Global Data for Watershed Modeling: The Case of Data Scarcity Areas

  • Abdelhamid FadilEmail author
  • Abdelali El Bouchti
Part of the Advances in Science, Technology & Innovation book series (ASTI)


Data availability is a main element in determining the watershed modeling success. This factor becomes more critical in the case of using spatial models that require space-time distributed data. In developing countries, the implementation of such approaches is often hampered by data scarcity. To deal with this situation, the use of global data captured by earth observation satellites is considered as a major issue. This work aims to show the utility of using this type of information in data scarcity areas, especially for spatial modeling of large watersheds. To estimate the global data contribution, an analysis was performed by comparing them with local measured data. The study focuses on data representing the watershed state (morphological properties) and the input variables of hydrological models (climate data). The quality assessment of these data is calculated through statistical indicators. The comparison of global data grids with local observations shows the utility of using some of these grids for watershed modeling and especially for the state parameters such as topography. For climate parameters, the comparison is very appropriate for the minimum and maximum temperature, and moderate for the humidity and solar radiation but low or very low for rainfall and wind speed data. This work reveals that if global data derived from satellites are an alternative and very promising solution to overcome data scarcity in some areas, they still need to be enhanced to make them more efficient and accurate, especially for climate data.


Global data Data scarcity Spatial data Climate data GIS Remote sensing Modeling Watershed Morocco 


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© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Laboratory of Systems Engineering (LaGes)Hassania School of Public WorksCasablancaMorocco
  2. 2.Institute for Forecasting and Futuristics (I2F)CasablancaMorocco

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