Analysis of groundwater drought building on the standardised precipitation index approach

A new index for standardising groundwater level time series and characterising groundwater droughts, the Standardised Groundwater level Index (SGI), is described. The SGI builds on the Standardised Precipitation Index (SPI) to account for differences in the form and characteristics of groundwater level and precipitation time series. The SGI is estimated using a non-parametric normal scores transform of groundwater level data for each calendar month. These monthly estimates are then merged to form a continuous index. The SGI has been calculated for 14 relatively long, up to 103 yr, groundwater level hydrographs from a variety of aquifers and compared with SPI for the same sites. The relationship between SGI and SPI is site specific and the SPI accumulation period which leads to the strongest correlation between SGI and SPI, qmax, varies between sites. However, there is a consistent positive linear correlation between a measure of the range of significant autocorrelation in the SGI series, mmax, and qmax across all sites. Given this correlation between SGI mmax and SPI qmax, and given that periods of low values of SGI can be shown to coincide with previously independently documented droughts, SGI is taken to be a robust and meaningful index of groundwater drought. The maximum length of groundwater droughts defined by SGI is an increasing function of mmax, meaning that relatively long groundwater droughts are generally more prevalent at sites where SGI has a relatively long autocorrelation range. Based on correlations between mmax, average unsaturated zone thickness and aquifer hydraulic diffusivity, the source of autocorrelation in SGI is inferred to be dependent on dominant aquifer flow and storage characteristics. For fractured aquifers, such as the Cretaceous Chalk, autocorrelation in SGI is inferred to be primarily related to autocorrelation in the recharge time series, while in granular aquifers, such as the Permo–Triassic sandstones, autocorrelation in SGI is inferred to be primarily a function of intrinsic saturated flow and storage properties of aquifer. These results highlight the need to take into account the hydrogeological context of groundwater monitoring sites when designing and interpreting data from groundwater drought monitoring networks.

[1]  Michael J. Hayes,et al.  The effect of the length of record on the standardized precipitation index calculation , 2005 .

[2]  D. Hannah,et al.  Regional hydrological drought in north‐western Europe: linking a new Regional Drought Area Index with weather types , 2011 .

[3]  Michael J. Hayes,et al.  Appropriate application of the standardized precipitation index in arid locations and dry seasons , 2007 .

[4]  E. Martin,et al.  Evolution of spatio-temporal drought characteristics: validation, projections and effect of adaptation scenarios , 2012 .

[5]  Simon Parry,et al.  Examining the large‐scale spatial coherence of European drought using regional indicators of precipitation and streamflow deficit , 2011 .

[6]  L. Tallaksen,et al.  Hydrological drought across the world: impact of climate and physical catchment structure , 2012 .

[7]  F. Fiorillo,et al.  Long karst spring discharge time series and droughts occurrence in Southern Italy , 2012, Environmental Earth Sciences.

[8]  J. Bloomfield.  Characterisation of hydrogeologically significant fracture distributions in the Chalk: an example from the Upper Chalk of southern England , 1996 .

[9]  Sergio M. Vicente-Serrano,et al.  Hydrological response to different time scales of climatological drought: an evaluation of the Standardized Precipitation Index in a mountainous Mediterranean basin , 2005 .

[10]  Francesco M. Guadagno,et al.  Karst Spring Discharges Analysis in Relation to Drought Periods, Using the SPI , 2010 .

[11]  L. Tallaksen,et al.  Hydrological drought : processes and estimation methods for streamflow and groundwater , 2004 .

[12]  P. Diggle.  Time Series: A Biostatistical Introduction , 1990 .

[13]  S. Shukla,et al.  Use of a standardized runoff index for characterizing hydrologic drought , 2008 .

[14]  T. McKee,et al.  THE RELATIONSHIP OF DROUGHT FREQUENCY AND DURATION TO TIME SCALES , 1993 .

[15]  H. Lanen,et al.  Drought in groundwater-drought distribution and performance indicators , 2005 .

[16]  N. Guttman.  ACCEPTING THE STANDARDIZED PRECIPITATION INDEX: A CALCULATION ALGORITHM 1 , 1999 .

[17]  S. Changnon.  Detecting drought conditions in Illinois , 1987 .

[18]  V. Hrissanthou,et al.  Computation of Drought Index SPI with Alternative Distribution Functions , 2012, Water Resources Management.

[19]  L. Tallaksen,et al.  Space–time modelling of catchment scale drought characteristics , 2009 .

[20]  Frank Trentmann,et al.  Drought is normal: the socio-technical evolution of drought and water demand in England and Wales, 1893-2006 , 2009 .

[21]  D. C. Edwards,et al.  Characteristics of 20th Century Drought in the United States at Multiple Time Scales. , 1997 .

[22]  S. Vicente‐Serrano,et al.  Dam effects on droughts magnitude and duration in a transboundary basin: The Lower River Tagus, Spain and Portugal , 2009 .

[23]  E. Peters.  Propagation of drought through groundwater systems , 2003 .

[24]  M. Fendeková,et al.  Groundwater Drought in the Nitra River Basin - Identification and Classification , 2012 .

[25]  Maria A. Santos.  Regional droughts: A stochastic characterization , 1983 .

[26]  Tiao J. Chang,et al.  Use of the Kriging Method for Studying Characteristics of Ground Water Droughts , 1995 .

[27]  Jean-Philippe Vidal,et al.  Multilevel and multiscale drought reanalysis over France with the Safran-Isba-Modcou hydrometeorological suite , 2009 .

[28]  G. Mendicino,et al.  A Groundwater Resource Index (GRI) for drought monitoring and forecasting in a mediterranean climate , 2008 .

[29]  H. Akaike,et al.  Information Theory and an Extension of the Maximum Likelihood Principle , 1973 .

[30]  Eric F. Wood,et al.  Global and Continental Drought in the Second Half of the Twentieth Century: Severity–Area–Duration Analysis and Temporal Variability of Large-Scale Events , 2009 .

[31]  G. Jenkins,et al.  UKCIP08: the climate of the United Kingdom and recent trends , 2009 .

[32]  E. Wood,et al.  Global Trends and Variability in Soil Moisture and Drought Characteristics, 1950–2000, from Observation-Driven Simulations of the Terrestrial Hydrologic Cycle , 2008 .

[33]  C. Anderson‐Cook.  The Cambridge Dictionary of Statistics (2nd ed.) , 2003 .

[34]  Melissa Widhalm,et al.  The Lincoln Declaration on Drought Indices: Universal Meteorological Drought Index Recommended , 2011 .

[35]  Robert L. Wilby,et al.  Major droughts in England and Wales, 1800–2006 , 2007 .

[36]  S. Vicente‐Serrano,et al.  A Multiscalar Drought Index Sensitive to Global Warming: The Standardized Precipitation Evapotranspiration Index , 2009 .

[37]  B. Lloyd‐Hughes,et al.  A drought climatology for Europe , 2002 .

[38]  H.A.J. van Lanen,et al.  A process-based typology of hydrological drought , 2011 .

[39]  U. Ulbrich,et al.  The 2003 European summer heatwaves and drought –synoptic diagnosis and impacts , 2004 .

[40]  E. Eltahir,et al.  On the asymmetric response of aquifer water level to floods and droughts in Illinois , 1999 .

[41]  H. V. Van Lanen,et al.  Propagation of drought through groundwater—a new approach using linear reservoir theory , 2003 .

[42]  J. Abatzoglou,et al.  An Evaluation of Multiscalar Drought Indices in Nevada and Eastern California , 2012 .

[43]  Ramesh P. Singh,et al.  Monitoring drought dynamics in the Aravalli region (India) using different indices based on ground and remote sensing data , 2006 .

[44]  John P. Bloomfield,et al.  Pore-throat size distributions in Permo-Triassic sandstones from the United Kingdom and some implications for contaminant hydrogeology , 2001 .

[45]  J. Barker,et al.  Karstic behaviour of groundwater in the English Chalk , 2006 .

[46]  Guillaume Ramillien,et al.  Basin‐scale, integrated observations of the early 21st century multiyear drought in southeast Australia , 2009 .

[47]  L. J. Anthony,et al.  The Cambridge Dictionary of Statistics (2nd ed.) , 2003 .

[48]  M. Lambert,et al.  On spatiotemporal drought classification in New South Wales: Development and evaluation of alternative techniques , 2008 .

[49]  Mark A. Sutton,et al.  The influence of model grid resolution on estimation of national scale nitrogen deposition and exceedance of critical loads , 2011 .

[50]  E. Wood,et al.  Bias correction of monthly precipitation and temperature fields from Intergovernmental Panel on Climate Change AR4 models using equidistant quantile matching , 2010 .

[51]  R. Silberstein,et al.  Drought, groundwater storage and stream flow decline in southwestern Australia , 2012 .

[52]  V. Singh,et al.  A review of drought concepts , 2010 .

[53]  H. Lanen,et al.  Propagation and spatial distribution of drought in a groundwater catchment , 2006 .

[54]  Andrew McKenzie,et al.  The physical properties of major aquifers in England and Wales , 1997 .

[55]  John P. Bloomfield,et al.  Examining geological controls on baseflow index (BFI) using regression analysis: An illustration from the Thames Basin, UK , 2009 .

[56]  D. Wilhite.  Drought as a natural hazard : Concepts and definitions , 2000 .

[57]  E. Wood,et al.  A simulated soil moisture based drought analysis for the United States , 2004 .