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A new methodology to assess the maximum irrigation rates at catchment scale using geostatistics and GIS


Soil hydraulic parameters are important for irrigation scheduling. In the domain of “precision irrigation”, knowledge of the spatial distribution of these parameters is useful in determining the maximum irrigation rate for each field in a catchment. This study focuses on the development of a new methodology to assess the spatial distribution of the maximum irrigation rate depending on the available soil water holding capacity (ASWHC). This methodology combines geostatistical techniques with geographical information system (GIS) tools. A pilot zone of 12 400 ha in a Spanish Mediterranean area was selected to develop this methodology. The linear coregionalization model (LMCR), considering the percentage of sand, carbonates, and ASWHC at others soil depths as covariates, was the best option to model the ASWHC. Other required soil parameters were also spatially modeled. The percent of coarse fragments was modeled by regression kriging considering the soil map as an auxiliary variable. The bulk density was spatially modeled by LMCR, and extended to the rooting depth by linear regression. The spatial distributions modeled were implemented in a GIS with other spatial information layers of irrigation management parameters, such as the maximum allowable depletion of soil water content, the percent of wetted soil and the irrigation depth. The combination of these layers in the GIS was used to estimate the maximum irrigation rates for each field. A propagation error analysis was performed to know the uncertainties in the maximum irrigation rate estimation. Based on this information, the irrigation managers could optimize the irrigation rates for each field.

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Fig. 6



Semivariogram range


Available soil water holding capacity

BDfine :

Soil bulk density of the fine earth (<2 mm Ø)


Semivariogram sill


Percentage of coarse fragments (>2 mm Ø)

Co :

Semivariogram nugget effect


Coefficient of variation


Soil wetted depth


Dependency index


Soil water content at field capacity


Geographical information system

IRmax :

Maximum irrigation rate


Kriging combined with soil map delineation


Kolmogorov–Smirnov test


Linear coregionalization model


Maximum allowable depletion of the soil water content


Ordinary kriging


Percentage of wetted soil surface


Soil water content at permanent wilting point


Regression kriging


Root mean square error


Root mean standardized square error


Standard error of the estimation of the BDfine


Standard error of the estimation of the CF


Standard error of the estimation of the FC

SE(IR max):

Standard error of the estimation of the IRmax


Standard error of the estimation of the PWP


Water use efficiency


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The authors would like to acknowledge the “Ministerio de Economia y Competitividad” from the Government of Spain for funding the Projects CGL2012-39725-C02-01and CGL2012-39725-C02-02 and the anonymous reviewers for the helpful suggestions to improve the manuscript.

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Correspondence to J. M. De Paz.

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De Paz, J.M., Albert, C., Visconti, F. et al. A new methodology to assess the maximum irrigation rates at catchment scale using geostatistics and GIS. Precision Agric 16, 505–531 (2015).

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  • Precision irrigation
  • Geostatistics
  • GIS
  • Irrigation rate
  • Soil water holding capacity