Abstract
The storage-discharge relationships of 26 watersheds in the inland Pacific Northwest of the United States were analyzed. Four fitting methods were used to obtain the baseflow coefficients: lower envelope, organic correlation, and ordinary and inverse least squares. Several climatic and terrain attributes were evaluated as predictors of baseflow coefficients. Watersheds dominated by basalt and flatter landscapes exhibited the smallest recession time scales (K) (12.5–20.0 days). Greater K values (33.3–66.7 days) were obtained over catchments dominated by metamorphic and sedimentary rocks. Mean basin slope and the aridity index were found to be the best estimators of baseflow coefficients. Baseflow in flat basalt landscapes, located in dry warm climates, decrease rapidly during summer months and are most sensitive to future droughts and warming climates. Groundwater systems feeding streams during the driest months can drop to less than 1 mm of effective storage in these sensitive systems. In contrast, the minimum annual storage in mountainous systems can have greater than 10 mm effective storage. By understanding the main factors controlling baseflow recession characteristics, environmental agencies could prioritize efforts in areas where future droughts and land use changes may affect ecological assemblages and socio-economic activities.
Résumé
Les relations entre stockage et décharge de 26 bassins versants dans l’arrière-pays du Pacifique Nord-Ouest des Etats-Unis d’Amérique ont été analysées. Quatre méthodes d’ajustement ont été utilisées pour obtenir les coefficients de débit de base: l’enveloppe inférieure, la corrélation organique, moindres carrés simple et inverse. Plusieurs paramètres climatiques et de terrain ont été évalués en tant que facteurs prédictifs des coefficients de débit de base. Les bassins versants dominés par le basalte et des morphologies plates sont caractérisés par les plus petites échelles de temps de récession (K) (12.5–20.0 jours). Des valeurs supérieures de K (33.3–66.7 jours) ont été obtenues pour des bassins versants dominés par des roches métamorphiques et sédimentaires. La pente moyenne des bassins et l’indice d’aridité se sont révélés être les meilleurs estimateurs des coefficients de débits de base. Le débit de base dans les bassins basaltiques à la morphologie plate localisés dans des climats secs et chauds diminue rapidement au cours des mois d’été et sont beaucoup plus sensibles à de futures sécheresses et des climats de réchauffement. Les systèmes d’eaux souterraines alimentant les cours d’eau au cours des mois les plus secs peuvent voir leur stock d’eau efficace chuter à moins d’1mm au sein de ces systèmes sensibles. Par contre, le stockage minimum annuel dans les systèmes montagneux peut être supérieur à 10mm de stockage d’eau efficace. En comprenant les principaux facteurs qui contrôlent les caractéristiques de la récession des débits de base, les agences environnementales pourraient définir les efforts prioritaires à mettre en œuvre dans les zones où les sécheresses futures et les modifications de l’utilisation du sol pourraient impacter les assemblages écologiques et les activités socio-économiques.
Resumen
Se analizan las relaciones almacenamiento – descarga de 26 cuencas del noroeste continental del Pacífico de los Estados Unidos. Se usaron cuatro métodos de ajustes para obtener los coeficientes del flujo base: límite inferior inferior, correlación orgánica, mínimos cuadrados ordinarios e inversos. Se evaluaron los atributos climáticos y geomorfológicos como predictores de los coeficientes del flujo base. Las cuencas dominadas por basaltos y topografías llanas exhibieron las escalas de tiempos de recesión menores (K) (12.5–20.0 días). Los valores mayores de K (33.3–66.7 días) se obtuvieron sobre cuencas dominadas por rocas sedimentarias y metamórficas. Se encontró que la pendiente media a la cuenca y el índice de aridez parecen ser los mejores estimadores de los coeficientes del flujo de base. El flujo base en paisajes basálticos llanos situados en climas cálidos secos, decrece rápidamente durante el verano y son más sensibles a futuras sequías y al aumento de la temperatura. Durante los meses más secos los sistemas de agua subterránea que alimentan a las corrientes pueden caer a menos de 1 mm de almacenamiento efectivo en estos sistemas sensibles. En contraste, el almacenamiento anual mínimo en sistemas montañosos puede tener más que 10 mm de almacenamiento efectivo. Al comprender los principales factores que controlan las características de la recesión del flujo base, las agencias ambientales podrían priorizar esfuerzos en áreas donde futuras sequías y cambios en el uso de la tierra pueden afectar el ensamblaje ecológico y las actividades socio económicas.
摘要
分析了美国内陆太平洋西北地区26个流域存储-排泄的相互关系。采用四个拟合方法获取了基流系数:下外壳层、有机关系、普通最小平方和反转最小平方。对作为基流系数预报因素的若干个气候和地势属性进行了评估。由玄武岩和较平坦地貌主导的流域显示衰退时标(K)最小(12.5–20.0天)。而由变质岩和沉积岩主导的流域衰退时标较大(33.3–66.7天)。发现平均盆地坡度和干燥指数是基流系数的最佳估计量。位于干燥温暖气候条件下平坦玄武岩地貌中的基流在夏季迅速降低,对未来干旱和变暖气候最敏感。在最干旱月份补给河流的地下水系统在这些敏感系统中有效存储量下降到不足1 mm。与此相反,山区系统中最小年存储有效存储量可大于10 mm。通过了解控制基流衰退特征的主要因素,环境机构可以优先把重点放在未来干旱和土地利用变化可能影响生态总体和社会-经济活动的地区。
Resumo
Foram analisadas as relações armazenamento-descarga de 26 bacias hidrográficas na parte continental do Pacífico noroeste dos Estados Unidos. Quatro métodos foram usados para obter os coeficientes de escoamento de base: envelope inferior, correlação orgânica e de mínimos quadrados ordinário e inverso. Vários atributos climáticos e de terreno foram avaliados como preditores dos coeficientes de escoamento de base. Bacias hidrográficas dominadas por basaltos e por paisagens mais planas exibem as menores escalas de tempo de recessão (K) (12.5–20.0 dias). Valores superiores de K (33.3–66.7 dias) foram obtidos em bacias hidrográficas dominadas por rochas metamórficas e sedimentares. Valores médios de inclinação da bacia e o índice de aridez foram considerados os melhores estimadores dos coeficientes de escoamento de base. Os escoamentos de base em ambientes de basaltos em zonas planas localizadas em climas secos e quentes decrescem rapidamente durante os meses de verão e são mais sensíveis a futuras secas e ao aquecimento climático. Os sistemas de águas subterrâneas que alimentam cursos de água durante os meses mais secos podem baixar para menos de 1 mm de armazenamento efetivo nestes sistemas sensíveis. Em contraste, o armazenamento mínimo anual em sistemas montanhosos pode ser superior a 10 mm de armazenamento efetivo. Através do entendimento dos fatores principais que controlam as caraterísticas de recessão do escoamento de base, as agências ambientais poderiam priorizar os esforços nas áreas onde futuras secas ou alterações do uso do solo podem afetar as estruturas ecológicas e as atividades socioeconómicas.
Similar content being viewed by others
References
Ajami H, Troch P, Maddock T, Meixner T, Eastoe C (2011) Quantifying mountain block recharge by means of catchment-scale storage-discharge relationships. Water Resour Res 47:W04504. doi:10.1029/2010WR009598
Arnell NW, Gosling SN (2013) The impacts of climate change on river flow regimes at the global scale. J Hydrol 486:351–364. doi:10.1016/j.jhydrol.2013.02.010
Bates B C, Kundzewicz Z W, Wu S, Palutikof J P (2008) Climate change and water. Technical Paper of the Intergovernmental Panel on Climate Change, IPCC Secretariat, Geneva, 210 pp
Beck HE, van Dijk AIJM, Miralles DG, de Jeu RAM, Bruijnzeel LA, McVicar TR, Schellekens J (2013) Global patterns in base flow index and recession based on streamflow observations from 3,394 catchments. Water Resour Res 49:7843–7863. doi:10.1002/2013WR013918
Berghuijs WR, Woods RA, Hrachowitz M (2014) A precipitation shift from snow towards rain leads to a decrease in streamflow. Nat Clim Chang 4:583–586. doi:10.1038/NCLIMATE2246
Biswal B, Marani M (2010) Geomorphological origin of recession curves. Geophys Res Lett 37:L24403. doi:10.1029/2010GL045415
Biswal B, Marani M (2014) ‘Universal’ recession curves and their geomorphological interpretation. Adv Water Resour 65:34–42. doi:10.1016/j.advwatres.2014.01.004
Biswal B, Nagesh Kumar D (2014a) Study of dynamic behavior of recession curves. Hydrol Process 28:784–792. doi:10.1002/hyp.9604
Biswal B, Nagesh Kumar D (2014b) What mainly controls recession flows in river basins? Adv Water Resour 65:25–33. doi:10.1016/j.advwatres.2014.01.001
Bloomfield JP, Allen DJ, Griffiths KJ (2009) Examining geological controls on baseflow index (BFI) using regression analysis: an illustration from the Thames Basin, UK. J Hydrol 373:164–176. doi:10.1016/j.jhydrol.2009.04.025
Boussinesq J (1877) Essai sur la theorie des eaux courantes: du movement non permanent des eaux souterraines [Essay on the theory of running waters: from non-permanent movement of groundwater]. Acad Sci Inst Fr 23:252–260
Boussinesq J (1903) Sur le débit, en temps de sécheresse, d’ une source alimentée par une nappe d’eaux infiltration [On the flow in times of drought, spring fed by groundwater outflow]. C R Seanes Acad 136:1511–1517
Boussinesq (1904) Recherches theories sur l’écoulement des nappes d’eau infiltrées dans le sol et sur débit sources [Research theories on groundwater flow and flowpaths]. J Math Pures Appl 10:5–78
Brandes D, Hoffman J, Mangarillo JT (2005) Baseflow recession rates, low flows, and hydrologic features of small watersheds in Pennsylvania, USA. Am Water Res Assoc 41(5):1177–1186. doi:10.1111/j.1752-1688.2005.tb03792.x
Brutsaert W (2005) Hydrology: an introduction. Cambridge University Press, Cambridge, UK, 605 pp
Brutsaert W (2008) Long-term groundwater storage trends estimated from streamflow records: climatic perspective. Water Resour Res 44:W022409. doi:10.1029/2007WR006518
Brutsaert W (2010) Annual drought flow and groundwater storage trends in the eastern half of the United States during the past two-third century. Theor Appl Climatol 100:93–103. doi:10.1007/s00704-009-0180-3
Brutsaert W (2012) Are the North American deserts expanding? Some climate signals from groundwater storage conditions. Ecohydrology 5:541–549. doi:10.1002/eco.263
Brutsaert W, Lopez JP (1998) Basin-scale geohydrologic drought flow features of riparian aquifers in the southern Great Plains. Water Resour Res 34(2):233–240. doi:10.1029/97WR03068
Brutsaert W, Nieber J (1977) Regionalized drought flow hydrographs from a mature glaciated plateau. Water Resour Res 13(3):637–643. doi:10.1029/WR013i003p00637
Brutsaert W, Sugita M (2008) Is Mongolia’s groundwater increasing or decreasing? The case of the Kherlen River basin. Hydrol Sci 53:1221–1229. doi:10.1623/hysj.53.6.1221
Clark GM (2010) Changes in patterns of streamflow from unregulated watersheds in Idaho, western Wyoming, and northern Nevada. Am Water Res Assoc 46(3):486–497. doi:10.1111/j.1752-1688.2009.00416.x
Dams J, Salvadore E, van Daele T, Ntegeka V, Willems P, Batelaan O (2012) Spatio-temporal impact of climate change on the groundwater system. Hydrol Earth Syst Sci 16:1517–1531. doi:10.5194/hessd-8-10195-2011
Del Genio AD, Lacis AA, Ruedy RA (1991) Simulations of the effect of a warmer climate on atmospheric humidity. Nature 351:382–385. doi:10.1038/351382a0
Döll P, Zhang J (2010) Impact of climate change on freshwater ecosystems: a global-scale analysis of ecologically relevant river flow alterations. Hydrol Earth Syst Sci 14(5):783–799. doi:10.5194/hessd-7-1305-2010
Döll P, Müller-Schmied H (2012) How is the impact of climate change on river flow regimes related to the impact on mean annual runoff? A global-scale analysis. Environ Res Lett 7(1). doi:10.1088/1748-9326/7/1/014037
Durack P, Wijffels SE, Matear RJ (2012) Ocean salinities reveal strong global water cycle intensification during 1950 to 2000. Science 336:455–458. doi:10.1126/science.1212222
Elsner MM, Cuo L, Voisin N, Deems JS, Hamlet AF, Vano JA, Mickelson K, Lee S, Lettenmaier DP (2010) Implications of 21st century climate change for the hydrology of Washington State. Clim Chang 102:225–260. doi:10.1007/s10584-010-9855-0
Fu G, Barber ME, Chen S (2010) Hydro-climatic variability and trends in Washington State for the last 50 years. Hydrol Process 24(7):866–878. doi:10.1002/hyp.7527
Hall FR (1968) Base-flow recession: a review. Water Resour Res 4(5):973–983. doi:10.1029/WR004i005p00973
Hirsch RM, Gilroy EJ (1984) Methods of fitting a straight line to data: examples in water resources. Water Resour Bull 20:705–711. doi:10.1111/j.1752-1688.1984.tb04753.x
Huntington TG (2006) Evidence for intensification of the global water cycle: review and synthesis. J Hydrol 319:83–95. doi:10.1016/j.jhydrol.2005.07.003
Kirchner JW (2009) Catchments as simple dynamical systems: catchment characterization, rainfall-runoff modeling, and doing hydrology backward. Water Resour Res 45:W02429, 34 pp. doi:10.1029/2008WR006912
Lacey GC, Grayson RB (1998) Relating baseflow to catchment properties in south-eastern Australia. J Hydrol 204:231–250. doi:10.1016/S0022-1694(97)00124-8
Leppi JC, DeLuca TH, Harrar SW, Running SW (2012) Impacts of climate change on August stream discharge in the Central-Rocky Mountains. Clim Chang 112:997–1014. doi:10.1007/s10584-011-0235-1
Luce CH, Holden ZA (2009) Declining annual streamflow distributions in the Pacific Northwest United States, 1948–2006. Geophys Res Lett 36:L16401. doi:10.1029/2009GL039407
Mayer TD (2012) Controls of summer stream temperature in the Pacific Northwest. J Hydrol 475:323–335. doi:10.1016/j.jhydrol.2012.10.012
McCabe GJ, Clark MP (2005) Trends and variability in snowmelt runoff in the western United States. J Hydrometeorol 6(4):476–482. doi:10.1175/JHM428.1
Mendoza GF, Steenhuis TS, Walter MT, Parlange JY (2003) Estimating basin-wide hydraulic parameters of a semi-arid mountainous watershed by recession-flow analysis. J Hydrol 279:57–69. doi:10.1016/S0022-1694(03)00174-4
Miles EL, Snover AK, Hamlet AF, Callahan B, Fluharty D (2000) Pacific Northwest regional assessment: the impacts of climate variability and climate change on the water resources of the Columbia River basin. Am Water Res Assoc 36(2):399–420
Milly PCD, Dunne KA, Vecchia AV (2005) Global pattern of trends in streamflow and water availability in a changing climate. Nat Lett 438:347–350
Mote PW (2003) Trends in snow water equivalent in the Pacific Northwest and their climatic causes. Geophys Res Lett 30:1601. doi:10.1029/2003GL017258
Mote PW, Salathé EP (2010) Future climate in the Pacific Northwest. Clim Chang 102(1–2):29–50. doi:10.1007/s10584-010-9848-z
National Oceanic and Atmospheric Administration (2011) National Climate Data Center. Available at: http://www.ncdc.noaa.gov/. Accessed February 20, 2011
Nijssen B, O’Donnell GM, Hamlet AF, Lettenmaier DP (2001) Hydrologic sensitivity of global rivers to climate change. Clim Chang 50:143–175. doi:10.1023/A:1010616428763
Ott R, Longnecker M (2008) An introduction to statistical methods and data analysis. Cenage Learning, Boston, MA, 1280 pp
Pale EJ (2002) Flood risk and flood management. J Hydrol 267:2–11. doi:10.1016/S0022-1694(02)00135-X
Palmroth S, Katul GG, Hui D, McCarthy HR, Jackson RB, Oren R (2010) Estimation of long-term basin scale evapotranspiration from streamflow time series. Water Resour Res 46:W10512. doi:10.1029/2009WR008838
Parlange J, Stagnitti F, Heilig A, Szilagyi J, Parlange M, Steenhuis T, Hogarth W, Barry D, Li L (2001) Sudden drawdown and drainage of a horizontal aquifer. Water Resour Res 37:2097–2101
Peña-Arancibia JL, van Dijk AIJM, Mulligen M, Bruijzeel LA (2010) The role of climatic and terrain attributes in estimating baseflow recession in tropical catchments. Hydrol Earth Syst Sci 7:4059–4087. doi:10.5194/hessd-7-4059-2010
Polubarinova-Kochina PY (1962) Theory of groundwater movement. Princeton University Press, Princeton, NJ. doi:10.1029/2000WR000189
Poole GC, Berman CH (2001) An ecological perspective on in-stream temperature: natural heat dynamics and mechanisms of human-caused thermal degradation. Environ Manag 27(6):787–802. doi:10.1007/s002670010188
Price K (2011) Effects of watershed topography, soils, land use, and climate on baseflow hydrology in humid regions: a review. Prog Phys Geogr 35(4):465–492. doi:10.1177/0309133311402714
Rupp DE, Selker JS (2006) Information, artifacts, and noise in dQ/dt-Q recession analysis. Adv Water Resour 29:154–160. doi:10.1016/j.advwatres.2005.03.019
Sánchez-Murillo R, Brooks ES, Sampson L, Boll J, Wilhelm F (2013) Ecohydrological analysis of steelhead (Oncorhynchus mykiss) habitat in an effluent dependent stream in the Pacific Northwest, USA. Ecohydrology. doi:10.1002/eco.1376
Shaw SB, Riha SJ (2012) Examining individual recession events instead of a data cloud: using a modified interpretation of dQ/dt–Q streamflow recession in glaciated watersheds to better inform models of low flow. J Hydrol 434–435:46–54. doi:10.1016/j.jhydrol.2012.02.034
Smakhtin VU (2001) Low flow hydrology: a review. J Hydrol 240:147–186. doi:10.1016/S0022-1694(00)00340-1
Stewart IT, Cayan DR, Dettinger MD (2005) Changes toward earlier streamflow timing across Western North America. Climate 18:1136–1155. doi:10.1175/JCLI3321.1
Stoelzle M, Stahl K, Weiler M (2012) Are streamflow recession characteristics really characteristic? Hydrol Earth Syst Sci 9:10563–10593. doi:10.5194/hessd-9-10563-2012
Szilagyi J, Parlange MB, Albertson JD (1998) Recession flow analysis for aquifer parameter determination. Water Resour Res 34(7):1851–1857. doi:10.1029/98WR01009
Tallaksen LM (1995) A review of baseflow recession analysis. J Hydrol 165:349–370. doi:10.1016/0022-1694(94)02540-R
Tang QH, Lettenmaier DP (2012) 21st century runoff sensitivities of major global river basins. Geophys Res Lett 39:L06403. doi:10.1029/2011gl050834
Troch P, De Troch F, Brutsaert W (1993) Effective water table depth to describe initial conditions prior to storm rainfall in humid regions. Water Resour Res 29(02):427–434. doi:10.1029/92WR02087
UNESCO (2005) International flood initiative. Available at: http://www.ifi-home.info/. Accessed February 20, 2011
United States Geological Survey (2011) National Water Information System. Available at: http://waterdata.usgs.gov/usa/nwis/rt. Accessed February 20, 2011
van Dijk AIJM (2010) Climate and terrain factors explaining streamflow response and recession in Australian catchments. Hydrol Earth Syst Sci 14:159–169. doi:10.5194/hess-14-159-2010
van Kirk RW, Naman SW (2008) Relative effects of climate and water use on base-flow trends in the Lower Klamath basin. Am Water Res Assoc 44(4):1032–1052. doi:10.1111/j.1752-1688.2008.00212.x
Vogel RM, Kroll CN (1992) Regional geohydrologic-geomorphic relationships for the estimation of low-flow statistics. Water Resour Res 28(9):2451–2458. doi:10.1029/92WR01007
Wang D (2011) On the base flow recession at the Panola Mountain Research Watershed, Georgia, USA. Water Resour Res 47:W03527. doi:10.1029/2010WR009910
Wang D, Cai X (2009) Detecting human interferences to low flows through base flow recession analysis. Water Resour Res 45:W07426. doi:10.1029/2009WR007819
Wang D, Cai X (2010a) Comparative study of climate and human impacts on seasonal baseflow in urban and agricultural watersheds. Geophys Res Lett 37:L06406. doi:10.1029/2009GL041879
Wang D, Cai X (2010b) Recession slope curve analysis under human interferences. Adv Water Resour 33(2010):1053–1061. doi:10.1016/j.advwatres.2010.06.010
Wittenberg H (1999) Baseflow recession and recharge as nonlinear storage processes. Hydrol Process 13:715–726. doi:10.1002/(SICI)1099-1085(19990415)13:5<715::AID-HYP775>3.0.CO;2-N
Wittenberg H (2003) Effects of season and man-made changes on baseflow and flow recession: case studies. Hydrol Process 17:2113–2123. doi:10.1002/hyp.1324
Wolock D (2003) Base-flow index grid for the conterminous United States. US Geol Surv Open-File Rep 03-146. Digital dataset available on http://water.usgs.gov/GIS/dsdl/bfi48grd.zip. March 2011
Zecharias Y, Brutsaert W (1988) Recession characteristics of groundwater outflow and base flow from mountainous watersheds. Water Resour Res 24(10):1651–1658. doi:10.1029/WR024i010p01651
Zhou YP, Kuan-Man X, Sud YC, Betts AK (2011) Recent trends of the tropical hydrological cycle inferred from Global Precipitation Climatology Project and International Satellite Cloud Climatology Project data. Geophys Res 116:D09101. doi:10.1029/2010JD015197
Acknowledgements
This project was funded by the joint venture agreement (No. 10-JV-11221634-252) between USDA-Forest Service Rocky Mountain Research Station and the University of Idaho. The authors thank the insights and useful comments from two anonymous reviewers.
Author information
Authors and Affiliations
Corresponding author
Electronic supplementary material
Below is the link to the electronic supplementary material.
ESM 1
(PDF 1177 kb)
Appendix 1
Appendix 1
To estimate the baseflow coefficients (i.e. a and b), four different fitting methods were used: lower envelope, the organic correlation technique (Eqs. 9 and 10), ordinary (Eqs. 11 and 12) and inverse (Eqs. 13 and 14) least square estimation. There is some argument over the best technique for fitting a line through data: either ordinary least squares (the commonly used approach in statistics), inverse least squares, or the organic correlation technique described by Hirsch and Gilroy (1984). The ordinary least squares technique determines a line which minimizes the sum of the square errors in the vertical or y direction. This is the preferred method for estimating a particular value of y, given a value of x where x is measured without error (Hirsch and Gilroy 1984). Conversely, the inverse least squares method is used to estimate x (assumed measured without error) given a value of y. The organic correlation technique minimizes the sum of the squared geometric means of the distances in both the vertical and horizontal directions. This technique is not suited for minimizing estimation errors, but is most applicable for establishing equivalence between x and y. In addition, Brutsaert (2005) emphasized that in hilly watersheds, it may be advisable to analyze an average value of the baseflow coefficients.
where StdevP is the standard deviation of the population.
Rights and permissions
About this article
Cite this article
Sánchez-Murillo, R., Brooks, E.S., Elliot, W.J. et al. Baseflow recession analysis in the inland Pacific Northwest of the United States. Hydrogeol J 23, 287–303 (2015). https://doi.org/10.1007/s10040-014-1191-4
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10040-014-1191-4