气候变化领域集成服务门户(CCPortal): A Bayesian approach to infer nitrogen loading rates from crop and land-use types surrounding private wells in the Central Valley; California

CCPortal

DOI	10.5194/hess-22-2739-2018
	A Bayesian approach to infer nitrogen loading rates from crop and land-use types surrounding private wells in the Central Valley; California
	Ransom K.M.; Bell A.M.; Barber Q.E.; Kourakos G.; Harter T.
发表日期	2018
ISSN	1027-5606
起始页码	2739
结束页码	2758
卷号	22 期号:5
英文摘要	This study is focused on nitrogen loading from a wide variety of crop and land-use types in the Central Valley, California, USA, an intensively farmed region with high agricultural crop diversity. Nitrogen loading rates for several crop types have been measured based on field-scale experiments, and recent research has calculated nitrogen loading rates for crops throughout the Central Valley based on a mass balance approach. However, research is lacking to infer nitrogen loading rates for the broad diversity of crop and landuse types directly from groundwater nitrate measurements. Relating groundwater nitrate measurements to specific crops must account for the uncertainty about and multiplicity in contributing crops (and other land uses) to individual well measurements, and for the variability of nitrogen loading within farms and from farm to farm for the same crop type. In this study, we developed a Bayesian regression model that allowed us to estimate land-use-specific groundwater nitrogen loading rate probability distributions for 15 crop and land-use groups based on a database of recent nitrate measurements from 2149 private wells in the Central Valley. The water and natural, rice, and alfalfa and pasture groups had the lowest median estimated nitrogen loading rates, each with a median estimate below 5 kgNha-1 yr-1. Confined animal feeding operations (dairies) and citrus and subtropical crops had the greatest median estimated nitrogen loading rates at approximately 269 and 65 kgNha-1 yr-1, respectively. In general, our probability-based estimates compare favorably with previous direct measurements and with mass-balance-based estimates of nitrogen loading. Nitrogen mass-balance-based estimates are larger than our groundwater nitrate derived estimates for manured and nonmanured forage, nuts, cotton, tree fruit, and rice crops. These discrepancies are thought to be due to groundwater age mixing, dilution from infiltrating river water, or denitrification between the time when nitrogen leaves the root zone (point of reference for mass-balancederived loading) and the time and location of groundwater measurement. © Author(s) 2018.
语种	英语
scopus关键词	Bayesian networks; Crops; Groundwater; Land use; Landforms; Nitrates; Nitrogen; Probability distributions; Regression analysis; Uncertainty analysis; Agricultural crops; Animal feeding operations; Bayesian approaches; Bayesian regression; Direct measurement; Field-scale experiments; Groundwater nitrates; Nitrogen mass balance; Loading; agricultural land; alfalfa; Bayesian analysis; cotton; crop plant; denitrification; groundwater; intensive agriculture; land use change; legume; nitrogen; nut; pasture; rhizosphere; rice; river water; subtropical region; California; Central Valley [California]; United States; Animalia; Citrus; Gossypium hirsutum; Medicago sativa
来源期刊	Hydrology and Earth System Sciences
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/160034
作者单位	Ransom, K.M., Department of Land, Air, and Water Resources, University of California, Davis, United States; Bell, A.M., Center for Watershed Sciences, University of California, Davis, United States; Barber, Q.E., Department of Renewable Resources, University of Alberta, Edmonton, Canada; Kourakos, G., Department of Land, Air, and Water Resources, University of California, Davis, United States; Harter, T., Department of Land, Air, and Water Resources, University of California, Davis, United States
推荐引用方式 GB/T 7714	Ransom K.M.,Bell A.M.,Barber Q.E.,et al. A Bayesian approach to infer nitrogen loading rates from crop and land-use types surrounding private wells in the Central Valley; California[J],2018,22(5).
APA	Ransom K.M.,Bell A.M.,Barber Q.E.,Kourakos G.,&Harter T..(2018).A Bayesian approach to infer nitrogen loading rates from crop and land-use types surrounding private wells in the Central Valley; California.Hydrology and Earth System Sciences,22(5).
MLA	Ransom K.M.,et al."A Bayesian approach to infer nitrogen loading rates from crop and land-use types surrounding private wells in the Central Valley; California".Hydrology and Earth System Sciences 22.5(2018).