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In the last century, India has progressed from a famine prone country to one that is food self-sufficient. However, India's water resources are now under threat from a growing population with increasing demands, a changing climate and water mismanagement. Developing realistic and sustainable solutions to water resource management in India requires an understanding of local scale water use practices, leading to improved water management tools which incorporate and examine the potential impacts brought by changes in socio-economic and environmental conditions. This research involved the collection of field level data within four districts of the Indian Gangetic Basin; one of the most intensely populated areas of the world, improving understanding of irrigation water use practices in the region. Semi-structured interviews; a method more commonly used in social sciences and healthcare, were used to collect both qualitative and quantitative hydrological information on individuals' water use. The approach provides an effective and efficient method for the collection of information in data scarce regions along with detailed insights into the drivers behind many water use practices. The importance of collecting and incorporating local scale information into large scale understanding is also highlighted, with significant differences between modelled irrigation water requirements, and field reported volumes shown. The information collected and insights gained were used to develop a modelling framework that is capable of accounting for changes in water level and farmer income, resulting from variations in climate, farmer irrigation behaviour, water source and agricultural costs. Calibrated model outputs match observed values of groundwater levels and crop yield in each of the four districts. The modelling framework is used to investigate how predicted and plausible changes in boundary conditions may impact water resources and farmer livelihood. Results show that predicted future climate is likely to have little direct impact on water resources or farmer income, and may lead to increased water availability. Utilising this increase in precipitation through an additional abstraction event suggests an increase in crop yields of up to 0.5 tonnes/ha. Results also suggest additional abstraction is likely to be more sustainable in certain districts if managed appropriately, highlighting the need for local scale understanding and tailor-made solutions. This practice can also help decrease incidences of flooding, and reduce runoff resulting from high groundwater levels in aquifers. The research undertaken could have significant implications for model development, water resource management and policy, as well as poverty alleviation in India and similar developing world settings. Open Access