Storage-yield analysis of surface water reservoirs: the role of reliability constraints and operating policies

Stochastic optimization methods are used for optimal design and operation of surface water reservoir systems under uncertainty. Chance-constrained (CC) optimization with linear decision rules (LDRs) is an old approach for determining the minimum reservoir capacity required to meet a specific yield at a target level of reliability. However, this approach has been found to overestimate the reservoir capacity. In this paper, we propose the reason for this overestimation to be the fact that the reliability constraints considered in standard CC LDR models do not have the same meaning as in other models such as reservoir operation simulation models. The simulation models have fulfilled a target reliability level in an average sense (i.e., annually), whereas the standard CC LDR models have met the target reliability level every season of the year. Mixed integer nonlinear programs are presented to clarify the distinction between the two types of reliability constraints and demonstrate that the use of seasonal reliability constraints, rather than an average reliability constraint, leads to 80–150 % and 0–32 % excess capacity for SQ-type and S-type CC LDR models, respectively. Additionally, a modified CC LDR model with an average reliability constraint is proposed to overcome the reservoir capacity overestimation problem. In the second stage, we evaluate different operating policies and show that for the seasonal (average) reliability constraints, open-loop, S-type, standard operating policy, SQ-type, and general SQ-type policies compared to a model not using any operation rule lead to 190–460 % (200–550 %), 100–200 % (80–300 %), 0–90 % (0–60 %), 30–90 % (0–20 %), and 10–90 % (0–10 %) excess capacity, respectively.     

Sediment mobilization study on Cretaceous,Tertiary and Quaternary lithological formations of an external Rif catchment,Morocco

ABSTRACT

Soil erosion is a serious ecological problem in Mediterranean areas. The IntErO model based on the erosion potential method (EPM) and the modified universal soil loss equation (MUSLE) have been used to assess soil erosion in several basins. This study aimed to assess and evaluate the effectiveness of these methods for evaluating sediment production and deposition rates in the Arbaa Ayacha basin, Morocco, in order to estimate sediment fluxes on a catchment scale. Our findings suggest that the basin is strongly exposed to erosion owing to geological formations, slope and land use, with average losses of about 28.4 t ha^?1 year^?1. Erosion processes were evaluated at the erosion production (Eocene marly formations) and sedimentation zones (Quaternary terraces). The results of these models may be useful to address soil and water management in this region and to assess the impact of a river dam that will be built in the basin.     

An integrated procedure to evaluate hydrological models

The growing concern for health‐related problems deriving from pollutants leaching is driving national and international administrations to support the development of tools for evaluating the effects of alternate management scenarios and identifying vulnerable areas. Cropping systems models are powerful tools for evaluating leachates under different environmental, social, and management conditions. As percolating water is the transport vehicle for pollutants transport in soil, a reliable evaluation of water balance models is a fundamental prerequisite for investigating pesticides and nitrate fate. As specific approaches for the evaluation of multi‐layer evolution of state variables are missing, we propose a fuzzy‐based, integrated indicator (I_SWC: 0, best; 1, worst) for a comprehensive evaluation of soil water content (SWC) simulations. We aggregated error metrics with others quantifying the homogeneity of errors across different soil layers, the capability of models to reproduce complex dynamics function of both time and soil depth, and model complexity. We tested I_SWC on a sample dataset where the models CropSyst and CERES‐Wheat were used to simulate SWC for winter wheat systems. I_SWC revealed that, in the explored conditions, the global assessment of the two models' performances allowed identification of CropSyst as the best (average I_SWC = 0·441, with a value of 0·537 obtained by CERES‐Wheat), although each model prevailed for some of the metrics. CropSyst presented the highest accuracy (average agreement module = 0·400), whereas CERES‐Wheat's accuracy was slightly worse, although achieved with a simplified modelling approach (average Akaike Information Criterion = − 230·44), thereby favouring large‐area applicability. The non‐univocal scores achieved by the models for the different metrics support the use of multi‐metric evaluation approaches for quantifying the different aspects of water balance model performances. Copyright © 2010 John Wiley & Sons, Ltd.     

The 2009 Samoan and 2010 Chilean Tsunamis Recorded on the Pacific Coast of Russia

Two remote tsunamis were recorded on the Pacific coast of Russia: a relatively weak Samoan tsunami of September 29, 2009 and a much stronger Chilean tsunami of February 28, 2010. In the area of the South Kuril Islands, records were obtained using autonomous bottom pressure gauges of the Institute of Marine Geology and Geophysics (IMGG). Additionally, for the oceanic coast of the Kamchatka Peninsula, Paramushir, and Bering Islands we used data transmitted from coastal tide gauges of the Russian Tsunami Warning Service (TWS). The maximum trough-to-crest heights of the Samoan tsunami were about 30–40 cm, and were recorded about 3 h after the first tsunami arrival. The maximum Chilean tsunami trough-to-crest wave heights were 218 cm at Severo-Kurilsk, 187 cm at Tserkovnaya Bay (Shikotan Island), and 140 cm at Khodutka Bay (Kamchatka Peninsula). The time between first and maximum waves reached 4 h. Strong sea level oscillations for both events range for a long time: about 15–17 h. The Samoan tsunami induced high-frequency oscillations; a considerable increase in spectral energy in the tsunami spectrum was observed at periods of 4–20 min. In contrast, the Chilean tsunami induced low-frequency oscillations; the dominant periods were 30–80 min. A probable reason for these differences is the different extensions of the source areas (the Chilean source was much larger than the Samoan source) and the different energy radiation directions from the sources. Local topography resonant effects were the main reason of well-expressed peaks in power spectra in different areas: with a period of 10 min (Khodutka Bay), 19–20 min (Malokurilskaya and Tserkovnaya bays), 29 min (Krabovaya Inlet), and 43 min (Avachinskaya Guba and Nikolskoe).     

Water‐Saving Crop Planning Using Multiple Objective Chaos Particle Swarm Optimization for Sustainable Agricultural and Soil Resources Development

Establishing a water‐saving planting structure is necessary for the arid, water‐deficient regions of northern China and of the world. Optimizing and adjusting a water‐saving agricultural planting structure is a typical semi‐structured, multi‐level, multi‐objective group decision‐making problem. Therefore, optimization can be best achieved with a swarm intelligence algorithm. We build an optimization model for a water‐saving planting structure with four target functions: (1) maximum total net output, (2) total grain yield, (3) ecological benefits, and (4) water productivity. The decision variable is the yearly seeded area of different crops, and its restrictions are the farmland area, the agricultural water resources, and the needs of the people and other farming‐related industries. Multiple objective particle swarm optimization (MOPSO) is an efficient optimization method, but its main shortcoming is that it can easily fall into a local optimum. Multiple objective chaos particle swarm optimization (MOCPSO) will greatly improve the searching performance of the algorithm by placing chaos technology with the advantages of ergodicity into MOPSO. When MOCPSO is used to solve the multi‐objective optimization model in the middle portion of the Heihe River basin, the results show that MOCPSO has the advantages of a high convergence speed and a tendency not to fall easily into a local optimum. After adopting a water‐saving agricultural planting structure, irrigation water would be reduced by about 7%, which would provide tangible economic, social, and ecological benefits for sustainable agricultural development.     

Multi‐objective particle swarm optimization for generating optimal trade‐offs in reservoir operation

A multi‐objective particle swarm optimization (MOPSO) approach is presented for generating Pareto‐optimal solutions for reservoir operation problems. This method is developed by integrating Pareto dominance principles into particle swarm optimization (PSO) algorithm. In addition, a variable size external repository and an efficient elitist‐mutation (EM) operator are introduced. The proposed EM‐MOPSO approach is first tested for few test problems taken from the literature and evaluated with standard performance measures. It is found that the EM‐MOPSO yields efficient solutions in terms of giving a wide spread of solutions with good convergence to true Pareto optimal solutions. On achieving good results for test cases, the approach was applied to a case study of multi‐objective reservoir operation problem, namely the Bhadra reservoir system in India. The solutions of EM‐MOPSOs yield a trade‐off curve/surface, identifying a set of alternatives that define optimal solutions to the problem. Finally, to facilitate easy implementation for the reservoir operator, a simple but effective decision‐making approach was presented. The results obtained show that the proposed approach is a viable alternative to solve multi‐objective water resources and hydrology problems. Copyright © 2007 John Wiley & Sons, Ltd.     

Estimation of Explosion Energy Yield at Chernobyl NPP Accident

The value of the ¹³³Xe/^133mXe isometric activity ratio for the stationary regime of reactor work is about 35, and that for an instant fission (explosion) is about 11, which allowed estimation of the nuclear component of the instant (explosion) energy release during the NPP accident. Atmospheric xenon samples were taken at the trajectory of accident product transfers (in the Cherepovetz area); these samples were measured by a gamma spectrometer, and the ¹³³Xe/^133mXe ratio was determined as an average value of 22.4. For estimations a mathematic model was elaborated considering both the value of instant released energy and the schedule of reactor power change before the accident, as well as different fractionation conditions on the isobaric chain. Comparison of estimated results with the experimental data showed the value of the instant specific energy release in the Chernobyl NPP accident to be 2·10⁵–2·10⁶ J/Wt or 6·10¹⁴–6·10¹⁵ J (100–1,000 kt). This result is matched up to a total reactor power of 3,200 MWt. However this estimate is not comparable with the actual explosion scale estimated as 10t TNT. This suggests a local character of the instant nuclear energy release and makes it possible to estimate the mass of fuel involved in this explosion process to be from 0.01 to 0.1% of total quantity.     

Probabilistic Assessment of Tsunami Recurrence in the Indian Ocean

The Indian Ocean is one of the most tsunamigenic regions of the world and recently experienced a mega-tsunami in the Sumatra region on 26 December 2004 (M _W 9.2 earthquake) with tsunami intensity I (Soloviev-Imamura intensity scale) equal to 4.5, causing heavy destruction of lives and property in the Indian Ocean rim countries. In this study, probabilities of occurrences of large tsunamis with tsunami intensities I ≥ 2.0 and I ≥ 3.0 (average wave heights H ≥ 2.83 m and H ≥ 5.66 m, respectively) during a specified time interval were calculated using three stochastic models, namely, Weibull, gamma and lognormal. Tsunami recurrence was calculated for the whole Indian Ocean and the special case of the Andaman-Sumatra-Java (ASJ) region, excluding the 1945 Makran event from the main data set. For this purpose, a reliable, homogeneous and complete tsunami catalogue with I ≥ 2.0 during the period 1797–2006 was used. The tsunami hazard parameters were estimated using the method of maximum likelihood. The logarithm of likelihood function (ln L) was estimated and used to test the suitability of models in the examined region. The Weibull model was observed to be the most suitable model to estimate tsunami recurrence in the region. The sample mean intervals of occurrences of tsunamis with intensity I ≥ 2.0 and I ≥ 3.0 were calculated for the observed data as well as for the Weibull, gamma and lognormal models. The estimated cumulative and conditional probabilities in the whole Indian Ocean region show recurrence periods of about 27–30 years (2033–2036) and 35–36 years (2039–2040) for tsunami intensities I ≥ 2.0 and I ≥ 3.0, respectively, while it is about 31–35 years (2037–2041) and 41–42 years (2045–2046) for a tsunami of intensity I ≥ 2.0 and I ≥ 3.0, respectively, in the ASJ region. A high probability (>0.9) of occurrence of large tsunamis with I ≥ 2.0 in the next 30–40 years in the Indian Ocean region was revealed.     

The influence of rain intensity on raindrop diameter and the kinetics of tropical rainfall: case study of Skudai,Malaysia

ABSTRACT

The modelling of soil loss and investigation of urban hydrology and wet weather pollution in Malaysia requires the definition of rainfall parameters for the region. In this study, an inexpensive method was applied to establish the influence of raindrop diameter on kinetics and rain intensity in Skudai, Peninsular Malaysia, as a prelude to wider regional research. Raindrop sizes vary from less than 1.2 mm to as big as 7.0 mm, with median raindrop diameters of 2.51 mm and a mean diameter of 2.56 mm. The median raindrop diameter–intensity relationship correlates strongly using power and exponential equations, with coefficients of determination of 0.75 and 0.73, respectively. The kinetic energy–intensity relationship fits an exponential function and also a linear equation with R² values of 0.49 and 0.34, respectively. An average rain kinetic energy of 30 J m^-2 mm^-1 was recorded. This research leads to an objective reclassification of rainfall intensities in the region.

Editor Z.W. Kundzewicz; Associate editor not assigned     

Effects of terrain smoothing on topographic shielding correction factors for cosmogenic nuclide‐derived estimates of basin‐averaged denudation rates

Estimation of spatially averaged denudation rates from cosmogenic nuclide concentrations in sediments depends on the surface production rates, the scaling methods of cosmic ray intensities, and the correction algorithms for skyline, snow and vegetation shielding used to calculate terrestrial cosmogenic nuclide production. While the calculation of surface nuclide production and application of latitude, altitude and palaeointensity scaling algorithms are subjects of active research, the importance of additional correction for shielding by topographic obstructions, snow and vegetation is the subject of ongoing debate. The derivation of an additional correction factor for skyline shielding for large areas is still problematic. One important issue that has yet to be addressed is the effect of the accuracy and resolution of terrain representation by a digital elevation model (DEM) on topographic shielding correction factors. Topographic metrics scale with the resolution of the elevation data, and terrain smoothing has a potentially large effect on the correction of terrestrial cosmogenic nuclide production rates for skyline shielding. For rough, high‐relief landscapes, the effect of terrain smoothing can easily exceed analytical errors, and should be taken into account. Here we demonstrate the effect of terrain smoothing on topographic shielding correction factors for various topographic settings, and introduce an empirical model for the estimation of topographic shielding factors based on landscape metrics. Copyright © 2008 John Wiley and Sons, Ltd.     

Stochastic competitive analysis of hydropower and water supplies within an energy–water nexus

Energy and water are scarce resources and understanding the complicated energy–water nexus is an important issue for effective resource management. The purpose of this research was to analyze the competitive and cooperative relationships involving energy and water production and use. Specifically, tradeoff and integrated management of hydropower generation and water supplies are analyzed for energy–water systems. A Nash–Cournot model was established to analyze strategic behaviors among participants in energy–water systems. In the model, tradeoff analysis and integrated management of hydropower and water supplies were simulated for a reservoir system. In addition, hydropower and thermal power generation in competitive energy markets was examined. A case study of Dajia River reservoirs in the Tai-Chung and Chang-Hwa energy–water systems is presented. Dajia River is the second longest river in central Taiwan; the reservoirs system of Dajia River generates hydropower with installed capacity of 1150 MW. Strategic competitive and cooperative behaviors regarding energy–water linkage were quantified in the results. The results show that integrated management of hydropower and water supplies can increase renewable energy production, lower electricity equilibrium price, and decrease carbon dioxide emission.     

Comparison of optimization algorithms for parameter estimation of multi-phase flow models with application to geological carbon sequestration

Optimization of multi-phase transport models is important both for calibrating model parameters to observed data and for analyzing management options. We focus on examples of geological carbon sequestration (GCS) process-based multi-phase models. Realistic GCS models can be very computationally expensive not only due to the spatial distribution of the model but also because of the complex nonlinear multi-phase and multi-component transport equations to be solved. As a result we need to have optimization methods that get accurate answers with relatively few simulations. In this analysis we compare a variety of different types of optimization algorithms to understand the best type of algorithms to use for different types of problems. This includes an analysis of which characteristics of the problem are important in choice of algorithm. The goal of this paper is to evaluate which optimization algorithms are the most efficient in a given situation, taking into account shape of the optimization problem (e.g. uni- or multi-modal) and the number of simulations that can be done. The algorithms compared are the widely used derivative-based PEST optimization algorithm, the derivative-based iTOUGH2, the Kriging response surface algorithm EGO, the heuristics-based DDS (Dynamically Dimensioned Search), and the Radial Basis Function surrogate response surface based global optimization algorithms ‘GORBIT’ and ‘Stochastic RBF’. We calibrate a simple homogeneous model ‘3hom’ and two more realistic models ‘20layer’ and ‘6het’. The latter takes 2 h per simulation. Using rigorous statistical tests, we show that while the derivative-based algorithms of PEST are efficient on the simple 3hom model, it does poorly in comparison to surrogate optimization methods Stochastic RBF and GORBIT on the more realistic models. We then identify the shapes of the optimization surface of the three models using enumerative simulations and discover that 3hom is smooth and unimodal and the more realistic models are rough and multi-modal. When the number of simulations is limited, surrogate response surfaces algorithms perform best on multi-modal, bumpy objective functions, which we expect to have for most realistic multi-phase flow models such as those for GCS.     

Implementation of a hybrid MLP-FFA model for water level prediction of Lake Egirdir,Turkey

The predictive ability of a hybrid model integrating the Firefly Algorithm (FFA), as a heuristic optimization tool with the Multilayer Perceptron (MLP-FFA) algorithm for the prediction of water level in Lake Egirdir, Turkey, is investigated. The accuracy of the hybrid MLP-FFA model is then evaluated against the standalone MLP-based model developed with the Levenberg–Marquadt optimization scheme applied for in the backpropagation-based learning process. To develop and investigate the veracity of the proposed hybrid MLP-FFA model, monthly time scale water level data for 56 years (1961–2016) are applied to train and test the hybrid model. The input combinations of the standalone and the hybrid predictive models are determined in accordance with the Average Mutual Information computed from the historical water level (training) data; generating four statistically significant lagged combinations of historical data to be adopted for the 1-month forecasting of lake water level. The proposed hybrid MLP-FFA model is evaluated with statistical score metrics: Nash–Sutcliffe efficiency, root mean square and mean absolute error, Wilmott’s Index and Taylor diagram developed in the testing phase. The analysis of the results showed that the hybrid MLP–FFA4 model (where 4 months of lagged combinations of lake water level data are utilized) performed more accurately than the standalone MLP4 model. For the fully optimized hybrid (MLP-FFA4) model evaluated in the testing phase, the Willmott’s Index was approximately 0.999 relative to 0.988 (MLP 4) and the root mean square error was approximately 0.029 m and compared to 0.102 m. Moreover, the inter-comparison of the forecasted and the observed data with various other performance metrics (including the Taylor diagram) verified the robustness of the proposed hybrid MLP-FFA4 model over the standalone MLP4 model applied in the problem of forecasting lake water level prediction in the current semi-arid region in Turkey.     

Crust and upper mantle structures beneath Northeast China from receiver function studies

P-wave and S-wave receiver function analyses have been performed along a profile consisted of 27 broadband seismic stations to image the crustal and upper mantle discontinuities across Northeast China. The results show that the average Moho depth varies from about 37 km beneath the Daxing’anling orogenic belt in the west to about 33 km beneath the Songliao Basin, and to about 35 km beneath the Changbai mountain region in the east. Our results reveal that the Moho is generally flat beneath the Daxing’anling region and a remarkable Moho offset (about 4 km) exists beneath the basin-mountain boundary, the Daxing’anling-Taihang Gravity Line. Beneath the Tanlu faults zone, which seperates the Songliao Basin and Changbai region, the Moho is uplift and the crustal thickness changes rapidly. We interpret this feature as that the Tanlu faults might deeply penetrate into the upper mantle, and facilitate the mantle upwelling along the faults during the Cenozoic era. The average depth of the lithosphere-asthenosphere boundary (LAB) is ~80 km along the profile which is thinner than an average thickness of a continental lithosphere. The LAB shows an arc-like shape in the basin, with the shallowest part approximately beneath the center of the basin. The uplift LAB beneath the basin might be related to the extensive lithospheric stretching in the Mesozoic. In the mantle transition zone, a structurally complicated 660 km discontinuity with a maximum 35 km depression beneath the Changbai region is observed. The 35 km depression is roughly coincident with the location of the stagnant western pacific slab on top of the 660 km discontinuity revealed by the recent P wave tomography.     

Waveform and Spectral Analyses of the 2011 Japan Tsunami Records on Tide Gauge and DART Stations Across the Pacific Ocean

We studied the 11 March 2011 Tohoku tsunami through analysis of the sea level records from 21 tide gauge and 16 DART (Deep-ocean Assessment and Reporting of Tsunamis) stations from across the Pacific Ocean. The extreme power of this trans-oceanic tsunami was indicated by the trough-to-crest heights of 3.03 m at Arena Cove on the western coast of the USA and 3.94 m at Coquimbo on the southern coast of Chile. The average value of the maximum amplitude was 163.9 cm for the examined tide gauge records. At many coastal tide gauge stations the largest wave arrived several hours after the first arrival of the tsunami wave, and the tsunami lasted for a long time with an average duration of 4 days. On the contrary, at most of the DART stations in the deep ocean, the first wave was the largest, the tsunami amplitudes were smaller with an average maximum of 51.2 cm, and the durations were shorter with an average of 2 days. The two dominant tsunami periods on the DART records were 37 and 67.4 min, which are possibly attributed to the width and length of the tsunami source fault, respectively. The dimensions of the tsunami source was estimated as 233 km × 424 km. Wavelet analyses of tide gauge and DART records showed that most of the tsunami energy was distributed at the wide period band of around 10–80 min during the first hour after the tsunami arrival, then it was concentrated in a relatively narrower band. The frequency-time plots showed the switches and lapses of tsunami energy at the 35- and 65-min period bands.     

Probabilistic ecological risk assessment of heavy metals in sediments from China’s major aquatic bodies

An overall and comparative ecological risk assessment of heavy metals (including Cd, Cr, Cu, Pb, Zn, Hg and As) in surface sediments from China’s eight major aquatic bodies was conducted to better understand their potential risks on a national scale. By applying the joint approach of Hakanson risk index (RI) and Monte Carlo simulation, ecological risk in this work is expressed as probability distribution of RI values instead of single point calculations to reflect the uncertainties in risk assessment process. The results show that the highest ecological risks posed by heavy metals existed in Xiangjiang River and Dianchi Lake. Although only a slim margin of high risk (651.88/600 = 1.08 and 700.61/600 = 1.17) was identified based on average RI values, the probabilities of high risk level derived from Monte Carlo simulation reached as high as 56.7 and 52.9 % in these two aquatic bodies, respectively. And the probability of low risk level was less than 1.6 %. Furthermore, the risk was mainly contributed by Hg and Cd, discharged through local intensive mining and industrial activities. The findings indicate that rigid control and effective management measures to prevent heavy metal pollution are urgently needed in China, especially for the high-risk aquatic bodies. This study shows that the joint approach can be used to identify the high risk water bodies and the major metal pollutants. It may avoid overestimating or underestimating the ecological risk and provide more decision-making support for risk alleviation in the polluted aquatic bodies.     

Lithospheric structure of NW Iran from P and S receiver functions

We computed P and S receiver functions to investigate the lithospheric structure beneath the northwest Iran and compute the Vp/Vs ratio within the crust of this seismologically active area. Our results enabled us to map the lateral variations of the Moho as well as those of the lithosphere–asthenosphere boundary (LAB) beneath this region. We selected data from teleseismic events (M_b?>?5.5, epicentral distance between 30° and 95° for P receiver functions and M_b?>?5.7, epicentral distance between 60° and 85° for S receiver functions) recorded from 1995 to 2008 at 8 three-component short-period stations of Tabriz Telemetry Seismic Network. Our results obtained from P receiver functions indicate clear conversions at the Moho boundary. The Moho depth was firstly estimated from the delay time of the Moho converted phase relative to the direct P wave. Then we used the H-Vp/Vs stacking algorithm of Zhu and Kanamori to estimate the crustal thickness and Vp/Vs ratio underneath the stations with clear Moho multiples. We found an average Moho depth of 48 km, which varies between 38.5 and 53 km. The Moho boundary showed a significant deepening towards east and north. This may reveal a crustal thickening towards northeast possibly due to the collision between the Central Iran and South Caspian plates. The obtained average Vp/Vs ratio was estimated to be 1.76, which varies between 1.73 and 1.82. The crustal structure was also determined by modeling of P receiver functions. We obtained a three-layered model for the crust beneath this area. The thickness of the layers is estimated to be 6–11, 18–35, and 38–53 km, respectively. The average of the shear wave velocity was calculated to be 3.4 km/s in the crust and reaches 4.3 km/s below the Moho discontinuity. The crustal thickness values obtained from P receiver functions are in good agreement with those derived by S receiver functions. In addition, clear conversions with negative polarity were observed at ~8.7 s in S receiver functions, which could be related to the conversion at the LAB. This may show a relatively thin continental lithosphere of about 85 km implying that the lithosphere was influenced by various geodynamical reworking processes in the past.     

Pan-European ground-motion prediction equations for the average horizontal component of PGA,PGV, and 5 %-damped PSA at spectral periods up to 3.0 s using the RESORCE dataset

This article presents a set of Ground-Motion Prediction Equations (GMPEs) for Europe and the Middle East, derived from the RESORCE strong motion data bank, following a standard regression approach. The parametric GMPEs are derived for the peak ground acceleration, peak ground velocity, and 5 %-damped pseudo-absolute acceleration response spectra computed over 23 periods between 0.02 and 3 s, considering the average horizontal-component ground-motions. The GMPEs are valid for distances less than 300 km, hypocentral depth up to 35 km and over the magnitude range 4–7.6. Two metrics for the source-to-station distance (i.e. Joyner-Boore and hypocentral) are considered. The selected dataset is composed by 2,126 recordings (at a period of 0.1 s) related to 365 earthquakes, that includes strong-motion data from 697 stations.The EC8 soil classification (four classes from A to D) discriminates recording sites and four classes (normal, reverse, strike-slip, and unspecified) describe the style of faulting. A subset which contains only stations with measured Vs30 and earthquakes with specified focal mechanism (1,224 records from 345 stations and 255 earthquakes) is used to test of the accuracy of the median prediction and the variability associated to the broader data set. A random effect regression scheme is applied and bootstrap analyses are performed to estimate the 95 % confidence levels for the parameters. The total standard deviation sigma is decomposed into between-events and within-event components, and the site-to-site component is evaluated as well. The results show that the largest contribution to the total sigma is coming from the within-event component. When analyzing the residual distributions, no significant trends are observed that can be ascribed to the earthquake type (mainshock-aftershock classification) or to the non-linear site effects. The proposed GMPEs have lower median values than global models at short periods and large distances, while are consistent with global models at long periods $(\hbox {T} > 1)$  s. Consistency is found with two regional models developed for Turkey and Italy, as the considered dataset is dominated by waveforms recorded in these regions.     

Multi-objective optimization for sustainable groundwater resource management in a semiarid catchment

Abstract

Groundwater is an important water resource and its management is vital for integrated water resources development in semiarid catchments. The River Shiyang catchment in the semiarid area of northwestern China was studied to determine a sustainable multi-objective management plan of water resources. A multi-objective optimization model was developed which incorporated water supplies, groundwater quality, ecology, environment and economics on spatial and temporal scales under various detailed constraints. A calibrated groundwater flow model was supplemented by grey simulation of groundwater quality, thus providing two lines of evidence to use in the multi-objective water management. The response matrix method was used to link the groundwater simulation models and the optimization model. Multi-phase linear programming was used to minimize and compromise the objectives for the multi-period, conjunctive water use optimization model. Based on current water demands, this water use optimization management plan was able to meet ecological, environmental and economic objectives, but did not find a final solution to reduce the overall water deficit within the catchment.     

Probabilistic assessment of aggregate risk for bisphenol A by integrating the currently available environmental data

Bisphenol A (BPA) is an endocrine disruptor widely used in the production of polycarbonate plastics and epoxy resins. Exposures to BPA have been associated with reproductive, developmental, and cardiovascular effects. In this study, the CalTOX model was used to assess the aggregate health risks on BPA by integrating the currently available BPA data in various environmental media in Taiwan. Local parameters such as chemical properties, local landscape data, and exposure factors were used as model inputs under the continuous source mode. A reference dose (RfD) of 50 μg/kg-day was adopted in this assessment. Monte Carlo simulation was used to simulate great variability of the environmental data. Our results show that an upper limit of 95 % confidence interval of aggregate exposures for the adults (19–64 years old) was 1.05 μg/kg-day, corresponding to a hazard index (HI) of 0.021. The chemical properties (BPA half-life in surface water), intake rates (fruit, vegetable, and fluid intake), and landscape data (average depth of surface waters and leaf wet density) are critical parameters. Finally, HI value would approach to 1 as BPA concentrations in ambient air, surface water, and sediment was greater than 20 ng/m³, 100 μg/L, and 3.3 mg/kg. The quality of the risk assessment on BPA can be further improved by reduction of uncertainty of the abovementioned critical parameters as well as considering additional BPA exposures from canned and packaged goods.