Natural vegetation covers as indicators of the soil water content in a semiarid mountainous watershed

Abstract This paper investigates the use of the vegetative state of natural covers as an indicator of soil moisture conditions at the end of the dry season in order to evaluate the cumulative effect of the hydrological regime. To achieve this, the three major vegetation covers in a mountainous semiarid environment in southern Spain were selected. Temporal and spatial trends of NDVI from Landsat-TM images were computed and related to the different hydrological patterns of variables in the study site, which were obtained with the hydrological WiMMed model. The heterogeneity in the hydrological behavior during the study period (914.5 mm of annual rainfall in the wettest year (2009–2010) and 284.4 mm in the driest year (2004–2005)) was reflected in the annual differences in NDVI values with steady mean NDVI values in coniferous vegetation (0.5–0.6) and more variable values in scrub cover. Both Correlation Analysis and Principal Component Analysis showed correlations among the different states of the vegetation cover, the variables involved in the soil water balance and those related to the snow dynamics of the antecedent year. Exponential fits were obtained between the mean annual soil water content and NDVI values with Pearson r 2 coefficients of over 0.7 in scrub cover. In certain years, the best fits were also found in scrub cover with r 2 values of up to 0.9. These results demonstrate the relationship between soil water content, the vigor of the natural vegetation and the hydrological characteristics of the antecedent year. The expressions obtained may serve to adjust the soil water content at the beginning of a hydrological year and to use the scrub cover as an indicator of the soil water balance in the area for a given year.

[1]  Compton J. Tucker,et al.  Sensitivity of Climate to Changes in NDVI , 2000 .

[2]  K. Price,et al.  Temporal responses of NDVI to precipitation and temperature in the central Great Plains, USA , 2003 .

[3]  P. Teillet,et al.  On the Slope-Aspect Correction of Multispectral Scanner Data , 1982 .

[4]  C. Tucker.  Red and photographic infrared linear combinations for monitoring vegetation , 1979 .

[5]  J. Cihlar,et al.  Relation between the normalized difference vegetation index and ecological variables , 1991 .

[6]  B. Markham,et al.  Summary of Current Radiometric Calibration Coefficients for Landsat MSS, TM, ETM+, and EO-1 ALI Sensors , 2009 .

[7]  Limin Yang,et al.  An analysis of relationships among climate forcing and time-integrated NDVI of grasslands over the U.S. northern and central Great Plains , 1998 .

[8]  M. Polo,et al.  Generating reference evapotranspiration surfaces from the Hargreaves equation at watershed scale , 2011 .

[9]  J. Refsgaard.  Parameterisation, calibration and validation of distributed hydrological models , 1997 .

[10]  C. Taylor,et al.  Evaluating the Simulated Seasonality of Soil Moisture with Earth Observation Data , 2009 .

[11]  Javier Herrero,et al.  Topographic effects on solar radiation distribution in mountainous watersheds and their influence on reference evapotranspiration estimates at watershed scale. , 2010 .

[12]  Kazuhito Ichii,et al.  Global monitoring of interannual changes in vegetation activities using NDVI and its relationships to temperature and precipitation , 2001 .

[13]  G. Asner,et al.  Satellite observation of El Niño effects on Amazon Forest phenology and productivity , 2000 .

[14]  V. Jetten,et al.  Continuous spatially distributed simulation of surface and subsurface hydrological processes in a small semiarid catchment , 2008 .

[15]  John R. Jensen,et al.  Introductory Digital Image Processing: A Remote Sensing Perspective , 1986 .

[16]  S. Brantley,et al.  Application of hyperspectral vegetation indices to detect variations in high leaf area index temperate shrub thicket canopies , 2011 .

[17]  Nanée Chahinian,et al.  Distributed hydrological modelling of a Mediterranean mountainous catchment – Model construction and multi-site validation , 2007 .

[18]  Cristina Aguilar,et al.  NDVI as an indicator for changes in water availability to woody vegetation , 2012 .

[19]  M. Losada,et al.  The hydrological response of baseflow in fractured mountain areas , 2009 .

[20]  Zheng Niu,et al.  Evaluation of atmospheric correction using FLAASH , 2008, 2008 International Workshop on Earth Observation and Remote Sensing Applications.

[21]  Javier Herrero,et al.  Terrestrial photography as an alternative to satellite images to study snow cover evolution at hillslope scale , 2012, Remote Sensing.

[22]  Gilles Boulet,et al.  Understanding hydrological processes with scarce data in a mountain environment , 2008 .

[23]  L. Ji,et al.  Assessing vegetation response to drought in the northern Great Plains using vegetation and drought indices , 2003 .

[24]  N. Pettorelli,et al.  Using the satellite-derived NDVI to assess ecological responses to environmental change. , 2005, Trends in ecology & evolution.

[25]  M. P. González-Dugo,et al.  Interception modeling with vegetation time series derived from Landsat TM data , 2011, Remote Sensing.

[26]  J. Adegoke,et al.  Relations between Soil Moisture and Satellite Vegetation Indices in the U.S. Corn Belt , 2002 .

[27]  V. Jayaraman,et al.  Interlinkages of NOAA/AVHRR derived integrated NDVI to seasonal precipitation and transpiration in dryland tropics , 1997 .

[28]  W. Wagner,et al.  Improving runoff prediction through the assimilation of the ASCAT soil moisture product , 2010 .

[29]  D. Groeneveld,et al.  Remotely-sensed groundwater evapotranspiration from alkali scrub affected by declining water table , 2008 .

[30]  M. Martínez-Mena,et al.  The role of antecedent soil water content in the runoff response of semiarid catchments: a simulation approach , 2003 .

[31]  J. E. Jackson.  A User's Guide to Principal Components , 1991 .

[32]  Sharon E. Nicholson,et al.  A STUDY OF RAINFALL AND VEGETATION DYNAMICS IN THE AFRICAN SAHEL USING NORMALIZED DIFFERENCE VEGETATION INDEX , 1990 .

[33]  F. Kogan.  Remote sensing of weather impacts on vegetation in non-homogeneous areas , 1990 .

[34]  William M. Baugh,et al.  Correcting satellite data to detect vegetation signal for eco-hydrologic analyses , 2007 .

[35]  A. Negri,et al.  A Comparison of the Normalized Difference Vegetation Index and Rainfall for the Amazon and Northeastern Brazil , 1997 .

[36]  Antonio Moñino,et al.  WiMMed, a distributed physically-based watershed model (I): Description and validation , 2009 .

[37]  Antonio Moñino,et al.  An energy balance snowmelt model in a Mediterranean site , 2009 .

[38]  Jeffrey P. Walker,et al.  Importance of soil moisture measurements for inferring parameters in hydrologic models of low-yielding ephemeral catchments , 2003, Environ. Model. Softw..

[39]  K. Beven,et al.  A hydraulic model to predict drought-induced mortality in woody plants: an application to climate change in the Mediterranean. , 2002 .

[40]  A. Millares,et al.  On the influence of cell size in physically-based distributed hydrological modelling to assess extreme values in water resource planning , 2012 .

[41]  C. Aguilar,et al.  NDVI sensitivity to the hydrological regime in semiarid mountainous environments , 2012, Remote Sensing.

[42]  Hui Sheng,et al.  Spatial Distribution Pattern of MODIS-NDVI and Correlation between NDVI and Meteorology Factors in Shandong Province in China , 2008 .