New Approaches to Hydrological Prediction in Data-sparse Regions

When data are scarce, hydrological predictions become unreliable, mainly due to the inability to specify model components and parameter values that consistently represent the dominant hydrological processes in a particular basin, and also due to the lack of high quality model forcing. This is a problem in developed and developing countries, and the focus of much research worldwide. These papers reflect differing aspects of, and approaches to, the problem and are grouped accordingly: Hydrological modelling in poorly gauged and ungauged basins; Hydrometeorology and climate change assessment; Remote sensing applications in hydrology; and Characterizing rainfall variability and its impacts on hydrological modelling.

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The areas that we publish in include:

• Ground water
• Surface water
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• Drought and desertification
• Runoff modelling
• Watershed
• Remote sensing
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• Ecohydrology/hydro-ecology
• Erosion and sediment
• Tracer hydrology