Estimation of runoff through Remote Sensing






Satellite view of the study area


These Curve Number are varying as soil type and land use, For this soil is classified into four groups.

Group A : Deep sand, Deep loess, Aggregated silts
Group B : Shallow loess, sandy loam.
Group C : Clay loams, shallow sandy loam, soils low in organic content and soils usually high in clay
Group D : Soils that swell significantly when wet, heavy plastic clays, and certain saline soils.



Landuse / landcover of surrounding area of Delhi


The value of CN for various land uses on these soil types are given in TABLE 1

click here to view large size table


Methodology
First of all overlays for landuse and soil is generated from RS data of the given area. Then CN value is obtained from the Table 1. This CN value is used in equation (6) and value of S is obtained .By using this value of S in equation (5) direct runoff is calculated in terms of precipitation.

Experiment
In this study the satellite LISS III imagery of surrounding area of Delhi like Gajiabad is interpreted for generating Landuse / landcover map, Geomorphological map, and Soil map. The Soil type of study area comes under Group C. Now according to landuse weighted CN value is calculated as given in table 2.

LANDUSE SOIL GROUP - C
1.Agricultural Land Percentage CN Value Product
75% 78 5850
2.Residential (65% impervious) 15% 90 1350
3.Forest 5% 77 385
4.Water bodies 3% 100 300
5.Roads with curbs and storm sewer 2% 98 196
Total = 8081


Thus weighted CN value = 8081/ 100 = 80.81
S = ((1000 / CN) - 10 ) = 12.37 inches .
substituting the value of S in equation (6)
Pe = ((P - (0.2*12.37) )2 ) / (P +(0.8*12.37))

Pe = ( P - 2.474 )2 / ( P + 9.896)
Assume collective precipitation is 5 inches.
Then Pe = 0.428 inches

Conclusion
However this approach does not give aquarate result, because the runoff not only depends upon the precipitation but also upon the recharge of the basin, but this gives more and more reliable result as the imperviousness of the drainage area increases the value of CN increases upto 100. This is a less time consuming approach. This can be used in the design of storm water drains design of dam, flood-forecasting etc.

References
  1. Applied Hydrology by Ven Te Chow , David R. Maidment and Larry W. Mays.
  2. Hydrology and water resources engineering by S. K. Garg.
  3. ASCE , Journal of Hydrology JAN 1999
  4. Remote sensing and image Interpretation By Lillisand and Keifer.
  5. Proceedings of ISRS Symposium 1999
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