Prediction of the sodium absorption ratio using data-driven models: a case study in Iran

Singh, Balraj

doi:10.1080/24749508.2019.1568129

Cited by 26 publications

(6 citation statements)

References 31 publications

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“…The SAR indicator is calculated by measuring the concentrations of sodium, calcium, and magnesium in the soil and using the following equation: SAR=

(italicNa) / \sqrt{\frac{1}{2} (Ca + Mg)}

(Singh, 2020).…”

Section: Methodsmentioning

confidence: 99%

Utilizing treated wastewater for pasture irrigation: Effects on productivity, plant community structure and soil properties

Lavi,

Bar‐Massada,

Dovrat

2024

Grass and Forage Science

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Surplus wastewater accumulates in winter and requires a discharging solution. In our study we examined the effects of using treated wastewater (TWW) as supplemental pasture irrigation in winter. To test the effect of TWW irrigation on the vegetation and soil, 10 grazing prevention exclosures were established at Ramat‐Hanadiv Park, Israel, with half of them irrigated with TWW. Soil and vegetation were sampled during 2 years of irrigation and 1 year after cessation of irrigation. Vegetation composition, species richness, and productivity were sampled at the peak of the growing season and various indices of herbage quality were measured. Our results show that irrigation with wastewater increased herbage production by an average of 38% and total pasture protein production by 9% relative to the control subplots. Conversely, TWW irrigation decreased plant protein content while increasing herbage fibre content and lowering its digestibility. Over a period of 2 years, species richness decreased in the irrigated subplots. Most of the soil indices examined were not affected by irrigation, but in the irrigation subplots, sodium values and the sodium adsorption‐ratio were higher than in areas without irrigation. Additional resources in winter enabled the plants to grow rapidly and increased interplant competition. Changes in vegetation composition were revealed through functional group reshuffling and species richness decline. The results of our study show that wastewater irrigation causes an increase in productivity but a decrease in forage quality. At the pastoral system level, the significant increase in productivity leads to increased availability of protein and herbage for animals.

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“…The SAR indicator is calculated by measuring the concentrations of sodium, calcium, and magnesium in the soil and using the following equation: SAR=

(italicNa) / \sqrt{\frac{1}{2} (Ca + Mg)}

(Singh, 2020).…”

Section: Methodsmentioning

confidence: 99%

Utilizing treated wastewater for pasture irrigation: Effects on productivity, plant community structure and soil properties

Lavi,

Bar‐Massada,

Dovrat

2024

Grass and Forage Science

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“…ANN, a concept taken from the human mind, is a widely used prediction technique (Sepahvand et al 2019;Sihag et al 2020;Singh 2020). ANN has a brain like architecture and neuron system.…”

Section: Artificial Neural Network (Ann)mentioning

confidence: 99%

Soft computing technique-based prediction of water quality index

Singh¹,

Sihag

Singh

et al. 2021

Water Supply

Self Cite

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Water quality (WQ) plays a crucial role in management of water resources. Water quality index (WQI) is frequently used methods to assess of water quality for drinking purposes. WQI can be predicted using chemical analysis which might not, however, be viable for a longer period in all the country-scale rivers. Thus, in this investigation, two neural-based soft computing techniques-artificial neural network (ANN), generalized neural network (GRNN)- and one hybrid soft computing techniques- adaptive neuro-fuzzy interference system (ANFIS) with four membership function- were used to predict WQI in Khorramabad, Biranshahr and Alashtar sub-watersheds in Iran. Ten distinct physiochemical parameters were used as input variables and WQI as output. Simultaneously, a correlation plot and pairs were used to ascertain the relation of input and output variables. The soft computing techniques were compared using six fitness criteria: NSE, MAE, LMI, RMSE, MAPE, CC. Results indicated that ANN better predicted WQI than did GRNN and ANFIS. Among the different membership functions of ANFIS, ANFIS_trimf was far better than were other membership functions. Thus, it was concluded that ANN was a viable tool for the prediction of WQI.

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“…They indicated the robustness of these algorithms to support the decision-making process for sustainable crop yield. [9] employed SVM and Gaussian process regression (GPR) for the simulation of SAR in three sub-watersheds in Iran. These studies demonstrated the potential of AI and ML as a tool for predicting various water quality indices in irrigation systems and highlighted the importance of such predictions in improving water management practices and ensuring sustainable agriculture.…”

Section: Introductionmentioning

confidence: 99%

Management of Agricultural Groundwater in Sudan: The Use of Artificial Intelligence Algorithms in Khartoum State

Mohammed,

Abba,

Szabó

et al. 2023

Geosciences and Engineering

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This research aims to predict the irrigation indices of sodium adsorption ratio (SAR) and sodium percentage (Na%) using innovative machine learning (ML) techniques, including support vector regression (SVR) and Gaussian process regression (GPR). Thirty-seven groundwater samples were collected, and the primary investigation indicated that Ca-Mg-HCO3 and Na-HCO3 water types dominate the samples. The data is divided into two sets for training (70%) and validation (30%), and the models are tested with three statistical criteria, including mean square error (MSE), root mean square error (RMSE), and determination coefficient (R2). The GPR algorithm showed better performance in predicting SAR and Na% than SVR since it provided the lowest errors. The implemented approach proved efficient for the sustainable management of agricultural water.

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Prediction of the sodium absorption ratio using data-driven models: a case study in Iran

Cited by 26 publications

References 31 publications

Utilizing treated wastewater for pasture irrigation: Effects on productivity, plant community structure and soil properties

Utilizing treated wastewater for pasture irrigation: Effects on productivity, plant community structure and soil properties

Soft computing technique-based prediction of water quality index

Management of Agricultural Groundwater in Sudan: The Use of Artificial Intelligence Algorithms in Khartoum State

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