Integrated remote sensing and GIS approach using Fuzzy-AHP to delineate and identify groundwater potential zones in semi-arid Shanxi Province, China

Shao Z., Huq M. E., Cai B., Altan O., Li Y.

ENVIRONMENTAL MODELLING & SOFTWARE, cilt.134, 2020 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 134
  • Basım Tarihi: 2020
  • Doi Numarası: 10.1016/j.envsoft.2020.104868
  • Dergi Adı: ENVIRONMENTAL MODELLING & SOFTWARE
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, PASCAL, Aerospace Database, Agricultural & Environmental Science Database, Applied Science & Technology Source, Aqualine, Aquatic Science & Fisheries Abstracts (ASFA), Biotechnology Research Abstracts, CAB Abstracts, Communication Abstracts, Compendex, Computer & Applied Sciences, Environment Index, Geobase, Greenfile, INSPEC, Metadex, Pollution Abstracts, Public Affairs Index, Veterinary Science Database, Civil Engineering Abstracts
  • İstanbul Teknik Üniversitesi Adresli: Evet

Özet

In Shanxi Province, China, groundwater is a major problem and exploration of groundwater potential zones (GWPZs) is a great necessity. This paper contributed to integrate RS-GIS to delineate GWPZ and applied Fuzzy-AHP method in a single platform. The main objective includes delineation GWPZs with RS and geoenvironmental factors using Fuzzy-AHP method. Fuzzy-AHP method was employed to calculate weight of factors. RS-GIS was used to create maps and discover groundwater availability. GWPZs were classified in five separate classes. Results indicated that 13.26%, 27.02%, 26.35%, 23.64%, and 9.71% area classified as very good, good, moderate, poor, and very poor GWPZs. The validated analytical results revealed 82.5%, 12.3%, 3.5%, and 1.7% existing water wells exhibited in very good, good, moderate, and poor/very poor GWPZs. This indicates Fuzzy-AHP model generated findings were in very good agreement with ground-truth data. This RS-GIS based Fuzzy-AHP method is proficient and efficient in identification and delineation of GWPZs.