Advertisement

Natural Hazards

, Volume 83, Supplement 1, pp 65–81 | Cite as

Assessing water erosion in Mediterranean tree crops using GIS techniques and field measurements: the effect of climate change

  • Nektarios N. KourgialasEmail author
  • Georgios C. Koubouris
  • George P. Karatzas
  • Ioannis Metzidakis
Original Paper

Abstract

In this work, a dynamic GIS modeling approach is presented that incorporates: a) geoinformatic techniques, b) 55-year historical meteorological data, and c) field measurements, in order to estimate soil erosion risk in intensively cultivated regions. The proposed GIS-based modeling approach includes the estimation of soil erosion rates due to surface water flow under current and future climate change scenarios A2 and B1 for the years 2030 and 2050. The soil erosion was estimated using the Universal Soil Loss Equation (USLE). The proposed soil erosion model was validated using field measurements at different sites of the study area. The results show that an extended part of the study area is under intense erosion with the mean annual loss to be 4.85 t/ha year−1. Moreover, an increase in rainfall intensity, especially for scenario B1, can generate a significant increase (32.44 %) in soil loss for the year 2030 and a much more (50.77 %) for the year 2050 in comparison with the current conditions. Regarding the scenario A2, a slight decrease (1.85 %) in soil loss was observed for the year 2030, while for 2050 the results show an adequate increase (7.31 %) in comparison with the present. All these approaches were implemented at one of the most productive agricultural areas of Crete in Greece dominated by olive and citrus crops.

Keywords

Agriculture GIS Soil erosion and climate change Crete 

References

  1. Angulo-Martínez M, López-Vicente M, Vicente-Serrano SM, Beguería S (2009) Mapping rainfall erosivity at a regional scale: a comparison of interpolation methods in the Ebro Basin (NE Spain). Hydrol Earth Syst Sci 13(10):1907–1920CrossRefGoogle Scholar
  2. Arnoldus HMJ (1980) An approximation of the rainfall factor in the Universal Soil Loss Equation. In: De Boodt M, Gabriels D (eds) Assessment of erosion. Wiley, Chichester, pp 127–132Google Scholar
  3. Benkobi L, Trlica MJ, Smith JL (1994) Evaluation of a refined surface cover subfactor for use in RUSLE. J Range Manage 47:74–78CrossRefGoogle Scholar
  4. Bhandari K, Aryal J, Darnsawasdi R (2015) A geospatial approach to assessing soil erosion in a watershed by integrating socio-economic determinants and the RUSLE model. Nat Hazards 75(1):321–342CrossRefGoogle Scholar
  5. Brown LR (1984) Conserving soils. In: Brown LR (ed) State of the world. Norton, New York, pp 53–75Google Scholar
  6. Cox C, Madramootoo C (1998) Application of geographic information systems in watershed management planning in St. Lucia Comput Electron Agric 20:229–250CrossRefGoogle Scholar
  7. Fadul HM, Salih AA, Ali IA, Inanaga S (1999) Use of remote sensing to map gully erosion along the Atbara River. Sudan Int J Appl Obs Geoinf 1(3–4):175–180CrossRefGoogle Scholar
  8. Ferro V, Porto P, Yu B (1999) A comparative study of rainfall erosivity estimation for southern Italy and southeastern Australia. Hydrol Sci J Sci Hydrol 44(1):3–24CrossRefGoogle Scholar
  9. Fu G, Chen S, McCool KD (2006) Modeling the impacts of no-till practice on soil erosion and sediment yield using RUSLE, SEDD and ArcView GIS. Soil Tillage Res 85:38–49CrossRefGoogle Scholar
  10. Hu Y, Tian G, Mayer A, He R (2015) Risk assessment of soil erosion by application of remote sensing and GIS in Yanshan reservoir catchment. China. Natural Hazards 79(1):277–289CrossRefGoogle Scholar
  11. Jiang L, Yao Z, Liu Z, Wu S, Wang R, Wang L (2015) Estimation of soil erosion in some sections of lower Jinsha River based on RUSLE. Nat Hazards 76(3):1831–1847CrossRefGoogle Scholar
  12. Kheir RB, Cerdan O, Abdallah C (2006) Regional soil erosion risk mapping in Lebanon. Geomorphology 82:347–359CrossRefGoogle Scholar
  13. Kosmas CN, Danalatos LH, Cammeraat M, Chabart J, Diamantopoulos R, Farand L, Gutierrez A, Jacob H, Marques J, Martinez-Fernandez A, Mizara N, Moustakas JM, Nicolau C, Oliveros G, Pinna R, Puddu J, Puigdefabregas M, Roxo A, Simao G, StamouMn Tomasi D, Usai D, Vacca A (1997) The effect of land use on runoff and soil erosion rates under Mediterranean conditions. Catena 29:45–59CrossRefGoogle Scholar
  14. 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):483–497CrossRefGoogle Scholar
  15. Kourgialas NN, Dokou Z, Karatzas GP (2015a) Statistical analysis and ANN modeling for predicting hydrological extremes under climate change scenarios. The example of a small Mediterranean agro-watershed. J Environ Manage 154:86–101CrossRefGoogle Scholar
  16. Kourgialas ΝΝ, Karatzas GP, Morianou G (2015b) Water management plan for olive orchards in a semi-mountainous area of Crete. Greece Global Nest J 17(1):72–81Google Scholar
  17. Laflen JM, Moldenhauer WC (2003) Pioneering soil erosion prediction-the USLE story. World Association of Soil and Water Conservation, BeijinGoogle Scholar
  18. Märker M, Angeli L, Bottai L, Costantini R, Ferrari R, Innocenti L, Siciliano G (2008) Assessment of land degradation susceptibility by scenario analysis: a case study in southern Tuscany. Italy Geomorphology 93(1–2):120–129CrossRefGoogle Scholar
  19. Merritt W, Letcher R, Jakeman A (2003) A review of erosion and sediment transport models. Environ Model Softw 18(8–9):761–799CrossRefGoogle Scholar
  20. Mignot J, Bony S (2013) Presentation and analysis of the IPSL and CNRM climate models used in CMIP5. Clim Dyn 40(9):2089CrossRefGoogle Scholar
  21. Möller M, Koschitzki T, Hartmann K-J, Jahn R (2012) Plausibility test of conceptual soil maps using relief parameters. CATENA 88(1):57–67CrossRefGoogle Scholar
  22. Moore ID, Burch GJ (1986) Physical basis of the length-slope factor in the Universal soil loss equation. Soil Science Society America Journal 50:1294–1298CrossRefGoogle Scholar
  23. Mullan D (2013) Soil erosion under the impacts of future climate change: assessing the statistical significance of future changes and the potential on-site and off-site problems. Catena 109:234–246CrossRefGoogle Scholar
  24. Nearing MA, Pruski FF, O’Neal MR (2004) Expected climate change impacts on soil erosion rates: a review. J Soil Water Conserv 59(1):43–50Google Scholar
  25. Nunes J, Nearing M (2011) Modelling impacts of climatic change. In: Morgan R, Nearing M (eds) Handbook of Erosion Modelling. Wiley-Blackwell, Oxford, pp 289–312CrossRefGoogle Scholar
  26. Onori F, Bonis P, Grauso S (2006) Soil erosion prediction at the basin scale using the revised universal soil loss equation (RUSLE) in a catchment of Sicily (southern Italy). Environ Geol 50:1129–1140CrossRefGoogle Scholar
  27. Panagos P, Meusburger K, Alewell C, Montanarella L (2012) Soil erodibility estimation using LUCAS point survey data of Europe. Environ Model Softw 30:143–145CrossRefGoogle Scholar
  28. Panagos P, Meusburger K, Marc VL, Alewell C, Hiederer R, Montanarella L (2014) Assessing soil erosion in Europe based on data collected through a European network. Soil Sci Plant Nutr 60:15–29CrossRefGoogle Scholar
  29. Paroissien J-B, Darboux F, Couturier A, Devillers B, Mouillot F, Raclot D, Le Bissonnais YA (2015) Method for modeling the effects of climate and land use changes on erosion and sustainability of soil in a Mediterranean watershed (Languedoc, France). J Environ Manage 150:57–68CrossRefGoogle Scholar
  30. Parry ML, Rosenzweig C, Iglesias A, Livermore M, Fischer G (2004) Assessing the effects of climate change on global food production under differing socioeconomic scenarios. Global Environ. Change 14(1):53–67CrossRefGoogle Scholar
  31. Prasannakumar V, Shiny R, Geetha N, Vijith H (2011) Spatial prediction of soil erosion risk of by remote sensing, GIS and RUSLE approach-a case study of Siruvani river watershed in Attapady valley, Kerala, India. Environ Earth Sci 64:965–972CrossRefGoogle Scholar
  32. Racsko P, Szeidl L, Semenov M (1991) A serial approach to local stochastic weather models. Ecol Model 57(1–2):27–41CrossRefGoogle Scholar
  33. Ramos MC, Duran B (2014) Assessment of rainfall erosivity and its spatial and temporal variabilities: case study of the Penede`s area (NE Spain). Catena 123:135–147CrossRefGoogle Scholar
  34. Ramos MC, Martínez-Casasnovas JA (2015) Climate change influence on runoff and soil losses in a rainfed basin with Mediterranean climate. Nat Hazards 78(2):1065–1089CrossRefGoogle Scholar
  35. Renard KG, Freimund JR (1994) Using monthly precipitation data to estimate the R factor in the revised USLE. J Hydrol 157:287–306CrossRefGoogle Scholar
  36. Renard KG, Foster GR, Weesies GA, Porter JP (1997) Revised universal soil loss equation. J Soil Water Conserv 46:30–33Google Scholar
  37. Routschek A, Schmidt J, Kreienkamp F (2014) Impact of climate change on soil erosion—A high-resolution projection on catchment scale until 2100 in Saxony/Germany. CATENA 121:99–109CrossRefGoogle Scholar
  38. Saadat H, Adamowski J, Tayefi V, Namdar M, Sharifi F, Ale-Ebrahim S (2014) A new approach for regional scale interrill and rill erosion intensity mapping using brightness index assessments from medium resolution satellite images. Catena 113:306–313CrossRefGoogle Scholar
  39. Semenov MA, Barrow EM (1997) Use of a stochastic weather generator on the development of climate change scenarios. Clim Change 35(4):397–414CrossRefGoogle Scholar
  40. Semenov MA, Barrow EM (2002) LARS - WG: a stochastic weather generator for use in climate impact studiesGoogle Scholar
  41. Silva RMD, Montenegro SMGL, Santos CAG (2012) Integration of GIS and remote sensing for estimation of soil loss and prioritization of critical sub-catchments-a case study of Tapacura catchment. Nat Hazards 62:953–970CrossRefGoogle Scholar
  42. Simms AD, Woodroffe CD, Jones BG (2003) Application of RUSLE for erosion management in a coastal catchment, southern NSW. International Congress on modelling and simulation, vol 2, integrative modelling of biophysical, social and economic systems for resource management solutions, Townsville, Queensland, pp 678–683Google Scholar
  43. Stroosnijder L (2005) Measurement of erosion—Is it possible. Catena. The future of olive plantation systems on sloping and mountainous land—Scenarios for production and natural resource conservation. FP6 OLIVERO 2003–2006 Ε.U. 64(2–3):162–173Google Scholar
  44. Tian YC, Zhou YM, Wu BF, Zhou WF (2009) Risk assessment of water soil ersoion in upper basin of Miyun Reservoir. Beijing China Environ Geol 57(4):937–942CrossRefGoogle Scholar
  45. Tsagarakis KP, Dialynas GE, Angelakis AN (2004) Water resources management in Crete (Greece) including water recycling and reuse and proposed quality criteria. Agric Water Manage 66:35–47CrossRefGoogle Scholar
  46. Tsanis IK, Koutroulis AG, Daliakopoulos IN, Jacob D (2011) Severe climate-induced water shortage and extremes in Crete. Clim Change 106(4):667–677CrossRefGoogle Scholar
  47. Tsara M, Kosmas C, Kirkby MJ, Kosma D, Yassoglou N (2006) An evaluation of the PESERA soil erosion model and its application to a case study in Zakynthos. Greece Soil Use Manage 21(4):377–385CrossRefGoogle Scholar
  48. Volk M, Möller M, Wurbs D (2010) A pragmatic approach for soil erosion risk assessment within policy hierarchies. Land Use Policy 27(4):997–1009CrossRefGoogle Scholar
  49. Vrieling A, Sterk G, Beaulieu N (2002) Erosion risk mapping—A methodological case study in the Colombian Eastern plains. J Soil Water Conserv 57(3):158–163Google Scholar
  50. Williams J, Nearing MA, Nicks A, Skidmore E, Valentine C, King K, Savabi R (1996) Using soil erosion models for global change studies. J Soil Water Conserv 51(5):381–385Google Scholar
  51. Wischmeier WH, Smith DD (1978) Predicting rainfall erosion losses—a guide to conservation planning, Agriculture Handbook No. 537, US department of agriculture science and education administration, Washington, DC, USA, 163 ppGoogle Scholar
  52. Zhang X, Wu B, Ling F, Zeng Y, Yan N, Yuan C (2010) Identification of priority areas for controlling soil erosion. Catena 83:76–86CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2016

Authors and Affiliations

  • Nektarios N. Kourgialas
    • 1
    • 2
    Email author
  • Georgios C. Koubouris
    • 2
  • George P. Karatzas
    • 1
  • Ioannis Metzidakis
    • 2
  1. 1.School of Environmental EngineeringTechnical University of Crete, PolytechneioupolisChaniaGreece
  2. 2.Hellenic Agricultural Organization – DIMITRA, National Agricultural Research Foundation (N.AG.RE.F.)Institute for Olive Tree, Subtropical Crops and Viticulture, AgrokipioChaniaGreece

Personalised recommendations