Hydrological modelling of changes in the water balance due to the impact of woody biomass production in the North German Plain

  • Jens Hartwich
  • Markus Schmidt
  • Jens Bölscher
  • Christian Reinhardt-Imjela
  • Dieter Murach
  • Achim Schulte
Thematic Issue
Part of the following topical collections:
  1. Water in Germany


Several studies have implied that cultivation of willow and poplar short-rotation coppices influence the area’s water balance. Due to the high density of sites suitable for SRCs in the Northern German Plain, this study focusses on four different model areas representative of the climatic, soil, and morphological heterogeneity of this landscape. The river basins selected for the study are the Ems, Treene, Aland, and Uecker–Randow–Welse basins. The water balance modelling was performed with the Soil Water Assessment Tool (SWAT) and automatically calibrated with SWAT-CUP. The implemented scenarios were set to 10 % SRC cover on suitable sites, based on the area’s predicted need to meet domestic demands for woody biomass by 2020. Additionally, an extreme scenario of 100 % cultivation on all suitable sites was implemented to determine the maximum effect of SRC on the regional water balance as well as to allow for a direct comparison with annual crops, pasture, and deciduous forest. For parametrization, field measurements were used to characterize the key physiological parameters for willow and poplar in SWAT. The results for the 10 % SRC scenarios did not show a substantial impact on the investigated water balance components at the water basin level. But at the local level, the effects of conversion to SRC are more pronounced. In general, actual evapotranspiration of SRC is 16 % higher compared to annual crops and average groundwater recharge decreases by 48 %. Also, available water capacity in the soil increases by 26 % for SRCs in comparison with annual crops.


Hydrological modelling SWAT model Water balance Woody biomass North German Plain Short-rotation coppice 



This work was supported by the Federal Ministry of Food and Agriculture, Germany through the Fachagentur Nachwachsende Rohstoffe e. V. (FNR) (Grant Numbers 2012410 and 22014812). In addition, our thanks go to the Federal Agency for Cartography and Geodesy, Institute for Geosciences and Natural Resources; State Office for Mining, Geology and Minerals Brandenburg; Lower Saxony State Office for Water Management, Coastal and Nature Conservation; State Office for Environment, Health and Consumer Protection Brandenburg; State Office for the Environment, Nature Conservation and Geology Mecklenburg-Vorpommern; State Agency for Nature, Environment and Consumer Protection North Rhine-Westphalia; State Agency for Coastal Defense, National Park and Marine Reserve Schleswig–Holstein; the German Weather Service; the High Performance Computing at the Freie Universität Berlin for providing data, provision of calculation time and service; and the Eberswalde Forestry State Center of Excellence—Landeskompetenzzentrum Forst Eberswalde—of the Brandenburg State Forestry Agency for the loan of an instrument.


  1. Abbaspour K (2015) SWAT‐CUP: SWAT calibration and uncertainty programs—a user manual. EAWAG: Swiss Federal Institute of Aquatic and Technology. Accessed 26 Apr 2016
  2. Abbaspour KC, van Genuchten M, Th Schulin R, Schläppi E (1997) A sequential uncertainty domain inverse procedure for estimating subsurface flow and transport parameters. Water Resour Res 33(8):1879–1892. doi: 10.1029/97WR01230 CrossRefGoogle Scholar
  3. Abbaspour KC, Sonnleitner M, Schulin R (1999) Uncertainty in estimation of soil hydraulic parameters by inverse modeling: example lysimeter experiments. Soil Sci Soc Am J 63(3):501–509. doi: 10.2136/sssaj1999.03615995006300030012x CrossRefGoogle Scholar
  4. Abbaspour KC, Yang J, Maximov I, Siber R, Bogner K, Mieleitner J, Zobrist J, Srinivasan R (2007) Modelling hydrology and water quality in the pre-alpine/alpine Thur watershed using SWAT. J Hydrol 333(2–4):413–430. doi: 10.1016/j.jhydrol.2006.09.014 CrossRefGoogle Scholar
  5. Abbaspour KD, Rouholahnejad E, Si Vaghef, Srinivasan R, Yang H, Kløve B (2015) A continental-scale hydrology and water quality model for Europe: calibration and uncertainty of a high-resolution large-scale SWAT model. J Hydrol 524:733–752. doi: 10.1016/j.jhydrol.2015.03.027 CrossRefGoogle Scholar
  6. Allen G, Pereira S, Raes D, Smith M (1998) Crop evapotranspiration—guidelines for computing crop water requirements—FAO irrigation and drainage paper 56. Rome: FAO. Accessed 20 Oct 2015
  7. Arnold J, Srinivasan R, Muttiah RS, Williams JR (1998) Large area hydrologic modeling and assessment part I: model development. J Am Water Resour Assoc 34(1):73–89. doi: 10.1111/j.1752-1688.1998.tb05961.x CrossRefGoogle Scholar
  8. Arnold JG, Moriasi DN, Gassman PW, Abbaspour PW, White PW, Srinivasan R, Santhi C, van Harmel RD, Van Griensven A, Van Liew MW, Kannan N, Jha MK (2012) SWAT: model use, calibration, and validation. Trans ASABE 55(4):1491–1508CrossRefGoogle Scholar
  9. Aust C (2012) Abschätzung der Nationalen und regionalen Biomassepotentiale von Kurzumtriebsplantagen auf landwirtschaftlichen Flächen in Deutschland. Dissertation. Albrecht-Ludwigs-Universität, Freiburg im BreisgauGoogle Scholar
  10. Bund für Umwelt und Naturschutz Deutschland (BUND) (2010) Kurzumtriebsplantagen für die Energieholzgewinnung – Chancen und Risiken. Bund für Umwelt und Naturschutz Deutschland. Retrieved from Accessed 26 Nov 2015
  11. Bungart R, Hüttl RF (2004) Growth dynamics and biomass accumulation of 8-year-old hybrid poplar clones in a short-rotation plantation on a clayey-sandy mining substrate with respect to plant nutrition and water budget. Eur J For Res 123:105–115. doi: 10.1007/s10342-004-0024-8 Google Scholar
  12. Dimitriou I, Busch G, Jacobs S, Schmidt-Walter P, Lamersdorf N (2009) A review of the impacts of short rotation coppice cultivation on water issues. Agric For Res 59(3):162–197Google Scholar
  13. Ettala MO (1988) Evapotranspiration from Salix aquatic plantation at a sanitary landfill. Aqua Fenn 18:3–14Google Scholar
  14. Fachargentur für Nachwachsende Rohstoffe (2014) Anteil erneuerbarer Energien am Endenergieverbrauch. Accessed 30 Jan 2015
  15. Fu YH, Piao S, Vitasse Y, Zhao H, De Boeck HJ, Liu Q, Yang H, Weber U, Hänninen H, Janssens IA (2015) Increased heat requirement for leaf flushing in temperate woody species over 1980–2012: effects of chilling, precipitation and insolation. Glob Change Biol 21:2687–2697CrossRefGoogle Scholar
  16. Gassman P, Reyes M, Green C, Arnold JG (2007) The soil and water assessment tool: historical development, applications, and future research directions. ASABE 50(4):1211–1250. doi: 10.13031/2013.23637 CrossRefGoogle Scholar
  17. Gupta HV, Sorooshian S, Yapo PO (1999) Status of automatic calibration for hydrologic models: comparison with multilevel expert calibration. J Hydrol Eng 4(2):135–143. doi: 10.1061/(ASCE)1084-0699(1999)4:2(135) CrossRefGoogle Scholar
  18. Guse B, Reusser DE, Fohrer N (2014) How to improve the representation of hydrological processes in SWAT for a lowland catchment—temporal analysis of parameter sensitivity and model performance. Hydrol Process 28:2651–2670. doi: 10.1002/hyp.9777 CrossRefGoogle Scholar
  19. Hall RL, Allen SJ (1997) Water use of poplar clones grown as short-rotation coppice at two sites in the United Kingdom. Asp Appl Biol 49:163–172Google Scholar
  20. Hartwich J, Bölscher J, Schulte A (2014) The impact of short rotation coppice on land and water resources. Water Int 39(6):813–841. doi: 10.1080/02508060.2014.959870 CrossRefGoogle Scholar
  21. Hartwich J, Bölscher J, Schulte A, Schmidt M, Pflugmacher C, Murach D (2015a) Das Transpirationswasserdargebot als steuernder Faktor für die Produktion von Energie aus Weiden in Kurzumtriebsplantagen – Abschätzung des Bioenergiepotentials für Deutschland. Hydrol Wasserbewirtsch 59(5):217–226. doi: 10.5675/HyWa_2015,5_2 Google Scholar
  22. Hartwich J, Reinhardt-Imjela C, Bölscher J, Schulte A (2015b) The impact of woody biomass production on the water balance of the North German Lowlands—model setup and calibration. In: Proceedings of conference on international soil and water assessment tool, Pula, Sardinia, Italy, pp 1–13Google Scholar
  23. Henriksen HJ, Troldborg L, Nyegaard P, Sonnenborg TO, Refsgaard JC, Madsen B (2003) Methodology for construction, calibration and validation of a national hydrological model for Denmark. J Hydrol 280(1–4):52–71. doi: 10.1016/S0022-1694(03)00186-0 CrossRefGoogle Scholar
  24. Internationales Institut für Wald und Holz NRW (2014) Entwicklung eines Nachhaltigkeitszertifikats für den Agrarholzanbau, AZ 29927-01/-02. Schlussbericht. Band 1. DBU, MünsterGoogle Scholar
  25. Lamersdorf N, Petzold R, Schwärzel K, Feger KH, Köstner B, Moderow U, Bernhofer C, Kunst C (2010) Bodenökologische Aspekte von Kurzumtriebsplantagen. In: Bemmann A, Knust C (eds) Agrowood. Kurzumtriebsplantagen in Deutschland und europäische Perspektiven. Weißensee Verlag, Berlin, pp 170–188Google Scholar
  26. Linderson M-J, Iritz Z, Lindroth A (2007) The effect of water availability on stand-level productivity, transpiration, water use efficiency and radiation use efficiency of field-grown willow clones. Biomass Bioenergy 31(7):460–468. doi: 10.1016/j.biombioe.2007.01.014 CrossRefGoogle Scholar
  27. Moriasi DN, Arnold JG, Van Liew MW, Bingner RL, Harmel RD, Veith TL (2007) Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Am Soc Agric Biol Eng 50(3):885–900Google Scholar
  28. Murach D, Hartmann H, Murn Y, Schultze M, Wael A, Röhle H (2009) Standortsbasierte Leistungsschätzung in Agrarholzbeständen in Brandenburg und Sachsen. In: Reeg T, Bemmann A, Kondold W, Murach D, Spiecker H (eds) Anbau und Nutzung von Bäumen auf Landwirtschaftlichen Flächen. Wiley, Weinheim, pp 29–40CrossRefGoogle Scholar
  29. Nash JE, Sutcliffe JV (1970) River flow forecasting through conceptual models. Part I: discussion of principles. J Hydrol 10:282–290. doi: 10.1016/0022-1694(70)90255-6 CrossRefGoogle Scholar
  30. Neitsch SL, Arnold JG, Kiniry JR, Williams JR (2011) Soil and Water Assessment Tool theoretical documentation version 2009. Texas Water Resources Institute technical report no. 406. Accessed 26 Nov 2015
  31. Neumann J, Wycisk P (2003) Mittlere jährliche Grundwasserneubildung. In: Liedtke H, Mäusbacher R, Schmidt KH (eds) Bundesrepublik Deutschland Nationalatlas – Relief, Boden und Wasser. Spektrum Akademischer Verlag, Heidelberg, pp 144–145Google Scholar
  32. Nisbet T (2005) Water use by trees. Forestry commission information note 65. Forestry Commission, EdinburghGoogle Scholar
  33. Nisbet T, Thomas H, Shah N (2011) Short rotation forestry and water. In: McKay H (ed) Short rotation forestry: review of growth and environmental impacts. Forest research monograph, vol 2. Forest Research, Surrey, pp 13–34Google Scholar
  34. Petzold R, Feger KH, Schwärzel K (2009) Wasserhaushalt von Kurzumtriebsplantagen. In: Reeg T, Bemmann A, Konold W, Murach D, Spiecker H (eds) Anbau und Nutzung von Bäumen auf landwirtschaftlichen Flächen. Wiley-VCH Verlag, Weinheim, pp 181–192CrossRefGoogle Scholar
  35. Pfannerstill M, Guse B, Fohrer N (2014) A multi-storage groundwater concept for the SWAT model to emphasize nonlinear groundwater dynamics in lowland catchments. Hydrol Process 28:5599–5612. doi: 10.1002/hyp.10062 CrossRefGoogle Scholar
  36. Rouholahnejad E, Abbaspour KC, Vejdani M, Srinivasan R, Schulin R, Lehmann A (2012) A parallelization framework for calibration of hydrological models. Environ Model Softw 31:28–36. doi: 10.1016/j.envsoft.2011.12.001 CrossRefGoogle Scholar
  37. Schmalz B, Tavares F, Fohrer N (2008) Modelling hydrological processes in mesoscale lowland river basins with SWAT—capabilities and challenges. Hydrol Sci J 53(5):989–1000. doi: 10.1623/hysj.53.5.989 CrossRefGoogle Scholar
  38. Schmidt M, Murach D (2015) Wassernutzungseffizienz von Gehölzen im Kurzumtrieb auf Ackerstandorten in Brandenburg. In: Kage H, Sieling H, Francke-Weltmann L (eds) Multifuntionale Agrarlandschaften – Pflanzenbaulicher Anspruch, Biodiversität, Ökosystemdienstleistungen. Verlag Liddy Halm, Göttingen, pp 41–42Google Scholar
  39. Servat E, Dezetter A (1991) Selection of calibration objective functions in the context of rainfall-runoff modelling in a Sudanese savannah area. Hydrol Sci J 36(4):307–330. doi: 10.1080/02626669109492517 CrossRefGoogle Scholar
  40. Singh J, Knapp HV, Demissie M (2004) Hydrologic modeling of the Iroquois River watershed using HSPF and SWAT. Illinois State Water Survey Contract Report 2004–08. Accessed 26 Nov 2015
  41. Singh J, Knapp HV, Arnold JG, Demissie M (2005) Hydrologic modeling of the Iroquois River watershed using HSPF and SWAT. J Am Water Resour Assoc 41(2):361–375. doi: 10.1111/j.1752-1688.2005.tb03740.x CrossRefGoogle Scholar
  42. Srinivasan R, Ramanarayanan TS, Arnold JG, Bednarz ST (1998) Large area hydrologic modeling and assessment part II: model application. J Am Water Resour Assoc 34:91–101. doi: 10.1111/j.1752-1688.1998.tb05962.x CrossRefGoogle Scholar
  43. Stisen S, Sonnenborg TO, Hojberg AL, Troldborg L, Refsgaard JC (2011) Evaluation of climate input biases and water balance issues using a coupled surface–subsurface model. Vadose Zone J 10(1):37–53. doi: 10.2136/vzj2010.0001 CrossRefGoogle Scholar
  44. Stork M, Schulte A, Murach D (2014) Large-scale fuelwood production on agricultural fields in mesoscale river catchments–GIS-based determination of potentials in the Dahme river catchment (Brandenburg, NE Germany). Biomass Bioenergy 64:42–49. doi: 10.1016/j.biombioe.2014.03.029 CrossRefGoogle Scholar
  45. Strauch M, Bernhofer C, Koide S, Lorz C, Volk M, Makeschin F (2012) Using precipitation data ensemble for uncertainty analysis in SWAT streamflow simulation. J Hydrol 414–415:413–424. doi: 10.1016/j.jhydrol.2011.11.014 CrossRefGoogle Scholar
  46. Tallis MJ, Casella E, Henshall PA, Aylott MJ, Randle TJ, Morison JIL, Taylor G (2013) Development and evaluation of ForestGrowth-SRC a process-based model for short rotation coppice yield and spatial supply reveals poplar uses water more efficiently than willow. Glob Change Biol Bioenergy 5:53–66. doi: 10.1111/j.1757-1707.2012.01191.x CrossRefGoogle Scholar
  47. Umweltbundesamt (2013) Strom- und Wärmeversorgung einer Siedlung bei unterschiedlichen Energieeffizienz-Standards. Umweltbundesamt, Dessau-RoßlauGoogle Scholar
  48. Van Liew M, Veith T, Bosch D, Arnold J (2007) Suitability of SWAT for the conservation effects assessment project: comparison on USDA agricultural research service watersheds. J Hydrol Eng 12(2):173–189. doi: 10.1061/(ASCE)1084-0699(2007)12:2(173) CrossRefGoogle Scholar
  49. Vitasse Y, Basler D (2013) What role for photoperiod in the bud burst phenology of European beech. Eur J For Res 132:1–8CrossRefGoogle Scholar
  50. Wahren A, Schwärzel K, Feger K-H (2012) Potentials and limitations of natural flood retention by forested land in headwater catchments: evidence from experimental and model studies. J Flood Risk Manag 5(4):321–335. doi: 10.1111/j.1753-318X.2012.01152.x CrossRefGoogle Scholar
  51. Wahren A, Julich S, Feger KH (2014) Modellgestützte Untersuchung zum Einfluss von Energieholz-Anbau auf ein mesoskaliges Einzugsgebiet (Hoyerswerdaer Schwarzwasser, Sachsen). In: Cyffka B (ed) Wasser – Landschaft – Mensch in Vergangenheit, Gegenwart und Zukunft. Beiträge zum Tag der Hydrologie am 20./21. März 2014 an der Katholischen Universität Eichstät-Ingolstadt. Forum für Hydrologie und Wasserbewirtschaftung Heft, vol 34, no 14, pp 245–252Google Scholar
  52. Wahren A, Richter F, Julich S, Jansen M, Feger KH (2015) The influence of more widespread cultivation of short rotation coppice on the water balance—from the site to regional scale. In: Manning DB, Bemmann A, Bredemeier M, Lamersdorf N, Ammer C (eds) Bioenergy from Dendromass for the sustainable development of rural areas. Wiley-VCH Verlag, Weinheim, pp 45–61. doi: 10.1002/9783527682973.ch5 CrossRefGoogle Scholar
  53. Webb J, Cook P, Skiba U, Levy P, Sajwaj T, Parker C, Mouat A (2009) Investigation of the economics and potential environmental impacts of the production of short rotation coppicing on poorer quality land. Report to the Scottish Government. AEA, DidcotGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • Jens Hartwich
    • 1
  • Markus Schmidt
    • 2
  • Jens Bölscher
    • 1
  • Christian Reinhardt-Imjela
    • 1
  • Dieter Murach
    • 2
  • Achim Schulte
    • 1
  1. 1.Institute of Geographical Science, Applied Geography, Environmental Hydrology and Resource ManagementFreie Universität BerlinBerlinGermany
  2. 2.Faculty of Forest and EnvironmentEberswalde University for Sustainable Development, University of Applied ScienceEberswaldeGermany

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