Assessing soil salinity hazard in cultivated areas using MODFLOW model and GIS tools: A case study from the Jezre’el Valley, Israel

Mirlas, Vladimir

doi:10.1016/j.agwat.2012.03.003

Cited by 23 publications

(8 citation statements)

References 10 publications

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“…Most of the soil salinization problems in the Beit She'an Valley are affiliated with the use of poor-quality irrigation water. The soil salinity is constantly increasing, owing to irrigation with high salinity-treated wastewater and blocking of the natural drainage to the underlying groundwater Mirlas, 2012). At a lemon tree plantation in the Jordan Valley, it was found that an increase in irrigation water salinity to 3.7 times freshwater salinity, increased soil salinity by 3.8-4.1 times during few years (Abu Awwad, 2001).…”

Section: Introductionmentioning

confidence: 99%

Soil salinization risk assessment owing to poor water quality drip irrigation: A case study from an olive plantation at the arid to semi-arid Beit She'an Valley, Israel

Mirlas

Anker

Aizenkod

et al. 2020

Preprint

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Abstract. Salinization causes soil degradation and soil fertility reduction. The main reasons for soil salinization are poor irrigation water quality and incorrect irrigation management. Soil salinization is accelerated owing to irrigation with treated wastewater with elevated salt concentration. The study area is located in the Beit She'an Valley, one of the most important agricultural regions in Israel. The combination of soil salinization and poor drainage conditions impedes plant development and is manifested in economic damage to crops. Without clear irrigation criteria, an increase in soil salinity and steady damage to soil fertility might occur. The study objective was to provide an assessment of soil salting processes as a result of low-quality irrigation water at the Kibbutz Meirav olive plantation. This study combined various research methods, including soil salinity monitoring, field experiments, remote sensing (FDEM), and unsaturated soil profile saline water movement modeling. The assessment included the salinization processes of chalky soil under drip irrigation by water with various qualities. With a drip irrigation regime of water with a dissolved salt content of 3.13 dS/m, the salinization process is characterized by salts accumulation in the upper root zone of the trees. The modeling results showed that there is a soil salinization danger in using brackish water and that irrigation with potable water helps to reduce soil salinization.

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Section: Introductionmentioning

confidence: 99%

Soil salinization risk assessment owing to poor water quality drip irrigation: A case study from an olive plantation at the arid to semi-arid Beit She'an Valley, Israel

Mirlas

Anker

Aizenkod

et al. 2020

Preprint

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“…The natural factors influencing the spatial distribution of soil salinity include soil types (Fang et al, 2005;Yu et al, 2014), soil water content (Wu et al, 2014), geology (Sheng et al, 2010;Yu et al, 2014), climate (Nosetto et al, 2008), normalized difference vegetation index (NDVI) (Yahiaoui et al, 2015) and soil texture (Wang et al, 2012;Zhao et al, 2016). The anthropogenic factors include irrigation practices (Akramkhanov et al, 2011), drainage systems (Mirlas et al, 2012;Yu et al, 2015), groundwater table (Shah et al, 2011;Wu et al, 2014) and land use (Akramkhanov et al, 2011;Nosetto et al, 2013). It is widely established that using correlated influencing factors as auxiliary variables can improve the mapping accuracy of soil properties (Liu et al, 2006;Zhang et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

Mapping Soil Electrical Conductivity Using Ordinary Kriging Combined with Back-propagation Network

YunXiang

Zhen

et al. 2019

Chin. Geogr. Sci.

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Accurate mapping of soil salinity and recognition of its influencing factors are essential for sustainable crop production and soil health. Although the influencing factors have been used to improve the mapping accuracy of soil salinity, few studies have considered both aspects of spatial variation caused by the influencing factors and spatial autocorrelations for mapping. The objective of this study was to demonstrate that the ordinary kriging combined with back-propagation network (OK_BP), considering the two aspects of spatial variation, which can benefit the improvement of the mapping accuracy of soil salinity. To test the effectiveness of this approach, 70 sites were sampled at two depths (0-30 and 30-50 cm) in Ningxia Hui Autonomous Region, China. Ordinary kriging (OK), back-propagation network (BP) and regression kriging (RK) were used in comparison analysis; the root mean square error (RMSE), relative improvement (RI) and the decrease in estimation imprecision (DIP) were used to judge the mapping quality. Results showed that OK_BP avoided the both underestimation and overestimation of the higher and lower values of interpolation surfaces. OK_BP revealed more details of the spatial variation responding to influencing factors, and provided more flexibility for incorporating various correlated factors in the mapping. Moreover, OK_BP obtained better results with respect to the reference methods (i.e., OK, BP, and RK) in terms of the lowest RMSE, the highest RI and DIP. Thus, it is concluded that OK_BP is an effective method for mapping soil salinity with a high accuracy.

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“…Geographical information systems (GIS) provide powerful tools for assessing salinization risks (Mirlas, 2012) and irrigation water quality at a regional scale (Romanelli et al, 2012). To this end, several open-source GIS software have shown their capabilities for managing water resources (Chen et al, 2010) beside other interesting advantages such as: low-cost, independence, security and privacy by always having the source code, adaptability since applications are constantly improving and evolving, quality by continuous improvement by a large number of developers and users, and interoperability, this being a fundamental aspect of public administration, given the large number of computing units with responsibilities.…”

Section: Introductionmentioning

confidence: 99%

A GIS-based quality assessment model for olive tree irrigation water in southern Spain

Peragón

Delgado

Pérez-Latorre

2015

Agricultural Water Management

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Assessing soil salinity hazard in cultivated areas using MODFLOW model and GIS tools: A case study from the Jezre’el Valley, Israel

Cited by 23 publications

References 10 publications

Soil salinization risk assessment owing to poor water quality drip irrigation: A case study from an olive plantation at the arid to semi-arid Beit She'an Valley, Israel

Soil salinization risk assessment owing to poor water quality drip irrigation: A case study from an olive plantation at the arid to semi-arid Beit She'an Valley, Israel

Mapping Soil Electrical Conductivity Using Ordinary Kriging Combined with Back-propagation Network

A GIS-based quality assessment model for olive tree irrigation water in southern Spain

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