Climatology
younes nikookhesal; Ali Akbar Rasouli; Davod Mokhtari; Khalil Valizadeh Kamran
Abstract
IntroductionThe water cycle in nature is directly related to the climate of that region. Reasonable and correct use of water resources requires accurate quantitative and qualitative knowledge and collection of appropriate climate data and information. Depletion of groundwater reservoirs, drying of canals ...
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IntroductionThe water cycle in nature is directly related to the climate of that region. Reasonable and correct use of water resources requires accurate quantitative and qualitative knowledge and collection of appropriate climate data and information. Depletion of groundwater reservoirs, drying of canals and springs and even semi-deep wells and reduction of deep well discharge, change of groundwater flow direction, salinization of aquifers, salinization of soil due to irrigation with saline water, barren The emergence of fields, soil erosion, etc. has put most of the plains of the country at risk of further desertification (Tavousi, 2009: 14).Atmospheric precipitation is the main source of surface and groundwater and the study area is poor in terms of atmospheric precipitation and its amount is between 150 to 450 mm per year, which varies in plain and mountainous areas. The climate of the region is semi-arid and cold and is mostly influenced by the Mediterranean climate. Due to the fact that groundwater is the most important source of water consumption in the study area, the impact of climate change, especially precipitation on the water table of wells in the area was investigated in this study.Materials and methodsTo study the trend of groundwater level changes in Marand plain, water table data of 23 piezometric wells and data of 8 rain gauge stations during the last 16 years of 1395-1395 were used. After using the correlation matrix method to select rainfall stations and considering the complete statistical data and appropriate coverage of the area by these stations, 4 stations were selected for the study and for each station, a piezometric well was selected within the station. This research was first calculated using precipitation data and water table of piezometric wells SPI and SWI values and then NRMC values for each index, respectively, in each method are briefly referred to:Calculate SPI and plot seasonal SPI variations of selected stationsThe standardized rainfall index was provided by McKay et al. (1993, 1995) to provide a warning and help assess drought severity and is calculated by the following formula: Relation 1: SPI = (X_ij-X_im) / σIn the above relation, X_ij is the seasonal rainfall at rainfall station i, with j number of observations, X_im is the long-term average rainfall and σ is the standard deviation.Calculate SWI and plot the seasonal SWI of selected wells The standard water level index was presented in 2004 by Bui Yan et al. (2006) to monitor fluctuations in groundwater aquifers in the study of hydrological droughts, which is calculated by the following formula:Relation 2: SWI = (W_ij-W_im) / σWhere W_ij is the seasonal average of the water table of observation wells i to j, W_im is the long-term seasonal average and σ is the standard deviation.Calculate the NRMC values of each indicator and plot the normalized distribution curveIn this method, seasonal normalized distribution curves were adjusted for both SPI and SWI indices. Cumulative normalized curve is a kind of condensation diagram of a climatic or hydrological variable (such as precipitation and water table) that is extracted from the subtraction of each observation in the statistical series of the long-term average and its division by the average according to the following formula. (Rasooli, 1994)Relation 3: NRMC xi = ( (Xi-X m) / ({(Xi-X ̅m) / X ̅m}) ) * 100 In the above formula, Xi represents the amount of each rainfall observation or the amount of water table and X ̅m is the long-term average in the series of observations.Results and DiscussionInvestigation of normalized distribution curves showed a correlation between precipitation changes and groundwater level in Marand plain. This correlation has a higher significance with a delay season. Shamsipoor (2003) in Hamedan plain achieved a 9-month delay between precipitation and water table. Mohammadi et al. (2012) in Arak plain expressed the impact of groundwater resources from drought with a delay of two months. The results of the study (Rudel and Lee 2014) in the study of groundwater drought index in the United States showed that the SPI drought index with a delay of 12 and 24 months had the highest correlation with the SWI index.ConclusionConsidering the more fluctuations of the water table than the fluctuations of the rainfall, it can be concluded that human factors such as uncontrolled harvesting is an effective factor on the water level of wells. Komasi et al. (2016) stated the effect of human factors on the decrease of groundwater level before the factor of climate change in Silakhor plain. Calculations showed that the value of correlation for both SPI and SWI indices in the nonlinear multivariate equation is higher than the value of the linear equation, which indicates the effect of several other factors in addition to precipitation fluctuations on the groundwater level. According to the results of the study, it seems that the groundwater level in addition to precipitation depends on other factors such as geology, lithology, tectonic morphology, the shape of the aquifer, the distance of aquifers to the feeding site and .... And to achieve more complete results, it seems necessary to address these factors in future research.
Climatology
Younes Nikookhesal; ali akbar rasoli; Davod Mokhtari; Khalil valizadeh kamran
Volume 26, Issue 80 , August 2022, , Pages 327-317
Abstract
IntroductionInvestigating the effect of drought on water resources of countries plain is high important at optimal management of water resources in the agriculture and natural resources part. The phenomenon of climate change, affects the amount of water existence in aquifer by changing amount of precipitation. ...
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IntroductionInvestigating the effect of drought on water resources of countries plain is high important at optimal management of water resources in the agriculture and natural resources part. The phenomenon of climate change, affects the amount of water existence in aquifer by changing amount of precipitation. The occurrence of consecutive climate droughts affects ground water resources. Knowing and awareness of the effect of time between two phenomenon of drought and hydrological drought, can help managers and planners of the water sector. Over the years, the effect of drought on ground water resources less attention has been paid. In order to understand the state of groundwater resources and optimum management, it is necessary to carry out a thorough study of groundwater fluctuations. In this research, Marand plain is the purpose of this study. Marand Plain is poor in rainfall and has a rainfall of 450 mm / year and at least 150 mm / year which varies in the plains and mountainous regions. In this research, we have tried to investigate the effect of atmospheric drops, including rainfall, on ground water level in the Marand watershed.MethodologyThe Marand plain with 45 °, 15 to 50 minutes east longitude and 37 ° 7 'to 38 ° 56' north latitude and with an area of 42.517 square kilometer is one of the vast plains in the northwest of East Azarbaijan province. Which is selected as the study area. In this study, in order to study the trend of ground water level changes in the Marand Plain, the static surface data of 23 piezometric wells was used during the 2000 to 2016. First, a common statistical period was chosen to analyze the data series (2000 to 2016). Then in order to reconstruct the statistical defects, the correlation between stations and piezometric wells and linear regression method was used. The IDW method was used to calculate the average rainfall of the plain. Finally, the standard water level index (SWI) and the SPI index for the studied basin were calculated and analyzed. Discussion The aim of this study was to investigate the effects of climate drought on the fell of groundwater level in the Marand plain using SPI and SWI indices. Meteorological drought conditions in the Marand plain were calculated using the SPI index on a 12-month time scale. The results and drought accuracy of the rain gauge stations in the studied basin showed that during the study period, the first period of drought since 2005 started gradually with decreasing atmospheric precipitation and continued until 2007 and after a period of humidity short-term, again, a short period of drought from 2008 to 2009 has been on the ruling area. The SWI index was used to survey the status of groundwater level. This indicator also showed that in terms of time and place, the drought based on this index corresponded to the drought caused by the SPI index.Conclusion Using the SPI index, the drought trend was studied in the region. The results showed that during the study period (2000-2016) three drought periods from winter 2005 to beginning of 2009, summer of 2011 to the end of 2012 and winter of 2015 to summer of 2016 occurred. Drought affected areas included the east and center of the study area and the west of the region witnessed more atmospheric precipitation. The SWI index was used to survey the status of groundwater level. The index showed that in terms of time and place, the drought based on this index corresponded to the drought caused by the SPI index. Data analysis showed that these two indices with a time interval of one season had a correlation of 1%. This means that the hydrological drought after a season has a direct impact on the surface of the water. In general, we can conclude from the results of this study that the trend of ground water surface changes has been consistent with the drought and weathering changes in the region. Therefore, the fall of the ground water level of Marand plain can be largely influenced by weathered droughts.
All other Geographic fields of studies , Interdisciplinary
Asghar Asghari Moghddam; Mir sajad Fakhri; Morteza Najib
Volume 19, Issue 54 , February 2016, , Pages 19-41
Abstract
Purpose of this study is zoning of Marand aquifer vulnerability mapping using DRASTIC, AVI methods and comparing their susceptibility adopted from these methods. The DRASTIC method is a combination of seven measurable hydro-geological characteristics that are effective on transportation of contaminant ...
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Purpose of this study is zoning of Marand aquifer vulnerability mapping using DRASTIC, AVI methods and comparing their susceptibility adopted from these methods. The DRASTIC method is a combination of seven measurable hydro-geological characteristics that are effective on transportation of contaminant into groundwater. The GODS and AVI methods combine four and have two properties respectively. The DRASTIC method results is the most complete index for assessing groundwater vulnerability, which has been estimated the vulnerability for the study area as moderate 50.4 percent, high 32.9 percent and very high16.7 percent. The GODS method results suggest three classes for the Marand aquifer vulnerability including moderate, high and very high with 43.8, 5.16 and 51.04 percent, respectively. Also the AVI method results indicate that the aquifer has a vulnerability of moderate, high and very high with 39.13, 6.5 and 54.37 percent, respectively. In all three methods, the degree of vulnerability in the East, Southeast and Northeast parts of the pain is more than the central and western parts of the pain. DRASTIC model is determined the vulnerability areas more accurately due to having more features and different weighting of the features based on their role in pollution.
