Rainwater Harvesting for Agriculture and Water Supply

Zhu, Qiang; Gould, John; Li, Yuanhong; Ma, Chengxiang

doi:10.1007/978-981-287-964-6

Cited by 12 publications

(3 citation statements)

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“…In addition, more reliable water supply is improved from storage [2]. [3] Describe in detail the adaptation of rainwater harvesting technology for where water resource to precipitation ratio is minimal. The approach was considered innovative and provided relief for agriculture and water supply.…”

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confidence: 99%

“…As a process of concentrating rainfall as runoff from a catchment to be used in a target area, surface harvesting technologies have become important options to supply drinking water, develop irrigated agriculture and improve the ecosystem in dry areas. Seventeen provinces in China have adopted rain-water utilization technique, building 5.6 million tanks with a total capacity of 1.8 billion cubic meters, supplying drinking water for approximately 15 million people and supplemental irrigation for 1.2 million ha of land [3].…”

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Identification of Surface Water Storing Sites Using Topographic Wetness Index (TWI) and Normalized Difference Vegetation Index (NDVI)

Berhanu

Bisrat

2018

JNRD

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Ethiopia is endowed with water and has a high runoff generation area compared to many countries, but the total stored water only goes up to approximately 36BCM. The problem of water shortage in Ethiopia emanates from the seasonality of rainfall and the lack of infrastructure for storage to capture excess runoff during flood seasons. Based on this premise, a method for a syndicate use of topography, land use and vegetation was applied to locate potential surface water storing sites. The steady-state Topographic Wetness Index (TWI) was used to represent the spatial distribution of water flow and water stagnating across the study area and the Normalized Difference Vegetation Index (NDVI) was used to detect surface water through multispectral analysis. With this approach, a number of water storing sites were identified in three categories: primary sources (water bodies based), secondary sources (Swampy/wetland based) and tertiary sources (the land based). A sample volume analysis for the 120354 water storing sites in category two, gives a 44.92BCM potential storing capacity with average depth of 4 m that improves the annual storage capacity of the country to 81BCM (8.6 % of annual renewable water sources). Finally, the research confirmed the TWI and NDVI based approach for water storing sites works without huge and complicated earth work; it is cost effective and has the potential of solving complex water resource challenges through spatial representation of water resource systems. Furthermore, the application of remote sensing captures temporal diversity and includes repetitive archives of data, enabling the monitoring of areas, even those that are inaccessible, at regular intervals.

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Identification of Surface Water Storing Sites Using Topographic Wetness Index (TWI) and Normalized Difference Vegetation Index (NDVI)

Berhanu

Bisrat

2018

JNRD

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“…Such challenges are climate change, population growth, environmental regulations, decaying infrastructure and calamities. Enhancing trading, and expanding storage and treatment capacities would increase supply reliability [Shamir, 1987, Goulter, 1995, Zhu et al, 2015. Therefore, satisfactory water management planning and design have to be in place [California Urban Water Agencies, 2012].…”

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confidence: 99%

Integration of environmental aspects in modelling and optimisation of water supply chains

Koleva

Calderón

Zhang

et al. 2018

Science of The Total Environment

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Climate change becomes increasingly more relevant in the context of water systems planning. Tools are necessary to provide the most economic investment option considering the reliability of the infrastructure from technical and environmental perspectives. Accordingly, in this work, an optimisation approach, formulated as a spatially-explicit multi-period Mixed Integer Linear Programming (MILP) model, is proposed for the design of water supply chains at regional and national scales. The optimisation framework encompasses decisions such as installation of new purification plants, capacity expansion, and raw water trading schemes. The objective is to minimise the total cost incurring from capital and operating expenditures. Assessment of available resources for withdrawal is performed based on hydrological balances, governmental rules and sustainable limits. In the light of the increasing importance of reliability of water supply, a second objective, seeking to maximise the reliability of the supply chains, is introduced. The epsilon-constraint method is used as a solution procedure for the multi-objective formulation. Nash bargaining approach is applied to investigate the fair trade-offs between the two objectives and find the Pareto optimality. The models' capability is addressed through a case study based on Australia. The impact of variability in key input parameters is tackled through the implementation of a rigorous global sensitivity analysis (GSA). The findings suggest that variations in water demand can be more disruptive for the water supply chain than scenarios in which rainfalls are reduced. The frameworks can facilitate governmental multi-aspect decision making processes for the adequate and strategic investments of regional water supply infrastructure.

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