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Hydrological Modelling with Remote Sensing

Elena Tarnavsky

ISBN 10: 3844382194 / ISBN 13: 9783844382198
Published by LAP LAMBERT Academic Publishing
New Condition: New Soft cover
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Paperback. 292 pages. Dimensions: 8.7in. x 5.9in. x 0.7in.This work investigates the hydrological aspects of desertification in drylands through water balance modelling. Rainfall, as the main water input to dryland hydrology, is characterised by strong variability over small spatial and temporal scales and determines water available as surface runoff, groundwater recharge and soil moisture. Thus, the focus here is on improving the realism of rainfall representation through optimal use of newly available remote sensing datasets. The hydrological importance of improved rainfall representation is investigated through modelling simulations using a dynamic, process-driven water balance model, DryMOD, applied in two distinctly different catchments in Tunisia and Senegal, respectively. The improved representation of rainfall in model-based scenarios helped to investigate small-scale variability of simulated rainfall, to identify runoff-generating areas, and to analyse the spatial distribution and seasonal variability of runoff and soil moisture all factors of paramount importance to water resource management in drylands. This item ships from multiple locations. Your book may arrive from Roseburg,OR, La Vergne,TN. Bookseller Inventory # 9783844382198

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Bibliographic Details

Title: Hydrological Modelling with Remote Sensing

Publisher: LAP LAMBERT Academic Publishing

Binding: Paperback

Book Condition:New

Book Type: Paperback

About this title

Synopsis:

This work investigates the hydrological aspects of desertification in drylands through water balance modelling. Rainfall, as the main water input to dryland hydrology, is characterised by strong variability over small spatial and temporal scales and determines water available as surface runoff, groundwater recharge and soil moisture. Thus, the focus here is on improving the realism of rainfall representation through optimal use of newly available remote sensing datasets. The hydrological importance of improved rainfall representation is investigated through modelling simulations using a dynamic, process-driven water balance model, DryMOD, applied in two distinctly different catchments in Tunisia and Senegal, respectively. The improved representation of rainfall in model-based scenarios helped to investigate small-scale variability of simulated rainfall, to identify runoff-generating areas, and to analyse the spatial distribution and seasonal variability of runoff and soil moisture – all factors of paramount importance to water resource management in drylands.

About the Author:

PhD Geography, King's College London. She has worked in academic research and private consulting before joining the TAMSAT Research Group at the Meteorology Department, University of Reading, where the main focus of her work is the research and development of satellite data for agro-meteorological modelling applications in Africa.

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