Water and nitrate loss from dryland agricultural soils is controlled by management, soils, and weather

Sigler, W. Adam; Ewing, S. A.; Jones, Clain; Payn, R. A.; Miller, Perry R.; Maneta, Marco P.

doi:10.1016/j.agee.2020.107158

Cited by 40 publications

(48 citation statements)

References 48 publications

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“…There is a growing appreciation for the role of non-growing season fallow periods in overall denitrification losses from cultivated soils (Shang et al 2020), but relatively few studies address denitrification rates during summer fallow periods (Vazquez et al 2019). Furthermore, summer fallow periods and associated increases in soil water content have been linked to higher NO 3 − leaching losses (Campbell et al 2006;John et al 2017;Sigler et al 2020), but few studies (Davis et al 2019) have explored the extent to which these periods of higher soil water content also influence denitrification in soils and downgradient aquifers or riparian corridors.…”

Section: Introductionmentioning

confidence: 99%

Isotopic signals in an agricultural watershed suggest denitrification is locally intensive in riparian areas but extensive in upland soils

et al. 2022

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Nitrogen loss from cultivated soils threatens the economic and environmental sustainability of agriculture. Nitrate (NO3−) derived from nitrification of nitrogen fertilizer and ammonified soil organic nitrogen may be lost from soils via denitrification, producing dinitrogen gas (N2) or the greenhouse gas nitrous oxide (N2O). Nitrate that accumulates in soils is also subject to leaching loss, which can degrade water quality and make NO3− available for downstream denitrification. Here we use patterns in the isotopic composition of NO3− observed from 2012 to 2017 to characterize N loss to denitrification within soils, groundwater, and stream riparian corridors of a non-irrigated agroecosystem in the northern Great Plains (Judith River Watershed, Montana, USA). We find evidence for denitrification across these domains, expressed as a positive linear relationship between δ15N and δ18O values of NO3−, as well as increasing δ15N values with decreasing NO3− concentration. In soils, isotopic evidence of denitrification was present during fallow periods (no crop growing), despite net accumulation of NO3− from the nitrification of ammonified soil organic nitrogen. We combine previous results for soil NO3− mass balance with δ15N mass balance to estimate denitrification rates in soil relative to groundwater and streams. Substantial denitrification from soils during fallow periods may be masked by nitrification of ammonified soil organic nitrogen, representing a hidden loss of soil organic nitrogen and an under-quantified flux of N to the atmosphere. Globally, cultivated land spends ca. 50% of time in a fallow condition; denitrification in fallow soils may be an overlooked but globally significant source of agricultural N2O emissions, which must be reduced along-side other emissions to meet Paris Agreement goals for slowing global temperature increase.

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Section: Introductionmentioning

confidence: 99%

Isotopic signals in an agricultural watershed suggest denitrification is locally intensive in riparian areas but extensive in upland soils

et al. 2022

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“…Since there was abundant precipitation following the application of compost, the loss of N by denitrification may have played an important role in the apparent inefficiency of N use. N loss by nitrate leaching from agro systems is also known to be common (Lu et al, 2021;Sigler et al, 2020). In this experiment, however, N loss as dissolved organic N (DON) may have been more relevant because of the high rates of MSWC applied.…”

Section: Discussionmentioning

confidence: 93%

The safe use of compost derived from municipal solid waste depends on its composition and conditions of application

Arrobas

Carvalho

Raimundo

et al. 2021

Soil Use and Management

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Municipal solid waste compost (MSWC) is a source of organic C and other nutrients, which, when free from potential contaminants, can be used as a soil amendment. This study was carried out over three years in a vineyard with soil pH close to neutral under an experimental design consisting of two treatments (with and without MSWC). Application of MSWC is currently authorized under national legislation to be used in vineyards, orchards and forests at a maximum rate of 10 t ha −1 year −1 . In this study, for experimental purposes, a double rate (20 t ha −1 year −1 ) was used. The accumulated grape yield increased in the amended plot by 28% and the dry biomass of weeds between rows by 119%. The MSWC significantly increased some relevant soil properties such as organic C, pH, cation exchange capacity (CEC) and extractable P, K and B. The concentration of K increased significantly in several tissues, and the concentration of P decreased.However, the concentration of K, P and other essential nutrients in the leaves remained within their sufficiency ranges. Tissue levels of heavy metals (Cr, Cd, Pb and Ni) did not increase with the MSWC application, and the values in the pulp remained below the limits established for foodstuffs. The results from this study indicate that the continuous application of the MSWC does not seem to be sustainable, because of the risk of causing nutritional disorders. Products with similar composition should therefore be used only on more acidic soils and should never exceed the legally established rates.

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“…Therefore, effective best management practices should be implemented for better sustainable management of soil erosion. Furthermore, there is a need for a regional estimate of soil loss to proper decision-making related to appropriate control practice, since erosion occurs diversely over space and time [11].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Rainfall Erosivity Factor Estimation Using Machine and Deep Learning Models

Lee

Hong

et al. 2021

Water

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Rainfall erosivity factor (R-factor) is one of the Universal Soil Loss Equation (USLE) input parameters that account for impacts of rainfall intensity in estimating soil loss. Although many studies have calculated the R-factor using various empirical methods or the USLE method, these methods are time-consuming and require specialized knowledge for the user. The purpose of this study is to develop machine learning models to predict the R-factor faster and more accurately than the previous methods. For this, this study calculated R-factor using 1-min interval rainfall data for improved accuracy of the target value. First, the monthly R-factors were calculated using the USLE calculation method to identify the characteristics of monthly rainfall-runoff induced erosion. In turn, machine learning models were developed to predict the R-factor using the monthly R-factors calculated at 50 sites in Korea as target values. The machine learning algorithms used for this study were Decision Tree, K-Nearest Neighbors, Multilayer Perceptron, Random Forest, Gradient Boosting, eXtreme Gradient Boost, and Deep Neural Network. As a result of the validation with 20% randomly selected data, the Deep Neural Network (DNN), among seven models, showed the greatest prediction accuracy results. The DNN developed in this study was tested for six sites in Korea to demonstrate trained model performance with Nash–Sutcliffe Efficiency (NSE) and the coefficient of determination (R2) of 0.87. This means that our findings show that DNN can be efficiently used to estimate monthly R-factor at the desired site with much less effort and time with total monthly precipitation, maximum daily precipitation, and maximum hourly precipitation data. It will be used not only to calculate soil erosion risk but also to establish soil conservation plans and identify areas at risk of soil disasters by calculating rainfall erosivity factors.

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Water and nitrate loss from dryland agricultural soils is controlled by management, soils, and weather

Cited by 40 publications

References 48 publications

Isotopic signals in an agricultural watershed suggest denitrification is locally intensive in riparian areas but extensive in upland soils

Isotopic signals in an agricultural watershed suggest denitrification is locally intensive in riparian areas but extensive in upland soils

The safe use of compost derived from municipal solid waste depends on its composition and conditions of application

Evaluation of Rainfall Erosivity Factor Estimation Using Machine and Deep Learning Models

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