Search results

The purpose of this study is to assess the spatiotemporal patterns of future meteorological drought in the Yellow River Basin under different representative concentration pathway (RCP) scenarios.

Delta method is used to process the future climate data of the global climate models, then analyzed the spatiotemporal variation trend of drought in the Yellow River Basin based on standardized precipitation evaporation index (SPEI) under four RCP scenarios.

This research was funded by the National Natural Science Foundation of China (41901239), Soft Science Research Project of Henan Province (212400410077, 192400410085), the National Key Research and Development Program of China (2016YFA0602703), China Postdoctoral Science Foundation (2018M640670) and the special fund of top talents in Henan Agricultural University (30501031).

This study can provide support for future meteorological drought management and prevention in the Yellow River Basin and provide a theoretical basis for water resources management.

The first aim of this study is to show the impact of global warming on temperature and precipitation changes in Algeria. The second objective is to exhibit the strategy planned by the country to mitigate these effects on water resources in the future.

This research assesses the expected changes in temperature, precipitation and SPEI index, over Algeria (16 weather stations), between two horizons (2030, 2050), by using an ensemble of 16 general circulation models under RCP2.6 and RCP8.5 scenarios.

More warming and drought will be experienced under RCP8.5 than RCP2.6 scenario. The highest warming is observed at the Southern stations. However, the lowest precipitation is projected in the western stations. The results of SPEI calculation indicate that the severity of drought spread progressively across time and space. The highest values were observed over 2050 with values varied between 0.15 and −2.08 under RCP2.6 scenario, and range from −0.73 to −2.63 under RCP8.5. These results indicate that Algeria is highly vulnerable to the impact of climate change on water resources, which stressed the need to develop a strategy against this situation.

This study is one of the first to simulate the future climate changes over 16 Algerian weather stations by using an average of 16 general circulation models data, under two RCP scenarios. This study shows the 2030 water development strategy to mitigate the effect of drought and water scarcity on different sectors.

Tackling the challenges of water scarcity requires comprehensive management according to financial, environmental and social issues. This paper aims to develop a planning approach for systematic decision-making and pay attention to uncertainties in water demand management and supply investment.

This study presents a multiobjective optimization model to manage water resources based on the balance of supply and demand. The objectives of the model include economic, social and environmental (sustainable development) factors. The model achieves an optimal urban water portfolio by using a scenario tree.

The mathematical goal programming (GP) in a multiobjective optimization model is applied and solved by the branch and bound method. The results indicate the selected supply augmentation and demand management options in each stage for 20 years according to the dry, normal and wetness year scenarios.

This model is based on a real-world case and has been implemented in the city of Karaj. It can be applied for water management of other cities concerning sustainable development as well.

This paper innovates by considering the sustainable development criteria that are defined using three objective functions, including economic, social and environmental factors. The balance of supply and demand concerning uncertainty has not been investigated in any urban water portfolios. The standardized precipitation evapotranspiration index (SPEI) is incorporated to generate different scenarios. To the best of the authors’ knowledge, this approach is used for the first time.

Using risk-related data often require a significant amount of upfront work to collect, extract and transform data. In addition, the lack of a consistent data structure hinders the development of tools that can be used with more than one set of data. The purpose of this paper is to report on an effort to solve these problems through the development of extensible, internally consistent schemas for risk-related data.

The consortia coordinated their efforts so the hazard, exposure and vulnerability schemas are compatible. Hazard data can be provided as either event footprints or stochastic catalogs. Exposure classes include buildings, infrastructure, agriculture, livestock, forestry and socio-economic data. The vulnerability component includes fragility and vulnerability functions and indicators for physical and social vulnerability. The schemas also provide the ability to define uncertainties and allow the scoring of vulnerability data for relevance and quality.

As a proof of concept, the schemas were populated with data for Tanzania and with exposure data for several other countries.

The data schema and data exploration tool are open source and, if widely accepted, could become widely used by practitioners.

A single set of hazard, exposure and vulnerability schemas will not fit all purposes. Tools will be needed to transform the data into other formats.

This paper describes extensible, internally consistent, multi-hazard, exposure and vulnerability schemas that can be used to store disaster risk-related data and a data exploration tool that promotes data discovery and use.