واکاوی حساسیت تراز سفرۀ آب زیرزمینی دشت ارومیه

توزیع ناهمگون و نابهنگام زمانی و مکانی بارش‌ها و جریانات آب سطحی، موجب تبدیل سفره‌های آب زیرزمینی به منابع ضروری کشور شده است. در سال‌های اخیر با افزایش تقاضای آب و عدم تامین بخش قابل ملاحظه ای از آن توسط منابع آب سطحی، استحصال مجاز و غیر مجاز منابع آب زیرزمینی بسیار مورد توجه قرارگرفته؛ به طوری که در کل کشور سطح سفره‌های زیرزمینی با افت شدید مواجه شده است. در پژوهش حاضر میزان تاثیر سه عامل بارش، جمعیت و تورم بر اُفت آبخوان دشت ارومیه مورد بررسی قرارگرفته است. برای انجام این کار، بین داده های اُفت سالانه سطح سفره آب زیرزمینی در 38 سال از 1360 تا 1398 با سه متغیر بارش، جمعیت و شاخص تورم سال قبل رگرسیون خطی چند متغیره برقرارشد. ضریب تعیین تعدیل شده رگرسیون بیش از 0.85 بود. با توجه به ضرایب بتای استاندارد، اولویت میزان تاثیر متغیرهای مورد بررسی بر افت آبخوان عبارت از جمعیت 0.514 افزایشی، تورم 0.434 افزایشی و بارش 0.241- کاهشی بود. همچنین برای شبیه سازی معادلات، از شبکه های عصبی مصنوعی تابع پایه شعاعی rbf:3-5-1 دارای سه لایه با 3، 5 و 1 نرون به ترتیب در لایه ورودی، لایه پنهان میانی و لایه خروجی و پرسپترون سه لایه mlp:3-5-1 و چهار لایه mlp:3-2-2-1 بهره ‌گیری شد؛ و نتایج تائید کننده یافته های رگرسیون بود. به عبارت دیگر بر اساس نتایج این پژوهش تاثیر تغییرات اقلیمی به ویژه بارندگی کمتر از سیاست‌ها و شرایط اجتماعی- اقتصادی بوده است. ضمناً با مقایسه مدل‌های شبیه ‌سازی مذکور، بهترین برآورد مربوط به شبکه عصبی مصنوعی پرسپترون سه لایه mlp:3-5-1 می باشد.

sensitivity analysis of the urmia plain aquifer level

introductionwater is the source of life and a strategic resource for human societies. the need for this vital resource is increasing exponentially due to the increase in population and the development of industry and agriculture. people are forced to use underground water because surface water is not generally and permanently responsive to diverse needs. a decrease in their volume and many problems have been caused by the excessive use of these resources. this crisis has caused regional crises caused by the imbalance of resources and consumption, along with climate changes, has raised the issue of integrated management of water resources more than ever. agricultural land has been developed due to the increase in population and the need for more food. programs without principles that rely solely on the quality and quantity of underground water resources have been harmful. groundwater aquifers are transformed into sources of the country’s needs due to the heterogeneous and untimely temporal and spatial distribution of discharges and surface water flows. in recent years, with the increase in water demand and the non-supply of a significant part of it by surface water sources, the extraction - permitted and unauthorized - of underground water sources has been given much attention; so that the level of underground aquifers has decreased dramatically across the country. the purpose of the present study was to investigate the impact of the important variables of precipitation, inflation and annual population as a representative of climatic, economic and social factors on the fluctuations of the underground water level in urmia region. material and methodsin the present study, the impact of three factors, precipitation, population and inflation, on the subsidence of the urmia plain aquifer has been investigated. to do this, multiple linear regressions was performed between the data of the annual loss of the groundwater level during 38 years, 1981 to 2019 with three variables of precipitation, population and inflation index of the previous year. according to the previous researches, firstly, an index of inflation has been established by comparing the average loss of the piezometric level of the underground water in  urmia region as a dependent variable, with the three independent variables of the average rainfall of water year as the most important climatic factor, the annual population of the major centers of human concentration located in the urmia plain of previous year, and the base coefficient of the annual monetary value of previous year compared to 1981 using a multivariable linear regression. then, the outcome is compared to the outcomes of artificial neural networks such as four-layer perceptron, three-layer perceptron, and radial basis function. all three networks have an input layer with three neurons to receive the values of the three independent variables of precipitation, population and inflation. one or two hidden layers with a number of neurons, to perform calculations and process the relationship between independent and dependent variables; and an output layer with a neuron to provide the processing results i.e., the estimated aquifer subsidence rate. the data used in the present study were derived from the years 1981-2019. the reference of the aquifer level data is the hydrograph extracted from 67 piezometer wells in the area by the underground water unit of basic studies of the west azerbaijan regional water company.