E3S Web Conf.
Volume 167, 20202020 11th International Conference on Environmental Science and Development (ICESD 2020)
|Number of page(s)||7|
|Published online||24 April 2020|
Estimation of surface runoff using NRCS curve number in some areas in northwest coast, Egypt
National Authority for Remote Sensing and Space Sciences (NARSS), Cairo, Egypt
2 Soil and Water Use Department, Agricultural and Biological Research Division, National Research Centre, Cairo 12622, Egyp
3 Soil Science Department, Faculty of Agriculture, Zagazig University, Zagazig, Egypt.
* Corresponding author: firstname.lastname@example.org
The sustainable agricultural development in the northwest coast of Egypt suffers constantly from the effects of surface runoff. Moreover, there is an urgent need by decision makers to know the effects of runoff. So the aim of this work is to integrate remote sensing and field data and the natural resource conservation service curve number model (NRCS-CN).using geographic information systems (GIS) for spatial evaluation of surface runoff .CN approach to assessment the effect of patio-temporal variations of different soil types as well as potential climate change impact on surface runoff. DEM was used to describe the effects of slope variables on water retention and surface runoff volumes. In addition the results reflects that the magnitude of surface runoff is associated with CN values using NRCS-CN model . The average of water retention ranging between 2.5 to 3.9m the results illustrated that the highest value of runoff is distinguished around the urban area and its surrounding where it ranged between 138 - 199 mm. The results show an increase in the amount of surface runoff to 199 mm when rainfall increases 200 mm / year. The north of the area may be exposed to erosion hazards more than the south and a change in the soil quality may occur in addition to the environmental imbalance in the region.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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