Application of Geodetector Method and Other Statistical Methods to Study Groundwater Vulnerability to Nitrate Contamination in the Central Valley Aquifer, California PDF Download
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Author: Anil Shrestha Publisher: ISBN: 9781085616966 Category : Geography Languages : en Pages : 183
Book Description
The Central Valley (CV) Aquifer, California is one of the most productive regions of the United States, where large amount of nitrogen fertilizer has been applied for the last few decades to increase the crop productivity. The application of excessive fertilizer has increased the level of nitrate (NO3-N) in the groundwater to above EPA's maximum contamination level (MCL) of 10 mg/L in several domestic, public and monitoring wells. The concentration of nitrate in the groundwater can vary spatially depending on the local nitrogen sources, aquifer characteristics and geochemical condition of the area. The changing hydrogeological conditions of the valley due to excessive groundwater pumping could further complicate the fate of nitrate in the aquifer. The statistical, index-overlay and process-based methods are commonly used to study the vulnerability of aquifer to nitrate contamination. The main purpose of this dissertation is to understand the spatial distribution of groundwater nitrate contamination in the CV which was achieved by applying a relatively new method called Geodetector. Geodetector analyzes the spatial distribution of groundwater NO3-N based on the spatial variance of groundwater nitrate in stratified geographic area of important explanatory variables such as fertilizer, cropland, permeability, slope, dissolved oxygen, etc. The assumption is that if an environmental factor contributes to a groundwater contamination, the spatial distribution of the groundwater contamination should be similar to that of the environmental factor and this spatial association is measured by the Power of Determinant (PD), which is derived based on local and global variances. This method identifies significant explanatory variables, vulnerable areas, relative significance of variables and interaction between variables to strengthen or weaken the effect. The watersheds in the Central Valley were used as the basic analysis units and the percent of wells with above 5 mg/L NO3-N (PWN>5) were calculated for each watershed for the period of 2002 to 2014 to represent its contamination level. Each explanatory variable was processed to different spatially stratified areas to quantify their spatial correspondence with PWN>5. The results of Geodetector method were compared with those from Principal Component Analysis (PCA) and Geographically Weighted Regression (GWR). Finally, maps of susceptibility to nitrate contamination of the CV were developed based on the groundwater basins using the optimized-DRASTIC index and Geodetector-Frequency Ratio Index (GFR). The quantitatively derived GFR index values resulted in better map as reflected by high PD values and correlation coefficient with observed nitrate contamination pattern. The Geodetector method makes no assumptions about the data and has the ability to process multiple data sets, which can be both categorical and continuous. Therefore, Geodetector is advantageous over PCA and GWR, which often suffer from the multicollinearity of data. The Geodetector method offers water resources managers and policy makers a general framework to assess groundwater contamination vulnerability in any other study areas.
Author: Anil Shrestha Publisher: ISBN: 9781085616966 Category : Geography Languages : en Pages : 183
Book Description
The Central Valley (CV) Aquifer, California is one of the most productive regions of the United States, where large amount of nitrogen fertilizer has been applied for the last few decades to increase the crop productivity. The application of excessive fertilizer has increased the level of nitrate (NO3-N) in the groundwater to above EPA's maximum contamination level (MCL) of 10 mg/L in several domestic, public and monitoring wells. The concentration of nitrate in the groundwater can vary spatially depending on the local nitrogen sources, aquifer characteristics and geochemical condition of the area. The changing hydrogeological conditions of the valley due to excessive groundwater pumping could further complicate the fate of nitrate in the aquifer. The statistical, index-overlay and process-based methods are commonly used to study the vulnerability of aquifer to nitrate contamination. The main purpose of this dissertation is to understand the spatial distribution of groundwater nitrate contamination in the CV which was achieved by applying a relatively new method called Geodetector. Geodetector analyzes the spatial distribution of groundwater NO3-N based on the spatial variance of groundwater nitrate in stratified geographic area of important explanatory variables such as fertilizer, cropland, permeability, slope, dissolved oxygen, etc. The assumption is that if an environmental factor contributes to a groundwater contamination, the spatial distribution of the groundwater contamination should be similar to that of the environmental factor and this spatial association is measured by the Power of Determinant (PD), which is derived based on local and global variances. This method identifies significant explanatory variables, vulnerable areas, relative significance of variables and interaction between variables to strengthen or weaken the effect. The watersheds in the Central Valley were used as the basic analysis units and the percent of wells with above 5 mg/L NO3-N (PWN>5) were calculated for each watershed for the period of 2002 to 2014 to represent its contamination level. Each explanatory variable was processed to different spatially stratified areas to quantify their spatial correspondence with PWN>5. The results of Geodetector method were compared with those from Principal Component Analysis (PCA) and Geographically Weighted Regression (GWR). Finally, maps of susceptibility to nitrate contamination of the CV were developed based on the groundwater basins using the optimized-DRASTIC index and Geodetector-Frequency Ratio Index (GFR). The quantitatively derived GFR index values resulted in better map as reflected by high PD values and correlation coefficient with observed nitrate contamination pattern. The Geodetector method makes no assumptions about the data and has the ability to process multiple data sets, which can be both categorical and continuous. Therefore, Geodetector is advantageous over PCA and GWR, which often suffer from the multicollinearity of data. The Geodetector method offers water resources managers and policy makers a general framework to assess groundwater contamination vulnerability in any other study areas.
Author: J. E. Moran Publisher: ISBN: Category : Languages : en Pages : 8
Book Description
The California Water Resources Control Board, in collaboration with the US Geological Survey and Lawrence Livermore National Laboratory, has implemented a program to assess the susceptibility of groundwater resources. Advanced techniques such as groundwater age dating using the tritium-helium method, extensive use of oxygen isotopes of the water molecule ({delta}{sup 18}O) for recharge water provenance, and analysis of common volatile organic compounds (VOCs) at ultra-low levels are applied with the goal of assessing the contamination vulnerability of deep aquifers, which are frequently used for public drinking water supply. Over 1200 public drinking water wells have been tested to date, resulting in a very large, tightly spaced collection of groundwater ages in some of the heavily exploited groundwater basins of California. Smaller scale field studies that include shallow monitoring wells are aimed at assessing the probability that nitrate will be transported to deep drinking water aquifers. When employed on a basin-scale, groundwater ages are an effective tool for identifying recharge areas, defining flowpaths, and determining the rate of transport of water and entrained contaminants. De-convolution of mixed ages, using ancillary dissolved noble gas data, gives insight into the water age distribution drawn at a well, and into the effective dilution of contaminants such as nitrate at long-screened production wells. In combination with groundwater ages, low-level VOCs are used to assess the impact of vertical transport. Special studies are focused on the fate and transport of nitrate with respect to vulnerability of aquifers in agricultural and formerly agricultural areas.
Author: Robert D. Gibbons Publisher: Wiley-Interscience ISBN: Category : Nature Languages : en Pages : 312
Book Description
This book explains the statistical methods used to analyze the huge volume of data that groundwater monitoring wells produce in a comprehensive manner accessible to engineers and scientists who may not have a strong background in statistics. In addition, the book provides statistical methods to make the most accurate use of the data and shows how to set up an effective monitoring system.
Author: Publisher: ISBN: Category : Languages : en Pages : 7
Book Description
In response to concerns expressed by the California Legislature and the citizenry of the State of California, the State Water Resources Control Board (SWRCB), implemented a program to assess groundwater quality, and provide a predictive capability for identifying areas that are vulnerable to contamination. The program was initiated in response to concern over public supply well closures due to contamination by chemicals such as methyl tert butyl ether (MTBE) from gasoline, and solvents from industrial operations. As a result of this increased awareness regarding groundwater quality, the Supplemental Report of the 1999 Budget Act mandated the SWRCB to develop a comprehensive ambient groundwater monitoring plan, and led to the initiation of the Groundwater Ambient Monitoring and Assessment (GAMA) Program. The primary objective of the California Aquifer Susceptibility (CAS) project (under the GAMA Program) is to assess water quality and to predict the relative susceptibility to contamination of groundwater resources throughout the state of California. Under the GAMA program, scientists from Lawrence Livermore National Laboratory (LLNL) collaborate with the SWRCB, the U.S. Geological Survey, the California Department of Health Services (DHS), and the California Department of Water Resources (DWR) to implement this groundwater assessment program. In 2003, LLNL carried out this vulnerability study in the Sacramento Valley and Volcanic Provinces. The goal of the study is to provide a probabilistic assessment of the relative vulnerability of groundwater used for the public water supply to contamination from surface sources. This assessment of relative contamination vulnerability is made based on the results of two types of analyses that are not routinely carried out at public water supply wells: ultra low-level measurement of volatile organic compounds (VOCs), and groundwater age dating (using the tritium-helium-3 method). In addition, stable oxygen isotope measurements help determine the recharge water source location. Interpreted together, and in the context of existing water quality and hydrogeologic data, these observable parameters help define the flow field of a groundwater basin, and indicate the degree of vertical communication between near-surface sources (or potential sources) of contamination, and deeper groundwater pumped at high capacity production wells.
Author: Jeffrey D. Smyth Publisher: ISBN: Category : Groundwater Languages : en Pages : 48
Book Description
A field study was conducted to determine the applicability of multivariate geostatistical methods to the problem of estimating and simulating pesticide concentrations in groundwater from measured concentrations of nitrate and pesticide, when pesticide is undersampled. Prior to this study, no published attempt had been made to apply multivariate geostatistics to groundwater contamination. The study was divided into two complementary aspects of geostatistics: estimation and simulation. The use of kriging and cokriging to estimate nitrate and the herbicide dimethyl tetrachloroterepthalate (DCPA) contaminant densities is described in Chapter I. Measured concentrations of nitrate and the DCPA were obtained for 42 wells in a shallow unconfined alluvial and basin-fill aquifer in a 16.5 km2 agricultural area in eastern Oregon. The correlation coefficient between log(nitrate) and log(DCPA) was 0.74. Isotropic, spherical models were fitted to experimental direct- and cross-semivariograms with correlation ranges and sliding neighborhoods of 4 km. The relative gain for estimates obtained by cokriging ranged from 14 to 34%. Additional sample locations were selected for nitrate and DCPA using the fictitious point method. A simple economic analysis demonstrated that additional nitrate samples would be more beneficial in reducing estimation variances than additional DCPA samples, unless the costs of nitrate and DCPA analysis were identical. These estimates are by definition, the Best Linear Unbiased Estimates (i.e., the estimates with minimized estimation variance), however the requirement of minimized variance smoothes the variability of contaminant values. The application of conditional simulations to groundwater contamination is described in Chapter 11. Conditional simulation allows the degree of fluctuation of nitrate and DCPA between sample points to be assesed. With knowledge of both the 'best' estimates and the of the variability between sample points, nitrate and DCPA groundwater contamination in the study area can be characterized Based on the semivariogram models found in Chapter I, univariate and multivariate conditional simulations of nitrate and DCPA were generated using the turning bands method and the kriging or cokriging system. Kriging was used to condition the univariate simulations, while cokriging was used to cross-correlate and condition the multivariate simulations. The mean of 25 conditional and coconditional simulations at 8 different locations in the study area were generated and compared to kriging and cokriging estimates and 95% confidence intervals. Both conditional and coconditional simulation of the DCPA and nitrate contaminant densities showed large variations when values in different simulations were compared. The fluctuation in values demonstrate the uncertainties in the contaminant distributions when sample sizes are small. As a result of this unkown component, simulated values vary widely. Coconditional simulation displayed the cross-correlation imposed by using the cokriging system to condition the simulations. After 25 simulations, the mean remained unstable indicating that more simulations would be required to enable comparisons with kriging and cokriging estimates.
Author: Jessica Warrack Publisher: ISBN: Category : Languages : en Pages :
Book Description
"We use geospatial and statistical analysis to identify areas where there may be gaps in current legislation that protects aquifers and to identify anthropogenic contamination sources and pathways. Specifically, we focus on phosphorus (P) concentrations in groundwater and total dissolved solids (TDS) concentrations in groundwater in California. The results obtained from the analysis of these datasets can be used to guide sustainable water and ecosystem management policies and inform future groundwater monitoring efforts. Excess P in surface waters is a main driver of eutrophication, but P monitoring in groundwater is often overlooked because it was historically assumed that P is immobile in groundwater. To examine the risk P in groundwater poses to surface waters and ecosystems, we compile and analyze 161,321 groundwater P measurements from 12 different countries. We find that all 12 countries report groundwater P concentrations high enough to potentially cause ongoing or continued eutrophication in sur-face waters. Additionally, in Canada and the United States, we find that 93% of total P (TP) samples are found within 50 km of crop/pastureland. We also find a correlation between distance from the closest oil and gas well and elevated TP concentrations in the Canadian provinces of Alberta and Ontario. We focus on these provinces because there is a high density of oil and gas wells and of TP concentrations >0.1 mg P/L. These case studies indicate the need to further investigate the role of agriculture and oil and gas wells on groundwater impacts by P and other contaminants. The global da-ta synthesis shows that there are many data gaps limiting our ability to assess groundwater P contamination, including their sources and pathways. Understanding the sources and pathways for groundwater contamination is important for sustainable groundwater management practices and protection. Total dissolved solids (TDS) concentrations represent minerals, salts, metals cations, or anions dissolved in water and is often taken as an indicator for overall ground-water quality. We use 216,754 total dissolved solids (TDS) concentration measurements in groundwater in California, United States, to examine the effectiveness of cur-rent groundwater legislation with respect to the base of fresh water (BFW), which is commonly used to identify the vertical extent to which aquifers are subject to ground-water management in the state. The definition for "fresh" water varies between regulating bodies but is generally taken to range from 1,000 to 3,000 mg/L. We analyze trends in the TDS dataset and find that we cannot estimate the BFW in 73% of California. We are able to estimate the BFW in 22% of the Central Valley, a key agricultural region with large groundwater demands and many critically overdrafted ground-water basins. Using a TDS limit of 3,000 mg/L, we estimate the shallowest BFW to be 155 m below ground surface in Kern County and the deepest BFW to be 589 m below ground surface in Stanislaus County. Our analysis demonstrates that geospatial and statistical analysis are useful for managing and analyzing groundwater contamination data. Specifically, there are opportunities for enhanced and strategic management and monitoring of groundwater, focusing on P and TDS. Currently, limitations in the availability of groundwater quality data make the delineation of usable groundwater and the extent of groundwater contamination challenging to identify. Moreover, implementing groundwater management that simultaneously considers and balances impacts of agricultural and oil and gas activities is needed. The results from this thesis can be used to design data-driven groundwater management programs and strategies that protect groundwater re-sources around the world"--
Author: Karthik Kumarasamy Publisher: ISBN: Category : Languages : en Pages :
Book Description
Groundwater is an important natural resource for numerous human activities, accounting for more than 50% of the total water used in the United States. Groundwater is vulnerable to contamination by several organic and inorganic pollutants such as nitrate, heavy metals, and pesticides. Assessment of groundwater vulnerability aids in the management and protection of limited groundwater resources. The focus of this thesis is to (1) statistically compare two groundwater vulnerability assessment models; modified DRASTIC (Acronym for Depth to water, net Recharge, Aquifer media, Soil media, Topography, Impact of vadose zone, and hydraulic Conductivity of aquifer) and ordinal logistic regression for NO3- contamination of shallow groundwater of the US, (2) analyze any discrepancies in the predictability of each of these models, and (3) discuss the advantage of each of the above-mentioned models with respect to performance, data requirement, and its ability to predict vulnerability. Analysis of NO3- concentration in groundwater allows for a reliable comparison of the two models. The results from the OLR model indicate a better correlation between the observed and average predicted probabilities. A very low R2 value was obtained between the modified DRASTIC and nitrate concentration, indicating poor prediction capabilities and need for high resolution data. Limitation with respect to requirement of more data with respect to prediction is seen in both the methods.
Author: Anil Shrestha
Author: Anil Shrestha
Author: Shakir Ali
Author: J. E. Moran
Author: Kenneth Belitz
Author: Robert D. Gibbons
Author: 
Author: 
Author: Jeffrey D. Smyth
Author: Jessica Warrack
Author: Karthik Kumarasamy