Efficiency of Two Models for Prediction of Exchangeable Sodium Percentage from Sodium Adsorption Ratio on Saline and Non Saline Soil

An experiment was conducted at the Wadi Soba farm, Khartoum-Sudan. The aim of this study is to estimate the Exchangeable Sodium Percentage (ESP) function to Sodium Adsorption Ratio. In this study, linear regression model (ESP -SAR model) for predicting soil ESP from SAR was suggested. For this purpose, 30 soil samples were collected from the field of experiment, soil ESP was estimated from soil SAR in order to compare the predicted results with measured SAR using laboratory tests on saline and non-saline soil samples. The results show that on saline soil Original Research Articlesamples, the Standard Error of Mean (SEM) of predicted ESP obtained by ESP -SAR model was (0.9389) and the P-value was (0.0572). On non-saline soil samples, the Standard Error of Mean (SEM) of predicted ESP acquired by ESP -SAR model was (0.2920) and the P-value was (0.2628). The statistical results indicated that the linear regression model (ESP -SAR model), ESP= 0.84 × SAR + 2.17 with R 2 = 0.7347 has a good performance in predicting soil ESP from SAR meanwhile the ESP -SAR model reflected more accuracy on non-saline soil samples and it can be recommended for both saline soil and non-saline soil samples.

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“…6). Generally, using of soil SAR to predict ESP showed a high degree of agreement with the results of [6,13].…”

Section: On Non-saline Soil Samplessupporting

confidence: 70%

“…Soil salinity and sodicity are recognized by soil Sodium Adsorption Ratio (SAR) and Exchangeable Sodium Percentage (ESP), as defined in Eq. ( 1) and (2) [6]:…”

Section: Introductionmentioning

confidence: 99%

Modeling of Soil Exchangeable Sodium Percentage Function to Soil Adsorption Ratio on Sandy Clay Loam Soil, Khartoum- Sudan

Elbashier

Shao

Ali

et al. 2016

IJPSS

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“…The ESP threshold of 15% was used to classify sodium hazard, that is, sodic soils are those with ESP of more than 15%. Sodium adsorption ratio (SAR) for each CLUS was calculated [58][59][60] as:…”

Section: Derived Soil Parametersmentioning

confidence: 99%

Variation in soil properties under different cropping and other land-use systems in Dura catchment, Northern Ethiopia

Tesfahunegn

Gebru

2020

PLoS ONE

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There are limited reports about the impacts of long-term cropping and land-use systems (CLUS) on soil properties and nutrient stocks under smallholder farmers' conditions in developing countries. The objective of this research was to examine variation in soil properties and OC and TN stocks across the different CLUS in Dura sub-catchment, northern Ethiopia. Surveys and discussions on field history were used to identify nine CLUS, namely, tef (Eragrostis tef (Zucc) Trot)) mono-cropping (TM), maize (Zea mays L.) mono-cropping (MM), cauliflower (Brassica oleracea var. botrytis)-maize intercropping (IC1), red beet (Beta Vulgaris)-maize intercropping (IC2), cauliflower-tef-maize rotation (R1), onion (Allium cepa L.)-maize-onion rotation (R2), tr eated gully (TG), untreated gully (UTG), and natural forest system (NF). A total of 27 composite soil samples were randomly collected from the CLUS for soil analysis. Data were subjected to one-way analysis of variance and PCA. The lowest and highest bulk density was determined from NF (1.19 Mg m-3) and UTG (1.77 Mg m-3), respectively. Soil pH, EC and CEC varied significantly among the CLUS. The highest CEC (50.3 cmol c kg-1) was reported under TG followed by NF. The highest soil OC stock (175.3 Mg C ha −1) and TN stock (13.6 Mg C ha −1) were found from NF. The PCA chosen soil properties explained 87% of the soil quality variability among the CLUS. Such soil properties and nutrient stocks variability among the CLUS suggested that introduction of suitable management practices that sustain the soil system of the CLUS with poor soil properties and nutrient stocks are crucial for the study area conditions.

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“…To study the current status of water quality, all parameters have used to compare with Cambodia Drinking Water Standard (DWS) established by Ministry of Industry, Mine and Energy [3] and with drinking water standard by World Health Organization (WHO) [4]. For irrigation purpose, sodium adsorption ratio (SAR), and sodium percentage (%Na) were calculated based on US salinity laboratory (USSL) [5], Food Agriculture Organization (FAO) [6], and Wilcox (1948) [7].…”

Section: Methodsmentioning

confidence: 99%

Seasonal comparison of groundwater level and quality in the catchment of the Tonle Sap Lake, Cambodia

Chhuon

Eang

Chork

2022

IOP Conf. Ser.: Earth Environ. Sci.

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Groundwater in the floodplain of Tonle Sap Lake has been used for domestic, agriculture, and small industries. The variation of surface water availability and increasing demand, cause the increasing of groundwater extraction especially during dry season. So far, the study on groundwater resources is extremely limited comparing to surface water in the Tonle Sap catchments. So that, this study focusses on groundwater quality and level from 27 wells in Kompong Thom, Siem Reap, and Preh Vihear province. Seasonal variation of groundwater level shows that groundwater level in Siem Reap is about 1.5m and 4.3m below the ground surface in rainy season and dry season respectively while in Kampong Thom province it is about 0.7m and 2m below the ground surface in rainy season and dry season, respectively. from in situ measurement, some parameters such as pH ranged from 4.1 to 8.1, total dissolved solid from 21 to 1200 mg/L, turbidity from 0 to 88 NTU, temperature from 28 to 31°C, ORP from −2.2 to 424mV, and EC from 35 to 2000 μSm/cm. The concentrations of major ions (Ca2+, Mg2+, K+, Na+, Cl−, SO4 2− and HCO3 −) were approximate or under the permissible value and it was suitable for irrigation.

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Efficiency of Two Models for Prediction of Exchangeable Sodium Percentage from Sodium Adsorption Ratio on Saline and Non Saline Soil

Cited by 7 publications

References 4 publications

Modeling of Soil Exchangeable Sodium Percentage Function to Soil Adsorption Ratio on Sandy Clay Loam Soil, Khartoum- Sudan

Modeling of Soil Exchangeable Sodium Percentage Function to Soil Adsorption Ratio on Sandy Clay Loam Soil, Khartoum- Sudan

Variation in soil properties under different cropping and other land-use systems in Dura catchment, Northern Ethiopia

Seasonal comparison of groundwater level and quality in the catchment of the Tonle Sap Lake, Cambodia

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