Hydrodynamic Tidal Model of the Persian Gulf Based on Spatially Variable Bed Friction Coefficient

The aim of this study is to develop a two-dimensional hydrodynamic tidal model for the Persian Gulf (PG2017) using 2D-MIKE21 software. The advantages of present study is accounting for the spatial variation of bed friction coefficient besides a precise bathymetry together with a 23-year of combined records of satellite altimetry data. We found that the bed friction coefficient has a significant effect on sea level changes in the region under our modeling consideration. Since the tidal behavior in the northern part of the Qeshm Island is significantly different from the other parts of the Persian Gulf, to present a more accurate hydrodynamic tidal model, the Gulf is divided into two regions where the bed friction coefficient is modeled separately for each region. The root mean square value of the differences between the amplitude of dominant constituents; M2, S2, K1, and O1 derived from the PG2017 model and that of 98 altimetry and coastal tide gauge stations are respectively equal to 1.6, 1.9, 2.8, and 1.3?cm. Moreover, comparing the PG2017 model efficiency with the FES2014, OSU12, EOT11a, DTU10, and Admiralty models shows that the PG2017 model has an improvement of 22.1%, 47.2%, 43.2%, 44.2%, and 57.6% in terms of relative error, respectively.     

A Modulated-Gradient Parametrization for the Large-Eddy Simulation of the Atmospheric Boundary Layer Using the Weather Research and Forecasting Model

The performance of the modulated-gradient subgrid-scale (SGS) model is investigated using large-eddy simulation (LES) of the neutral atmospheric boundary layer within the weather research and forecasting model. Since the model includes a finite-difference scheme for spatial derivatives, the discretization errors may affect the simulation results. We focus here on understanding the effects of finite-difference schemes on the momentum balance and the mean velocity distribution, and the requirement (or not) of the ad hoc canopy model. We find that, unlike the Smagorinsky and turbulent kinetic energy (TKE) models, the calculated mean velocity and vertical shear using the modulated-gradient model, are in good agreement with Monin–Obukhov similarity theory, without the need for an extra near-wall canopy model. The structure of the near-wall turbulent eddies is better resolved using the modulated-gradient model in comparison with the classical Smagorinsky and TKE models, which are too dissipative and yield unrealistic smoothing of the smallest resolved scales. Moreover, the SGS fluxes obtained from the modulated-gradient model are much smaller near the wall in comparison with those obtained from the regular Smagorinsky and TKE models. The apparent inability of the LES model in reproducing the mean streamwise component of the momentum balance using the total (resolved plus SGS) stress near the surface is probably due to the effect of the discretization errors, which can be calculated a posteriori using the Taylor-series expansion of the resolved velocity field. Overall, we demonstrate that the modulated-gradient model is less dissipative and yields more accurate results in comparison with the classical Smagorinsky model, with similar computational costs.     

Fluid venting and seepage at accretionary ridges: the Four Way Closure Ridge offshore SW Taiwan

Within the accretionary prism offshore SW Taiwan, widespread gas hydrate accumulations are postulated to occur based on the presence of a bottom simulating reflection. Methane seepage, however, is also widespread at accretionary ridges offshore SW Taiwan and may indicate a significant loss of methane bypassing the gas hydrate system. Four Way Closure Ridge, located in 1,500 m water depth, is an anticlinal ridge that would constitute an ideal trap for methane and consequently represents a site with good potential for gas hydrate accumulations. The analysis of high-resolution bathymetry, deep-towed sidescan sonar imagery, high-resolution seismic profiling and towed video observations of the seafloor shows that Four Way Closure Ridge is and has been a site of intensive methane seepage. Continuous seepage is mainly evidenced by large accumulations of authigenic carbonate precipitates, which appear to be controlled by the creation of fluid pathways through faulting. Consequently, Four Way Closure Ridge is not a closed system in terms of fluid migration and seepage. A conceptual model of the evolution of gas hydrates and seepage at accretionary ridges suggests that seepage is common and may be a standard feature during the geological development of ridges in accretionary prisms. The observation of seafloor seepage alone is therefore not a reliable indicator of exploitable gas hydrate accumulations at depth.     

Copper isotope fractionation in the Meiduk porphyry copper deposit,Northwest of Kerman Cenozoic magmatic arc,Iran

The Meiduk deposit possesses three different Cu reservoirs each with a unique Cu isotope signature. δ⁶⁵Cu for the leached cap minerals ranges from ?2.5 to +0.49‰ to ?0.45 to +0.3‰ for hypogene minerals and from +1.3 to +4.4‰ for supergene enrichment minerals. Oxidation of hypogene sulphides and effective trapping of copper (from solutions derived from the leached cap) in the supergene enrichment zone caused this relationship. A systematic pattern of low Cu isotope values close to the surface and higher isotope values with depth reveals a palaeo‐fluid pathway in the northwest–southeast direction over the deposit. Thus, the copper isotope data from leached cap and enrichment minerals can be used to monitor copper migration during supergene weathering at the Meiduk deposit.     

What future for the voluntary carbon offset market after Paris? An explorative study based on the Discursive Agency Approach

The Paris Agreement heralds a new era in international climate governance. Yet, the Agreement's implementation rulebook is still under negotiation. During this transition, from the Kyoto Protocol to the new regime under the Paris Agreement, many non-state actors are facing a high level of uncertainty. In particular, actors in the voluntary carbon market are struggling to define their new role. The business model of producing carbon credits in developing countries and selling them elsewhere is threatened. Although its financial significance and achieved emission reductions are limited, the voluntary market's role as an incubator for innovation has made it a prominent representative of non-state mitigation mechanisms. Therefore, we ask: What effects will the regime change to the Paris Agreement have on the voluntary carbon offset market (VCM) and how does it react to these effects?

This study analyses perceptions of, and reactions to, the new regulatory environment within the VCM. We apply the Discursive Agency Approach to scrutinize the institutions, discourses and influential agents involved in the VCM, and the strategic practices they apply to manage the transition towards the Paris regime. We find two dominant coping strategies: to align the voluntary offsetting mechanism with the Paris Agreement, and to re-invent its overall purpose as a tool to deliver sustainable development rather than solely emission reductions. Based on these results, we outline ‘thought spaces’ for a future VCM: (1) voluntary and non-party offsetting beyond nationally determined contributions (NDCs), (2) results-based financing for emission reductions and sustainable development, and (3) private climate action under international oversight.

Key policy insights

• The Paris Agreement threatens the VCM's business model, prompting market agents to frame and legitimize their work in new ways.

• The voluntary market's viability depends on the future accounting rules for emission reductions under Paris Agreement Article 6. Discursive struggles surround the risks of double counting and NDC ambitions.

• Based on an understanding of the past, we can draw lessons from agents’ attempts to re-legitimize their role under the new Paris Agreement; their future visions will shape the debates about this nascent regime.

     

Application of soft-computing techniques in forecasting sediment load and concentration

ABSTRACT

This paper investigates conventional and soft-computing methods for the estimation of suspended sediment concentration (SSC) and load (SSL) in rivers. Frequently used methods of sediment rate curve (SRC) and multi-nonlinear regression, and soft-computing methods of multi-layer perceptron, multi-linear regression and adaptive neuro-fuzzy inference system are implemented using various hydrological and hydraulic parameters for the Little Kickapoo Creek Watershed, Illinois, USA. All methods performed equally well in the estimation of SSL, without any noticeable outperformance from any from the methods. However, the application of soft-computing methods decreased SSC estimation errors considerably as compared to the results of SRC. The results are significant in the way they reconcile traditionally used hydrological parameters into the soft-computing methods. Overall, soft-computing methods are recommended for the estimation of SSC in rivers because of their reasonably better performance and ease of implementation.     

Preserving spatial linear correlations between neighboring stations in simulating daily precipitation using extended Markov models

Most stochastic weather generators have their focus on precipitation because it is the most important variable affecting environmental processes. One of the methods to reproduce the precipitation occurrence time series is to use a Markov process. But, in addition to the simulation of short-term autocorrelations in one station, it is sometimes important to preserve the spatial linear correlations (SLC) between neighboring stations as well. In this research, an extension of one-site Markov models was proposed to preserve the SLC between neighboring stations. Qazvin station was utilized as the reference station and Takestan (TK), Magsal, Nirougah, and Taleghan stations were used as the target stations. The performances of different models were assessed in relation to the simulation of dry and wet spells and short-term dependencies in precipitation time series. The results revealed that in TK station, a Markov model with a first-order spatial model could be selected as the best model, while in the other stations, a model with the order of two or three could be selected. The selected (i.e., best) models were assessed in relation to preserving the SLC between neighboring stations. The results depicted that these models were very capable in preserving the SLC between the reference station and any of the target stations. But, their performances were weaker when the SLC between the other stations were compared. In order to resolve this issue, spatially correlated random numbers were utilized instead of independent random numbers while generating synthetic time series using the Markov models. Although this method slightly reduced the model performances in relation to dry and wet spells and short-term dependencies, the improvements related to the simulation of the SLC between the other stations were substantial.     

Groundwater quality assessment using entropy weighted water quality index (EWQI) in Lenjanat,Iran

Human health is strongly influenced by water quality which is threatened by the poor quality of polluted groundwater. In this study, the groundwater quality and its suitability for drinking have been studied in Lenjanat plain aquifer, Iran. Fifty-nine groundwater samples from study area were evaluated based on WHO and Iranian standards for drinking water. Groundwater samples from selected monitoring sources were sampled seasonally during 2009–2010. Physical and chemical parameters of groundwater such as electrical conductivity, pH, total dissolved solids, Ca²⁺, Na⁺, K⁺, Mg²⁺, HCO₃ ^?, SO₄ ^2?, Cl^?, F^? and NO₃ ^? were determined. During the water quality index calculating process, the weight of each parameter is usually given by experts according to their practical experience, which is subjective, so much useful and valuable information about the water quality gets lost. In order to avoid personal judgments about the weight of parameters, an information entropy method was used to assign weight to each parameter. Calculation of entropy weighted water quality index (EWQI) for groundwater samples showed that in the wet season, over 57 and 74 % of samples were in the range of “excellent” to “medium” quality based on WHO and Iranian standards, respectively. Due to groundwater quality reduction during dry season, 42 and 62 % of samples were in the range of “excellent” to “medium” quality based on WHO and Iranian standards, respectively. The results indicate that application of the EWQI is very useful to help the public and decision-makers will be able to identify and to evaluate groundwater quality in Lenjanat, Iran.     

Climate extreme and its linkage to regional drought over Idaho, USA

To investigate consequences of climate extreme and variability on agriculture and regional water resource, twenty-seven climatic indices of temperature and precipitation over Idaho, USA, were computed. Precipitation, mean temperature and maximum temperature, self-calibrated Palmer Drought Index and Standardized Precipitation Index for 1-, 3-, 6- and 12-month time scales were used to identify spatial and temporal distribution of climatic extreme and variability as well as drought frequency and magnitude. Seven oceanic indices were also used to detect teleconnections between climatic indices and regional droughts. The analyses were conducted for 56 meteorological stations, during 1962?C2008, characterized by a long-term and high-quality data set. The result indicates that decreasing trends and increasing trends are identified for precipitation and temperature, respectively. Consequently, it appears that frost and ice days dwindle as growing season (May?CAugust) length, tropical nights and summer days increase. Given current climate conditions, the results also imply that these trends will continue in the future possibly driven by uncertain climate variability. We anticipate that these indices explained by teleconnections will improve drought-forecasting capability in this region.