Delineation of salinity management zones for precision irrigation in a saltaffected pomegranate orchard using DualEM-based remote sensing and Empirical Bayesian Kriging

¹Faculty of Agriculture and Environment, Agricultural University of Tirana, Albania

²Department of Mathematics, University of Texas, Arlington, Texas, USA

³Blackland Research & Extension Center, Texas A&M AgriLife Research, Temple, TX, USA

⁴USDA Agricultural Research Service, USA.

^*Corresponding author; E-mail: zamir.libohova@usda.gov

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Abstract

Soil salinity is a significant challenge for irrigated agriculture in low-lying coastal areas. Salts can vary greatly, even within a single orchard. This study tested a method to identify salinity management zones and develop a precision irrigation plan for a commercial pomegranate (Punica granatum L.) farm in Karavasta, Lushnja, Albania. The focus was on five parcels, covering about 50 hectares, within a 100-hectare salt-affected orchard on raised mounds. Researchers used satellite-derived salinity (NDSI, SI, SI3) and terrain attributes (MRVBF) for initial zoning. DualEM-1S electromagnetic induction sensor, a Delta-T W.E.T. field sensor were used in the field and electrical conductivity from soil-water extracts was determined in the laboratory for soil samples collected in the field. The DualEM readings were calibrated separately for raised mounds and inter-row spaces. Spatial patterns were mapped using Empirical Bayesian Kriging and regression-kriging methods. The results showed strong spatial variation in salinity, highlighting the clear differences between the raised mounds and the inter-row areas. The median electrical conductivity (EC) measured with the W.E.T. sensor was significantly higher in inter-row spaces than on raised mounds (862.0 versus 237.5 mS m–1; P = 0.002), while soil moisture and temperature showed no significant difference. More than half of the inter-row area was classified as saline or highly saline, whereas most raised mounds were non-saline. The resulting maps were divided into five management zones, MZ-0 to MZ4, each with different irrigation frequency, leaching fraction, and monitoring guidelines. This approach combined remote sensing, laboratory calibration, geostatistical mapping, and practical irrigation decisions, creating a useful framework for managing salinity in perennial orchards in Mediterranean coastal regions.

Keywords: soil salinity; precision irrigation; management zones; pomegranate; remote sensing; DualEM-1S; Empirical Bayesian Kriging