Assessing agricultural drought management strategies in the Northern Murray–Darling Basin

Abstract

The Northern Murray-Darling Basin (MDB) is a key Australian agricultural region requiring efficient Agricultural Drought Management (ADM), focused on resilience. Although a need for resilience in local farming communities has long been recognised, previous studies assessing ADM in the Northern MDB did not consider two key elements of resilient management: proactivity (preparing for drought prior to a drought event) and suitability (localised drought management targeted at decision-makers). This study assessed the current ADM Strategy (ADMS) implemented within five selected Northern MDB Local Government Areas (LGAs) (Paroo Shire, Balonne Shire, Murweh Shire, Maranoa Region, and Goondiwindi Region), specifically investigating the extent of ADMS proactivity, effectiveness, and suitability. To investigate suitability, drought risk extent of each LGA was determined. A region-specific drought risk index consisting of hazard, vulnerability and exposure indices was developed; risk mapping was conducted. All LGAs displayed very high levels of drought risk due to hazardous climatic conditions, vulnerable socio-economic attributes, and drought-exposed geographical features. A Criteria-Based Ranking (CBR) survey produced a quantitative effectiveness and proactivity rank for each major ADMS used in the Northern MDB. Government Assistance was the most proactive and effective ADMS. Strategy effectiveness ranks of the major ADMS used and drought risk extent found in each LGA were correlated to determine ADMS suitability. Overall, Balonne Shire and the Goondiwindi Region were identified as high priority areas requiring improved ADM. A user-centred Integrated Early Warning System (I-EWS) for drought could potentially increase ADM proactivity and suitability in such areas, strengthening drought resilience of farming communities.

Validating a tailored drought risk assessment methodology: drought risk assessment in local Papua New Guinea regions

“…Suitability is seen as the level of appropriateness that drought management strategies have for application at localised levels in vulnerable places. A drought management strategy is deemed suitable if it can be independently implemented by local stakeholders and/or communities and if it addresses the specific impacts faced by local decision-makers (Aitkenhead et al, 2021). Thus, when seeking to increase drought resilience in PNG, the proactivity and suitability of localised drought risk management is of critical focus (Mercer, 2010).…”

“…Indicator thresholds that signal different stages of drought risk. These thresholds have been decided upon based on use in past studies (Rahmati et al, 2020;Nasrollahi et al, 2018;Aitkenhead et al, 2021), the advice of the PNG National Weather Service, as well as past data trends in PNG .…”

Applying Machine Learning for Threshold Selection in Drought Early Warning System

“…Various types of droughts include meteorological (when dry conditions within an area are influenced by climactic factors), agricultural (when dry conditions have an impact on agricultural productivity and crops), etc. To measure drought severity, there are some indices which are proposed based on meteorological, hydrological, agricultural and socioeconomic information [5][6][7][8]. Aitkenhead et al [8] develop a region-specific drought risk index based on the integration of drought vulnerability, exposure, and hazard indices, in order to evaluate drought in the Northern Murray-Darling Basin.…”

“…To measure drought severity, there are some indices which are proposed based on meteorological, hydrological, agricultural and socioeconomic information [5][6][7][8]. Aitkenhead et al [8] develop a region-specific drought risk index based on the integration of drought vulnerability, exposure, and hazard indices, in order to evaluate drought in the Northern Murray-Darling Basin. Vicente-Serrano et al [9] propose a climatic drought index, namely, the standardized precipitation evapotranspiration index (SPEI), by exploring precipitation and temperature data.…”

Statistical modelling of extreme temperature in Peninsular Malaysia

“…Flood leads to severe economic loss, causes impacts to human life and damages properties [2]. The prolonged period of drought has weakened the economy of Malaysia due to the less production of crops which causes a severe impact on the agricultural industry [3]. Thus, the investigation of the best fit distribution of maximum temperature is important as it can provide information on the temperature trends.…”