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51.
This paper investigates monthly, seasonal, and annual trends in rainfall, streamflow, temperature, and humidity amounts at Urmia lake (UL) basin and analyzes the interaction between these variables and UL’s water level fluctuation during the 1971–2013 period. Two new methods including nonparametric hybrid wavelet Mann–Kendall test and ?en’s methodology have been used to determine potential trends in the variables and their dominant periods. The results showed significant decreasing trends in the water level and streamflow series, moderate decreasing trend in the rainfall and relative humidity series, and increasing trends in the observed temperature data. The 8- , 12-month, and 2-year periods were detected as the dominant periods of the variables in monthly, seasonal, and annual timescales, respectively. The results from the interaction analysis revealed that the main factor influencing the water level at UL is decreasing trend in the streamflow series. Both the monthly series of UL’s water level and the streamflow series of the stations indicated two start points of significant decreasing trend in 1973 and 1998. Furthermore, a comparative analysis among the applied methods indicated a good agreement between the results of hybrid wavelet Mann–Kendall test and ?en’s trend analyzing method. 相似文献
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Geospatial modeling to identify the effects of anthropogenic processes on landscape pattern change and biodiversity 总被引：1，自引：0，他引：1
Saeideh maleki najafabadi Alireza Soffianian Vahid Rahdari Fazel Amiri Biswajeet Pradhan Tayebh Tabatabaei 《Arabian Journal of Geosciences》2015,8(3):1557-1569
This research used geospatial data to quantify biodiversity changes and landscape pattern change to track anthropogenic impacts of such changes at the Mouteh Wildlife Refuge (MWR), Isfahan, Iran. Satellite image duration of four decades, LandSat1-5, and IRS-P6 data were used to develop land cover classification maps for 1971, 1987, 1998, and 2011. The number and size of land cover patches, the degree of naturalness, and the diversity indices were calculated and compared for a 40-year period. The results showed an increasing concern with regard to unplanned human activities. Some improvements of the natural landscape also occurred in the core protected zone of the study area. The number and size of land cover patches, the degree of naturalness, and the diversity indices were calculated. Overall changes in natural land use between 1971 and 1998 at MWR showed that the number of patches for natural land use has increased, but it also showed a decrease in 2011. Similar changes were observed for seminatural land use. Within the artificial classes, the number and area of patches were higher and the largest patch occurred in 2011. The maximum variation of diversity is related to the year 2011. The results showed an increasing concern with regard to unplanned human activities. Some improvements of the natural landscape also occurred in the core protected zone of the study area. Remote sensing and geographic information system offers an important means of detecting and analyzing temporal changes occurring in our landscape. 相似文献
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Safavi Hamid R. Sajjadi Sayed Mahdi Raghibi Vahid 《Theoretical and Applied Climatology》2017,130(1-2):635-653
Water resources in snow-dependent regions have undergone significant changes due to climate change. Snow measurements in these regions have revealed alarming declines in snowfall over the past few years. The Zayandeh-Rud River in central Iran chiefly depends on winter falls as snow for supplying water from wet regions in high Zagrous Mountains to the downstream, (semi-)arid, low-lying lands. In this study, the historical records (baseline: 1971–2000) of climate variables (temperature and precipitation) in the wet region were chosen to construct a probabilistic ensemble model using 15 GCMs in order to forecast future trends and changes while the Long Ashton Research Station Weather Generator (LARS-WG) was utilized to project climate variables under two A2 and B1 scenarios to a future period (2015–2044). Since future snow water equivalent (SWE) forecasts by GCMs were not available for the study area, an artificial neural network (ANN) was implemented to build a relationship between climate variables and snow water equivalent for the baseline period to estimate future snowfall amounts. As a last step, homogeneity and trend tests were performed to evaluate the robustness of the data series and changes were examined to detect past and future variations. Results indicate different characteristics of the climate variables at upstream stations. A shift is observed in the type of precipitation from snow to rain as well as in its quantities across the subregions. The key role in these shifts and the subsequent side effects such as water losses is played by temperature.
相似文献54.
Vahid TAVAKOLI 《《地质学报》英文版》2016,90(5):1852-1864
The Upper Permian Dalan Formation and the Lower Triassic Kangan Formation in the Persian Gulf area are mainly composed of shallow marine facies limestone and dolomite. Two subsurface-cored intervals were investigated in order to understand the original mineralogy and paleoceanic conditions. The decreasing trend of Sr concentration in these deposits shows that aragonite was precipitated during the Late Permian and then gradually changed to calcite toward the Permian–Triassic boundary (PTB). The dissolution rate of aragonite decreased from 60 m below the PTB toward the boundary, with the only exception at 10 m below the Permian-Triassic Boundary (PTB) due to the Permian–Triassic unconformity in this region. The increasing trend of Mg/Ca ratio in a global scale at the end-Permian time shows that the interpreted variation of mineralogy does not result from the change of this ratio. The increasing pCO2 and decreasing pH are considered to be the main controlling factors. The increase of Ca2+ at the end-Permian time due to the input of meteoric waters is too little to fully compensate this effect. A local maximum of the Si content just at the PTB confirms the input of runoff waters. 相似文献
55.
Successful modeling of hydro-environmental processes widely relies on quantity and quality of accessible data, and noisy data can affect the modeling performance. On the other hand in training phase of any Artificial Intelligence (AI) 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 paper, wavelet-based denoising method was used to smooth hydrological time series. Thereafter, small normally distributed noises with the mean of zero and various standard deviations were generated and added to the smooth time series to form different denoised-jittered data sets. Finally, the obtained pre-processed data were imposed into Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) models for daily runoff-sediment modeling of the Minnesota River. To evaluate the modeling performance, the outcomes were compared with results of multi linear regression (MLR) and Auto Regressive Integrated Moving Average (ARIMA) models. The comparison showed that the proposed data processing approach which serves both denoising and jittering techniques could enhance the performance of ANN and ANFIS based runoff-sediment modeling of the case study up to 34% and 25% in the verification phase, respectively. 相似文献
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Seyed Taleb Hosseini Vahid Chegini Masoud Sadrinasab Seyed Mostafa Siadatmousavi Sadegh Yari 《Ocean Science Journal》2016,51(2):195-208
This study investigated the tidal asymmetry imposed by both the interaction of principal tides and the higher harmonics generated by distortions within a tidal creek network with mixed mainly semidiurnal tide in the Bushehr Port, Persian Gulf. Since velocity and water-level imposed by principal triad tides K1-O1-M2 are in quadrature, duration asymmetries during a tidal period in this short, shallow inverse estuary should be manifest as skewed velocities. The principal tides produce periodic asymmetries including a strong ebb-dominance and a weak flood-dominance condition during spring and neap tides respectively. The higher harmonics induced by nonlinearities engender a flood-dominance condition where the convergence effects are higher than frictional effects, and an ebbdominance condition where intertidal storage are extended. Since the triad K1-O1-M2 driven asymmetry is not overcome by higher harmonics close to the mouth, the periodic asymmetry dominates within the creek in which higher harmonics reinforce the weak flood-dominance (strong ebb-dominance) condition in the convergent channel (divergent area). Also, the maximum flood and the maximum ebb from all harmonic constituents occurred close to high water slack time during both spring and neap tides in this short creek. Since occational wetting of intertidal areas happened close to the high water (HW) time during spring tide, the water level flooded slowly close to the HW time of the spring tide. 相似文献
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Water Resources - In the comprehensive management of watersheds, the knowledge of the sedimentation process in flood conditions is considered as an important and challenging issue. The aim of this... 相似文献
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Vahid Nourani Biswajeet Pradhan Hamid Ghaffari Seyed Saber Sharifi 《Natural Hazards》2014,71(1):523-547
Without a doubt, landslide is one of the most disastrous natural hazards and landslide susceptibility maps (LSMs) in regional scale are the useful guide to future development planning. Therefore, the importance of generating LSMs through different methods is popular in the international literature. The goal of this study was to evaluate the susceptibility of the occurrence of landslides in Zonouz Plain, located in North-West of Iran. For this purpose, a landslide inventory map was constructed using field survey, air photo/satellite image interpretation, and literature search for historical landslide records. Then, seven landslide-conditioning factors such as lithology, slope, aspect, elevation, land cover, distance to stream, and distance to road were utilized for generation LSMs by various models: frequency ratio (FR), logistic regression (LR), artificial neural network (ANN), and genetic programming (GP) methods in geographic information system (GIS). Finally, total four LSMs were obtained by using these four methods. For verification, the results of LSM analyses were confirmed using the landslide inventory map containing 190 active landslide zones. The validation process showed that the prediction accuracy of LSMs, produced by the FR, LR, ANN, and GP, was 87.57, 89.42, 92.37, and 93.27 %, respectively. The obtained results indicated that the use of GP for generating LSMs provides more accurate prediction in comparison with FR, LR, and ANN. Furthermore; GP model is superior to the ANN model because it can present an explicit formulation instead of weights and biases matrices. 相似文献
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Marjan Marbouti Oleg Antropov Jaan Praks Patrick B.Eriksson Vahid Arabzadeh Eero Rinne Matti Lepp?ranta 《地球空间信息科学学报》2021,24(2):313-332
In this study, we assess the potential of X-band Interferometric Synthetic Aperture Radar imagery for automated classification of sea ice over the Baltic Sea. A bistatic SAR scene acquired by the TanDEM-X mission over the Bothnian Bay in March of 2012 was used in the analysis. Backscatter intensity, interferometric coherence magnitude, and interferometric phase have been used as informative features in several classification experiments. Various combinations of classification features were evaluated using Maximum likelihood (ML), Random Forests (RF) and Support Vector Machine (SVM) classifiers to achieve the best possible discrimination between open water and several sea ice types (undeformed ice, ridged ice, moderately deformed ice, brash ice, thick level ice, and new ice). Adding interferometric phase and coherence-magnitude to backscatter-intensity resulted in improved overall classification per- formance compared to using only backscatter-intensity. The RF algorithm appeared to be slightly superior to SVM and ML due to higher overall accuracies, however, at the expense of somewhat longer processing time. The best overall accuracy (OA) for three methodologies were achieved using combination of all tested features were 71.56, 72.93, and 72.91％ for ML, RF and SVM classifiers, respectively. Compared to OAs of 62.28, 66.51, and 63.05％ using only backscatter intensity, this indicates strong benefit of SAR interferometry in discriminating different types of sea ice. In contrast to several earlier studies, we were particularly able to successfully discriminate open water and new ice classes. 相似文献