013.793872

    Article  Google Scholar 

  • Soil Survey Staff. (2014). Keys to Soil Taxonomy (12th ed.). USDA-Natural Resources Conservation Service.

    Google Scholar 

  • Torri, D., Poesen, J., & Borselli, L. (1997). Predictability and uncertainty of the soil erodibility factor using a global dataset. CATENA, 31(1–2), 1–22. https://doi.org/10.1016/S0341-8162(97)00036-2

    Article  Google Scholar 

  • Torri, D., Poesen, J., & Borselli, L. (2002). Corrigendum to Predictability and uncertainty of the soil erodibility factor using a global dataset (Catena 31 (1997) 1–22) and to erratum t Predictability and uncertainty of the soil erodibility factor using a global dataset (Catena 32 (1998) 307–308). Catena (giessen), 46(4), 309–310. https://doi.org/10.1016/S0341-8162(01)00175-8

    Article  Google Scholar 

  • Toy, T. J., Foster, G. R. (1998). In J.R. Galetevic (Ed.). Guidelines for the revised universal soil loss equation (RUSLE) version 1.06 on mined lands. construction sites and reclaimed lands. Suite 3320. 1999 Broadway. Denver. CO 80202–5733: The Office of Technology Transfer Western Regional Coordinating Center Office of Surface Mining.

  • Ulukan, H. (2021). Climate change and global warming effect (s) on wheat landraces: A general approach. In Wheat Landraces (pp. 169–191). Springer, Cham. https://doi.org/10.1007/978-3-030-77388-5_9

  • van der Knijff, J. M., Jones, R. J. A., & Montanarella, L (2000). Soil erosion risk assessment in Europe. Ispra: European Soil Bureau. Joint Research Centre. EUR 19044 EN.

  • Vatandaşlar, C., & Yavuz, M. (2017). Modeling cover management factor of RUSLE using very high-resolution satellite imagery in a semiarid watershed. Environmental Earth Sciences, 76(2), 65. https://doi.org/10.1007/s12665-017-6388-0

    Article  Google Scholar 

  • Wischmeier, W. H., & Smith, D. D. (1978). Predicting rainfall erosion losses a guide for conservation planning. U.S. Department of Agriculture, Agriculture Handbook 537.

  • Zerihun, M., Mohammedyasin, M. S., Sewnet, D., Adem, A. A., & Lakew, M. (2018). Assessment of soil erosion using RUSLE, GIS and remote sensing in NW Ethiopia. Geoderma Regional, 12, 83–90. https://doi.org/10.1016/j.geodrs.2018.01.002

    Article  Google Scholar 

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Acknowledgements

The authors would like to acknowledge the support of all the technical staff at the Republic of Turkey Ministry of Agriculture and Forestry, General Directorate of Combating Desertification and Erosion, and General Directorate of Agricultural Reform services for their kind assistance.

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  1. Department of Soil Science and Plant Nutrition, Faculty of Agriculture, University of Ankara, 06110, Diskapi, Ankara, Turkey

    Resat Akgöz, Selen Deviren Saygin & Günay Erpul

  2. Department of Soil Conservation and Field Assessment, Ministry of Agriculture and Forestry, 06800, Cankaya, Ankara, Turkey

    Selda Tel

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  1. Resat Akgöz
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Akgöz, R., Deviren Saygin, S., Erpul, G. et al. Monitoring seasonal and phenological variability of cover management factor for wheat cropping systems under semi-arid climate conditions. Environ Monit Assess 194, 395 (2022). https://doi.org/10.1007/s10661-022-10064-1

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