1. Digital model for estimation of flash floods using GISBy
Dr. R K SURYAWANSHI
CHIEF ENGINEER
CWC, GANDHINAGAR

2. Flood/Inflow Forecasting
WMO DEFINITION:
“The prediction of stage, discharge, time of occurrence and duration of flow
– especially at peak discharge
at a specified point on a stream
resulting from precipitation
and for snow melt ”.

3. Issues in flood forecasting
Forecast lead time
Forecast accuracy

4. To address the issues…
Physically based (deterministic) distributed model using rainfall as input with objective of increasing forecast lead time as well as accuracy.
Extensive use of GIS tools & site specific remotely sensed data for estimation of model components to address their spatial variability .
Development of simple model with minimum parameters for calibration with limited site specific data in contrast to models in vouge (SWAT,MIKE, HEC-GEOHMS etc..)

5. Typical Flood Forecasting Unit
Data collection unit
Data transmission unit
Forecast formulation unit
Forecast dissemination unit
Data bank unit
Forecast evaluation and updating unit
R&D unit

6. Aims & Objectives Aims: Objectives:
To develop flood/ inflow estimation model which would enhance the forecast lead time and the accuracy of the forecast compared with the conventional methods in vogue by using Geo-spatial technologies.
To device digital methodology for better estimation of areal rainfall, spatial runoff and more accurate flows at the outlet using GIS
Aims:
To improve the forecast lead time for advance warning :
By adopting rainfall based forecasts
To achieve better forecast accuracy:
Using physically based (Deterministic) models
Distributed approach using GIS based tools

7. Geospatial Tools & Other Software
ARC-MAP of ARC-GIS,
ERDAS IMAGINE
Spatial Analyst (IDW)
ARC-CN / RUN-OFF tools
ANN - ALYUDA NEURO-INTELLIGENCE 2.2 (577)
FORTRAN CODE (Parameter optimization)
MS-EXEL
MS-Office (MS-WORD & MS-POWER POINT)

8. Study Basin

9. Study Basin Features Panshet reservoir catchment (Krishna basin)
Basin area :116 sq km (Length : 30 km & width : about 4 km)
Area is mostly hilly with stiff slopes& Major land use :forest
Average annual rainfall : 2500 mm
Raingauge stations : Four
Reservior level recorder at the dam site
Reservoir storage is about 300 Mm3
Major issue : Reservoir operation during flash floods

10. Hydrological Network

11. Storm Events Event No. Storm Period Month Storm Duration (Hrs)
Time step
Total
Rainfall
(mm)
Obs
Runoff
Runoff factor - 1
July-86 66 3
192
100
0.52 2
July-89 63
529
307
0.58 57
266
166
0.62 4
Aug-90 51 92 55
0.60 5 75
250
201
0.80 6
362
219 7
162
101 8
179
126
0.70 9 54 89
0.61

12. Rainfall Analysis Objective : Inputs :
Conversion of point rainfall to areal rainfall using GIS based model and compare the results with other methods.
Inputs :
Point rainfall data of four stations for three hrly durations
Tool used :
Geospatial rainfall distribution (Digital rainfall analysis)
Using (IDW –ARCMAP)
Other tools used :
Thiessen polygon method, Arithmatic mean method
Comparative analysis:
Mean variation, scatter plots

13. Rainfall Analysis R=
Digital rainfall distribution

14. Rainfall Analysis Results`

15. Runoff Estimation Event wise areal rainfall as input
SCS – CN equation for runoff estimation
Q =[CN (P+2) –200 ]2/CN[CN(P-8) + 800]
Subject to, P > (200/CN)-2, Q = 0, otherwise
Where
Q : runoff depth ,CN : curve no [0 to 100],P : rainfall depth
CN estimation
Development of Land use -soil clip
Lookup Table for AMC –II condition
CN/runoff layers
Estimation of basin runoff depths for each rainfall input

16. Runoff Estimation
FLOW CHART
SOURCE: (ZHAN ET AL 2004-ELSEVIER LTD.).

17. Runoff Estimation
Land Use & Soil Layers

18. Runoff Estimation Deriving runoff layer
Q =[CN (P+2) –200 ]2/CN[CN(P-8) + 800]

19. Flow Estimation
Objective: Conversion of runoff depths into flow at the outlet Input: Runoff depths as obtained using various models Output: Flow at the outlet Tools: GIS tools for Clark’s approach Distributed flow (digitized isochrones) Parameter estimation /convolution : Fortran code Comparative analysis : with observed runoff Mean Relative Error, correlation Coef, Scatter plots

20. Digitized isochrones & Time area histogram
Flow Estimation
Digitized isochrones & Time area histogram

21. Flow Estimation Results

22. Flow Estimation Evaluation
Mean Relative Error( MRE)
Scatter plots
Correlation Coefficient

23. Results & Discussions From the analysis it is seen that,
The areal distribution of the rainfall using digital method with inverse distance weights (IDW) tool in ARC GIS gives better results as compared to the areal rainfall hyetographs obtained using conventional methods.
More accurate estimation of runoff for the storm event has been attempted using deterministic and distributed approach which takes into account spatially variable basin properties like land use, land cover and antecedent moisture condition (AMC) adopting the SCS method using ARC-CN (ARC-GIS) tool.
The flows estimated using deterministic /distributed method (Clark’s approach) are comparatively closer to the observed values.
This study developed the digital model including the three components of the process that needs calibration of a single parameter i.e. storage coefficient (R) as the other parameters like CN and Tc being generalized or estimated for the given basin.

24. 2006 EVENT -SURAT

25. THANK YOU