Theoretical and Applied Climatology

, Volume 132, Issue 1–2, pp 1–13 | Cite as

Evaluation of a simple, point-scale hydrologic model in simulating soil moisture using the Delaware environmental observing system

  • David R. Legates
  • Katherine T. Junghenn
Original Paper


Many local weather station networks that measure a number of meteorological variables (i.e., mesonetworks) have recently been established, with soil moisture occasionally being part of the suite of measured variables. These mesonetworks provide data from which detailed estimates of various hydrological parameters, such as precipitation and reference evapotranspiration, can be made which, when coupled with simple surface characteristics available from soil surveys, can be used to obtain estimates of soil moisture. The question is Can meteorological data be used with a simple hydrologic model to estimate accurately daily soil moisture at a mesonetwork site? Using a state-of-the-art mesonetwork that also includes soil moisture measurements across the US State of Delaware, the efficacy of a simple, modified Thornthwaite/Mather-based daily water balance model based on these mesonetwork observations to estimate site-specific soil moisture is determined. Results suggest that the model works reasonably well for most well-drained sites and provides good qualitative estimates of measured soil moisture, often near the accuracy of the soil moisture instrumentation. The model exhibits particular trouble in that it cannot properly simulate the slow drainage that occurs in poorly drained soils after heavy rains and interception loss, resulting from grass not being short cropped as expected also adversely affects the simulation. However, the model could be tuned to accommodate some non-standard siting characteristics.



Funding for Ms. Junghenn was provided by National Science Foundation EPSCoR Grant No. IIA-1301765 and the State of Delaware. The authors wish to thank Ms. Linden Wolf for her help with the DEOS rainfall data, Mr. Steven Noyes for his assistance in developing a computer program to validate the rainfall data, and Dr. Gregory J. McCabe Jr. of the US Geological Survey and an anonymous reviewer for their comments on earlier versions of the manuscript.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflicts of interest.


  1. Ahmad A, Zhang Y, Nichols S (2011) Review and evaluation of remote sensing methods for soil-moisture estimation. SPIE Reviews 2, paper 028001, doi: 10.1117/1.3534910
  2. Allen RG, Smith M, Pereira LS, Perrier A (1994) An update for the calculation of reference evapotranspiration. ICID Bulletin 43(2):35–92Google Scholar
  3. American Society of Civil Engineers (2009) Curve number hydrology: state of the practice. American Society of Civil Engineers and the Environmental and Water Resources Institute, 73 ppGoogle Scholar
  4. Andersson L, Harding RJ (1991) Soil-moisture deficit simulations with models of varying complexity for forest and grassland sites in Sweden and the U.K. Water Resour Manag 5:25–46CrossRefGoogle Scholar
  5. Arnold JG, Srinivasan R, Muttiah RS, Williams JR (1998) Large area hydrologic modeling and assessment part I: model development. J Am Water Resour Assoc 34(1):73–89CrossRefGoogle Scholar
  6. Baier W, Robertson GW (1966) A new versatile soil moisture budget. Can J Plant Sci 46:299–315Google Scholar
  7. Bartholf DP (1994) An evaluation of the ASOS temperature sensors and heated tipping bucket rain gauge at Syracuse, New York. Eastern Region Technical Attachment, No. 94-11A, National Weather Service, 9 ppGoogle Scholar
  8. Benson CH, Wang X (2006) Temperature-compensating calibration procedure for water content reflectometers. Proceedings of TDR 2006, paper ID 50. Purdue University, West Lafayette, Indiana 16ppGoogle Scholar
  9. Brock FV, Crawford KC, Elliott RL, Cuperus GW, Stadler SJ, Johnson HL, Elilts MD (1995) The Oklahoma mesonet: a technical overview. J Atmos Ocean Technol 12(1):5–19CrossRefGoogle Scholar
  10. Campbell Scientific (2014). CS616 and CS625 Water Content Reflectometers. Downloaded from on January 19, 2015
  11. Chandler DG, Seyfried M, Murdock M, McNamara JP (2004) Field calibration of water content reflectometers. Soil Sci Soc Am J 68(5):1501–1507CrossRefGoogle Scholar
  12. Chávez JL, Evett SR (2012) Using soil water sensors to improve irrigation management. Proceedings, 24th annual Central Plains irrigation conference. Central Plains Irrigation Association, Colby Kansas, pp 187–202Google Scholar
  13. Choi HI, Liang X-Z (2010) Improved terrestrial hydrologic representation in mesoscale land surface models. J Hydrometeorol 11(6):797–809CrossRefGoogle Scholar
  14. Chow L, Xing Z, Rees HW, Meng F, Monteith J, Stevens L (2009) Field performance of nine soil water content sensors on a sandy loam soil in New Brunswick, Maritime Region, Canada. Sensors 9:9398–9413CrossRefGoogle Scholar
  15. Corbane C, Raclot D, Jacob F, Albergel J, Andrieux P (2008) Remote sensing of soil surface characteristics from a multiscale classification approach. Catena 75:308–318CrossRefGoogle Scholar
  16. Dingman SL (2008) Physical hydrology, Second edn. Prentice Hall, Upper Saddle River 656ppGoogle Scholar
  17. Dunne T, Leopold LB (1978) Water in environmental planning. W.H. Freeman & Co., San Francisco, CA 818ppGoogle Scholar
  18. Ferguson BK (1996) Estimation of direct runoff in the Thornthwaite water balance. Prof Geogr 48(3):263–271Google Scholar
  19. Guswa AJ, Celia MA, Rodriguez-Inturbe I (2002) Models of soil moisture dynamics in ecohydrology: a comparative study. Water Resour Res 38(9):1166. doi: 10.1029/2001WR000826 CrossRefGoogle Scholar
  20. Kannan N, Santhi C, Williams JR, Arnold JG (2008) Development of a continuous soil moisture accounting procedure for curve number methodology and its behavior with different evapotranspiration methods. Hydrol Process 22:2114–2121CrossRefGoogle Scholar
  21. Kelleners TJ, Seyfried MS, Blonquist JM, Bilskie J, Chandler DG (2005) Improved interpretation of water content reflectometer measurements in soils. Soil Sci Soc Am J 69(6):1684–1690CrossRefGoogle Scholar
  22. Lakshmi V (2013) Remote sensing of soil moisture. ISRN Soil Science, Article ID 424178Google Scholar
  23. Legates DR (2000) Real-time calibration of radar precipitation estimates. Prof Geogr 52(2):235–246CrossRefGoogle Scholar
  24. Legates DR, McCabe GJ (1999) Evaluating the use of ‘goodness-of-fit’ measures in hydrologic and hydroclimatic model validation. Water Resour Res 35(1):233–241CrossRefGoogle Scholar
  25. Legates DR, McCabe GJ (2013) A refined index of model performance: a rejoinder. Int J Climatol 33:1053–1056CrossRefGoogle Scholar
  26. Legates DR, Mahmood R, Levia DF, DeLiberty TL, Quiring SM, Houser C, Nelson FE (2011) Soil moisture: a central and unifying theme in physical geography. Prog Phys Geogr 35(1):65–86CrossRefGoogle Scholar
  27. Lim KJ, Engel BA, Muthukrishnan S, Harbor J (2006) Effects of initial abstraction and urbanization on estimate runoff using technology. J Am Water Resour Assoc 42(3):629–643CrossRefGoogle Scholar
  28. Mather JR (1954) The determination of soil moisture from climatic data. Bull Am Meteorol Soc 35(2):63–68Google Scholar
  29. Mather JR (1974) Climatology: fundamentals and applications. McGraw-Hill, New York 412ppGoogle Scholar
  30. Mather JR (1978) The climatic water budget in environmental analysis. Lexington Books, New York 239ppGoogle Scholar
  31. Mather JR (1981) Using computed stream flow in watershed analysis. Water Resour Bull 17(3):474–482CrossRefGoogle Scholar
  32. McPherson RA, Fiebrich CA, Crawford KC et al (2007) Statewide monitoring of the mesoscale environment: a technical update on the Oklahoma mesonet. J Atmos Ocean Technol 24(3):301–321CrossRefGoogle Scholar
  33. Mello CR, Viola MR, Norton LD, Silva AM, Weimar FA (2008) Development and application of a simple hydrologic model simulation for a Brazilian headwater basin. Catena 75(3):235–247CrossRefGoogle Scholar
  34. Nadler A (2005) Comments on ‘field calibration of water content reflectometers’. Soil Sci Soc Am J 69(4):1356–1357CrossRefGoogle Scholar
  35. Narasimhan B, Srinivasan R, Arnold JG, Di Luzio M (2005) Estimation of long-term soil moisture using a distributed parameter hydrologic model and verification using remotely sensed data. Transactions of the ASAE 48(3):1101–1113CrossRefGoogle Scholar
  36. Nash JE, Sutcliffe JV (1970) River flow forecasting through conceptual models. Part I – a discussion of principles. J Hydrol 10:282–290CrossRefGoogle Scholar
  37. Natural Resources Conservation Service (2013) Web Soil Survey, United States Department of Agriculture,, retrieved July 2014
  38. Oke TR (1987) Boundary layer climates, 2nd edn. Routledge, Abingdon-on-Thames 435ppGoogle Scholar
  39. Pandey V, Pandey PK (2010) Spatial and temporal variability of soil moisture. Int J Geosci 1:87–98CrossRefGoogle Scholar
  40. Saxton KE, Rawls WJ (2006) Soil water characteristic estimates by texture and organic matter for hydrologic solutions. Soil Sci Soc Am J 70:1569–1578CrossRefGoogle Scholar
  41. Sevruk B (1983) Correction of measured precipitation in the alps using the water equivalent of new snow. Nord Hydrol 14:49–58Google Scholar
  42. Sheikh V, Visser S, Stroosnijer L (2009) A simple model to predict soil moisture: bridging event and continuous hydrological (BEACH) modelling. Environ Model Softw 24(4):542–556CrossRefGoogle Scholar
  43. Soliman A, Heck RJ, Brenning A, Brown R, Miller S (2013) Remote sensing of soil moisture in vineyards using airborne and ground-based thermal inertia data. Remote Sens 5:3729–3748CrossRefGoogle Scholar
  44. Thornthwaite CW (1948) An approach toward a rational classification of climate. Geogr Rev 38(1):55–94CrossRefGoogle Scholar
  45. Thornthwaite CW, Mather JR (1955) The water balance. Publications in Climatology 55(1):104ppGoogle Scholar
  46. Vereecken H, Huisman JA, Bogena H, Vanderborght J, Vrugt JA, Hopmans JW (2008) On the value of soil moisture measurements in vadose zone hydrology: a review. Water Resour Res 44:W00D06Google Scholar
  47. Willmott CJ, Ackleson SG, Davis RE, Feddema JJ, Klink KM, Legates DR, O’Donnell J, Rowe CM (1985) Statistics for the evaluation and comparison of models. J Geophys Res 90(C5):8995–9005CrossRefGoogle Scholar
  48. Yao X, Fu B, Lu Y, Sun F, Wang S, Liu M (2013) Comparison of four spatial interpolation methods for estimating soil moisture in a complex terrain catchment. PLoS One 8(1):e54660CrossRefGoogle Scholar
  49. Zhang C, Walters D, Kovacs JM (2014) Applications of low altitude remote sensing in agriculture upon farmers’ requests—a case study in northeastern Ontario, Canada. PLoS One 9(11):e112894CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Wien 2017

Authors and Affiliations

  1. 1.College of Earth, Ocean, and EnvironmentUniversity of DelawareNewarkUSA
  2. 2.Environmental Science ProgramUniversity of DelawareNewarkUSA
  3. 3.Department of Atmospheric and Oceanic ScienceUniversity of MarylandCollege ParkUSA

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