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1.
We assess the effects of prospective climate change until 2100 on water management of two major reservoirs of Iran, namely, Dez (3.34 × 109 m3) and Alavian (6 × 107 m3). We tune the Poly‐Hydro model suited for simulation of hydrological cycle in high altitude snow‐fed catchments. We assess optimal operation rules (ORs) for the reservoirs using three algorithms under dynamic and static operation and linear and non‐linear decision rules during control run (1990–2010 for Dez and 2000–2010 for Alavian). We use projected climate scenarios (plus statistical downscaling) from three general circulation models, EC‐Earth, CCSM4, and ECHAM6, and three emission scenarios, or representative concentration pathways (RCPs), RCP2.6, RCP4.5, and RCP8.5, for a grand total of nine scenarios, to mimic evolution of the hydrological cycle under future climate until 2100. We subsequently test the ORs under the future hydrological scenarios (at half century and end of century) and the need for reoptimization. Poly‐Hydro model when benchmarked against historical data well mimics the hydrological budget of both catchments, including the main processes of evapotranspiration and streamflows. Teaching–learning‐based optimization delivers the best performance in both reservoirs according to objective scores and is used for future operation. Our projections in Dez catchment depict decreased precipitation along the XXI century, with ?1% on average (of the nine scenarios) at half century and ?6% at the end of century, with changes in streamflows on average ?7% yearly and ?13% yearly, respectively. In Alavian, precipitation would decrease by ?10% on average at half century and ?13% at the end of century, with streamflows ?14% yearly and ?18% yearly, respectively. Under the projected future hydrology, reservoirs' operation would provide lower performance (i.e., larger lack of water) than now, especially for Alavian dam. Our results provide evidence of potentially decreasing water availability and less effective water management in water stressed areas like Northern Iran here during this century.  相似文献   
2.
Although the Volterra models are non-parsimonious ones, they are being used because they can mimic dynamics of complex systems. However, applying and identification of the Volterra models using data may result in overfitting problem and uncertainty. In this investigation we evaluate capability of different wavelet forms for decomposing and compressing the Volterra kernels in order to overcome this problem by reducing the number of the model coefficients to be estimated and generating smooth kernels. A simulation study on a rainfall?runoff process over the Cache River watershed showed that the method performance is successful due to multi-resolution capacity of the wavelet analysis and high capability of the Volterra model. The results also revealed that db2 and sym2 wavelets have the same high potential in improving the linear Volterra model performance. However, QS wavelet was more successful in yielding smooth kernels. Moreover, the probability of overfitting while identifying the nonlinear Volterra model may be less than the linear model.  相似文献   
3.
Frequency analysis of climate extreme events in Zanjan, Iran   总被引:2,自引:1,他引:1  
In this study, generalized extreme value distribution (GEV) and generalized Pareto distribution (GPD) were fitted to the maximum and minimum temperature, maximum wind speed, and maximum precipitation series of Zanjan. Maximum (minimum) daily and absolute annual observations of Zanjan station from 1961 to 2011 were used. The parameters of the distributions were estimated using the maximum likelihood estimation method. Quantiles corresponding to 2, 5, 10, 25, 50, and 100 years return periods were calculated. It was found that both candidate distributions fitted to extreme events series, were statistically reasonable. Most of the observations from 1961 to 2011 were found to fall within 1–10 years return period. Low extremal index (θ) values were found for excess maximum and minimum temperatures over a high threshold, indicating the occurrence of consecutively high peaks. For the purpose of filtering the dependent observations to obtain a set of approximately independent threshold excesses, a declustering method was performed, which separated the excesses into clusters, then the de-clustered peaks were fitted to the GPD. In both models, values of the shape parameters of extreme precipitation and extreme wind speed were close to zero. The shape parameter was less negative in the GPD than the GEV. This leads to significantly lower return period estimates for high extremes with the GPD model.  相似文献   
4.
Data reduction methods such as principal components analysis and factor analysis can be used to define drought prone areas of a basin. In this study, factor analysis method applied for the purpose of projecting the information space on the few dominant axes. The main aim of this study is regionalization of Lake Urmia Basin from the view of drought using factor analysis. For this purpose, monthly precipitation data of 30 weather stations in the period 1972–2009 were used. For each of the selected stations, 3- and 12-month Standardized Precipitation Index (SPI) values were calculated. Factor analysis conducted on SPI values to delineate the study area with respect to drought characteristics. Homogeneity of obtained regions tested using the S statistics proposed by Wiltshire. Results of factor analysis of 3- and 12-month SPI values showed that 5 (6) factors having eigenvalues >1 accounted for 68.08 (78.88) % of total variance. The Lake Urmia Basin was delineated into the five distinct homogeneous regions using the 3-month SPI time series. This was six in the case of the 12-month SPI time series. It can be concluded that there are different distinct regions in Lake Urmia Basin according to drought characteristics. The map of regions defined using the 3- and 6-month SPI time series presented in this paper for Lake Urmia Basin.  相似文献   
5.
This study evaluates the performances of two distinct linear and non-linear models for simulating non-linear rainfall–runoff processes and their applications to flood forecasting in the Navrood River basin, Iran. Due to the excellent capacity of the artificial neural networks [multilayer perceptron (MLP)] and Volterra model, these models were used to approximate arbitrary non-linear rainfall–runoff processes. The MLP model was trained using two different training algorithms. The Volterra model was applied as a linear model [the first-order Volterra (FOV) model] and solved using the traditional ordinary least-square (OLS) method. Storm events within the Navrood River basin were used to verify the suitability of the two models. The models’ performances were evaluated and compared using five performance criteria namely coefficient of efficiency, root mean square error, error of total volume, relative error of peak discharge, and error of time for peak to arrive. Results indicated that the non-linear MLP models outperform the linear FOV model. The latter was ineffective because of the non-linearity of the rainfall–runoff process. Moreover, the OLS method is inefficient when the FOV model has many parameters that must be estimated.  相似文献   
6.
Modeling flood event characteristics using D-vine structures   总被引:1,自引:0,他引:1  
The authors investigate the use of drawable (D-)vine structures to model the dependences existing among the main characteristics of a flood event, i.e., flood volume, flood peak, duration, and peak time. Firstly, different three- and four-dimensional probability distributions were built considering all the permutations of the conditioning variables. The Frank copula was used to model the dependence of each pair of variables. Then, the appropriate D-vine structures were selected using information criteria and a goodness-of-fit test. The influence of varying the data length on the selected D-vine structure was also investigated. Finally, flood event characteristics were simulated using the four-dimensional D-vine structure.  相似文献   
7.
In the present study, the trends in the reference evapotranspiration (ETO) estimated through the Penman‐Monteith method were investigated over the humid region of northeast (NE) India by using the Mann‐Kendall (MK) test after removing the effect of significant lag‐1 serial correlation from the time series of ETO by pre‐whitening. During the last 22 years, ETO has been found to decrease significantly at annual and seasonal time scales for 6 sites in NE India and NE India as a whole. The seasonal decreases in ETO have, however, been more significant in the pre‐monsoon season, indicating the presence of an element of a seasonal cycle. The decreases in ETO are mainly attributed to the net radiation and wind speed, which are also corroborated by the observed trends in these two parameters at almost all the times scales over most of the sites in NE India. The steady decrease in wind speed and decline in net radiation not only balanced the impact of the temperature increases on ETO, but may have actually caused the decreases in ETO over the humid region of northeast India. Copyright © 2011 John Wiley & Sons, Ltd.  相似文献   
8.
Bivariate drought frequency analysis using the copula method   总被引:7,自引:2,他引:5  
Droughts are major natural hazards with significant environmental and economic impacts. In this study, two-dimensional copulas were applied to the analysis of the meteorological drought characteristics of the Sharafkhaneh gauge station, located in the northwest of Iran. Two major drought characteristics, duration and severity, as defined by the standardized precipitation index, were abstracted from observed drought events. Since drought duration and severity exhibited a significant correlation and since they were modeled using different distributions, copulas were used to construct the joint distribution function of the drought characteristics. The parameter of copulas was estimated using the method of the Inference Function for Margins. Several copulas were tested in order to determine the best data fit. According to the error analysis and the tail dependence coefficient, the Galambos copula provided the best fit for the observed drought data. Some bivariate probabilistic properties of droughts, based on the derived copula-based joint distribution, were also investigated. These probabilistic properties can provide useful information for water resource planning and management.  相似文献   
9.
In the present study, the trends in groundwater level and fifteen hydro-geochemical elements at 32 piezometric stations located in the Ardabil plain of the northwest of Iran were analyzed using the non-parametric Mann–Kendall method after removing the effect of significant lag-1 serial correlation from the respective time series by pre-whitening. The magnitudes of trends were computed using the Sen’s estimator method. The homogeneity of trend was tested using the method proposed by van Belle and Hughes as well. Results showed that significant (α < 0.1) negative trends in groundwater level were witnessed for all but five stations of the Ardabil plains during the last 22 years from 1988 to 2009. The groundwater levels over Ardabil plain have declined at the rate of about 18 cm/year, with the strongest decline (1.93 m/year) witnessed at Khalife-loo-sheikh station. The results of homogeneity of trends showed that trends were homogeneous for months but not for stations. Strong positive trends were detected in the groundwater quality concentration across the whole plain. Decline in groundwater level and increase in geochemical elements in the groundwater were attributed to the human activities in the Ardabil plain located in the northwest of Iran.  相似文献   
10.
Reliable estimation of missing data is an important task for meteorologists, hydrologists and environment protection workers all over the world. In recent years, artificial intelligence techniques have gained enormous interest of many researchers in estimating of missing values. In the current study, we evaluated 11 artificial intelligence and classical techniques to determine the most suitable model for estimating of climatological data in three different climate conditions of Iran. In this case, 5 years (2001–2005) of observed data at target and neighborhood stations were used to estimate missing data of monthly minimum temperature, maximum temperature, mean air temperature, relative humidity, wind speed and precipitation variables. The comparison includes both visual and parametric approaches using such statistic as mean absolute errors, coefficient of efficiency and skill score. In general, it was found that although the artificial intelligence techniques are more complex and time-consuming models in identifying their best structures for optimum estimation, but they outperform the classical methods in estimating missing data in three distinct climate conditions. Moreover, the in-filling done by artificial neural network rivals that by genetic programming and sometimes becomes more satisfactory, especially for precipitation data. The results also indicated that multiple regression analysis method is the suitable method among the classical methods. The results of this research proved the high importance of choosing the best and most precise method in estimating different climatological data in Iran and other arid and semi-arid regions.  相似文献   
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