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991.
Continuous real‐time analysis of the isotopic composition of precipitation during tropical rain events: Insights into tropical convection 下载免费PDF全文
Shaoneng He Nathalie F. Goodkin Dominik Jackisch Maria Rosabelle Ong Dhrubajyoti Samanta 《水文研究》2018,32(11):1531-1545
To investigate stable isotopic variability of precipitation in Singapore, we continuously analysed the δ‐value of individual rain events from November 2014 to August 2017 using an online system composed of a diffusion sampler coupled to Cavity Ring‐Down Spectrometer. Over this period, the average value (δ18OAvg), the lowest value (δ18OLow), and the initial value (δ18OInit) varied significantly, ranging from ?0.45 to ?15.54‰, ?0.9 to ?17.65‰, and 0 to ?13.13‰, respectively. All 3 values share similar variability, and events with low δ18OLow and δ18OAvg values have low δ18OInit value. Individual events have limited intraevent variability in δ‐value (Δδ) with the majority having a Δδ below 4‰. Correlation of δ18OLow and δ18OAvg with δ18OInit is much higher than that with Δδ, suggesting that convective activities prior to events have more control over δ‐value than on‐site convective activities. The d‐excess of events also varies considerably in response to the seasonal variation in moisture sources. A 2‐month running mean analysis of δ18O reveals clear seasonal and interannual variability. Seasonal variability is associated with the meridional movement of the Intertropical Convergence Zone and evolution of the Asian monsoon. El Niño–Southern Oscillation is a likely driver of interannual variability. During 2015–2016, the strongest El Niño year in recorded history, the majority of events have a δ18O value higher than the weighted average δ18O of daily precipitation. δ18O shows a positive correlation with outgoing longwave radiation in the western Pacific and the Asian monsoon region, and also with Oceanic Niño Index. During El Niño, the convection centre shifts eastward to the central/eastern Pacific, weakening convective activities in Southeast Asia. Our study shows that precipitation δ‐value contains information about El Niño–Southern Oscillation and the Intertropical Convergence Zone, which has a significant implication for the interpretation of water isotope data and understanding of hydrological processes in tropical regions. 相似文献
992.
Hendrik Rujner Günther Leonhardt Jiri Marsalek Anna‐Maria Perttu Maria Viklander 《水文研究》2018,32(5):644-654
The effects of soil water content (SWC) on the formation of run‐off in grass swales draining into a storm sewer system were studied in two 30‐m test swales with trapezoidal cross sections. Swale 1 was built in a loamy fine‐sand soil, on a slope of 1.5%, and Swale 2 was built in a sandy loam soil, on a slope of 0.7%. In experimental runs, the swales were irrigated with 2 flow rates reproducing run‐off from block rainfalls with intensities approximately corresponding to 2‐month and 3‐year events. Run‐off experiments were conducted for initial SWC (SWCini) ranging from 0.18 to 0.43 m3/m3. For low SWCini, the run‐off volume was greatly reduced by up to 82%, but at high SWCini, the volume reduction was as low as 15%. The relative swale flow volume reductions decreased with increasing SWCini and, for the conditions studied, indicated a transition of the dominating swale functions from run‐off dissipation to conveyance. Run‐off flow peaks were reduced proportionally to the flow volume reductions, in the range from 4% to 55%. The swale outflow hydrograph lag times varied from 5 to 15 min, with the high values corresponding to low SWCini. Analysis of swale inflow/outflow hydrographs for high SWCini allowed estimations of the saturated hydraulic conductivities as 3.27 and 4.84 cm/hr in Swales 1 and 2, respectively. Such estimates differed from averages (N = 9) of double‐ring infiltrometer measurements (9.41 and 1.78 cm/hr). Irregularities in swale bottom slopes created bottom surface depression storage of 0.35 and 0.61 m3 for Swales 1 and 2, respectively, and functioned similarly as check berms contributing to run‐off attenuation. The experimental findings offer implications for drainage swale planning and design: (a) SWCini strongly affect swale functioning in run‐off dissipation and conveyance during the early phase of run‐off, which is particularly important for design storms and their antecedent moisture conditions, and (b) concerning the longevity of swale operation, Swale 1 remains fully functional even after almost 60 years of operation, as judged from its attractive appearance, good infiltration rates (3.27 cm/hr), and high flow capacity. 相似文献
993.
Quantifying differences between reservoir inflows and dam site floods using frequency and risk analysis methods 总被引:1,自引:1,他引:0
Yixuan?Zhong Shenglian?GuoEmail author Zhangjun?Liu Yun?Wang Jiabo?Yin 《Stochastic Environmental Research and Risk Assessment (SERRA)》2018,32(2):419-433
Reservoirs are the most important constructions for water resources management and flood control. Great concern has been paid to the effects of reservoir on downstream area and the differences between inflows and dam site floods due to the changes of upstream flow generation and concentration conditions after reservoir’s impoundment. These differences result in inconsistency between inflow quantiles and the reservoir design criteria derived by dam site flood series, which can be a potential risk and must be quantificationally evaluated. In this study, flood frequency analysis (FFA) and flood control risk analysis (FCRA) methods are used with the long reservoir inflow series derived from a multiple inputs and single output model and a copula-based inflow estimation model. The results of FFA and FCRA are compared and the influences on reservoir flood management are also discussed. The Three Gorges Reservoir (TGR) in China is selected as a case study. Results show that the differences between the TGR inflow and dam site floods are significant which result in changes on its flood control risk rates. The mean values of TGR’s annual maximum inflow peak discharge and 3 days flood volume have increased 5.58 and 3.85% than the dam site ones, while declined by 1.82 and 1.72% for the annual maximum 7 and 15 days flood volumes. The flood control risk rates of middle and small flood events are increased while extreme flood events are declined. It is shown that the TGR can satisfy the flood control task under current hydrologic regime and the results can offer references for better management of the TGR. 相似文献
994.
995.
Fabio?OrianiEmail authorView authors OrcID profile Raj?Mehrotra Grégoire?Mariethoz Julien?Straubhaar Ashish?Sharma Philippe?Renard 《Stochastic Environmental Research and Risk Assessment (SERRA)》2018,32(2):321-340
Daily rainfall is a complex signal exhibiting alternation of dry and wet states, seasonal fluctuations and an irregular behavior at multiple scales that cannot be preserved by stationary stochastic simulation models. In this paper, we try to investigate some of the strategies devoted to preserve these features by comparing two recent algorithms for stochastic rainfall simulation: the first one is the modified Markov model, belonging to the family of Markov-chain based techniques, which introduces non-stationarity in the chain parameters to preserve the long-term behavior of rainfall. The second technique is direct sampling, based on multiple-point statistics, which aims at simulating a complex statistical structure by reproducing the same data patterns found in a training data set. The two techniques are compared by first simulating a synthetic daily rainfall time-series showing a highly irregular alternation of two regimes and then a real rainfall data set. This comparison allows analyzing the efficiency of different elements characterizing the two techniques, such as the application of a variable time dependence, the adaptive kernel smoothing or the use of low-frequency rainfall covariates. The results suggest, under different data availability scenarios, which of these elements are more appropriate to represent the rainfall amount probability distribution at different scales, the annual seasonality, the dry-wet temporal pattern, and the persistence of the rainfall events. 相似文献
996.
Amir?NafiEmail author Eric?Crastes Rehan?Sadiq Denis?Gilbert Olivier?Piller 《Stochastic Environmental Research and Risk Assessment (SERRA)》2018,32(2):527-544
Performing a comprehensive risk analysis is primordial to ensure a reliable and sustainable water supply. Though the general framework of risk analysis is well established, specific adaptation seems needed for systems such as water distribution networks (WDN). Understanding of vulnerabilities of WDN against deliberate contamination and consumers’ sensitivity against contaminated water use is very vital to inform decision-maker. This paper presents an innovative step-by-step methodology for developing comprehensive indicators to perform sensitivity, vulnerability and criticality analyses in case of absence of early warning system (EWS). The assessment and the aggregation of these indicators with specific fuzzy operators allow identifying the most critical points in a WDN. Intentional intrusion of contaminants at these points can potentially harm both the consumers as well as water infrastructure. The implementation of the developed methodology has been demonstrated through a case study of a French WDN unequipped with sensors. 相似文献
997.
Vahid?NouraniEmail authorView authors OrcID profile Afshin?Partoviyan 《Stochastic Environmental Research and Risk Assessment (SERRA)》2018,32(2):545-562
Successful modeling of stochastic hydro-environmental processes widely relies on quantity and quality of accessible data and noisy data might effect on the functioning of the modeling. On the other hand in training phase of any Artificial Intelligence based model, each training data set is usually a limited sample of possible patterns of the process and hence, might not show the behavior of whole population. Accordingly in the present article first, wavelet-based denoising method was used in order to smooth hydrological time series and then small normally distributed noises with the mean of zero and various standard deviations were generated and added to the smoothed time series to form different denoised-jittered training data sets, for Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) modeling of daily and multi-step-ahead rainfall–runoff process of the Milledgeville station of the Oconee River and the Pole Saheb station of the Jighatu River watersheds, respectively located in USA and Iran. The proposed hybrid data pre-processing approach in the present study is used for the first time in modeling of time series and especially in modeling of hydrological processes. Furthermore, the impacts of denoising (smoothing) and noise injection (jittering) have been simultaneously investigated neither in hydrology nor in any other engineering fields. To evaluate the modeling performance, the outcomes were compared with the results of multi linear regression and Auto Regressive Integrated Moving Average models. Comparing the achieved results via the trained ANN and ANFIS models using denoised-jittered data showed that the proposed data pre-processing approach which serves both denoising and jittering techniques could improve performance of the ANN and ANFIS based single-step-ahead rainfall–runoff modeling of the Milledgeville station up to 14 and 12% and of the Pole Saheb station up to 22 and 16% in the verification phase. Also the results of multi-step-ahead modeling using the proposed data pre-processing approach showed improvement of modeling for both watersheds. 相似文献
998.
A minimum 1-D seismic velocity model for routine seismic event location purposes was determined for the area of the western Barents Sea, using a modified version of the VELEST code. The resulting model, BARENTS16, and corresponding station corrections were produced using data from stations at regional distances, the vast majority located in the periphery of the recorded seismic activity, due to the unfavorable land–sea distribution. Recorded seismicity is approached through the listings of a joint bulletin, resulting from the merging of several international and regional bulletins for the region, as well as additional parametric data from temporary deployments. We discuss the challenges posed by this extreme network-seismicity geometry in terms of velocity estimation resolution and result stability. Although the conditions do not facilitate the estimation of meaningful station corrections at the farthermost stations, and even well-resolved corrections do not have a convincing contribution, we show that the process can still converge to a stable velocity average for the crust and upper mantle, in good agreement with a priori information about the regional structure and geology, which reduces adequately errors in event location estimates. 相似文献
999.
Yanhu?He Jie?Yang Xiaohong?ChenEmail author 《Stochastic Environmental Research and Risk Assessment (SERRA)》2018,32(11):3083-3097
Water resources provide the foundation for human development and environmental sustainability. Water shortage occurs more or less in some regions, which usually causes sluggish economic activities, degraded ecology, and even conflicts and disputes over water use sectors. Game theory can better reflect the behaviors of involved stakeholders and has been increasingly employed in water resources management. This paper presents a framework for the allocation of river basin water in a cooperative way. The proposed framework applies the TOPSIS model combined with the entropy weight to determine stakeholders’ initial water share, reallocating water and net benefit by using four solution concepts for crisp and fuzzy games. Finally, the Fallback bargaining model was employed to achieve unanimous agreement over the four solution concepts. The framework was demonstrated with an application to the Dongjiang River Basin, South China. The results showed that, overall, the whole basin gained more total benefits when the players participated in fuzzy coalitions rather than in crisp coalitions, and \(\left\{ {NHS_{Fuzzy} \,and\, SV_{Crisp} } \right\}\) could better distribute the total benefit of the whole basin to each player. This study tested the effectiveness of this framework for the water allocation decision-making in the context of water management in river basins. The results provide technical support for water right trade among the stakeholders at basin scale and have the potential to relieve water use conflicts of the entire basin. 相似文献
1000.
Amit?KumarEmail authorView authors OrcID profile M.?P.?Sharma Tao?Yang 《Stochastic Environmental Research and Risk Assessment (SERRA)》2018,32(11):3183-3193
The identification and accurate quantification of sources or sinks of greenhouse gas (GHG) have become a key challenge for scientists and policymakers working on climate change. The creation of a hydropower reservoir, while damming a river for power generation, converts the terrestrial ecosystems into aquatic and subsequently aerobic and anaerobic decomposition of flooded terrestrial soil organic matter resulting in the emission of significant quantity of GHG to the atmosphere. Tropical/subtropical hydropower reservoirs are more significant sources of GHG compared to boreal or temperate one. This paper aims to estimate the emission factor (gCO2eq./kWh) and net GHG emission from Koteshwar hydropower reservoir in Uttarakhand, India. Further, estimated GHG are compared with those from global reservoirs located in the same eco-region so that its impact could be timely minimized/mitigated. Results have shown that emission factor and net GHG emission of Koteshwar reservoir are, respectively, estimated as 13.87 gCO2eq./kWh and 167.70 Gg C year?1 which are less than other global reservoirs located in the same eco-region. This information could be helpful for the hydropower industries to construct reservoirs in tropical eco-regions. 相似文献