بررسی ارتباط بین خشکسالی و کاهش کیفیت آب با استفاده از سنجش از دور و روش شبکه‌های عصبی

نوع مقاله : مقاله پژوهشی

نویسندگان

1 استادیار، گروه سنجش از دور و GIS، دانشگاه تربیت مدرس

2 دانشیار بخش جغرافیا، دانشکدة اقتصاد، مدیریت و علوم اجتماعی، دانشگاه شیراز

چکیده

با توجه به تأثیر خشکسالی در کیفیت و کمّیت آب، هدف از این مطالعه بررسی خشکسالی با استفاده از شاخص‌های خشکسالی و ارتباط آن با میزان کیفیت آب در مناطق شمالی استان فارس ایران است. برای این منظور، شاخص‌های خشکسالی PCI، TVDI، NDVI در سال‌های 2000 تا 2020 استفاده شد. در ادامه، نقشه‌های پهنه‌بندی عناصر آب (Ca، Cl، EC، K، Na، Mg) با استفاده از روش کریجینگ تولید شد. سپس با به‌کارگیری روش شبکه‌های عصبی (MLP)، میزان عناصر آب با استفاده از شاخص‌های خشکسالی پیش‌بینی شد. نتایج نشان داد که با توجه به مقادیر شاخص‌های خشکسالی، روند تغییرات خشکسالی در منطقه از سال 2000 تا 2020 افزایشی بوده و بخش‌های جنوبی منطقه در وضعیت حادتری به‌نسبت دیگر بخش‌ها قرار دارد. نتایج حاصل از نقشه‌های پهنه‌بندی عناصر آب هم نشان داد که در بخش‌های جنوبی، غلظت املاح بیشتر از بخش‌های شمالی است. طبق نتایج حاصل از همبستگی بین شاخص‌های خشکسالی و مقادیر عناصر آب، Ca همبستگی بالایی (820/0 R=) با شاخص TVDI دارد و عناصر Cl، EC، K، Na، Mg نیز دارای همبستگی معنی‌داری (80/0 R>) با شاخص PCI است. نتایج حاصل از روش MLP، برای پیش‌بینی وضعیت کیفیت آب با استفاده از شاخص‌های خشکسالی، نشان داد که در مناطق جنوبی میزان املاح بیشتر و در نتیجه، کیفیت آب کمتر است. میزان دقت مدل در پیش‌بینی عناصر Cl، EC، K، Na، Mg، TH،TDS  با استفاده از شاخص PCI برابر با 85/0 R2= و درمورد عنصر Ca، با استفاده از شاخص TVDI برابر با 71/0 R2= است.

کلیدواژه‌ها

عنوان مقاله [English]

Investigating the Relationship between Drought and Water Quality Reduction Using Remote Sensing and Neural Network Methods

نویسندگان [English]

  • Mehran Shaygan 1
  • Marzieh Mokarram 2
1 Assistant Prof., Dept. of Remote Sensing & GIS, Tarbiat Modares University
2 Associate Prof., Dep. of Geography, Faculty of Economics, Management and Social sciences, Shiraz University
چکیده [English]

Due to the fact that droughts can affect both water quality and quantity, the purpose of this study is to determine the effect of droughts on water quality and quantity in Northern Fars province, Iran, based on drought indicators. The drought indices PCI, TVDI, and NDVI are used to study drought from 2000 to 2020. Also, the kriging method is used to generate zoning maps of elements in water (Ca, Cl, EC, K, Na, Mg). Then, using the neural network (MLP) method, the amount of elements in the water is predicted based on drought indices. Based on the values of the drought indicators, the trend of drought changes in the region is increasing from 2000 to 2020, with the southern areas of the region experiencing a more acute drought than the rest of the region. In addition, the zoning map of the elements in water indicated that salt concentrations are higher in the southern parts than in the northern parts. Correlation between drought indices and the amounts of elements in water showed that Ca has a high correlation (R2= 0.820) with TVDI index, and also Cl, EC, K, Na, and Mg have significant correlations (R > 0.8) with the index. Using drought indicators, MLP results for predicting water quality status show that southern regions have more solutes and lower water quality. Furthermore, the R2 values of the model for predicting the elements Cl, EC, K, Na, Mg, TDS, TH using PCI index equal to 0.85 and for Ca using TVDI index equal to 0.71, which indicates high accuracy.

کلیدواژه‌ها [English]

  • Drought
  • Water quality
  • Remote sensing
  • Neural network method

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