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One of the most commonly used models for describing solute sorption to soils is the Langmuir model. Because the Langmuir model is nonlinear, fitting the model to sorption data requires that the model be solved iteratively using an optimization program. To avoid the use of optimization programs, a linearized version of the Langmuir model is often used so that model parameters can be obtained by linear regression. Although the linear and nonlinear Langmuir equations are mathematically equivalent, there are several limitations to using linearized Langmuir equations. We examined the limitations of using linearized Langmuir equations by fitting P sorption data collected on eight different soils with four linearized versions of the Langmuir equation and comparing goodness-of-fit measures and fitted parameter values with those obtained with the nonlinear Langmuir equation. We then fit the sorption data with two modified versions of the Langmuir model and assessed whether the fits were statistically superior to the original Langmuir equation. Our results demonstrate that the use of linearized Langmuir equations needlessly limits the ability to model sorption data with good accuracy. To encourage the testing of additional nonlinear sorption models, we have made available an easily used Microsoft Excel spreadsheet (ars.usda.gov/msa/awmru/bolster/Sorption_spreadsheets) capable of generating best-fit parameters and their standard errors and confidence intervals, correlations between fitted parameters, and goodness-of-fit measures. The results of our study should promote more critical evaluation of model fits to sorption data and encourage the testing of more sophisticated sorption models.

He fair allocation and wise use of fresh water presents significant challenges across the world. To avoid unresolvable crises in the future, judiciously managing water resources in the twenty-first century is fundamentally important. Integrating the underlying science of hydrology with real-world usage scenarios, Water Resources offers a nuanced, modern treatment of contemporary water resource management issues. -- Provided by Publisher.

Food, energy, and water (FEW) are primary resources required for human populations and ecosystems. Availability of the raw resources is essential, but equally important are the services that deliver resources to human populations, such as adequate access to safe drinking water, electricity, and sufficient food. Any failures in either resource availability or FEW resources‐related services will have an impact on human health. The ability of countries to intervene and overcome the challenges in the FEW domain depends on governance, education, and economic capacities. We distinguish between FEW resources, FEW services, and FEW health outcomes to develop an analysis framework for evaluating interrelationships among these critical resources. The framework is applied using a data‐driven approach for sub‐Saharan African countries, a region with notable FEW insecurity challenges. The data‐driven approach using a cross‐validated stepwise regression analysis indicates that limited governance and socioeconomic capacity in sub‐Saharan African countries, rather than lack of the primary resources, more significantly impact access to FEW services and associated health outcomes. The proposed framework helps develop a cohesive approach for evaluating FEW metrics and could be applied to other regions of the world to continue improving our understanding of the FEW nexus. Key Points Food, energy, and water (FEW) resources, provisioning services, and health outcomes are interrelated Data‐driven techniques can elucidate FEW interrelationships Socioeconomic and governance factors strongly influence FEW security in sub‐Saharan Africa

Seasonal to annual forecasts of precipitation patterns are very important for water infrastructure management. In particular, such forecasts can be used to inform decisions about the operation of multipurpose reservoir systems in the face of changing climate conditions. Success in making useful forecasts is often achieved by considering climate teleconnections such as the El Niño–Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) as related to sea surface temperature variations. We present a statistical analysis to explore the utility of using rainfall relationships in Sri Lanka with ENSO and IOD to predict rainfall to the Mahaweli and Kelani River basins of the country. Forecasting of rainfall as the classes flood, drought, and normal is helpful for water resource management decision-making. Results of these models give better accuracy than a prediction of absolute values. Quadratic discrimination analysis (QDA) and classification tree models are used to identify the patterns of rainfall classes with respect to ENSO and IOD indices. Ensemble modeling tool Random Forest is also used to predict the rainfall classes as drought and not drought with higher skill. These models can be used to forecast the areal rainfall using predicted climate indices. Results from these models are not very accurate; however, the patterns recognized provide useful input to water resource managers as they plan for adaptation of agriculture and energy sectors in response to climate variability.

Climate change coupled with increasing demands for water necessitates an improved understanding of the water–food nexus at a scale local enough to inform farmer adaptations. Such assessments are particularly important for nations with significant small-scale farming and high spatial variability in climate, such as Sri Lanka. By comparing historical patterns of irrigation water requirements (IWRs) to rice planting records, we estimate that shifting rice planting dates to earlier in the season could yield water savings of up to 6%. Our findings demonstrate the potential of low-cost adaptation strategies to help meet crop production demands in water-scarce environments. This local-scale assessment of IWRs in Sri Lanka highlights the value of using historical data to inform agricultural management of water resources when high-skilled forecasts are not available. Given national policies prioritizing in-country production and farmers’ sensitivities to water stress, decision-makers should consider local degrees of climate variability in institutional design of irrigation management structures.

Monitoring drinking water quality is essential to protect people’s health and wellbeing. In the United States, the Safe Drinking Water Information System (SDWIS) database records the occurrence of a drinking water violation regulation in public water systems. A notable shortcoming of SDWIS is the lack of the contaminant concentration level about the allowable maximum contaminant threshold. In this study, we take advantage of both the SDWIS violation database and the contaminants sampling database at the state level to examine the drinking water quality of all kinds of drinking water systems in detail. We obtained sampling data (i.e., the concentration level of contaminants) of public water systems (PWSs) in Tennessee and explored the statistical distribution of contaminant concentration data in relation to the enforceable maximum regulatory contaminant level). We use both SDWIS violation records and actual concentrations of contaminants from the sampling data to study the factors that influence the drinking water quality of PWSs. We find that different types of violations were more frequent in (1) specific geological regions, (2) counties with PWSs that serve a larger population (10,000 to 100,000 people), and (3) places with abundant surface water, such as near a lake or major river. Additionally, the distribution of measured concentrations for many contaminants was not smooth but was punctuated by discontinuities at selected levels, such as at 50% of the maximum contaminant level. Such anomalies in the sampling data do not indicate violations, but more investigation is needed to determine the reasons behind the punctuated changes.

Although there are multiple causes of the water scarcity crisis in the American Southwest, it can be used as a model of the long-term problem of freshwater shortages that climate change will exacerbate. We examine the water-supply crisis for 22 cities in the extended Southwest of the United States and develop a unique, new measure of water conservation policies and programs. Convergent qualitative and quantitative analyses suggest that political conflicts play an important role in the transition of water-supply regimes toward higher levels of demand-reduction policies and programs. Qualitative analysis using institutional theory identifies the interaction of four types of motivating logics—development, rural preservation, environmental, and urban consumer—and shows how demand-reduction strategies can potentially satisfy all four. Quantitative analysis of the explanatory factors for the variation in the adoption of demand-reduction policies points to the overwhelming importance of political preferences as defined by Cook's Partisan Voting Index. We suggest that approaches to water-supply choices are influenced less by direct partisan disagreements than by broad preferences for a development logic based on supply-increase strategies and discomfort with demand-reduction strategies that clash with conservative beliefs.

The downward flux of dissolved organic carbon (DOC) in the vadose zone was examined using “artificial rain” experiments on a soil lysimeter at the White Clay Creek watershed in southeastern Pennsylvania. Refractory DOC (RDOC) and labile biodegradable DOC (BDOC) were transported from the organic rich soil layer and eluted from the base of a soil lysimeter during the experimental water applications. A physically based, distributed model that considers water flow and the transport of heat, RDOC and labile BDOC was developed and used to explore the hypothesis that the delivery of DOC to the water table occurs primarily in the riparian zone. Macropores were considered by adopting a dual permeability modeling approach. The calibrated model successfully replicated the temporal dynamics of a bromide tracer, and of RDOC and labile BDOC eluted from the soil lysimeter during the experiments. An estimated annual DOC delivery to groundwater in the watershed was obtained by scaling up the vertical one‐dimensional model to the watershed. The results suggest that the subsurface contribution of DOC accounts for about 72% of the total annual export from the watershed, and the riparian zone contributes more than 90% of total DOC in groundwater. Key Points Measurements of transport of dissolved organic carbon (DOC) through a soil lysimeter Calculations indicating that a dual permeability model of DOC transport is needed Calculations suggesting that the riparian zone contributes the bulk of DOC to streams

Urban water supply systems in the United States are increasingly stressed as economic and population growth confront limited water resources. Demand management, through conservation and improved efficiency, has long been promoted as a practical alternative to building Promethean energy‐intensive water supply infrastructure. Some cities are making great progress at managing their demand, but study of conservation policies has been limited and often regionally focused. We present a hierarchical Bayesian analysis of a new measure of urban water conservation policy, the Vanderbilt Water Conservation Index, for 195 cities in 45 states in the contiguous United States. This study does not attempt to establish causal relationships but does observe that cities in states with arid climates tend to adopt more conservation measures. Within a state, cities with more Democratic‐leaning voting preferences and large and rapidly growing populations tend to adopt more conservation measures. Economic factors and climatic differences between cities do not correlate with the number of measures adopted, but they do correlate with the character of the measures, with arid cities favoring mandatory conservation actions and cities in states with lower real personal income favoring rebates for voluntary actions. Understanding relationships between environmental and societal factors and cities' support for water conservation measures can help planners and policy makers identify obstacles and opportunities to increase the role of conservation and efficiency in making urban water supply systems sustainable. Plain Language Summary As urban water supply systems confront growing populations, growing economies, and climatic stress, water conservation measures are often more effective and economical ways to assure reliable and sustainable access to water than building ever larger supply systems. We present the first analysis of a comprehensive index of urban water conservation policies for 195 cities in the contiguous United States. We find that the number of conservation measures a city adopts correlates both with environmental and societal factors and with the characteristics both of the city itself and of the state in which it is located. Cities in drier states and cities that vote for Democratic candidates in greater numbers tend to adopt more conservation policies. By identifying characteristics associated with water conservation, these results can help planners and policy makers understand how different cities face different obstacles and opportunities for adopting conservation policies. Key Points Reports an analysis of water conservation policies of 195 cities in 45 states Water conservation policies correlate with both environmental and social variables Correlations with partisan voting patterns explain much of the variation in policy adoption