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Migdal Ha‘Emeq, Israel

Mirlas V.,C o Rupin Institute
Journal of Irrigation and Drainage Engineering | Year: 2013

Overwetting and soil salinization processes are common in irrigated date palm orchards in Israel. Subsurface drainage systems are generally used to overcome soil salinity. Subsurface drainage models can contribute to the selection of a proper drainage system and its proper placement in the field. In this paper, the groundwater flow modeling program MODFLOW was used to simulate groundwater levels in a date palm orchard in Argaman, in the Jordan Valley, Israel. Using a three-layer groundwater flow model, the most efficient drainage system was a combination of 4.5-m depth primary drains and 3-m depth drains of different lengths installed at a different spacing between drains. Installation of this drainage system would cost approximately NIS$'2.6 million, i.e., 30% less than the initially proposed project. Given certain input, a spatially distributed groundwater flow model such as MODFLOW can provide more reliable information than different analytical solutions for planning an effective subsurface drainage system. © 2013 American Society of Civil Engineers. ASCE/AUGUST 2013. Source

Goldshleger N.,C o Rupin Institute | Goldshleger N.,Ariel University | Chudnovsky A.,Weizmann Institute of Science | Ben-Dor E.,Tel Aviv University
Applied and Environmental Soil Science | Year: 2012

We explored the effect of raindrop energy on both water infiltration into soil and the soil's NIR-SWIR spectral reflectance (1200-2400 nm). Seven soils with different physical and morphological properties from Israel and the US were subjected to an artificial rainstorm. The spectral properties of the crust formed on the soil surface were analyzed using an artificial neural network (ANN). Results were compared to a study with the same population in which partial least-squares (PLS) regression was applied. It was concluded that both models (PLS regression and ANN) are generic as they are based on properties that correlate with the physical crust, such as clay content, water content and organic matter. Nonetheless, better results for the connection between infiltration rate and spectral properties were achieved with the non-linear ANN technique in terms of statistical values (RMSE of 17.3% for PLS regression and 10% for ANN). Furthermore, although both models were run at the selected wavelengths and their accuracy was assessed with an independent external group of samples, no pre-processing procedure was applied to the reflectance data when using ANN. As the relationship between infiltration rate and soil reflectance is not linear, ANN methods have the advantage for examining this relationship when many soils are being analyzed. © 2012 Naftali Goldshleger et al. Source

Goldshleger N.,C o Rupin Institute | Livne I.,Tel Aviv University | Chudnovsky A.,Weizmann Institute of Science | Ben-Dor E.,Tel Aviv University
Soil Science | Year: 2012

Irrigated lands in Israel are subjected to salinization processes, mostly as a result of low-quality irrigation water. The Jezre'el Valley in northern Israel, which exemplifies this phenomenon, was selected for this study. This area has been characterized by increasing soil salinity over the years, with consequent increase in soil sodium adsorption ratio, leading to significant deterioration of the soil structure and a reduced infiltration rate. The traditional methods of soil mapping (soil sampling, laboratory tests, and mapping) are time-consuming and do not provide near-real-time information. We evaluated an alternative method consisting of passive and active remote sensing: (i) in situ and airborne sensor spectral measurements, (ii) frequency domain electromagnetic, and (iii) ground penetration radar. A partial least-squares regression model was used to assess a thematic electrical conductivity map of the surface based on the airborne hyperspectral images. A sub-surface salinity map was also generated by applying the surface-to-sub-surface correlation on the surface thematic electrical conductivity map. The generated maps were found to be in good agreement with those based on laboratory chemical data. The results indicated that traditional methods are correlated with remote sensing from the air and ground observations, which can therefore account for soil salinity. Importantly, merging the passive and active remote sensing methods yields a better understanding of the underlying processes than either approach alone. Copyright © 2012 by Lippincott Williams & Wilkins. Source

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