Digital model for estimation of flash floods using GIS By Dr. R K SURYAWANSHI CHIEF ENGINEER CWC, GANDHINAGAR rksurya2000@yahoo.com 9879200530

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 ”.

Issues in flood forecasting Forecast lead time Forecast accuracy

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..)

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

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

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)

Study Basin

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

Hydrological Network

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

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

Rainfall Analysis R= Digital rainfall distribution

Rainfall Analysis Results `

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

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

Runoff Estimation Land Use & Soil Layers

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

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

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

Flow Estimation Results

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

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.

2006 EVENT -SURAT

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