In this study, a new method was proposed to model the occurrence of related variables based on the conditional density of copula functions. The proposed method was adopted to investigate the dynamics ...of meteorological and hydrological droughts in the Zarinehroud basin, southeast of Lake Urmia, during the period 1994–2015. For this purpose, the modified precipitation anomaly percentage and streamflow drought indices were extracted. Finally, the joint frequency analysis of duration-duration and severity-severity characteristics of meteorological and hydrological droughts was analyzed. Analysis of 7 different copulas used to create the joint distribution in the Zarinehroud basin indicated that the Frank copula had the best performance in describing the relationship between the meteorological and hydrological drought severities and durations. By examining the results of the bivariate analysis of duration-duration of meteorological and hydrological droughts at different stations, the expected meteorological and hydrological drought durations were estimated in the years ahead. For example, at Chalkhmaz station, 4- to 7-month duration for the hydrological drought and 9- to 12-month duration for the meteorological drought is expected in the years ahead. The joint frequency analysis of drought characteristics allows to determine the meteorological and hydrological drought characteristics at a single station at the same time using joint probabilities. Also, the results indicated that by knowing the conditional density, the hydrological drought characteristics can be easily estimated for the given meteorological drought characteristics. This could provide users and researchers useful information about the probabilistic behavior of drought characteristics for optimal operation of surface water.
An optimal pumping policy ensures the sustainability of groundwater resources when groundwater is extracted. In this paper, several simulation models (genetic algorithms, particle swarm optimization ...and firefly algorithm) are used to evaluate optimal pumping policy in an hypothetical aquifer. In this study, the level of groundwater in an unconfined hypothetical aquifer with a surface area of 1.5 km
2
and three different hydraulic conductivities with a thickness of 100 m, as well as four pumping wells were investigated. The finite element method was employed to estimate the groundwater level of the aquifer and the mentioned algorithms were used to optimize the position of the pumping wells. The position of the pumping wells with a specific discharge is optimized to minimize groundwater drawdown in the aquifer. The results indicated that with increasing number of iterations, there was little improvement in the results of the FA, and after five iterations, the algorithm entrapped in local optima. By investigating the values of the objective function of two other algorithms (PSO and GA), the results indicated that the GA has a better performance than the PSO in optimizing groundwater pumping well locations. As a result, the GA reduces the value of objective function by 31% compared to the PSO algorithm. With this value of objective function, the maximum drawdown groundwater was about 2.5 m in the southwest of aquifer. The results indicated that the optimum location of wells is on the western side of the aquifer where the aquifer boundary has a constant head on this side.
Investigation of precipitation characteristics on daily, monthly, and annual time scales can contribute to gaining important information related to temporal and spatial distribution of precipitation ...or even flow rate challenges (e.g., hydrological droughts). The low levels of long-term precipitation and high variability in different time scales are considered the main inherent characteristics of climate in Iran. Due to the direct effects of precipitation on water resources, especially on the river flow rate, it is necessary to assess the efficient indices to visualize the variations in the components of water resources. One of the main indices is the precipitation concentration index (PCI) which is known as a strong indicator of the precipitation distribution generally used on annual and seasonal scales. In this study, drought analysis in the Lake Urmia Basin (LUB) located in northwest of Iran was performed with the daily river flow rate and monthly precipitation values within the period of 1984–2013. The results of changes in precipitation indicated that the irregularity of precipitation distribution had grown in spring months. Also, due to the diminishing precipitation trend on the annual time scale, PCI index also increased. It is concluded that LUB detected a significant descending trend on the annual, spring, and winter time scales in the last 30 years. The PCI values were proved high irregularity in summer with PCI amount of 20.1 and most regularity in winter with PCI amount of 10.4. This paper also aims to assess the effects of PCI on the river flow rate along with the flow shortness volume values using hydrometric and rain gauge stations within LUB. The results obtained from the changes in river flow rate and flow shortness volume revealed that the river flow rate has mostly a falling trend. Finally, it was observed that the time when the river flow rate data changed happened after beginning of changes in the precipitation data. A decrease in inflow from 900 million cubic meters up to 14 billion cubic meters with high flow shortness volume may happen in worst conditions. These results highlighted the importance of applying water resources management in LUB.
AbstractIn this study, the frequency analysis of river flow deficiency (FD) of the Siminehrood River in the south of Lake Urmia located in northwest Iran was investigated with regard to rainfall ...deficiency (RD) during the period of 1992–2013 using copula functions. The main purpose of this study is to provide a comprehensive method for bivariate simulation and forecasting based on marginal distribution and joint behavior of the studied series. For this purpose, the FD and RD values were extracted using the deficiency value method. By preparing deficiency values, 57 different distribution functions were fitted to the studied values, and the generalized extreme value (GEV) distribution was selected as the best marginal distribution function based on the evaluation criteria. Before fitting the copula function, the correlation between the RD and FD values was examined using Kendall’s tau, and a correlation of 70% was obtained. After selecting the marginal distribution function and examining the correlation, the goodness of fit of seven different copula functions was examined for frequency analysis of RD and FD values in the Siminehrood River at the Dashband station. The results indicated that the Clayton copula had the best performance for creating a joint distribution of RD and FD values. It was also determined from the joint analysis of deficiency values that the FD values can be estimated with high accuracy for RD values of more than 0.68 mm. Also, the results indicated that if rainfall in the study area were less than long-term mean for 10-day and 60-day durations, with different return periods and probabilities, different conditions will occur for FD values, which can be used as typical curves for water resources management and allocation in the basin. Finally, the accuracy of the copula-based model and its conditional density in the two phases of simulation and forecasting were investigated. The accuracy of the copula-based model and its conditional density in the simulation phase was confirmed R2=0.87, root mean square error (RMSE)=0.1 m3/s, and nash-sutcliffe efficiency (NSE)=0.86. In the forecasting phase, the forecasting equation based on the proposed method had a RMSE of 0.14 m3/s and NSE of 0.89. By using the violin plot, the model certainty was also confirmed. According to the proposed equation, FD values can be forecasted affected by RD values for 10-day duration with high certainty and accuracy.
Practical ApplicationsIn this paper, a method for forecasting and simulation of meteorological and hydrological parameters is presented that considers two parameters simultaneously. This study discusses meteorology and hydrology from a different perspective. Given the current climate change, this study uses deficiency values. The proposed forecasting method provides regional results that can be used in the water resources management in each basin specifically. By implementing this method, it is easy to forecast the desired values in the basin with different probabilities and return periods. In this study, river flow deficiency (FD) affected by rainfall deficiency (RD) can be forecasted. The difference between the proposed method and other methods and models of simulation and forecasting is in the connection of two variables with each other, which makes the results more certain and reliable. This method can be used in the field of basin management and water resources allocation and also water resources monitoring.
In this study, temperature changes and its concentration distribution in the period of 1984–2015 and 2015–2100 were investigated under CanESM5 climate model and SSP126, SSP245 and SSP585 scenarios. ...By confirming the correlation (more than 0.96) and the efficiency coefficient of the model (more than 0.82), the trend of temperature values using modified Mann-Kendall test and temperature concentration index (TCI) values in the sub-basins of Zayanderood Dam, Iran was estimated. The results indicated a non-significant upward trend in the base period (1984–2015) and a significant increasing trend at the level of 5% in the future period (2015–2100) produced by the mentioned scenarios. According to the slope of the trend line, an increase of 1.45, 4 and 9.8 degrees Celsius is predicted during the period of 2015–2100 according to the SSP126, SSP245 and SSP585 scenarios, respectively. The evaluation of changes in TCI values in the studied area showed that in the future period, the distribution of rainfall patterns will be regular and the uniformity of temperature distribution in the SSP585 scenario is more than in the other two scenarios. The results of the temperature pattern distribution in the study area showed that according to the upcoming climate changes and under the studied scenarios, it is expected that while the study area is warming in the future, the uniformity of the temperature distribution will also appear in the months of the year. This shows the reduction of temperature fluctuations and the uniformity of the average temperature in the months of the year. The reduction of TCI values shows the equalization of average temperature changes in the seasons. The results of the investigations showed that the combination of climate change scenarios with the TCI can well show the concentration and distribution of the temperature in different periods.
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•Examining the different scenarios of the 6th IPCC such as SSP126, SSP245 and SSP585 based on temperature concentration index.•Investigate the temperature distribution pattern in the study area, considering climate changes.•Evaluation the trend of temperature and its concentration in the base period (1984–2015) and the future period (2015-2100).
ABSTRACT
The long‐term trends in temperature over Iran were examined over 34 synoptic stations during a 50 year period (1961–2010) on seasonal and annual time scales. Two methods, a modified version ...of the Mann–Kendall test by eliminating the effect of all significant autocorrelation co‐efficients and the regional Kendall test, were used in trend identification. The results revealed that the temperature had experienced significant positive trends in autumn, spring and especially summer over the study area. On an annual time scale and in the winter, the highest increasing trends were observed at stations located in the southern and southeastern parts of Iran. For regional analysis of trends, the stations were divided into five clusters based on the K‐means clustering method and the silhouette index. Subsequently, the regional trend of temperature was analysed on seasonal and annual time scales using the regional Kendall test. The results of the regional Kendall test also indicated the rising trends in temperature during the last 50 years throughout the country on both seasonal and annual time scales. After verifying the presence of an increasing trend in the temperature time series, the non‐parametric Pettitt test was used to detect the change points in the annual and seasonal time scales. The results showed that the change point of average temperature began from the summer of 1972 (Sabzevar station) and continued until the summer of 1998 (Zahedan station). The most frequent change point occurrence was between the years 1986 and 1994.
The results of the regional Kendall test indicated rising trends in temperature during the last 50 years (1961–2010) throughout Iran on both seasonal and annual time scales.
Due to the increasing frequency of extreme rainfalls in recent years, it is necessary to use more precise models in simulating extreme rainfall. In recent years, machine learning models have been ...widely used for this purpose. The accuracy of machine learning models can be improved by increasing the dimension. This study aims to introduce the wavelet-copula approach, and investigate the effect of signal decomposition on the accuracy of daily river flow prediction in the Qale Shahrokh, a sub-basin in the Zayanderood dam basin, Iran, during 1994–2019. For this purpose, the wavelet theory and Daubechies 4 wavelet at two levels, 1 and 2, were used considering three different input patterns. Long short-term memory (LSTM), Gaussian Process Regression (GPR), Random Forest (RF), copula-based model, and Kstar models were also used in simple and hybrid wavelet modes with 45 different patterns as input of models. The results indicated that the increase in dimension and the use of signal decomposition in the predictions caused an increase in the error of the Kstar model. In other investigated models, the decomposition of the main input signals has reduced the error and improved the model's efficiency. The LSTM and copula models with P3L2 input pattern had the lowest RMSE values of 16.06 and 18.17 (m
3
/s), respectively. The P3L2 pattern includes the input model 3 (rainfall values of 4 stations and river flow values of 2 stations) and level 2 wavelet decomposition. However, the LSTM model provided more out-of-domain points than the copula model. Although the error rate of the LSTM model was lower than the copula-based model in the P3L2 pattern, the LSTM model overestimated the maximum river flow rate by about 30%. For this reason, the copula-based model and the P3L2 pattern were recommended as the best model and pattern for predicting the daily river flow in the Qale Shahrokh sub-basin.
In this study, the trend of southwestern Asia’s rainfall (4152 stations) was investigated in two annual and monthly scales during the statistical period of 1970–2014 using non-parametric Mann–Kendall ...test with complete removal of the self-correlation structure. The results of the study of annual rainfall’s trend in South West Asia indicated that of the studied countries, the trend of rainfall in two countries, namely Iraq and Iran, was more critical than other countries and showed an approximate drop of 1.2 and 1.03 mm, respectively, in total annual rainfall year on year. All the regions of these two countries were studied and showed a declining trend of rainfall on an annual scale, and due to the rainfall shortage, these countries can be considered to be facing crisis. The results of annual and seasonal rainfall distribution in the studied area showed that, apart from winter, all of the studied scales during the period of 2005–2014 have shown a regular distribution of rainfall from 1970 to 1997, which is due to the declining trend in monthly rainfall and changes that reduce the monthly rainfall as a result of the regular distribution of rainfall between seasons and years. Moreover, the results indicated that in winter, rainfall distribution in Iran and its eastern neighbors were more irregular during the statistical period of the study, which could be the result of a rainfall disorder affecting these countries in the past decade. The irregular distribution of rainfall causes rainfall to be unevenly distributed across the seasons, which will then cause extreme rainfall.
In this study, two efficient approaches for bivariate simulation are presented, which include meteorological and hydrological variables. For this purpose, the applicability of support vector ...regression (SVR) model optimized by Ant colony and Copula-GARCH (Generalized Autoregressive Conditional Heteroscedasticity) algorithms were investigated and compared in simulating the river discharge based on total monthly rainfall in Talezang Basin, Iran. Entropy theory was used to select a suitable meteorological station corresponding to a hydrometric station. The vector autoregressive model was also used as the base model in Copula-GARCH simulations. According to the 99% confidence intervals of the simulations, the accuracy of both models was confirmed. The simulation results showed that the Copula-GARCH model was more accurate than the optimized SVR (OSVR) model. Considering the 90% efficiency (NSE=0.90) of the Copula-GARCH approach, the results show a 36% improvement of RMSE statistics by the Copula-GARCH model compared to the OSVR model in simulating the river discharge on a monthly scale. The results also showed that by combining nonlinear ARCH models with the copula-based simulations, the reliability of the simulation results increases, which was also confirmed using the violin plot. The results also showed an increase in the accuracy of the Copula-GARCH model at the minimum and maximum values of the data.
Temperature and precipitation are the basic elements of climate, and their variation can change the water demands of different uses. In this study, the trend of temperature and precipitation of ...Iran’s largest agricultural products hub (i.e., Khuzestan Province) was examined in monthly, seasonal, and annual timescales in the period 1988–2018 (30 years) in six synoptic stations. The effect of long-term persistence was eliminated, considering the effect of the Hurst coefficient using the fourth version of the Mann–Kendall nonparametric test. The time of occurring sudden change in the time series and concentration of precipitation and the temperature of the study area were also analyzed using the Pettitt test, precipitation concentration index (PCI), and temperature concentration index (TCI), respectively. The results showed that there is a direct relationship between increasing temperature and decreasing precipitation in the study area. The annual temperature has experienced a significant increasing trend, while the annual precipitation has decreased significantly in all stations. Due to the significant trend in the studied series, the Pettitt test detected a total of 94 significant failure points (year of failure) and it was found that sudden changes in air temperature time series began in November 1993 at Ramhormoz station and continued to January 2009. The results of investigating the temperature and precipitation trends in the two sub-periods (1988–2000 and 2001–2018) showed that most of the significant increasing trends in temperature time series were experienced in the first period and most of the significant decreasing trends in precipitation time series were experienced in the second period. In addition to the trend and sudden changes in precipitation and temperature series of the study area, PCI and TCI showed that the climate of the study area is changing and the tendency to climatic irregularities is increasing. Therefore, the trend evaluation of temperature and precipitation at different time and space scales has great importance in planning and managing water resources.
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