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51.
Changes over the twentieth century in seasonal mean potential predictability (PP) of global precipitation, 200 hPa height and land surface temperature are examined by using 100-member ensemble. The ensemble simulations have been conducted by using an intermediate complexity atmospheric general circulation model of the International Center for Theoretical Physics, Italy. Using the Hadley Centre sea surface temperature (SST) dataset on a 1° grid, two 31 year periods of 1920–1950 and 1970–2000 are separated to distinguish the periods of low and high SST variability, respectively. The standard deviation values averaged for the (“Niño-3.4”; 5°S–5°N, 170°W–120°W) region are 0.71 and 1.15 °C, for the periods of low and high SST variability, respectively, with a percentage change of 62 % during December–January–February (DJF). The leading eigenvector and the associated principal component time series, also indicate that the amplitude of SST variations have positive trend since 1920s to recent years, particularly over the El Niño Southern Oscillation (ENSO) region. Our hypothesis states that the increase in SST variability has increased the PP for precipitation, 200 hPa height and land surface temperature during the DJF. The analysis of signal and noise shows that the signal-to-noise (S/N) ratio is much increased over most of the globe, particularly over the tropics and subtropics for DJF precipitation. This occurs because of a larger increase in the signal and at the same time a reduction in the noise, over most of the tropical areas. For 200 hPa height, the S/N ratio over the Pacific North American (PNA) region is increasing more than that for the other extratropical regions, because of a larger percentage increase in the signal and only a small increase in noise. It is also found that the increase in seasonal mean transient signal over the PNA region is 50 %, while increase in the noise is only 12 %, during the high SST variability period, which indicates that the increase in signal is more than the noise. For DJF land surface temperature, the perfect model notion is utilized to confirm the changes in PP during the low and high SST variability periods. The correlation between the perfect model and the other members clearly reveal that the seasonal mean PP changed. In particular, the PP for the 31 years period of 1970–2000 is higher than that for the 31 years period of 1920–1950. The land surface temperature PP is increased in northern and southern Africa, central Europe, southern South America, eastern United States and over Canada. The increase of the signal and hence the seasonal mean PP is coincides with an increase in tropical Pacific SST variability, particularly in the ENSO region.  相似文献   
52.
Karstic rocks (soluble rocks) exist in different areas of the world having useful/harmful structural and environmental impacts. One of the useful aspect is availability of rich water resources in some regions. An important defect of this kind of rocks is their low strength against water flows. These rocks usually dissolve in acidic water and as a result abundant caverns are created inside them. The gypsum and salt present in these rocks dissolve even in non-acidic water. Presence of these rocks in different foundations and reservoirs especially in dams could be potentially dangerous and cause enormous problems. If dams are located above soluble rocks like limestone, dolomite or gypsum they are endangered by karstification. Karstification is a dynamic process resulting in voids within the rocks due to dissolution. This dissolution leads to the formation of a pipe system within the sub-surface In the physical modeling, effects of cut-off wall height within gypsum layer were examined and monitored. Then with GeoStudio and Flac software, results of physical modeling are analyzed. In each experiment, cut-off wall height was changed. The result of the experiments indicated that as the gypsum Karst is very weak against water, cut-off wall must continue completely within the gypsum layer, as a complete positive cut-off wall.  相似文献   
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Conservative tracer experiments can provide information useful for characterizing various subsurface transport properties. This study examines the effectiveness of three different types of transport observations for sensitivity analysis and parameter estimation of a three-dimensional site-specific groundwater flow and transport model: conservative tracer breakthrough curves (BTCs), first temporal moments of BTCs (m 1), and tracer cumulative mass discharge (M d) through control planes combined with hydraulic head observations (h). High-resolution data obtained from a 410-day controlled field experiment at Vandenberg Air Force Base, California (USA), have been used. In this experiment, bromide was injected to create two adjacent plumes monitored at six different transects (perpendicular to groundwater flow) with a total of 162 monitoring wells. A total of 133 different observations of transient hydraulic head, 1,158 of BTC concentration, 23 of first moment, and 36 of mass discharge were used for sensitivity analysis and parameter estimation of nine flow and transport parameters. The importance of each group of transport observations in estimating these parameters was evaluated using sensitivity analysis, and five out of nine parameters were calibrated against these data. Results showed the advantages of using temporal moment of conservative tracer BTCs and mass discharge as observations for inverse modeling.  相似文献   
54.
Soil salinity is a major environmental hazard. The global extent of primary and secondary salt affected soils is about 955 and 77 M?ha, respectively. Soil salinity tends to increase in spite of considerable effort dedicated to land reclamation. This requires careful monitoring of the soil salinity status. The objectives of this study were: (a) to evaluate the capability of thematic mapper (TM) and multispectral scanner (MSS) imagery for mapping land cover types, (b) to analyse the spectral features of sail crusts relative to bare soil and gravely soil surface conditions, and (c) to detect the soil salinity changes during the period 1975–2004 in the Ardakan area located in the central Iranian Deserts. The Landsat MSS and TM on two different dates of September 14, 1975 and September 11, 2004, respectively, were used. Due to great confusion between some classes, the TM 6 was included in the band combination. The result of the image classification based on the combination of TM bands 3, 4, 5, and 6 showed of the classification results. For multi-temporal analysis, both TM and MSS images were classified with the same method but with a different number of training classes. The TM-classified image was regrouped to make it comparable with MSS regrouped classified image. The comparison between the classified images showed about 39% of the total area had changed in 29 years. The result of this study revealed the possibility of detecting important soil salinity changes by using Landsat satellite data  相似文献   
55.
The cadence and resolution of solar images have been increasing dramatically with the launch of new spacecraft such as STEREO and SDO. This increase in data volume provides new opportunities for solar researchers, but the efficient processing and analysis of these data create new challenges. We introduce a fuzzy-based solar feature-detection system in this article. The proposed system processes SDO/AIA images using fuzzy rules to detect coronal holes and active regions. This system is fast and it can handle different size images. It is tested on six months of solar data (1 October 2010 to 31 March 2011) to generate filling factors (ratio of area of solar feature to area of rest of the solar disc) for active regions and coronal holes. These filling factors are then compared to SDO/EVE/ESP irradiance measurements. The correlation between active-region filling factors and irradiance measurements is found to be very high, which has encouraged us to design a time-series prediction system using Radial Basis Function Networks to predict ESP irradiance measurements from our generated filling factors.  相似文献   
56.
The amount of volunteered geographic information (VGI) has increased over the past decade, and several studies have been conducted to evaluate the quality of VGI data. In this study, we evaluate the completeness of the road network in the VGI data set OpenStreetMap (OSM). The evaluation is based on an accurate and efficient network-matching algorithm. The study begins with a comparison of the two main strategies for network matching: segment-based and node-based matching. The comparison shows that the result quality is comparable for the two strategies, but the node-based result is considerably more computationally efficient. Therefore, we improve the accuracy of node-based algorithm by handling topological relationships and detecting patterns of complicated network components. Finally, we conduct a case study on the extended node-based algorithm in which we match OSM to the Swedish National Road Database (NVDB) in Scania, Sweden. The case study reveals that OSM has a completeness of 87% in the urban areas and 69% in the rural areas of Scania. The accuracy of the matching process is approximately 95%. The conclusion is that the extended node-based algorithm is sufficiently accurate and efficient for conducting surveys of the quality of OSM and other VGI road data sets in large geographic regions.  相似文献   
57.
Conditioning stochastic simulations are very important in many geostatistical applications that call for the introduction of nonlinear and multiple-point data in reservoir modeling. Here, a new methodology is proposed for the incorporation of different data types into multiple-point statistics (MPS) simulation frameworks. Unlike the previous techniques that call for an approximate forward model (filter) for integration of secondary data into geologically constructed models, the proposed approach develops an intermediate space where all the primary and secondary data are easily mapped onto. Definition of the intermediate space, as may be achieved via application of artificial intelligence tools like neural networks and fuzzy inference systems, eliminates the need for using filters as in previous techniques. The applicability of the proposed approach in conditioning MPS simulations to static and geologic data is verified by modeling a real example of discrete fracture networks using conventional well-log data. The training patterns are well reproduced in the realizations, while the model is also consistent with the map of secondary data.  相似文献   
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ABSTRACT

In order to provide more accurate reservoir-operating policies, this study attempts to implement effective monthly forecasting models. Seven inflow forecasting schemes, applying discrete wavelet transformation and artificial neural networks are proposed and provided to forecast the monthly inflow of Dez Reservoir. Based on some different performance indicators the best scheme is achieved comparing to the observed data. The best forecasting model is coupled with a simulation-optimization framework, in which the performance of five different reservoir rule curves can be compared. Three applied rules are based on conventional Standard operation policy, Regression rules, and Hedging rule, and two others are forecasting-based regression and hedging rules. The results indicate that forecasting-based operating rule curves are superior to the conventional rules if the forecasting scheme provides results accurately. Moreover, it can be concluded that the time series decomposition of the observed data enhances the accuracy of the forecasting results efficiently.  相似文献   
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