Flooding and the interannual variability of hydrologic quantities in the Missouri River basin

The six mainstem reservoirs in the Missouri River basin (MRB) are managed mainly to prevent flooding from snowmelt and heavy rainfall, a goal for which the interannual variabilities of precipitation ($P$), evapotranspiration ($\mathit{ET}$), and surface air temperature ($T_{\mathrm{air}}$) are vitally important. We tested the hypothesis that under the expected higher variability owing to global climate change, the months with the highest contributions to the interannual variability of $P$, $\mathit{ET}$, and $T_{\mathrm{air}}$ in the MRB will remain unchanged and quantified likely temporal trends in these quantities. Using high-resolution, downscaled Coupled Model Intercomparison Project Phase 5 multi-model ensemble data sets, we compared the multi-year ratio of monthly and annual interannual variability and temporal trends in $P$, $\mathit{ET}$, and $T_{\mathrm{air}}$ during 2011–2020 with three future decades. Results showed that the 6 months with the highest interannual variability in $P$ and $\mathit{ET}$ (April–September) are the same in all four decades. However, for $T_{\mathrm{air}}$, only 4 months (December–March) retain their status as highly variable throughout the four decades; September and October variability is exceeded by the variability in other months. This implies that, compared to $P$ and $\mathit{ET}$, the cyclical change in the probabilities of $T_{\mathrm{air}}$ in the MRB is less stable under future global climate change. This finding can be used to consider the need to alter existing strategies for reservoir release while minimizing the likelihood of aggravating flooding below the reservoirs.     

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.     

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

     

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.     

Electricity consumption and economic growth nexus in Zimbabwe revisited: fresh evidence from Maki cointegration

This study explores the relationship between electricity consumption, real gross domestic product per capita and carbon dioxide emissions in Zimbabwe. To achieve this, the study set off by examining the stationarity properties of the variables under review with the Zivot-Andrews (1992 Zivot, E., and D.W.K. Andrews. 1992. Further evidence on the great crash, the oil-price shock, and the unit-root hypothesis. Journal Of Business and Economic Statistics 10:251-270. doi: http://dx.doi.org/10.2307/1391541.[Taylor &; Francis Online], [Web of Science ®] , [Google Scholar]) unit root test that accounts for a single structural break. Subsequently, Maki (2012 Maki, Daiki. 2012. “Tests for Cointegration Allowing for an Unknown Number of Breaks.” Economic Modelling 29 (5): 2011–15. https://doi.org/10.1016/J.ECONMOD.2012.04.022 [Google Scholar]) cointegration test, which accounts for multiple structural breaks, is applied for equilibrium relationship between the variables under review while the long run regression of dynamic ordinary least square (DOLS) is employed for long-run coefficients as estimation procedures. In order to account for the direction of causality flow, the Toda-Yamamoto (1995 Toda, H Y.., and Taku Yamamoto. 1995. Statistical inference in vector autoregressions with possibly integrated processes. Journal Of Econometrics 66 (1–2):225–50. doi: 10.1016/0304-4076(94)01616-8.[Crossref], [Web of Science ®] , [Google Scholar]) causality test is used for annual frequency data set spanning from 1971–2014. Empirical evidence from the Maki cointegration test shows that there exists a long-run equilibrium relationship between electricity consumption, carbon dioxide emissions and real gross domestic product per capita over the sampled period. The long-run regression suggests that there exist a positive statistically significant relationship between real income and electricity consumption. Thus, corroborating the electricity-led growth hypothesis. This result is supported by the causality test, as one-way causality is observed running from electricity consumption to real gross domestic product. Thus, this is suggestive to government administrators and policymakers that the Zimbabwean economy is electricity dependent. However, there is a tradeoff for environmental quality. As the increase in electricity consumption increases carbon dioxide emissions. The need for diversification of Zimbabwe energy portfolio to cleaner and environmentally friendly energy sources is recommended, given the world global consciousness for cleaner energy consumption.