Estimating soil ammonium adsorption using pedotransfer functions in an irrigation district of the North China Plain

doi:10.1016/S1002-0160(20)60054-6

Pedosphere

Volume 31, Issue 1, February 2021, Pages 157-171

https://doi.org/10.1016/S1002-0160(20)60054-6 Get rights and content

ABSTRACT

Extensive use of chemical fertilizers in agriculture can induce high concentration of ammonium nitrogen (NH₄⁺-N) in soil. Desorption and leaching of NH₄⁺-N has led to pollution of natural waters. The adsorption of NH₄⁺-N in soil plays an important role in the fate of the NH₄⁺-N. Understanding the adsorption characteristics of NH₄⁺-N is necessary to ascertain and predict its fate in the soil-water environment, and pedotransfer functions (PTFs) could be a convenient method for quantification of the adsorption parameters. Ammonium nitrogen adsorption capacity, isotherms, and their influencing factors were investigated for various soils in an irrigation district of the North China Plain. Fourteen agricultural soils with three types of texture (silt, silty loam, and sandy loam) were collected from topsoil to perform batch experiments. Silt and silty loam soils had higher NH₄⁺-N adsorption capacity than sandy loam soils. Clay and silt contents significantly affected the adsorption capacity of NH₄⁺-N in the different soils. The adsorption isotherms of NH₄⁺-N in the 14 soils fit well using the Freundlich, Langmuir, and Temkin models. The models’ adsorption parameters were significantly related to soil properties including clay, silt, and organic carbon contents and Fe²⁺ and Fe³⁺ ion concentrations in the groundwater. The PTFs that relate soil and groundwater properties to soil NH₄⁺-N adsorption isotherms were derived using multiple regressions where the coefficients were predicted using the Bayesian method. The PTFs of the three adsorption isotherm models were successfully verified and could be useful tools to help predict NH₄⁺-N adsorption at a regional scale in irrigation districts.

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The primary water source for agricultural irrigation in the People's Victory Canal irrigation area was the Yellow River water in the early stage, and the Yellow River water diversion volume decreased in the later stage. Hence, the groundwater became the primary water source for the irrigation area. It is significant for the rational utilization of groundwater resources to explore groundwater hydrochemistry's evolution characteristics and formation mechanism. Based on the hydrochemical data of groundwater and Yellow River in the irrigation area from 1987 to 2022. The spatiotemporal evolution of chemical components of groundwater and the main influencing factors were revealed using traditional hydrochemistry research methods, self-organizing map, and stable isotopes. The results show that the classification results of groundwater and Yellow River water samples by the self-organizing map show regional and phased characteristics. Regionally, the self-organizing map classifies groundwater into five clusters, and Cluster Ⅰ–III of groundwater are mainly distributed in the head, middle and northeast areas. Cluster Ⅳ and V of groundwater are mainly distributed in the northwest region. In terms of time, from 1987 to 2001, the Yellow River water diversion volume was higher, and the ion concentration of groundwater showed a decreasing trend. The ion concentration was close to the Yellow River water ion concentration except in the northwest area. Accordingly, the classification results of the self-organizing map change from Cluster Ⅰ of groundwater to Cluster Ⅱ of groundwater. After 2001, the amount of water diverted from the Yellow River decreased, and the concentration of each ion in the groundwater at the head of the canal and the central area showed an overall increasing trend from 2001 to 2022. The classification results of the self-organizing map change to Cluster Ⅰ of groundwater. Due to the change in runoff conditions and the influence of domestic sewage, the classification results of the self-organizing map in the funnel area in the middle of the irrigation district changed to Cluster III of groundwater after 2013.
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Shallow groundwater nitrate nitrogen (NO₃⁻-N) concentrations in agricultural areas usually show high spatial and intra-annual variability. It is hard to predict such concentrations due to the complexity of influencing factors (e.g., different forms of N in soil, vadose zone characteristics, and groundwater physiochemical conditions). Here, a large number of groundwater and soil samples were collected monthly over two years at 14 sites to analyze the soil and groundwater physiochemical properties and the stable isotopes of δ¹⁵N and δ¹⁸O of groundwater NO₃⁻-N in agricultural areas. Based on field observations, a random forest (RF) model was used to predict the groundwater NO₃⁻-N concentrations and reveal the importance of effect factors. The results show that there are large spatiotemporal variations in NO₃⁻-N, δ¹⁵N-NO₃⁻, and δ¹⁸O-NO₃⁻ in groundwater. NO₃⁻-N is the major dominant specie of inorganic N in groundwater, and the groundwater NO₃⁻-N concentration in 24 % of the samples failed to meet the drinking water standard of the WHO (10 mg L⁻¹). The RF model satisfactorily predicted groundwater NO₃⁻-N concentrations with R² of 0.90–0.94, RMSE of 4.54–5.07, and MAE of 2.17–3.38. Groundwater nitrite and ammonium are the most important factors related to NO₃⁻-N consumption and production, respectively, in groundwater. Denitrification and nitrification were further identified by the relationships among δ¹⁵N-NO₃⁻, δ¹⁸O-NO₃⁻, and NO₃⁻-N, and by the ranges of δ¹⁵N-NO₃⁻, δ¹⁸O-NO₃⁻, temperature, pH, DO, and ORP in groundwater. Soil-soluble organic nitrogen (S-SON) and the depth of groundwater table were identified as vital factors related to N sourcing and leaching. Overall, as a first approach to adopting a RF model for high spatiotemporal-resolution prediction of groundwater NO₃⁻-N variations, the findings of this study enable a better understanding of groundwater N pollution in agricultural areas. Optimizing management of irrigation and N inputs is anticipated to reduce S-SON accumulation and mitigate the threat to groundwater quality in agricultural areas.
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Estimating soil ammonium adsorption using pedotransfer functions in an irrigation district of the North China Plain

ABSTRACT

Geoderma

Geoderma

Geoderma

Ecol Modell

Geoderma

Appl Clay Sci

Agric Water Manage

Agric Ecosyst Environ

J Hydrol

Environ Pollut

Agric Sci China

Agric Ecosyst Environ

Adsorption of ammonium by different natural clay minerals: Characterization, kinetics and adsorption isotherms

Appl Clay Sci

Neural network models to predict cation exchange capacity in arid regions of Iran

Eur J Soil Sci

Distribution coefficients of Cd, Co, Ni, and Zn in soils

J Soil Sci

Modeling exchangeable NH$$ adsorption in marine sediments: Process and controls of adsorption

Limnol Oceanogr

The influence of iron oxides on phosphate adsorption by soil

Eur J Soil Sci

Extraction techniques for selective dissolution of amorphous iron oxides from soils and sediments

Soil Sci Soc Am J

Ammonium adsorption on albic black soil under the influence of Fe2+ in irrigation water

Adv Mater Res

Ammonium adsorption on albic black soil under the influence of Fe²+ in irrigation water