Advertisement

Hydrogeology Journal

, Volume 26, Issue 3, pp 869–880 | Cite as

Comparison of specific-yield estimates for calculating evapotranspiration from diurnal groundwater-level fluctuations

  • Zoltán GribovszkiEmail author
Paper
  • 328 Downloads

Abstract

Methods that use diurnal groundwater-level fluctuations are commonly used for shallow water-table environments to estimate evapotranspiration (ET) and recharge. The key element needed to obtain reliable estimates is the specific yield (Sy), a soil-water storage parameter that depends on unsaturated soil-moisture and water-table fluxes, among others. Soil-moisture profile measurement down to the water table, along with water-table-depth measurements, can provide a good opportunity to calculate Sy values even on a sub-daily scale. These values were compared with Sy estimates derived by traditional techniques, and it was found that slug-test-based Sy values gave the most similar results in a sandy soil environment. Therefore, slug-test methods, which are relatively cheap and require little time, were most suited to estimate Sy using diurnal fluctuations. The reason for this is that the timeframe of the slug-test measurement is very similar to the dynamic of the diurnal signal. The dynamic characteristic of Sy was also analyzed on a sub-daily scale (depending mostly on the speed of drainage from the soil profile) and a remarkable difference was found in Sy with respect to the rate of change of the water table. When comparing constant and sub-daily (dynamic) Sy values for ET estimation, the sub-daily Sy application yielded higher correlation, but only a slightly smaller deviation from the control ET method, compared with the usage of constant Sy.

Keywords

Groundwater recharge Unsaturated zone Diurnal signal Specific yield Evapotranspiration 

Comparaison de valeurs estimées de porosité efficace pour calculer l’évapo-transpiration à partir de fluctuations piézométriques diurnes

Résumé

Les méthodes qui utilisent les fluctuations piézométriques diurnes sont généralement utilisées en contexte de nappe peu profonde pour estimer l’évapo-transpiration (ETP) et la recharge. L’élément-clé nécessaire pour obtenir des estimations fiables est. la porosité efficace (Pe), un paramètre de stockage de l’eau du sol qui dépend de la teneur en eau de la zone non saturée du sol et des fluctuations du niveau de la nappe, entre autres. Les mesures en profil vertical de la teneur en eau du sol jusqu’au niveau piézométrique, conjointement à des mesures piézométriques, peuvent constituer un bon moyen de calculer les valeurs de Pe, même à un pas de temps quasi-journalier. Ces valeurs ont été comparées avec des valeurs estimées de Pe issues de techniques classiques, et il s’est. avéré que les valeurs de Pe issues d’essais par injection instantanée (slug-tests) ont donné des résultats assez similaires en contexte de sols sableux. Par conséquent, les méthodes de slug-test, qui sont peu coûteuses et peu chronophages, ont été les plus adaptées pour estimer Pe avec des méthodes utilisant les fluctuations diurnes. L’explication vient du délai de réalisation du slug-test qui est. très proche de la dynamique du signal diurne. La composante dynamique de Pe a aussi été analysée à un pas de temps quasi-journalier (dépendant essentiellement de la vitesse de drainage à travers le profil du sol) et une différence remarquable a été identifiée pour Pe en fonction du taux de variation du niveau piézométrique. En comparant les valeurs constantes et quasi-journalières (dynamiques) de Pe pour estimer l’ETP, l’utilization de valeurs quasi-journalières de Pe permet une meilleure corrélation, en comparaison de l’usage de Pe constantes, et seulement une légère déviation par rapport à la méthode ETP de contrôle.

Comparación de estimaciones de rendimiento específico para calcular la evapotranspiración a partir de las fluctuaciones diurnas del nivel del agua subterránea

Resumen

Los métodos que usan las fluctuaciones diurnas para estimar la evapotranspiración (ET) y la recarga se emplean comúnmente en ambientes con el nivel freático somero. El elemento clave que se necesita para obtener estimaciones confiables es el rendimiento específico (Sy), un parámetro de almacenamiento de agua y suelo que depende del flujo no saturado de humedad en el suelo y en la capa freática, entre otros. La medición del perfil de humedad del suelo hasta la capa freática, junto con las mediciones de profundidad del nivel freático, puede proporcionar una buena oportunidad para calcular los valores de Sy incluso en una escala sub-diaria. Estos valores se compararon con estimaciones de Sy derivadas por técnicas tradicionales, y se encontró que los valores de Sy basados ​​en ensayos “slug” dieron los resultados más similares en un ambiente de suelo arenoso. Por lo tanto, los métodos de ensayos “slug”, que son relativamente económicos y requieren poco tiempo, fueron los más adecuados para calcular Sy mediante el uso de las fluctuaciones diurnas. La razón de esto es que el marco temporal de la medición de los ensayos “slug” es muy similar a la dinámica de la señal diurna. La característica dinámica de Sy también se analizó en una escala sub-diaria (dependiendo principalmente de la velocidad de drenaje del perfil del suelo) y se encontró una diferencia notable en Sy con respecto a la tasa de cambio de la capa freática. Al comparar los valores de Sy constantes y sub-diarios (dinámicos) para la estimación de ET, la aplicación sub-diaria de Sy arrojó una correlación más alta, pero solo una desviación ligeramente más pequeña del método ET de control, en comparación con el uso de Sy constante.

对单位出水量估算值进行对比,进而根据白天地下水位波动计算蒸发蒸腾量

摘要

利用日间地下水位波动的方法通常用于浅层水位环境中估算蒸发蒸腾量和补给量。需要获取可靠估算值的关键要素是众多要素中的单位出水量、依赖于非饱和土壤水和水位通量的土壤水储量参数。土壤水剖面抵达水位的测量结果,加上水位深度测量结果甚至可为计算日以下尺度的单位出水量提供很好的机会。这些值与根据传统技术得出的单位出水量估算值进行了对比,发现基于微水试验的单位出水量值在砂质土壤环境中给出了最相似的结果。因此,相对费用不高、需要很少时间的微水试验最适合采用日间波动的方法估算单位出水量。理由就是微水试验测量的时间框架与日间信号的动态非常相似。还分析了日以下尺度的单位出水量的动态特征(主要取决于土壤剖面的排水速度),发现单位出水量与水位变化率相比有很大差别。通过比较用于蒸发蒸腾估算的常数和日以下(动态)单位出水量值,采用日以下单位出水量可以出现较高的相关性,与采用恒定单位出水量相比,控制蒸发蒸腾量方法有稍微小的误差。

Comparação de estimativas de rendimento especifico para o cálculo da evapotranspiração a partir de flutuações diurnas do nível da água subterrânea

Resumo

Métodos que utilizam as flutuações diurnas no nível das águas subterrâneas são comumente usados em ambientes com lençol freático raso para estimar a evapotranspiração (ET) e recarga. O elemento chave necessário para obter estimativas confiáveis é o rendimento especifico (Sy), um parâmetro de armazenamento de água no solo que depende da umidade do solo não saturado e fluxos do lençol freático, dentre outros. A medição do perfil de umidade do solo até o lençol freático, juntamente com medições da profundidade do nível freático, pode fornecem uma boa oportunidade para calcular os valores de Sy mesmo em uma escala sub-diária. Esses valores foram comparados com estimativas de Sy derivadas de técnicas tradicionais, e verificou-se que os valores de Sy baseado em slug-test deram os resultados mais semelhantes em um ambiente de solo arenoso. Assim sendo, métodos de slug-test, que são relativamente baratos e requerem pouco tempo, foram mais adequados para estimar o Sy utilizando flutuações diurnas. A razão para isso é que o prazo do slug-test é muito similar à dinâmica do sinal diurno. As características dinâmicas do Sy também foram analisadas em uma escala sub-diária (dependendo principalmente da velocidade de drenagem do perfil do solo) e uma diferença notável foi encontrada em Sy com relação a taxa de variação do lençol freático. Ao comparar valores de Sy constantes e sub-diários (dinâmicos) para estimativa da ET, a aplicação de Sy sub-diário rendeu uma maior correlação, mas apenas um desvio ligeiramente menor do método de controle da ET, comparado ao uso de Sy constante.

Notes

Acknowledgements

This research has been supported by the “Agroclimate 2 (VKSZ_12-1-2013-00-34)” and the EFOP-3.6.2-16-2017-00018 projects. The research of Zoltán Gribovszki was supported by the European Union and the State of Hungary, and co-financed by the European Social Fund in the framework of TÁMOP 4.2.4. A/2-11-1-2012-0001 ‘National Excellence Program’.

References

  1. Bear J (1972) Dynamics of fluids in porous materials. Dover, Mineola, NYGoogle Scholar
  2. Carsel RF, Parrish RS (1988) Developing joint probability distributions of soil water retention characteristics. Water Resour Res 24:755–769CrossRefGoogle Scholar
  3. Cheng DH, Li Y, Chen XH (2013) Estimation of groundwater evapotranspiration using diurnal water table fluctuations in the Mu Us Desert, northern China. J Hydrol 490:106–113CrossRefGoogle Scholar
  4. Child EC (1960) The nonsteady state of water table in drained land. J Geophys Res 65:780–782CrossRefGoogle Scholar
  5. Coduto DP, Yeung MC, Kitch WA (2011) Geotechnical engineering: principles and practices. Pearson, Upper Saddle River, NJGoogle Scholar
  6. Crosbie RS, Binning P, Kalma JD (2005) A time series approach to inferring groundwater recharge using the water table fluctuation method. Water Resour Res 41:W01008.  https://doi.org/10.1029/2004WR003077 CrossRefGoogle Scholar
  7. Danszky I (ed) (1963) Magyarország Erdőgazdasági Tájainak Erdőfelújítási, Erdőtelepítési Irányelvei és Eljárásai, I. Nyugat-Dunántúl Erdőgazdasági Tájcsoport [Regeneration and afforestation guidelines for the Hungarian Forest Regions, I. Western-Transdanubian Forest Region]. Országos Erdészeti Főigazgatóság. BudapestGoogle Scholar
  8. Duke HR (1972) Capillary properties of soils-influence upon specific yield. Trans ASAE 15:688–699Google Scholar
  9. Fahle M, Dietrich O (2014) Estimation of evapotranspiration using diurnal groundwater level fluctuations: comparison of different approaches with groundwater lysimeter data. Water Resour Res 50:273–286.  https://doi.org/10.1002/2013WR014472 CrossRefGoogle Scholar
  10. Freeze RA, Cherry JA (1979) Groundwater. Prentice-Hall, Upper Saddle River, NJGoogle Scholar
  11. Gribovszki Z (2014) Diurnal method for evapotranspiration estimation from soil moisture profile. Acta Silv Lign Hung 10(1):67–75.  https://doi.org/10.2478/aslh-2014-0005 Google Scholar
  12. Gribovszki Z, Kalicz P, Kucsara M (2006) Streamflow characteristics of two forested catchments in Sopron Hills. Acta Silv Lign Hung 2:81–92Google Scholar
  13. Gribovszki Z, Kalicz P, Szilágyi J, Kucsara M (2008) Riparian zone evapotranspiration estimation from diurnal groundwater level fluctuations. J Hydrol 349(1–2):6–17CrossRefGoogle Scholar
  14. Gribovszki Z, Szilágyi J, Kalicz P (2010) Diurnal fluctuations in shallow groundwater levels and in streamflow rates and their interpretation: a review. J Hydrol 385:371–383.  https://doi.org/10.1016/j.jhydrol.2010.02.001 CrossRefGoogle Scholar
  15. Gribovszki Z, Kalicz P, Szilágyi J (2013) Does the accuracy of fine-scale water level measurements by vented pressure transducers permit for diurnal evapotranspiration estimation? J Hydrol 488:166–169  https://doi.org/10.1016/j.jhydrol.2013.03.001 CrossRefGoogle Scholar
  16. Healy RW, Cook PG (2002) Using groundwater levels to estimate recharge. Hydrogeol J 10:91–109CrossRefGoogle Scholar
  17. ILRI (1972) Fieldbook for land and water management experts. ILRI. Wageningen, The NetherlandsGoogle Scholar
  18. Jamison VC, Kroth EM (1958) Available moisture storage capacity in relation to textural composition and organic matter content of several Missouri soils. Soil Sci Soc Am Proc 22:189–192CrossRefGoogle Scholar
  19. Johnson AI (1967) Specific yield: compilation of specific yields for various materials. US Geol Surv Water Supply Pap 1662-D, 74 ppGoogle Scholar
  20. Johnson AI, Prill RC, Morris DA (1963) Specific yield: column drainage and centrifuge moisture content. US Geol Surv Water Supply Pap 1662-A, 60 ppGoogle Scholar
  21. Kishazi P, Ivancsics J (1985) Sopron Kornyeki Uledekek Osszefoglalo Foldtani Ertekelese [Geological assessment of sediments in the neighbourhood of Sopron]. Kezirat, Sopron, Hungary, 48 ppGoogle Scholar
  22. Loheide SPII, Butler JJ Jr, Gorelick SM (2005) Estimation of groundwater consumption by phreatophytes using diurnal water table fluctuations: a saturated-unsaturated flow assessment. Water Resour Res 41:W07030.  https://doi.org/10.1029/2005WR003942 CrossRefGoogle Scholar
  23. Logsdon SD, Schilling KE, Hernandez-Ramirez G, Prueger JH, Hatfield JL, Sauer TJ (2010) Field estimation of specific yield in a central Iowa crop field. Hydrol Process 24(10):1369–1377.  https://doi.org/10.1002/hyp.7600 Google Scholar
  24. Marosi S, Somogyi S (eds) (1990) Magyarorszag Kistajainak Katasztere I [Cadastre of small regions in Hungary I]. MTA Foldrajztudomanyi Kutato Intezet, Budapest, 479 ppGoogle Scholar
  25. Meyboom P (1964) Three observations on streamflow depletion by phreatophytes. J Hydrol 2(3):248–261CrossRefGoogle Scholar
  26. van der Molen WH, Beltrán JM, Ochs WJ (2007) Guidelines and computer programs for the planning and design of land drainage systems. FAO Irrigation and Drainage Paper 62, FAO, RomeGoogle Scholar
  27. Moench AF (1994) Specific yield as determined by type-curve analysis of aquifer-test data. Groundwater 32:949–957CrossRefGoogle Scholar
  28. Móricz N, Mátyás C, Berki I, Rasztovits E, Vekerdy Z, Gribovszki Z, (2012) Comparative water balance study of forest and fallow plots. iForest 5:188–196Google Scholar
  29. Nachabe MH (2002) Analytical expressions for transient specific yield and shallow water table drainage. Water Resour Res 38(10):1193.  https://doi.org/10.1029/2001WR001071 CrossRefGoogle Scholar
  30. Nachabe MH, Ahuja LR, Rokicki R (2003) Field capacity of soil-water, concept, measurement, and approximation. In: Stewart BA, Howell T (eds) Encyclopedia of water science. Dekker, New YorkGoogle Scholar
  31. Nachabe M, Shah N, Ross M, Womacka J (2005) Evapotranspiration of two vegetation covers in a shallow water table environment. Soil Sci Soc Am J 69:492–499CrossRefGoogle Scholar
  32. Neuman SP (1987) On methods of determining specific yield. Groundwater 25:679–684CrossRefGoogle Scholar
  33. Radcliffe DE, Simunek J (2010) Soil physics with HYDRUS: modeling and applications. CRC, Boca Raton, FLGoogle Scholar
  34. Robson SD (1993) Techniques for estimating specific yield and specific retention from grain size data and geophysical logs from clastic bedrock aquifers. US Geol Surv Water Resour Invest Rep 93-4198, 23 ppGoogle Scholar
  35. Romano N, Santini A (2002) Water retention and storage: field. In: Dane JH, Topp GC (eds) Methods of soil analysis, part 4: physical methods. SSSA, Madison, WI, pp 721–738Google Scholar
  36. Schaap MG, Leij FJ, van Genuchten MT (2001) Rosetta: a computer program for estimating soil hydraulic parameters with hierarchical pedotransfer functions. J Hydrol 251:163–176CrossRefGoogle Scholar
  37. Schwartz WF, Zhang H (2003) Fundamentals of groundwater. Wiley, New YorkGoogle Scholar
  38. Shah N, Nachabe M, Ross M (2007) Extinction depth and evapotranspiration from ground water under selected land covers. Ground Water 45(3):329–338.  https://doi.org/10.1111/j.1745-6584.2007.00302.x CrossRefGoogle Scholar
  39. Soylu ME, Lenters JD, Istanbulluoglu E, Loheide SP II (2012) On evapotranspiration and shallow groundwater fluctuations: a Fourier-based improvement to the white method. Water Resour Res 48:W06506.  https://doi.org/10.1029/2011WR010964 CrossRefGoogle Scholar
  40. Szilágyi J (2004) Vadose zone influences on aquifer parameter estimates of saturated-zone hydraulic theory. J Hydrol 286:78–86.  https://doi.org/10.1016/j.jhydrol.2013.03.001 CrossRefGoogle Scholar
  41. Tukey J (1949) Comparing individual means in the analysis of variance. Biometrics 5(2):99–114CrossRefGoogle Scholar
  42. USBR (1984) Drainage manual: a water resources technical publication, 2nd printing. US Bureau of Reclamation, Denver, CO, 286 ppGoogle Scholar
  43. van Genuchten MT (1980) A closed form equation for predicting the hydraulic conductivity of unsaturated soils. Soil Sci Soc Am J 44:892–898CrossRefGoogle Scholar
  44. White WN (1932) Method of estimating groundwater supplies based on discharge by plants and evaporation from soil: results of investigation in Escalant Valley. US Geol Surv Water Supply Pap 659-AGoogle Scholar
  45. Wang P, Pozdniakov SP (2014) A statistical approach to estimating evapotranspiration from diurnal groundwater level fluctuations. Water Resour Res 50:2276–2292.  https://doi.org/10.1002/2013WR014251 CrossRefGoogle Scholar
  46. Wang P, Grinevsky SO, Pozdniakov SP, Yu J, Dautova DS, Min L, Dua C, Zhang Y (2014) Application of the water table fluctuation method for estimating evapotranspiration at two phreatophyte-dominated sites under hyper-arid environments. J Hydrol 519:2289–2300.  https://doi.org/10.1016/j.jhydrol.2014.09.087 CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  1. 1.Institute of Geomatics and Civil EngineeringUniversity of SopronSopronHungary

Personalised recommendations