Groundwater Asia

Mapping Groundwater Resilience to Climate Change and Human Development in Asian Cities
Mapping Groundwater Resilience to Climate Change and Human Development in Asian Cities
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About Project

Groundwater plays an important role in the sustainable development of major cities in Asia. The strategic importance of groundwater for the city’s water supply will probably intensify under climate change and human development (population growth, urbanization) in the future. Therefore, it is imperative to assess the resiliency of groundwater under climate change and human development for strategic planning and management of water resources in urban areas. The outputs of the project will enhance the understanding of the impact of climate change and human development on groundwater system and will help to provide transparency in identifying the vulnerable or sensitive part of the system which will significantly enhance the chances of developing strategies for preparedness, response, and recovery against disruptive events.

Project objectives

The aim of the project is to improve understanding of the impacts of climate change and human development on groundwater resources and local demand. The project will develop policy recommendations for sustainable groundwater development and management that will support adaptation and build resilience. There are four key objectives:

August 2016
Considerable uncertainty occurs in the parameter estimates of traditional rainfall–water level transfer function noise (TFN) models, especially with the models built using monthly time step datasets. This is due to the equal weights assigned for rainfall occurring during both water level rise and water [...]
January 2019
Groundwater level prediction and forecasting using univariate time series models are useful for effective groundwater management under data limiting conditions. The seasonal autoregressive integrated moving average (SARIMA) models are widely used for modeling groundwater level data as the groundwater level signals possess the seasonality [...]
April 2020
Discrete groundwater level datasets are interpolated often using kriging group of models to produce a spatially continuous groundwater level map. There is always some level of uncertainty associated with different interpolation methods. Therefore, we developed a new trend function with the mean groundwater level [...]

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