Two solution methods for dynamic game in reservoir operation

During the last decade, a number of models have been developed to consider the conflict in dynamic reservoir operation. Most of these models are discrete dynamic models which are developed based on game theory. In this study, a continuous model of dynamic game and its corresponding solutions are developed for reservoir operation. Two solution methods are used to solve the model of continuous dynamic game, namely the Ricatti equations and collocation methods. The Ricatti equations method is a closed form solution, requiring less computational efforts compared with discrete models. The collocation solution method applies Newton's method or a quasi-Newton method to find the problem solution. These approaches are able to generate operating policies for dynamic reservoir operation. The Zayandeh-Rud river basin in central Iran is used as a case study and the results are compared with alternative water allocation models. The results show that the proposed solution methods are quite capable of providing appropriate reservoir operating policies, while requiring rather short computational times due to continuous formulation of state and decision variables. Reliability indices are used to compare the overall performance of the proposed models. Based on the results from this study, the collocation method leads to improved values of the reliability indices for total reservoir system and utility satisfaction of water users, compared to the Ricatti equations method. This is attributed to the flexible structure of the collocation model. When compared to alternative water allocation models, lower values of reliability indices are achieved by the collocation method.     

The behaviour of trace and rare earth elements (REE) during hydrothermal alteration in the Rangan area (Central Iran)

The rhyolitic dome in the Rangan area has been subjected to hydrothermal alterations by two different systems, (1) A fossil magmatic–hydrothermal system with a powerful thermal engine of a deep monzodioritic magma, (2) An active hydrothermal system dominated by meteoric water. Based on mineralogical and geochemical studies, three different alteration facies have been identified (phyllic, advanced argillic and silicic) with notable differences in REE and other trace elements behaviour. In the phyllic alteration zone with assemblage minerals such as sericite, pyrite, quartz, kaolinite, LREE are relatively depleted whereas HREE are enriched. The advanced argillic zone is identified by the presence of alunite–jarosite and pyrophyllite as well as immobility of LREE and depletion in HREE. In the silicic zone, most of LREE are depleted but HREE patterns are unchanged compared to their fresh rock equivalents. All the REE fractionation ratios (La/Yb)_cn, (La/Sm)_cn, (Tb/Yb)_cn, (Ce/Ce¹)_cn and (Eu/Eu¹)_cn are low in the phyllic altered facies. (Eu/Eu¹)_cn in both advanced and silicic facies is low too. In all alteration zones, high field strength elements (HFSE) (e.g. Ti, Zr, Nb) are depleted whereas transition elements (e.g. V, Cr, Co, Ni, Fe) are enriched. Geochemically speaking, trace and rare earth elements behave highly selective in different facies.     

Analyzing spatiotemporal land use/cover dynamic using remote sensing imagery and GIS techniques case: Kan basin of Iran

Land use/land cover (LU/LC) that are significant elements for the interconnection of human activities and environment monitoring can be useful to find out the deviations of saving a maintainable environment. Remote sensing is a very useful tool for the affair of land use or land cover monitoring, which can be helpful to decide the allocation of land use and land cover. Supervised classification-maximum likelihood algorithm in GIS was applied in this study to detect land use/land cover changes observed in Kan basin using multispectral satellite data obtained from Landsat 5 (TM) and 8 (OLI) for the years 2000 and 2016, respectively. The main aim of this study was to gain a quantitative understanding of land use and land cover changes in Kan basin of Tehran over the period 2000–2016. For this purpose, firstly supervised classification technique was applied to Landsat images acquired in 2000 and 2016. The Kan basin was classified into five major LU/LC classes including: Built up areas, garden, pasture, water and bare-land. Change detection analysis was performed to compare the quantities of land cover class conversions between time intervals. The results revealed both increase and decrease of the different LU/LC classes from 2000 to 2016. The results indicate that during the study period, built-up land, and pastures have increased by 0.2% (76.4 km²) and 0.3% (86.03 km²) while water, garden and bare land have decreased by 0, 0.01% (3.62 km²) and 0.4% (117.168 km²), respectively. Information obtained from change detection of LU/LC can aid in providing optimal solutions for the selection, planning, implementation and monitoring of development schemes to meet the increasing demands of human needs in land management.     

Flow discharge simulation based on land use change predictions

Haraz River is one of the most important rivers in Iran, which has been faced with successive inappropriate land use changes and environmental degradation practices in recent decades. In this way, the impact of land use changes on stream flow generation, evaporation and hydrological processes of the Haraz basin has been studied. Land use maps for the years of 1988, 2000 and 2013 were prepared and assessed for any changes in land use using land change modeler and logistic regression methods. GEOMOD method was also used for accuracy tests of models. The calibration periods of 1988–2000, 1988–2013 and also Markov chain with hard prediction model were applied in order to predict the future land use for 2025. Besides, SWAT model was used to evaluate the watershed-scale impacts of land use change. Evaluating the calibration periods using GEOMOD method and some parameters showed a more accurate prediction for the period of 1988–2013 than the 1988–2000 period. Likewise, the results indicated that the rate of changes from 2013 to 2025 will be decreased in terms of forest and range lands (6751.05 and 168,09.01 ha, respectively) and will be increased in terms of residential areas, irrigated farming, gardens and bare lands up to 1567.2, 1405.68, 3039.38 and 174,05.55 ha, respectively. The assessment of model efficiency showed that the SWAT model has acceptable performance to simulate the flow discharge. Overall, the model outcomes indicated that land use changes lead to increase the average runoff in the study area. As a matter of fact, this issue has significant effects on water resources, economic and social situations, and hence, efficient strategies are needed for an integrated management in the Haraz basin.     

Bedload transport of small rivers in Malaysia

Numerous time-consuming equations, based on the relationship between the reliability and representativeness of the data utilized in defining variables and constants, require complex parameters to estimate bedload transport. In this study the easily accessible data including flow discharge, water depth, water surface slope, and surface grain diameter （ds0） from small rivers in Malaysia were used to estimate bedload transport. Genetic programming （GP） and artificial neural network （ANN） models are applied as complementary tools to estimate bed load transport based on a balance between simplicity and accuracy in small rivers. The developed models demonstrate higher performance with an overall accuracy of 97% and 93% for ANN and GP, respectively compared with other traditional methods and empirical equations.     

Spatial changes of Extended De Martonne climatic zones affected by climate change in Iran

In order to better understand the effect associated with global climate change on Iran’s climate condition, it is important to quantify possible shifts in different climatic types in the future. To this end, monthly mean minimum and maximum temperature, and precipitation from 181 synoptic meteorological stations (average 1970–2005) have been collected from the meteorological organization of Iran. In this paper, to study spatial changes of Iran’s climatic zones affected by climate changes, Extended De Martonne’s classification (originally formulated by De Martonne and extended by Khalili (1992)) was used. Climate change scenarios were simulated in two future climates (average conditions during the 2050s and the 2080s) under each of the SRES A1B and A2, for the CSIRO-MK3, HadCM3, and CGCM3 climate models. Coarse outputs of GCMs were downscaled by delta method. We produced all maps for three time periods (one for the current and two for the future) according to Extended De Martonne’s classification. Finally, for each climatic zone, changes between the current and the future were compared. As the main result, simulated changes indicate shifts to warmer and drier zones. For example, in the current, extra arid-cold (A1.1m2) climate is covering the largest area of the country (21.4 %), whereas in both A1B and A2 scenarios in the 2050s and the 2080s, extra arid-moderate (A1.1m3) and extra arid-warm (A1.1m4) will be the climate and will occupy the largest area of the country, about 21 and 38 %, respectively. This analysis suggests that the global climate change will have a profound effect on the future distribution of severe aridity in Iran.     

Investigation of spatial and temporal variability of precipitation in Iran over the last half century

Investigation of the precipitation phenomenon as one of the most important meteorological factors directly affecting access to water resources is of paramount importance. In this study, the precipitation concentration index (PCI) was calculated using annual precipitation data from 34 synoptic stations of Iran over a 50-year period (1961–2010). The trend of precipitation and the PCI index were analyzed using the Mann–Kendall test after removing the effect of autocorrelation coefficients in annual and seasonal time scales. The results of zoning the studied index at annual time scale revealed that precipitation concentration follows a similar trend within two 25-year subscales. Furthermore, the PCI index in central and southern regions of the country, including the stations of Kerman, Bandarabbas, Yazd, Zahedan, Shahrekord, Birjand, Bushehr, Ahwaz, and Esfahan indicates a strong irregularity and high concentration in atmospheric precipitations. In annual time scale, none of the studied stations, had shown regular concentration (PCI < 10). Analyzing the trend of PCI index during the period of 1961–2010 witnessed an insignificant increasing (decreasing) trend in 16 (15) stations for winter season, respectively, while it faced a significant negative trend in Dezful, Saghez, and Hamedan stations. Similarly, in spring, Kerman and Ramsar stations exhibited a significant increasing trend in the PCI index, implying significant development of precipitation concentration irregularities in these two stations. In summer, Gorgan station showed a strong and significant irregularity for the PCI index and in autumn, Tabriz and Zahedan (Babolsar) stations experienced a significant increasing (decreasing) trend in the PCI index. At the annual time scale, 50 % of stations experienced an increasing trend in the PCI index. Investigating the changes in the precipitation trend also revealed that in annual time scale, about 58 % of the stations had a decreasing trend. In winter, which is the rainiest season in Iran, about 64 % of stations experienced a decreasing trend in precipitation that caused an increasing trend in PCI index. Comparing the spatial distribution of PCI index within two 25 years sub-periods indicated that the PCI index of the second sub-period increased in the spring time scale that means irregularity of precipitation distribution has been increased. But in the other seasons any significant variations were not observed. Also in the annual time scale the PCI index increased in the second sub-period because of the increasing trend of precipitation.     

Simulating winter wheat production potential under near-future climate change in arid regions of northeast Iran

Theoretical and Applied Climatology - Water scarcity is the key challenge in arid regions, which exacerbates under climate change (CC) and must be considered to assess the impacts of CC on cropping...     

Optimization of Bottom Friction Coefficient Using Inverse Modeling in the Persian Gulf

Ocean Science Journal - A practical method for the calibration of the ocean circulation model is introduced using measured water levels along the Persian Gulf coastlines. Dimensional analysis is...