List of Articles Urmia Lake Basin

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  1 - Temporal analysis of storms in East of Urmia Lake using the Huff curves method
  Yagob Dinpashoh Saina Vakili Azar
  In this study, the Huff curves were extracted using the 418 events in the four selected stations. Firstly, the total storms were classified into the four distinct classes according to their durations including i) 0-2, ii) 2-6, iii) 6-12 and more than 12 hours. Then, the More

  In this study, the Huff curves were extracted using the 418 events in the four selected stations. Firstly, the total storms were classified into the four distinct classes according to their durations including i) 0-2, ii) 2-6, iii) 6-12 and more than 12 hours. Then, the Huff curves were plotted for the 10%, 20%, … and 90% non-exceedance probabilities. Analysis conducted for each of the classes, separately, for the stations. Another Huff curve plotted using the all events in a unit class. Some statistical distributions commonly used in hydrology were utilized. The three indices (S2/10, I2/10, and Q2/10) calculated. The design hyetographs for each of the selected stations using the information of all events in a unit class prepared for 2 and 10-years return periods. The mathematical models of Huff curves derived as the Logistic model. The parameters estimated for all models. Results indicated that except Sarab, having the first quartile precipitation type, the three other stations had the second quartile types. The same results obtained for the class of storms with duration less than two hours. But for the classes of 2-6 and 6-12 hours, in some stations the type of precipitation shifted to the further quartile. The vertical distance of 50% and 90% Huff curves in the first, second and third quartiles shortened as the quartiles increases (S>I>Q). It was found that the Logistic model is capable in fitting the curves. The correlation coefficients between the observed and modeled values were found to be from 0.978 to 0.998. Manuscript profile
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  2 - Effect of Land Use Trends on the Amount of Agricultural Water Consumption in Urmia Lake Watershed in the Next 20 Years Using Markov Chain
  Kiyoumars Roushangar Mohammad Taghi Aalami Hassan Golmohammadi
  10.30495/wsrcj.2022.68546.11310
  Background and Aim: Reducing the water level of Urmia Lake and its effects on the environment around the lake has been one of the important national and international issues and challenges in the last two decades. In accord with the studies, one of the critical factors More

  Background and Aim: Reducing the water level of Urmia Lake and its effects on the environment around the lake has been one of the important national and international issues and challenges in the last two decades. In accord with the studies, one of the critical factors affecting this declining trend has been the rise in harvest, especially for agriculture. Accordingly, the purpose of this study is to simulate the future status of water resources in the Urmia Lake basin, influenced by the area of agricultural land uses.Method:  For this purpose, Landsat satellite image data for the period 2000 to 2020 are firstly classified using the SVM algorithm in ENVI5.3 software and the classification accuracy is analyzed using the Kappa Coefficient algorithm.In the following, the statistics and information related to the change of cultivation pattern (from arable to garden) and water sources discharging Lake Urmia are calculated. In the next step, the simulation of land use changes for 2030 and 2040 is done using two LCM and CA-MARKOV methods. And finally, after determining the amount of changes in each land use, the amount of water required for agricultural affairs in the catchment is simulated using NETWAT model.Conclusion: The results show that the area of two uses, irrigated agriculture and garden will increase from 1450 and 395 square kilometers in 2000 to more than 3600 and 1650 square kilometers in 2040, respectively, This will increase the amount of water Needed or agriculture from 1,500 million cubic meters in 2000 to more than 4,100 million cubic meters in 2040.Results: From 2000 to 2020, water consumption in irrigated agriculture has increased by 1253.05 Km2; which according to Markov's prediction method, this amount will reach 2049.54 Km2 in 2040 that raises the amount of water consumption by 1 billion and 473 million cubic meters. The gardens land use has increased by 688.02 Km2 from 2000 to 2020, and according to Markov's prediction method, this amount will reach 1276.14 Km2 in 2040, which raises the amount of water consumption by 703 million cubic meters. From 2000 to 2020, 367.06 Km2 has been added to the drayland farming, which according to the prediction of Markov method, this amount will reach 531 Km2 in 2040, which soars the amount of water consumption by 253 MCM. Manuscript profile