PMID- 33798887
OWN - NLM
STAT- PubMed-not-MEDLINE
DCOM- 20210526
LR  - 20210526
IS  - 1879-1026 (Electronic)
IS  - 0048-9697 (Linking)
VI  - 781
DP  - 2021 Aug 10
TI  - Determining and forecasting drought susceptibility in southwestern Iran using 
      multi-criteria decision-making (MCDM) coupled with CA-Markov model.
PG  - 146703
LID - S0048-9697(21)01771-X [pii]
LID - 10.1016/j.scitotenv.2021.146703 [doi]
AB  - Forecasting drought and determining relevant data to predict drought are an 
      important topic for decision-makers and planners. It is critical to predicting 
      drought in the south of Fars province, an important agricultural center in Iran 
      located in arid and semi-arid climates. The purpose of this study was to generate 
      a drought map in 2019 using 12 parameters: altitude, aridity index, erosion, 
      groundwater depth, land use, PET (Potential evapotranspiration), precipitation 
      days, precipitation, slope, soil texture, soil salinity, and distance to river, 
      and predict drought maps in 2030 and 2040 using the cellular automata (CA)-Markov 
      model spatially. The fuzzy method was first used to homogenize the data. Next, by 
      evaluating each parameter, the weight of each parameter was calculated using the 
      analytic hierarchy process (AHP), and a map of drought-prone areas was generated. 
      The results of the fuzzy-AHP method showed that the eastern and southeastern 
      regions of the study area were prone to drought. The four most predictive 
      parameters in causing drought, i.e., aridity index, PET, precipitation, and soil 
      texture, were selected using the Best search method and were then chosen as the 
      input to determine drought mapping using the fuzzy and AHP methods. Finally, the 
      CA-Markov model was used to predict future drought maps, and the results showed 
      that in 2030 and 2040 the drought situation in the east and south of the study 
      area would intensify.
CI  - Copyright (c) 2021 Elsevier B.V. All rights reserved.
FAU - Mokarram, Marzieh
AU  - Mokarram M
AD  - Department of Range and Watershed Management, College of Agriculture and Natural 
      Resources of Darab, Shiraz University, Shiraz, Iran. Electronic address: 
      m.mokarram@shirazu.ac.ir.
FAU - Pourghasemi, Hamid Reza
AU  - Pourghasemi HR
AD  - Department of Natural Resources and Environmental Engineering, College of 
      Agriculture, Shiraz University, Shiraz, Iran.
FAU - Hu, Ming
AU  - Hu M
AD  - Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland 
      Clinic Foundation, Cleveland, OH 44195, United States of America. Electronic 
      address: hum@ccf.org.
FAU - Zhang, Huichun
AU  - Zhang H
AD  - Department of Civil and Environmental Engineering, Case Western Reserve 
      University, Cleveland, OH 44106, United States of America. Electronic address: 
      hjz13@case.edu.
LA  - eng
PT  - Journal Article
DEP - 20210325
PL  - Netherlands
TA  - Sci Total Environ
JT  - The Science of the total environment
JID - 0330500
SB  - IM
OTO - NOTNLM
OT  - AHP method
OT  - Best search method
OT  - CA-Markov
OT  - Drought
OT  - Fuzzy method
OT  - Southwestern Iran
COIS- Declaration of competing interest The authors declare that they have no known 
      competing financial interests or personal relationships that could have appeared 
      to influence the work reported in this paper.
EDAT- 2021/04/03 06:00
MHDA- 2021/04/03 06:01
CRDT- 2021/04/02 20:20
PHST- 2020/12/23 00:00 [received]
PHST- 2021/03/02 00:00 [revised]
PHST- 2021/03/19 00:00 [accepted]
PHST- 2021/04/03 06:00 [pubmed]
PHST- 2021/04/03 06:01 [medline]
PHST- 2021/04/02 20:20 [entrez]
AID - S0048-9697(21)01771-X [pii]
AID - 10.1016/j.scitotenv.2021.146703 [doi]
PST - ppublish
SO  - Sci Total Environ. 2021 Aug 10;781:146703. doi: 10.1016/j.scitotenv.2021.146703. 
      Epub 2021 Mar 25.