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Agricultural use of soils implies tillage and often compaction and therefore influences processes on soil surface and affects infiltration of water into the subsoil. Although many studies on soil surface processes or flow patterns in soils exist, works relating both are rare in literature. We did two tracer experiments with Brilliant Blue FCF on a tilled and compacted plot and a non‐tilled one to investigate water storage on the soil surface during simulated rainfall and changes of soil microtopography, to analyse the associated flow patterns in the soil and to relate both to tillage and compaction. Our results show that storage was larger on the tilled and compacted plot than on the non‐tilled one. After tillage, transport processes above the plough pan were partly disconnected from those underneath because macropores were disrupted and buried by the tillage operation. However, preferential flow along cracks occurred on both plots and the macropores buried below the tillage pan still functioned as preferential flow paths. Therefore, we conclude that the studied soil is susceptible to deep vertical solute propagation at dry conditions when cracks are open, irrespective of tillage and compaction. Copyright © 2012 John Wiley & Sons, Ltd. 相似文献
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Solar radiation incident on the earth’s surface is a fundamental input for many aspects of climatology, hydrology, biology, and architecture. In addition, it is an important parameter in solar energy applications. Due to the high cost of the measuring instruments of solar radiation, many researchers have suggested different empirical methods to estimate this essential parameter. In this study, with the help of fuzzy systems and neural networks, two models have been designed to estimate the instantaneous global solar radiation in Rafsanjan city which has a typical climatic conditions of semi-arid region of middle eastern countries. In fuzzy and neural network model, the inputs are the number of the given day in the year, time, ambient temperature and cloudiness, The comparison between the results of the models and the measurements, shows that the estimated global radiation is similar to the measurement; for fuzzy model, statistical indicators RMSE, MBE and t-test are 103.4367 \((\hbox {w/m}^{2})\), 4.1169 \((\hbox {w/m}^{2})\) and 9.1318, respectively and for ANN, they are 85.46 \((\hbox {w/m}^{2})\), 3.08 \((\hbox {w/m}^{2})\) and 5.41, respectively. As the results indicate, both models are able to estimate the amount of radiation well, while the neural network has a higher accuracy. The output of the modes for six other cities of Iran, with similar climate conditions, also proves the ability of the proposed models. 相似文献
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Zamani Reza Akhond-Ali Ali-Mohammad Roozbahani Abbas Fattahi Rouhollah 《Theoretical and Applied Climatology》2017,129(3-4):1109-1121
Water shortage and climate change are the most important issues of sustainable agricultural and water resources development. Given the importance of water availability in crop production, the present study focused on risk assessment of climate change impact on agricultural water requirement in southwest of Iran, under two emission scenarios (A2 and B1) for the future period (2025–2054). A multi-model ensemble framework based on mean observed temperature-precipitation (MOTP) method and a combined probabilistic approach Long Ashton Research Station-Weather Generator (LARS-WG) and change factor (CF) have been used for downscaling to manage the uncertainty of outputs of 14 general circulation models (GCMs). The results showed an increasing temperature in all months and irregular changes of precipitation (either increasing or decreasing) in the future period. In addition, the results of the calculated annual net water requirement for all crops affected by climate change indicated an increase between 4 and 10 %. Furthermore, an increasing process is also expected regarding to the required water demand volume. The most and the least expected increase in the water demand volume is about 13 and 5 % for A2 and B1 scenarios, respectively. Considering the results and the limited water resources in the study area, it is crucial to provide water resources planning in order to reduce the negative effects of climate change. Therefore, the adaptation scenarios with the climate change related to crop pattern and water consumption should be taken into account.
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A method to determine the position and magnetization vector of buried objects producing a magnetic anomaly is described. The data used were collected in boreholes. Since the anomaly is due to a number of objects, a ‘stripping’ procedure is employed for finding them, and therefore the process of inversion for finding all objects causing the anomaly consists of a few inversion steps. In each inversion step, two dipoles are considered as a model which approximates an object. The position and magnetic moments of the dipoles are the unknown parameters. The initial parameters are optimized by minimization of an objective function. The optimization procedure consists of a combination of linear and non-linear inversion. The solution of the linear inversion is obtained by singular value decomposition and that of the non-linear inversion by a six-dimensional simplex method (polytope algorithm). After finding one object, its effect is subtracted (‘stripped’) from the data and a new inversion step is started with new initial models and with a reduced data set. The inversion steps for finding different objects are continued until the absolute norm of the data becomes less than some adjustable value. The data will also be inverted assuming a three-dipole model in order to find the effect of using a more complex model in the inversion. The efficiency of the method is demonstrated using synthetic and real borehole data. 相似文献
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Behnam Ababaei Teymour Sohrabi Farhad Mirzaei 《Theoretical and Applied Climatology》2014,118(1-2):195-202
Most stochastic weather generators have their focus on precipitation because it is the most important variable affecting environmental processes. One of the methods to reproduce the precipitation occurrence time series is to use a Markov process. But, in addition to the simulation of short-term autocorrelations in one station, it is sometimes important to preserve the spatial linear correlations (SLC) between neighboring stations as well. In this research, an extension of one-site Markov models was proposed to preserve the SLC between neighboring stations. Qazvin station was utilized as the reference station and Takestan (TK), Magsal, Nirougah, and Taleghan stations were used as the target stations. The performances of different models were assessed in relation to the simulation of dry and wet spells and short-term dependencies in precipitation time series. The results revealed that in TK station, a Markov model with a first-order spatial model could be selected as the best model, while in the other stations, a model with the order of two or three could be selected. The selected (i.e., best) models were assessed in relation to preserving the SLC between neighboring stations. The results depicted that these models were very capable in preserving the SLC between the reference station and any of the target stations. But, their performances were weaker when the SLC between the other stations were compared. In order to resolve this issue, spatially correlated random numbers were utilized instead of independent random numbers while generating synthetic time series using the Markov models. Although this method slightly reduced the model performances in relation to dry and wet spells and short-term dependencies, the improvements related to the simulation of the SLC between the other stations were substantial. 相似文献
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The effect of the Zagros Mountains on the formation and maintenance of the Iran Anticyclone using RegCM4 总被引：3，自引：0，他引：3
Azar Zarrin Hooshang Ghaemi Majid Azadi Abbas Mofidi Ebrahim Mirzaei 《Meteorology and Atmospheric Physics》2011,112(3-4):91-100
Iran anticyclone is one of the main features of the summer circulation over the Middle East in the middle and upper troposphere. To examine the effect of the Zagros Mountains on the formation and maintenance of the Iran anticyclone, an experiment was conducted by Regional Climate Model (RegCM4) in an area between 22°?C44°N and 35°?C70°E with a 40?km horizontal grid spacing. The NCEP/NCAR re-analysis data set were used to provide the initial and lateral boundary conditions in a control run and in a simulation run by removing the Zagros Mountains. The result reveals that the Zagros Mountains have an important effect on the formation and maintenance of the low-level cyclonic circulation and mid-level anticyclonic circulation in summer. Examining the diabatic heating shows that the elimination of the Zagros Mountains causes a significant change in the heating values and its spatial distributions over the study area. Comparing the diabatic heating terms, the vertical advection term has the main contribution to the total heating. In the absence of the Zagros Mountains, the vertical advection and the mid-troposphere anticyclonic circulation are apparently weak and, therefore, the Iran subtropical anticyclone vanishes over the west of Iran. The study indicates that the Zagros Mountains as an elevated heat source have the main impact in the formation of a thermally driven circulation over the Middle East. 相似文献
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Mixed model for interoccurrence times of earthquakes based on the expectation-maximization algorithm 总被引：1，自引：0，他引：1
In this paper, the goodness-of-fit test based on a convex combination of Akaike and Bayesian information criteria is used
to explain the features of interoccurrence times of earthquakes. By analyzing the seismic catalog of Iran for different tectonic
settings, we have found that the probability distributions of time intervals between successive earthquakes can be described
by the generalized normal distribution. This indicates that the sequence of successive earthquakes is not a Poisson process.
It is found that by decreasing the threshold magnitude, the interoccurrence time distribution changes from the generalized
normal distribution to the gamma distribution in some seismotectonic regions. As a new insight, the probability distribution
of time intervals between earthquakes is described as a mixture distribution via the expectation-maximization algorithm. 相似文献