Effects of Season and Phenology-based Changes on Soil Erodibility and Other Dynamic RUSLE Factors for Semi-arid Winter Wheat Fields

Abstract

Time-dependent and phenology-based erodibility assessments in agricultural areas are extremely important for a more accurate evaluation of erosion. This paper aims to investigate soil erodibility factor (RUSLE-K) of the “Revised Universal Soil Loss Equation (RUSLE)” model in terms of phenological and seasonal variations in the 50 different winter wheat growing parcels with the interactions other dynamic RUSLE factors (RUSLE-R, RUSLE-C). For that, parcel-based erosion assessments were performed with the help of Dynamic Erosion Model and Monitoring System, digital elevation model, and satellite images in Polatlı, Ankara. Findings showed that RUSLE-K factor varied from 0.0150 to 0.0357 t ha h ha-1 MJ-1 mm-1 during the period the seeding germination to the end of the tillering from autumn to spring, and the lowest RUSLE-K was obtained when the plant was in the three-leaf stage. After the frost-free period, corresponding to the flowering and fertilization stages of the wheat plant, the RUSLE-K values changed between 0.0786 and 0.0976 t ha h ha-1 MJ-1 mm-1. This reveals that erodibility can vary up to nine times due to seasonality. However, the other dynamic model factors are not taken into consideration. Considering all dynamic factors on soil losses, the change coefficients from the highest to the lowest were obtained for RUSLE-R, RUSLE-K and RUSLE-C, respectively. These changes caused soil losses to change by 82% during the year. So, this study is expected to shed new light on studies of wheat or other commonly cultivated crops to accurately assess the water erosion risk as a significant land degradation problem.

Keywords

• Erodibility
• Modeling
• Normalize different vegetation index (NDVI)
• Satellite images
• Sustainability
• Water erosion

References

1. 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.
2. Alewell C, Borelli P, Meusburger K, & Panagos P (2019). Using the USLE: Chances, challenges and limitations of soil erosion modelling. International Soil and Water Conservation Research 7(3):203-225.
3. Anonymous (2019). Turkey Grain and Feed Annual Report 2019. United States Department of Agriculture, Foreign Agriculture Service, Global Agricultural Information Network, GAIN Report Number: TR9008.
4. Auerswald K, Fiener P, Martin W, & Elhaus D (2014). Use and misuse of the K factor equation in soil erosion modeling: An alternative equation for determining USLE nomograph soil erodibility values. Catena 118:220–225.
5. Bajracharya R M, & Lal R (1992). Seasonal Soil Loss and Erodibility Variation on a Miamian Silt Loam Soil. Soil Science Society of America Journal 56(5):1560–1565.
6. Başkan O & Dengiz O (2008). Comparison of Traditional and Geostatistical Methods to Estimate Soil Erodibility Factor. Arid Land Research and Management 22 (1): 29-45.
7. Benavidez R, Jackson B, Maxwell D, & Norton K (2018). A review of the (Revised) Universal Soil Loss Equation ((R) USLE): with a view to increasing its global applicability and improving soil loss estimates. Hydrology and Earth System Sciences 22(11):6059-6086. Borselli L, Torri D, Poesen J, & Iaquinta P (2012). A robust algorithm for estimating soil erodibility in different climates. Catena 97: 85–94. Comino J R, Sinoga J R, González J S, Guerra-Merchán A, Seeger M, & Ries J B (2016). High variability of soil erosion and hydrological processes in Mediterranean hillslope vineyards (Montes de Málaga, Spain). Catena 145: 274-284.
8. Erpul G, Sahin S, Akgöz R, Ince K, Guden A, & Çetin E (2016). Türkiye Yağışlarının Özellikleri ve Yenilenmiş Evrensel Toprak Kayıpları Eşitliği (YETKE) R Faktörü. Ankara: General Directorate of Combating Desertification and Erosion, Republic of Turkey Ministry of Agriculture and Forestry (TR). Turkish.

9. Erpul G, Sahin S, Ince K, Kucumen A, Akdag M A, Demirtas İ, and Cetin E (2018). Turkey water erosion map. Ankara: General Directorate of Combating Desertification and Erosion, Republic of Turkey Ministry of Agriculture and Forestry (TR). Turkish.
10. Ferreira V & T. Panagopoulos. 2014. Seasonality of soil erosion under Mediterranean conditions at the Alqueva dam watershed. Environmental Management 54(1): 67–83.
11. FAO (Food and Agriculture Organization) & ITPS (Intergovermental Technical Panel on Soils). 2015. Status of the World’s Soil Resources (SWSR) – Main Report. Rome, Italy.
12. Huang C H, & Laften J M (1996). Seepage and soil erosion for a clay loam soil. Soil Science Society of America Journal 60(2): 408-416.
13. Huang C H (1998). Sediment regimes under different slope and surface hydrologic conditions. Soil Science Society of America Journal 62(2): 423-430.
14. Kapur S, Akca E, & Gunal H (2017). The soils of Turkey. World Soils Book Series. Switzerland: Springer Nature.
15. Knapen A, Poesen J, & De Baets S (2007). Seasonal variations in soil erosion resistance during concentrated flow for a loess-derived soil under two contrasting tillage practices. Soil and Tillage Research 94(2):425–440.
16. Lee S (2004). Soil erosion assessment and its verification using the Universal Soil Loss Equation and geographic information system: a case study at Boun, Korea. Environmental Geology 45: 457–465.
17. López-Vicente M, Navas A, & Machín J (2008). Identifying erosive periods by using RUSLE factors in mountain fields of the Central Spanish Pyrenees. Hydrology and Earth System Sciences 12(2): 523–535.
18. Moore I D, & Burch G J (1986a). Modeling erosion and deposition. Topographic effects. Transactions of the ASAE 29: 1624–1630.
19. Moore I D, & Burch G J (1986b). Physical basis of the length–slope factor in the Universal soil loss equation. Soil Science Society of America Journal 50: 1294–1298.
20. 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.
21. Ogawa S, Saito G, Mino N, Uchida S, Khan N M, & Shafiq M (1997). Estimation of soil erosion using USLE and Landsat TM in Pakistan. In Asian Conference for Remote Sensing (ACRS).
22. Ostovari Y, Ghorbani-Dashtaki S, Kumar L, & Shabani F (2019). Soil erodibility and its prediction in semi-arid regions. Archives of Agronomy and Soil Science 65(12): 1688-1703.
23. Oztas T, & Fayetorbay F (2003). Effect of freezing and thawing processes on soil aggregate stability. Catena 52(1): 1–8.
24. Panagos P, Meusburger K, Ballabio C, Borrelli P, & Alewell C (2014). Soil erodibility in Europe: a high-resolution dataset based on LUCAS. Science of the Total Environment 479: 189–200.
25. Panagos P, Borrelli P, Poesen J, Ballabio C, Lugato E, Meusburger K, Montanarella L, & Alewell C (2015). The new assessment of soil loss by water erosion in Europe. Environmental Science & Policy 54: 438-447.
26. Peel M C, Finlayson B L, & McMahon T A (2007). Updated world map of the Köppen-Geiger climate classification. Hydrology and Earth System Sciences 4(2):439–473.
27. Renard K G, Foster GR, Yoder D C, & McCool D K (1994). RUSLE revisited: status, questions, answers, and the future. Journal of Soil and Water Conservation 49(3):213–220.
28. Renard K G, Foster G R, Weesies G, McCool D K, & Yoder D C (1997). Predicting soil erosion by water: a guide to conservation planning with the Revised Universal Soil Loss Equation (RUSLE). 703. Washington (DC): US Government Printing Office.
29. Römkens M J M, Young R A, Poesen J W A, McCool D K, El-Swaify S A, & Bradford J M (1997). Chapter 3. Soil erodibility factor (K). In Renard KG, Foster GR, Weesies, GA, McCool DK, Yoder DC, editors. Predicting soil erosion by water: a guide to conservation planning with the Revised Universal Soil Loss Equation (RUSLE). Washington (DC): US Government Printing Office; p. 65-99.
30. Saygin 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. Environ Monitoring and Assessesment 180(1–4): 201–215. Saygin 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.
31. 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.
32. 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 to Predictability and uncertainty of the soil erodibility factor using a global dataset. [Catena 32 (1998) 307–308]”. Catena 46(4): 309–310.
33. MGM (Turkish State Meteorological Service, Republic of Turkey Ministry of Agriculture and Forestry). 2018. Meteorological data information sales and presentation system. Turkish. Van der Kniff J M, Jones R J A, & Montanarella L (2000). Soil erosion risk assessment in Europe, EUR 19044 EN. Luxembourg: Office for Official Publications of the European Communities.
34. Wischmeier W H, & Smith D D (1978). Predicting rainfall erosion losses: a guide to conservation planning. Agriculture Handbook, vol. 537. Washington DC: US Department of Agriculture; pp. 13–27.
35. Wu X, Wei Y, Wang J, Cai C, Deng Y, & Xia J (2018). RUSLE erodibility of heavy‐textured soils as affected by soil type, erosional degradation, and rainfall intensity: A field simulation. Land Degradation and Development 29(3):408–421.
36. Yıldırım U, & Erkal T (2013). Assessment of soil erosion in the Ihsaniye watershed area, Afyonkarahisar, Turkey. Scientific Research and Essays 8(10):388–397.