Inversion of magnetic data is complicated by the presence of remanent magnetization, and it provides limited information about the magnetic source because of the insufficiency of data and constraint information. We propose a Fourier domain transformation allowing the separation of magnetic anomalies into the components caused by induced and remanent magnetizations. The approach is based on the hypothesis that each isolated source is homogeneous with a uniform and specific Koenigsberger ratio. The distributions of susceptibility and remanent magnetization are subsequently recovered from the separated anomalies. Anomaly components, susceptibility distribution and distribution of the remanent and total magnetization vectors (direction and intensity) can be achieved through the processing of the anomaly components. The proposed method therefore provides a procedure to test the hypotheses about target source and magnetic field, by verifying these models based on available information or a priori information from geology. We test our methods using synthetic and real data acquired over the Zhangfushan iron-ore deposit and the Yeshan polymetallic deposit in eastern China. All the tests yield favourable results and the obtained models are helpful for the geological interpretation. 相似文献
Natural Hazards - Risk perception plays a vital part in flood risk management and mitigation strategies. Therefore, this study aims at first to measure the risk perception of the vulnerable... 相似文献
Natural Hazards - Tornadoes pose a significant threat to residential communities, causing enormous physical damage and losses to their social fabric. The dominant type of single-family residential... 相似文献
Discharge of the Shatt Al-Arab is believed to be a dominating component of the northern Arabian Gulf’s ecology and largely
responsible for productivity of Kuwait’s fisheries. With major construction of dams on the Tigris and Euphrates Rivers in
Turkey, river discharge has been substantially reduced, and flooding essentially eliminated. We attempted to relate river
flow and shrimp landings indirectly by correlating 19 years of salinity and temperature data from Kuwait’s waters with corresponding
annual shrimp landings. For green tiger prawns (Penaeus semisulcatus), the combination of October salinities and January temperatures provided the best correlation (r = 0.67) with landings in the following shrimping season. For the combined landings of jinga and kiddi shrimps (Metapenaeus affinis and Parapenaeopsis stylifera, respectively), December salinity during season and May temperature prior to season resulted in the best correlation (r = 0.87). Landings of these two species also correlated well with spring and summer temperatures. Under normal conditions,
late winter or early spring temperatures prior to fishing season influence recruitment of the green tiger prawn, whereas December
salinities during harvest season influence the abundance of jinga–kiddi shrimps. With further reductions in the Shatt Al-Arab
discharge and the elimination of flood events, Kuwait’s shrimp landings will most likely decrease over time. 相似文献
Soil particle size distribution (PSD) is used to estimate some soil processes, soil moisture characteristics, and infiltration rate (IR). Prediction of infiltration rate from soil texture data requires an accurate characterization of PSD. The objective of this study was to determine more important primary particle diameters that control IR. The experiments were conducted using double-ring method with constant head of 5 cm in 15 different soils and three replications. The range of measured IR for studied soils varied from 1.6 to 30.66 cm h?1. The results indicated that the primary PSD had a significant influence on IR. In other words, most Dn fractions had significant positive effect on the final IR. Among different fractions, D30, D40, and D60 showed higher relationships with IR than the others. These diameters are attributed to particles with diameter of 0.05, 0.08, and 0.16 mm, respectively. The results also showed that increasing the percent of sand have intensified influence on increasing the final IR. Reversely, clay and silt contents showed negative effects on final IR. Furthermore, the CaCO3 had a meaningful effect on the IR that showed the importance of lime in arid and semiarid regions. Finally, it is revealed that the role of texture was important, especially in behavior of infiltration, runoff, and production capability. 相似文献
Arabian Journal of Geosciences - The bauxite ore deposits are mainly found around the Az Zabirah area in the central northern part of Saudi Arabia. The age of the Az Zabirah bauxites was suggested... 相似文献
The present study describes the effect of clouds(macro-physical parameters) on global solar radiation(G).Data from four years of hourly measurements of G on a horizontal surface were used.These data were collected at the South Valley University(SVU) meteorological research station(26.2°N,32.7°E,96 m above mean see level.In addition,the cloud modification factor for G(CMFG) was estimated in three cases:high-level,mid-level,and low-level clouds.For every level,the variation of hourly CMFG as a function of cloud amount(CA) was illustrated.A third-order polynomial between hourly values of CMFG and CA was established.Furthermore,the effect of CA in the attenuation of G relative to its corresponding value in cloudless conditions is discussed.For cloud cover > 88%,G was reduced by 54%,34%,and 28% by low-,mid-,and high-level clouds,respectively. 相似文献
Flooding is one of the most problematic natural events affecting urban areas. In this regard, developing flooding models plays a crucial role in reducing flood-induced losses and assists city managers to determine flooding-prone areas (FPAs). The aim of this study is to investigate on the prediction capability of fuzzy analytical hierarchy process (FAHP) and Mamdani fuzzy inference system (MFIS) methods as two completely and semi-knowledge-based models to identify FPAs in Tehran, Iran. Six flooding conditioning factors including density of channel, distance from channel, land use, elevation, slope, and water discharge were extracted from various geo-spatial datasets. A total of 62 flooding locations were identified in the study area based on the existing reports and field surveys. Of these, 44 (70%) floods were randomly selected as training data and the remaining 18 (30%) cases were used for the validation purposes. After the data preparation step, data were processed by means of two statistical (FAHP) and soft computing (MFIS) methods. Unlike most statistical and soft computing approaches which use flooding inventory data for both training and evaluation of models, only conditioning factor was involved in data processing and inventory data were used in the current study to assess models prediction accuracy. Also, the efficiency of two approaches was evaluated by pixel matching (PM) and area under curve to validate the prediction capability of models. The prediction rate for MFIS and FAHP was 89% and 84%, respectively. Moreover, according to the results obtained from PM, it was found out that about 90% of known flooding locations fell in high-risk areas, whereas it was 83% for FAHP, indicating that flooding susceptibility map of MFIS has higher performance.
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