Agricultural drought risk assessment of Northern New South Wales, Australia using geospatial techniques
Creators
- 1. Department of Geography and Environment, Jagannath University, Dhaka 1100 (Bangladesh)
- 2. Centre for Advanced Modelling and Geospatial Information Systems (CAMGIS), Faculty of Engineering and IT, University of Technology Sydney, Ultimo, NSW 2007 (Australia)
- 3. Earth Observation Center, Institute of Climate Change, Universiti Kebangsaan Malaysia, 43600 UKM, Bangi, Selangor (Malaysia)
- 4. Center of Excellence for Climate Change Research, King Abdulaziz University, P. O. Box 80234, Jeddah 21589 (Saudi Arabia)
- 5. Department of Energy and Mineral Resources Engineering, Sejong University, Choongmu-gwan, 209 Neungdong-ro, Gwangjin-gu, Seoul 05006 (Korea, Republic of)
- 6. Department of Environmental Science and Management, North South University, Dhaka 1229 (Bangladesh)
Description
Highlights: • Evaluated agricultural drought risk for Northern New South Wales, Australia. • The model considered all risk components and 16 relevant criteria. • Geospatial techniques were used to prepare the drought risk model. • Risk model identified the spatial extents and levels of agricultural drought risk. Droughts are recurring events in Australia and cause a severe effect on agricultural and water resources. However, the studies about agricultural drought risk mapping are very limited in Australia. Therefore, a comprehensive agricultural drought risk assessment approach that incorporates all the risk components with their influencing criteria is essential to generate detailed drought risk information for operational drought management. A comprehensive agricultural drought risk assessment approach was prepared in this work incorporating all components of risk (hazard, vulnerability, exposure, and mitigation capacity) with their relevant criteria using geospatial techniques. The prepared approach is then applied to identify the spatial pattern of agricultural drought risk for Northern New South Wales region of Australia. A total of 16 relevant criteria under each risk component were considered, and fuzzy logic aided geospatial techniques were used to prepare vulnerability, exposure, hazard, and mitigation capacity indices. These indices were then incorporated to quantify agricultural drought risk comprehensively in the study area. The outputs depicted that about 19.2% and 41.7% areas are under very-high and moderate to high risk to agricultural droughts, respectively. The efficiency of the results is successfully evaluated using a drought inventory map. The generated spatial drought risk information produced by this study can assist relevant authorities in formulating proactive agricultural drought mitigation strategies.
Availability note (English)
Available from http://dx.doi.org/10.1016/j.scitotenv.2020.143600Additional details
Identifiers
- DOI
- 10.1016/j.scitotenv.2020.143600;
- PII
- S004896972037131X;
Publishing Information
- Journal Title
- Science of the Total Environment
- Journal Volume
- 756
- Journal Page Range
- vp.
- ISSN
- 0048-9697
- CODEN
- STENDL
INIS
- Country of Publication
- Netherlands
- Country of Input or Organization
- International Atomic Energy Agency (IAEA)
- INIS RN
- 54060486
- Subject category
- S54: ENVIRONMENTAL SCIENCES;
- Descriptors DEI
- FUZZY LOGIC; GEOGRAPHIC INFORMATION SYSTEMS; HAZARDS; REMOTE SENSING; RISK ASSESSMENT; WATER RESOURCES
- Descriptors DEC
- INFORMATION SYSTEMS; MATHEMATICAL LOGIC; RESOURCES
Optional Information
- Copyright
- Copyright (c) 2020 Elsevier B.V. All rights reserved.