This study uses a multi-criteria decision analysis approach based on geographic information system (GIS) to identify suitable sites for rainwater harvesting (RWH) structures (such as farm dam, check dam and contour bund) to meet irrigation demand in Greater Western Sydney region, New South Wales, Australia. Data on satellite image, soil, climate, and digital elevation model (DEM) were stored in GIS layers and merged to create a ranking system, which were then used to identify suitable RWH (rainwater harvesting) areas. The resulting thematic layers (such as rainfall, land use/land cover, soil type, slope, runoff depth, drainage density, stream order and distance from road) were combined into one overlay to produce map of RWH suitability. The results showed that 9% of the study region is ‘very highly suitable’ and 25% is ‘highly suitable’. On the other hand, 36% of the area, distributed in the north-west, west and south-west of the study region, is ‘moderately suitable’. While 21% of the region, distributed in east and south-east part of the region, has ‘low suitability’ and 9% is found as ‘unsuitable area’. The findings of this research will contribute towards wider adoption of RWH in Greater Western Sydney region to meet irrigation demand. The developed methodology can be adapted to any other region/country.

This paper presents reliability, water demand and economic analysis of rainwater harvesting (RWH) systems for eight Australian capital cities (Adelaide, Brisbane, Canberra, Darwin, Hobart, Melbourne, Perth and Sydney). A Python-based tool is developed based on a daily water balance modelling approach, which uses input data such as daily rainfall, roof area, overflow losses, daily water demand and first flush. Ten different tank volumes are considered (1, 3, 5, 10, 15, 20, 30, 50, 75 and 100 m³). It is found that for a large roof area and tank size, the reliability of RWH systems for toilet and laundry use is high, in the range of 80–100%. However, the reliability for irrigation use is highly variable across all the locations. For combined use, Adelaide shows the smallest reliability (38–49%), while Hobart demonstrates the highest reliability (61–77%). Furthermore, economic analysis demonstrates that in a few cases, benefit–cost ratio values greater than one can be achieved for the RWH systems. The findings of this study will help the Australian Federal Government to enhance RWH policy, programs and subsidy levels considering climate-sensitive inputs in the respective cities.

Due to climate change, freshwater supply will be limited at many locations around the globe. Rainwater harvesting (RWH) has emerged as an alternative and sustainable freshwater source. In this study, the impacts of climate change on water saving as well as the reliability of a RWH system are investigated using data from eight Australian capital cities. Both historical and projected rainfall data were incorporated into a daily water balance model to evaluate the performance of a RWH system in relation to its reliability, water savings and scarcity. Indoor (toilet and laundry), outdoor (irrigation) and combined (indoor plus outdoor) water demands were considered for a 5 m³ tank size. It has been found that in the future period, the water savings and reliability of a RWH system will reduce slightly across the selected cities. Different capital cities of Australia will experience different level of performance for a RWH system depending on their locations, water uses and seasons. The findings of this study will be useful to water authorities and policy makers to plan for a sustainable RWH system under changing climate conditions.

The spatial and temporal variability of quantity and quality of water are important aspects of water resources management. Water demand has been increasing across the globe, but the fresh water supply is limited. Rainwater harvesting (RWH) systems are increasingly being embraced as an alternative freshwater source. This study reviews the dynamics of global research on RWH that utilises geographic information systems (GIS). It is found that the interest and use of RWH utilising GIS have increased over the recent years. However, the full potential of GIS in large scale RWH is yet to be untapped. We make recommendations for future research on RWH based on GIS. This includes new software and model development that links RWH with GIS to plan and design large scale RWH and automated building footprint extraction for estimating RWH potential. GIS can play a bigger role in achieving Sustainable Development Goals (SDGs) by incorporating GIS with RWH since GIS can handle large spatial data efficiently, which can help in locating areas that are suitable for rainwater harvesting

The present study has developed the time series database surface soil moisture over India, for June, July and August months for the period of 20 years from 1991 to 2010, using data products generated under Climate Change Initiative Programme of European Space Agency. These three months represent the crop sowing period in the prime cropping season in the country and the soil moisture data during this period is highly useful to detect the drought conditions and assess the drought impact. The time series soil moisture data which is in 0.25 degree spatial resolution was analyzed to generate different indicators. Rainfall data of same spatial resolution for the same period, generated by India Meteorological Department was also procured and analyzed. Geospatial analysis of soil moisture and rainfall derived indicators was carried out to study (1) inter annual variability of soil moisture and rainfall, (2) soil moisture deviations from normal during prominent drought years, (3) soil moisture and rainfall correlations and (4) drought exposure based on soil moisture and rainfall variability. The study has successfully demonstrated the potential of these soil moisture time series data sets for generating regional drought surveillance information products, drought hazard mapping, drought exposure analysis and detection of drought sensitive areas in the crop planting period.