Toward reliable calibration of aquifer hydrodynamic parameters: characterizing and optimization of arid groundwater system using swarm intelligence optimization algorithm     

S. Sadeghi-Tabas  A. Akbarpour  M. Pourreza-Bilondi  S. Samadi 《Arabian Journal of Geosciences》2016,9(18):719

Despite advanced development in computational techniques, the issue of how to adequately calibrate and minimize misfit between system properties and corresponding measurements remains a challenging task in groundwater modeling. Two important features of the groundwater regime, hydraulic conductivity (k) and specific yield (S _y), that control aquifer dynamic vary spatially within an aquifer system due to geologic heterogeneity. This paper provides the first attempt in using an advanced swarm-intelligence-based optimization algorithm (cuckoo optimization algorithm, COA) coupled with a distributed hydrogeology model (i.e., MODFLOW) to calibrate aquifer hydrodynamic parameters (S _y and k) over an arid groundwater system in east Iran. Our optimization approach was posed in a single-objective manner by the trade-off between sum of absolute error and the adherent swarm optimization approach. The COA optimization algorithm further yielded both hydraulic conductivity and specific yield parameters with high performance and the least error. Estimation of depth to water table revealed skillful prediction for a set of cells located at the middle of the aquifer system whereas showed unskillful prediction at the headwater due to frequent water storage changes at the inflow boundary. Groundwater depth reduced from east toward west and southwest parts of the aquifer because of extensive pumping activities that caused a smoothening influence on the shape of the simulated head curve. The results demonstrated a clear need to optimize arid aquifer parameters and to compute groundwater response across an arid region.  相似文献   

Analyzing long-term spatial variability of blue and green water footprints in a semi-arid mountainous basin with MIROC-ESM model (case study: Kashafrood River Basin,Iran)     

A.?Aghakhani AfsharEmail authorView author&#;s OrcID profile  Y.?Hassanzadeh  M.?Pourreza-Bilondi  A.?Ahmadi 《Theoretical and Applied Climatology》2018,132(3-4):885-903

Atmospheric modeling is considered an important tool with several applications such as prediction of air pollution levels, air quality management, and environmental impact assessment studies. Therefore, evaluation studies must be continuously made, in order to improve the accuracy and the approaches of the air quality models. In the present work, an attempt is made to examine the air pollution model (TAPM) efficiency in simulating the surface meteorology, as well as the SO₂ concentrations in a mountainous complex terrain industrial area. Three configurations under different circumstances, firstly with default datasets, secondly with data assimilation, and thirdly with updated land use, ran in order to investigate the surface meteorology for a 3-year period (2009–2011) and one configuration applied to predict SO₂ concentration levels for the year of 2011.The modeled hourly averaged meteorological and SO₂ concentration values were statistically compared with those from five monitoring stations across the domain to evaluate the model’s performance. Statistical measures showed that the surface temperature and relative humidity are predicted well in all three simulations, with index of agreement (IOA) higher than 0.94 and 0.70 correspondingly, in all monitoring sites, while an overprediction of extreme low temperature values is noted, with mountain altitudes to have an important role. However, the results also showed that the model’s performance is related to the configuration regarding the wind. TAPM default dataset predicted better the wind variables in the center of the simulation than in the boundaries, while improvement in the boundary horizontal winds implied the performance of TAPM with updated land use. TAPM assimilation predicted the wind variables fairly good in the whole domain with IOA higher than 0.83 for the wind speed and higher than 0.85 for the horizontal wind components. Finally, the SO₂ concentrations were assessed by the model with IOA varied from 0.37 to 0.57, mostly dependent on the grid/monitoring station of the simulated domain. The present study can be used, with relevant adaptations, as a user guideline for future conducting simulations in mountainous complex terrain.  相似文献   

Climate change forecasting in a mountainous data scarce watershed using CMIP5 models under representative concentration pathways     

Aghakhani Afshar  A.  Hasanzadeh  Y.  Besalatpour  A. A.  Pourreza-Bilondi  M. 《Theoretical and Applied Climatology》2017,129(1-2):683-699

Hydrology cycle of river basins and available water resources in arid and semi-arid regions are highly affected by climate changes. In recent years, the increment of temperature due to excessive increased emission of greenhouse gases has led to an abnormality in the climate system of the earth. The main objective of this study is to survey the future climate changes in one of the biggest mountainous watersheds in northeast of Iran (i.e., Kashafrood). In this research, by considering the precipitation and temperature as two important climatic parameters in watersheds, 14 models evolved in the general circulation models (GCMs) of the newest generation in the Coupled Model Intercomparison Project Phase 5 (CMIP5) were used to forecast the future climate changes in the study area. For the historical period of 1992–2005, four evaluation criteria including Nash–Sutcliffe (NS), percent of bias (PBIAS), coefficient of determination (R ²) and the ratio of the root-mean-square-error to the standard deviation of measured data (RSR) were used to compare the simulated observed data for assessing goodness-of-fit of the models. In the primary results, four climate models namely GFDL-ESM2G, IPSL-CM5A-MR, MIROC-ESM, and NorESM1-M were selected among the abovementioned 14 models due to their more prediction accuracies to the investigated evaluation criteria. Thereafter, climate changes of the future periods (near-century, 2006–2037; mid-century, 2037–2070; and late-century, 2070–2100) were investigated and compared by four representative concentration pathways (RCPs) of new emission scenarios of RCP2.6, RCP4.5, RCP6.0, and RCP8.5. In order to assess the trend of annual and seasonal changes of climatic components, Mann–Kendall non-parametric test (MK) was also employed. The results of Mann–Kendall test revealed that the precipitation has significant variable trends of both positive and negative alterations. Furthermore, the mean, maximum, and minimum temperature values had significant positive trends at 90, 99, and 99.9 % confidence level. On the other hand, in all parts of the Kashafrood Watershed (KW), the average temperature of watershed will be increased up to 0.56–3.3 °C and the mean precipitation will be decreased up to 10.7 % by the end of the twenty-first century comparing to the historical baselines. Also, in seasonal scale, the maximum and minimum precipitations will occur in spring and summer, respectively, and the mean temperature is higher than the historical baseline in all seasons. The maximum and minimum values of the mean temperature will occur in summer and winter, respectively, and the amount of seasonal precipitation in these seasons will be reduced.

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Quantifying the uncertainty of semiarid flash floods using generalized likelihood uncertainty estimation   总被引：1，自引：0，他引：1  

Mohsen Pourreza-Bilondi  S. Zahra Samadi 《Arabian Journal of Geosciences》2016,9(13):622

This paper aims to address the question of how the parameter uncertainty associated with a mixed conceptual and physical based rainfall-runoff model (AFFDEF) has influences on flood simulation of the semiarid Abolabbas catchment (284 km²), in Iran. AFFDEF was modified and coupled with the generalized likelihood uncertainty estimation (GLUE) algorithm to simulate four flash flood events. Analysis suggests that AFFDEF parameters showed non-unique posterior distributions depending on the magnitudes and duration of flash flood events. Model predictive uncertainty was heavily dominated by error and bias in soil antecedent moisture condition that led to large storage effect in simulation. Overall, multiplying parameter for the infiltration reservoir capacity and multiplying parameter for the interception reservoir capacity along with potential runoff contributing areas were identified the key model parameters and more influential on flood simulation. Results further revealed that uncertainty was satisfactorily quantified for the event with low to moderate flood magnitudes while high magnitude event exhibited unsatisfactory result.  相似文献