A Bayesian approach to infer nitrogen loading  rates from crop and land-use types surrounding  private wells in the Central Valley, California

Ransom, Katherine Marie; Bell, Andrew M.; Barber, Quinn E.; Kourakos, George; Harter, Thomas

doi:10.5194/hess-22-2739-2018

Cited by 15 publications

(14 citation statements)

References 48 publications

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“…Machine‐learning methods have recently gained attention for applications in environmental sciences and particularly for predicting the occurrence of contaminants in groundwater (Nolan et al, ; Ransom et al, ; Rosencrans et al, ). Like other statistical models, machine‐learning techniques do not directly determine causative factors, but machine learning can give better predictive accuracy than more traditional models (Breiman, ).…”

Section: Introductionmentioning

confidence: 99%

Predicting geogenic Arsenic in Drinking Water Wells in Glacial Aquifers, North‐Central USA: Accounting for Depth‐Dependent Features

Erickson

Elliott

Christenson

et al. 2018

Water Resources Research

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Chronic exposure to arsenic (As) via drinking groundwater is a human health concern worldwide. Probabilities of elevated geogenic As concentrations in groundwater were predicted in complex, glacial aquifers in Minnesota, north-central USA, a region that commonly has elevated As concentrations in well water. Maps of elevated As hazard were created for depths typical of drinking water supply and with well construction attributes common for domestic wells. Conventional variables describing aquifer properties and materials, position on the hydrologic landscape, and soil geochemistry were among the most influential for predicting the probability of elevated As. We also found that certain well construction attributes were influential in predicting As hazard. Smaller distances between the top of the well screen and overlying aquitard (proximity) and shorter well screen lengths were each associated with higher probabilities of elevated As. Influential predictor variables, which are either mapped across the region or are well construction attributes, are proxies in the model for measurable physical or geochemical causes of elevated As (e.g., redox condition, till or aquifer sediment chemistry, and water chemistry), which are not mapped across the region. Our setting shares some important characteristics with deltaic and other high-As aquifers in Southeast Asia: late Quaternary age, complex layering of coarse-and fine-grained materials, low-As sediment concentrations, and geochemical controls on As mobilization. Translating three-dimensional geologic and geochemical understanding of As mobility to quantifiable variables for modeling with powerful, flexible statistical tools could improve predictions and help identify safer groundwater supply options in the USA, Southeast Asia, and elsewhere.Plain Language Summary This study demonstrates that certain well construction attributes are influential in predicting arsenic (As) concentrations in drinking water wells. Smaller distances between the top of the well screen and overlying aquitard, and shorter well screen lengths, were each associated with higher probabilities of elevated As. Chronic exposure to As via drinking groundwater is a human health concern worldwide, and Minnesota, USA, commonly has elevated As concentrations in well water. This study describes a new, novel, and important finding from an As probability model: Controllable well construction choices (not just location or depth) influence As concentrations in drinking water from wells.

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Section: Introductionmentioning

confidence: 99%

Predicting geogenic Arsenic in Drinking Water Wells in Glacial Aquifers, North‐Central USA: Accounting for Depth‐Dependent Features

Erickson

Elliott

Christenson

et al. 2018

Water Resources Research

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“…Like many other major agricultural regions worldwide ( 46 , 47 ), human activities have substantially influenced groundwater in the SJV since the mid-20th century. Groundwater overdraft has induced meters of land subsidence ( 15 ), and land-use changes have both increased groundwater salinity ( 14 ) and led to contamination by agriculture ( 48 , 49 ). Here, we propose that irrigation seepage has directly influenced groundwater DIC in the SJV through the delivery of carbonate soil amendments, known as agricultural lime, to shallow groundwater.…”

Section: Discussionmentioning

confidence: 99%

Groundwater residence time estimates obscured by anthropogenic carbonate

et al. 2021

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Groundwater is an important source of drinking and irrigation water. Dating groundwater informs its vulnerability to contamination and aids in calibrating flow models. Here, we report measurements of multiple age tracers (14C, 3H, 39Ar, and 85Kr) and parameters relevant to dissolved inorganic carbon (DIC) from 17 wells in California’s San Joaquin Valley (SJV), an agricultural region that is heavily reliant on groundwater. We find evidence for a major mid-20th century shift in groundwater DIC input from mostly closed- to mostly open-system carbonate dissolution, which we suggest is driven by input of anthropogenic carbonate soil amendments. Crucially, enhanced open-system dissolution, in which DIC equilibrates with soil CO2, fundamentally affects the initial 14C activity of recently recharged groundwater. Conventional 14C dating of deeper SJV groundwater, assuming an open system, substantially overestimates residence time and thereby underestimates susceptibility to modern contamination. Because carbonate soil amendments are ubiquitous, other groundwater-reliant agricultural regions may be similarly affected.

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“…Sewage systems are more recommended for the collection, transport and disposal of wastewater as compared to the cesspits [1]. However, leaky sewage lines can be considered as a potential source of nitrogen [31]. The annual nitrogen amount resulting from the leaky sewage lines was estimated using the following formula:…”

Section: Leakage From Urban Sewage Linesmentioning

confidence: 99%

“…The quantification of the on-ground nitrogen amounts from the different sources is common between all the aforementioned studies. Nevertheless, this was tackled in different ways and approaches [25,[31][32][33]. There are studies that demonstrated the spatiality and magnitudes of the on-ground nitrogen loadings and corresponding nitrate leaching to groundwater in order to facilitate the development of groundwater fate and transport models.…”

Section: Introductionmentioning

confidence: 99%

“…There are studies that demonstrated the spatiality and magnitudes of the on-ground nitrogen loadings and corresponding nitrate leaching to groundwater in order to facilitate the development of groundwater fate and transport models. These models can be based on governing equations of nitrate fate and transport [30,[34][35][36] or based on artificial intelligence for instance [37,38] or statistical models [31].…”

Section: Introductionmentioning

confidence: 99%

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Identification of the Nitrogen Sources in the Eocene Aquifer Area (Palestine)

Almasri

Judeh

Shadeed

2020

Water

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Groundwater is the main source of water in many countries all over the world. Prevention of the pollution of this source is essential for a sustainable utilization. Nitrate pollution of groundwater is a common problem due to the association between intensive agriculture to achieve food security and fertilization. For an efficient management of groundwater pollution from nitrate, the first step would be to quantify the different sources of nitrogen in the aquifer of concern. This paper aims at demonstrating a general approach based on Geographic Information Systems (GIS) to characterize the spatial distribution of the nitrogen amounts in the area of the Eocene aquifer (Palestine). The aquifer is heavily utilized for agricultural and domestic water supply. Fertilization in the study area is a widespread practice. As a result, the aquifer is undergoing a nitrate pollution problem. The methodology relies mainly on specifying all the sources of nitrogen in the aquifer area using GIS to account for spatiality. Thereafter, GIS attribute tables and Excel spreadsheets were utilized to quantify the magnitudes of nitrogen from the different sources. Maps of the corresponding on-ground nitrate, ammonium, organic nitrogen and total nitrogen were developed for the study area. The results indicate that the total on-ground annual nitrogen loading in the study area is about 3260 tons of which 38% is attributed to fertilizers (chemical and manure) where the dominant form of nitrogen is NH4 (58.3%). The average total on-ground nitrogen loading is 7028 kg-N/km2·year. The estimated annual nitrate leaching to the aquifer is 1968 kg-N/km2. The areas of high sources of nitrogen have long-term impacts on the degradation of the water quality of the aquifer. It is therefore essential to build up on the outcomes of this work and to develop a nitrate fate and transport model for the Eocene aquifer. This model will enable the stakeholders to arrive at the efficient alternatives to manage the nitrate contamination of the aquifer.

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A Bayesian approach to infer nitrogen loading rates from crop and land-use types surrounding private wells in the Central Valley, California

Cited by 15 publications

References 48 publications

Predicting geogenic Arsenic in Drinking Water Wells in Glacial Aquifers, North‐Central USA: Accounting for Depth‐Dependent Features

Predicting geogenic Arsenic in Drinking Water Wells in Glacial Aquifers, North‐Central USA: Accounting for Depth‐Dependent Features

Groundwater residence time estimates obscured by anthropogenic carbonate

Identification of the Nitrogen Sources in the Eocene Aquifer Area (Palestine)

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