Novel dimensionless index for physically based assessment of thermal refugia characterizes off-channel habitat on gravel bed river

In the Willamette River, OR, main channel temperatures can be too warm for cold water fishes, causing fish to concentrate in secondary channel features that provide thermal refugia. However, temperature regimes vary among and within features. Improved understanding of physical processes controlling thermal regimes is needed. This study developed a dimensionless index for assessment of thermal refugia on the upper Willamette River. The novel hyporheic insolation (HIN) index uses minimal field measurements to predict thermal refugia resulting from buffering. Continuous water temperature measurements at one side channel, eight alcoves, and six beaver ponds provided data to ground truth calculated ${ℍ}_{\text{in}}$ predictions. Water temperature records were first used to characterize stratification at sites. Calculation of the Richardson number, an index of stability, showed two well-mixed sites and 13 stratified sites. At stratified sites, calculated ${ℍ}_{\text{in}}$ values characterized the ratio of cooling flux from hyporheic discharge to heat flux from incoming solar radiation. As ${ℍ}_{\text{in}}$ increased, measured temperatures at sites decreased. Despite overall scatter, a logarithmic fit to bin-averaged ${ℍ}_{\text{in}}$ values showed R² = 0.91. Calculations suggest that secondary channel features characterized by stratification and cool hyporheic discharge can provide thermal refugia. Accordingly, the HIN index may serve as a practical tool grounded in physical processes governing temperature across a floodplain.     

A 21st-Century perspective on snow drought in the Upper Colorado River Basin

In the Upper Colorado River Basin (UCRB), there is a deep reliance on seasonal snowpack for maintenance of water resources. The term “snow drought” has recently emerged to describe periods of anomalously low snowpack. Unique seasonal patterns in precipitation and temperature that drive snow drought can have distinct hydrologic signatures, and these relationships have not been carefully studied in the UCRB. Here we examine snow drought with a new classification scheme using peak snow water equivalent (SWE) and the ratio of basin-wide modeled peak SWE to accumulated (onset to peak) precipitation (SWE/P) that clusters snow drought years into three distinct groups—“warm,” “dry,” and “warm & dry”—that minimize within-group variance. Over the period 1916–2018, we identify 14 warm years ($\overline{P}$ = 160 mm; $\overline{\mathrm{SWE}/P}$ = 0.24), 24 dry years ($\overline{P}$ = 117 mm; $\overline{\mathrm{SWE}/P}$ = 0.35), and 21 warm & dry years ($\overline{P}$ = 94 mm; $\overline{\mathrm{SWE}/P}$ = 0.23). An elevation-based analysis reveals two distinct patterns: warm snow droughts see severe SWE reductions primarily at lower (<2600 m) elevations (65% at lower elevations, 37% overall), whereas “dry” scenarios exhibit a consistent reduction across all elevations (39% overall). Using naturalized streamflow data, we also differentiate snow droughts by their earlier streamflow timing and decreased peakedness (warm: 7 days, 2%; dry: 7 days, 2%; warm & dry: 13 days, 5%). This research provides new insights into snow drought patterns relevant for regional water management.     

Modes of Variability of Annual and Seasonal Rainfall in Mexico

The aim of this study is to identify temporal and spatial variability patterns of annual and seasonal rainfall in Mexico. A set of 769 weather stations located in Mexico was examined. The country was divided into 12 homogeneous rainfall regions via principal component analysis. A Pettitt test was conducted to perform a homogeneity analysis for detecting abrupt changes in mean rainfall levels, and a Mann‐Kendall test was conducted to examine the presence of monotonically increasing/decreasing patterns in the data. In total, 14.4% of the annual series was deemed nonstationary. Fourteen percent of the samples were nonstationary in the winter and summer, and 9% were nonstationary in the spring and autumn. According to the results, the nonstationarity of some seasonal rainfall series may be associated with the presence of atmospheric phenomena (e.g., El Niño/Southern Oscillation, Pacific Decadal Oscillation, Atlantic Multidecadal Oscillation, and North Atlantic Oscillation). A rainfall frequency analysis was performed for the nonstationary annual series, and significant differences in the return levels can be expected for the scenarios analyzed. The identification of areas that are more susceptible to changes in rainfall levels will improve water resource management plans in the country, and it is expected that these plans will take into account nonstationary theory.     

Use of Hydrologic Landscape Classification to Diagnose Streamflow Predictability in Oregon

We implement a spatially lumped hydrologic model to predict daily streamflow at 88 catchments within the state of Oregon and analyze its performance using the Oregon Hydrologic Landscape (OHL) classification. OHL is used to identify the physio‐climatic conditions that favor high (or low) streamflow predictability. High prediction catchments (Nash‐Sutcliffe efficiency of (NS) > 0.75) are mainly classified as rain dominated with very wet climate, low aquifer permeability, and low to medium soil permeability. Most of them are located west of the Cascade Mountain Range. Conversely, most low prediction catchments (NS < 0.6) are classified as snow‐dominated with high aquifer permeability and medium to high soil permeability. They are mainly located in the volcano‐influenced High Cascades region. Using a subset of 36 catchments, we further test if class‐specific model parameters can be developed to predict at ungauged catchments. In most catchments, OHL class‐specific parameters provide predictions that are on par with individually calibrated parameters (NS decline < 10%). However, large NS declines are observed in OHL classes where predictability is not high enough. Results suggest higher uncertainty in rain‐to‐snow transition of precipitation phase and external gains/losses of deep groundwater are major factors for low prediction in Oregon. Moreover, regionalized estimation of model parameters is more useful in regions where conditions favor good streamflow predictability.     

Application of Artificial Neural Networks to Predict Total Dissolved Solids at the Karaj Dam

We applied multilayer perceptron (MLP) and radial basis function (RBF) neural networks using data from two water quality monitoring stations at the Karaj Dam in Iran. Input data were calcium ions (Ca²⁺), magnesium ions (Mg²⁺), sodium ions (Na⁺), chloride ions (Cl^?), sulfate (), and pH, and the output data were total dissolved solids (TDS). An MLP with one hidden layer containing eight neurons was selected for the upstream water quality station using normalized input data. We developed a second MLP neural network for the downstream station with one hidden layer containing 10 neurons in the hidden layer using normalized input data. Considering applying normalized input data and one hidden layer, the coefficient of determination (R ²) and index of agreement (IA) between the observed and the predicted data for the upstream and downstream monitoring stations using the MLP neural networks were 0.985, 0.84, 0.99, and 0.92, respectively. The RBF neural network with 100 neurons in its hidden layer reached the minimum errors between the observed and the predicted results in upstream and downstream stations. The R ² between observed and predicted data for upstream and downstream monitoring stations for the RBF was 0.999 and 0.998, respectively. Data normalization improved the performance of the MLP neural networks. Sensitivity analysis indicated that magnesium is the most effective water quality parameter for predicting TDS, and sulfate is the second most effective water quality parameter affecting TDS prediction at the Karaj Dam.     

A simple mineral market model: Can it produce super cycles in prices?

This paper develops a stylized supply–demand model for a mineral/nonrenewable commodity. It embodies important distinctions between short-run and long-run mineral supply and the derived demand for minerals as intermediate goods in production sectors with differing intensities of use. This framework is used to address the question: under what conditions might one expect to observe super cycles (i.e. cycles with a period of 20–70 years) in minerals prices? A plausible time path for GDP$GDP$ growth and the structural transformation that accompanies economic development in an emerging region is specified. Using these drivers and reasonable supply and demand parameters, price dynamics are simulated. The result is an asymmetric price cycle with a peak price that is about 250% above trend and an expansion phase that lasts for about 20 years. Thus, this simple model is capable of producing a single cycle with a frequency and amplitude in the range estimated in the empirical literature on super cycles. As other regions reach the development ‘take-off' phase, additional super cycles should emerge.     

Experimental investigation of wellbore integrity and CO2–brine flow along the casing–cement microannulus

Wellbore integrity is one of the key performance criteria in the geological storage of CO₂. It is significant in any proposed storage site but may be critical to the suitability of depleted oil and gas reservoirs that may have 10’s to 1000’s of abandoned wells. Much previous work has focused on Portland cement which is the primary material used to seal wellbore systems. This work has emphasized the potential dissolution of Portland cement. However, an increasing number of field studies (e.g., Carey et al., 2007), experimental studies (e.g., Kutchko et al., 2006) and theoretical considerations indicate that the most significant leakage mechanism is likely to be flow of CO₂ along the casing–cement microannulus, cement–cement fractures, or the cement–caprock interface.In this study, we investigate the casing–cement microannulus through core-flood experiments. The experiments were conducted on a synthetic wellbore system consisting of a 5-cm diameter sample of cement that was cured with an embedded rectangular length of steel casing that had grooves to accommodate fluid flow. The experiments were conducted at 40 $°$ C and 14 MPa pore pressure for 394 h. During the experiment, 6.2 l of a 50:50 mixture of supercritical CO₂ and 30,000 ppm NaCl-rich brine flowed through 10-cm of limestone before flowing through the 6-cm length cement–casing wellbore system. Approximately 59,000 pore volumes of fluid moved through the casing–cement grooves. Scanning electron microscopy revealed that the CO₂–brine mixture impacted both the casing and the cement. The Portland cement was carbonated to depths of 50–250 $\mu$m by a diffusion-dominated process. There was very little evidence for mass loss or erosion of the Portland cement. By contrast, the steel casing reacted to form abundant precipitates of mixed calcium and iron carbonate that lined the channels and in one case almost completely filled a channel. The depth of steel corroded was estimated at 25– $30\mu$m and was similar in value to results obtained with a simplified corrosion model.The experimental results were applied to field observations of carbonated wellbore cement by Carey et al. (2007) and Crow et al. (2009) to show that carbonation of the field samples was not accompanied by significant CO₂–brine flow at the casing–cement interface. The sensitivity of standard-grade steel casing to corrosion suggests that relatively straight-forward wireline logging of external casing corrosion could be used as a useful indicator of flow behind casing. These experiments also reinforce other studies that indicate rates of Portland cement deterioration are slow, even in the high-flux CO₂–brine experiments reported here.     

Reinventing marine spatial planning: a critical review of initiatives worldwide

ABSTRACT

Although marine spatial planning (MSP) is increasingly being applied worldwide, it appears to be based on an ambiguity that has arisen from its dichotomous role of ensuring both conservation and development. This elusive ideal hints at a possible discrepancy between theory and practice. This paper explores the hypothesis that beyond a performative narrative, MSP is actually better described as a variety of devices which fulfil other roles and converge in terms of planning type. To test this hypothesis, this paper analyses the content of past and present MSP initiatives from around the world. The findings show that these initiatives view MSP either as a strategic sectoral spatial planning tool or strategic planning tool, brought in to complement existing initiatives. Furthermore, these two approaches can actually be seen to converge in the type of planning used, through the role attributed to spatial aspects, and more specifically in the place given to zoning. There are two key implications of these findings: the need to open up theoretical debates more broadly to different disciplinary perspectives on MSP; and the need for crucial choices to be made to ensure that MSP does not become an illusion behind which other agendas lie.

Highlights

• Several scientific communities are working on MSP in parallel

• MSP does not in reality fulfil its theoretical objectives, but it fulfils other roles

• We make a critical review of 44 experiences of MSP from throughout the world

• Different forms of MSP generally make similar uses of zoning

• MSP is both illusory and necessary and must engage a critical turn

     

Resource Consumption and Environmental Impacts of the Agrofood Sector: Life Cycle Assessment of Italian Citrus-Based Products

Food production and consumption cause significant environmental burdens during the product life cycles. As a result of intensive development and the changing social attitudes and behaviors in the last century, the agrofood sector is the highest resource consumer after housing in the EU. This paper is part of an effort to estimate environmental impacts associated with life cycles of the agrofood chain, such as primary energy consumption, water exploitation, and global warming. Life cycle assessment is used to investigate the production of the following citrus-based products in Italy: essential oil, natural juice, and concentrated juice from oranges and lemons. The related process flowcharts, the relevant mass and energy flows, and the key environmental issues are identified for each product. This paper represents one of the first studies on the environmental impacts from cradle to gate for citrus products in order to suggest feasible strategies and actions to improve their environmental performance.