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ASSESSMENT OF FLOOD POTENTIAL IN VISHWAMITRI RIVER BASIN USING REMOTE SENSING & GIS, GUJARAT. Devanshi P. Gosai1, Dr. G. S. Joshi2, IndraPrakash3, Ajay Patel4

Abstract: The flood hazard maps depict the vulnerable area during extreme flood events. For preparation of flood disaster management plan of a city and a nearby area, the local authority should have the knowledge of the flood-vulnerable areas in the city and nearby region. The map of the flood plain zone may be available at national or a Global level but task of identifying the flood plain zone at a micro level is yet to be done. Assessment of the runoff potential is the preliminary step towards identifying / delineating the flood plain zone. The attempt has been made in this study towards preparation of the runoff potential maps in the Vishwamitri basin. It is necessary to identify the flood potential area (flood pockets) so as to prepare the flood action plan of a city. Vadodara is located in a lower Vishwamitri basin. The assessment of the flood potential has been carried out in this study in the vishwamitri basin using remote sensing and Geographic information system (GIS). Keywords: GIS; thematic maps; DEM; geospatial data; runoff potential; Flood at community level. INTRODUCTION Flood is among the most devastating natural hazards in the world claiming lives and properties more than any other natural phenomena. Flood is a state of high water level along a river channel or on coast that leads to inundation of land which is not normally submerged. Flood is an attribute of physical environment and thus is an important component of hydrological cycle of drainage basin. Flood is a natural phenomenon in response to heavy rainfall but it becomes a hazard when it inflicts loss to the lives and properties of the people. Geographic Information System is a tool that can assist floodplain managers in identifying flood prone areas in their community. With a GIS, geographical information is stored in a database that can be queried and graphically displayed for analysis. By overlaying or intersecting different geographical layers, flood prone areas can be identified and targeted for mitigation floodplain management practices. Remote Sensing can be very effective for flood management in the following way: 1 Devanshi P. Gosai, ME Student, Hydraulic Structures, Department of Civil Engineering, Maharaja Sayajirao University, Vadodara, India, Email:[email protected] 2 Dr. G.S.Joshi, Associate Professor, Department of of Civil Engineering, Maharaja Sayajirao University, Vadodara, India, Email:[email protected] 3 IndraPrakash, Faculty, Bhaskaracharya Institute for Space Applications and Geoinformatics (BISAG), Gandhinagar, India, Email:[email protected] 4 Ajay Patel, Manager, Bhaskaracharya Institute for Space Applications and Geoinformatics (BISAG), Gandhinagar, India, Email:[email protected]

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Recent Advances in Civil Engineering (RACE 2016)

Assessment Of Flood Potential In Vishwamitri River Basin Using Remote Sensing & GIS,Gujarat

 

Detailed mapping that is required for the production of hazard assessment maps and for input to various types of hydrological models. Developing a larger scale view of the general flood situation within a river basin with the aim of identifying areas at greatest risk and in the need of immediate assistance.

In this study, a modern approach involving the use of a simple hydrological model appropriate for data scarce environment in a GIS is proposed to map the runoff potential. STUDY AREA The Vishwamitri basin is a part of Dhadhar basin, which extends over an area of 3423 sq km, located in the state of Gujarat. It raises in the Pavagadh hills. The total length of the river from the head to its outfall into the Dhadhar is about 80 km. In this study, the vishwamitri basin is selected for the assessment of the flood potential. Vadodara is the largest urban centre in the basin and is divided by river in two parts like Eastern and Western Part [3]. As the city of vadodara is lying in the lower vishwamitri basin, the study is carried out at community level to identify the flood potential in the city of vadodara and in the basin. The map of vishwamitri basin is shown in figure 1.

Figure 1. Study area 555 2

Recent Advances in Civil Engineering (RACE 2016)

Assessment Of Flood Potential In Vishwamitri River Basin Using Remote Sensing & GIS,Gujarat

METHODOLOGY

Development of flood hazard maps has habitually been through the integration of spatial layers indicating flood causal factors (e.g., percentage slope, characteristics of soil, land use, rainfall etc) in a Geographic Information System (GIS) environment [1]. For this study, a modified version of the rational hydrological model is used to estimate the runoff based on rainfall intensity, the area of Land use/Land cover type within catchments and a runoff coefficient [2]. The Rational model being most simple and easy of implementation, have been widely use to calculate the peak surface runoff rate in a drainage basin. The rational model converts rainfall in a catchment into runoff by determining the product of the rainfall intensity in the catchment and its area, reduced by a runoff coefficient (C, between 0 and 1), which is a function of the soil, land cover and slope in the study catchment. The runoff coefficient, which is the most critical parameter in the rational model, provides an estimation of how much water (rainfall) is lost due to infiltration (soil), interception and evapotranspiration (land cover). Thus, the runoff coefficient of a catchment can be considered as the fraction of rainfall that actually becomes storm water runoff. Accurate determination of this parameter is, therefore, vital to the successful implementation of this method. The rational model operates on a number of assumptions including:  The entire unit of analysis is considered as a single unit.  Rainfall is uniformly distributed over the drainage area.  Predicted peak runoff has the same probability of occurrence (return period) as the used rainfall intensity (I).  The runoff coefficient (C) is constant during the rain storm. The Rational model is given by the equation: = 0.28 x C x I x A

(1)

where, = Peak runoff rate ( /sec) C = Runoff coefficient (-) I = Rainfall intensity (mm/hr) A = Drainage area (K ) Determitation of flood casual factors In this study, spatial layers of land use and land cover, soil and slope were analyzed to accurately determine the runoff co-efficient prior to the implementation of Equation (1). The sections below (3.1.1 to 3.1.4) details the methodology used to determine flood casual factors. Land Use/Land Cover (LULC) The type of LULC in an area determines how much rainfall infiltrates the soil and how much becomes runoff. Impervious surfaces such as concretes have runoff coefficients approaching one while surfaces with vegetation to intercept rainfall and promote water infiltration have lower runoff coefficients. There is a direct relationship between land cover and hydrological 556 3

Recent Advances in Civil Engineering (RACE 2016)

Assessment Of Flood Potential In Vishwamitri River Basin Using Remote Sensing & GIS,Gujarat

parameters of interception, infiltration, runoff and concentration which ultimately influence flooding. The Land use data available at BISAG have been incorporated in ArcGIS software and Land use/Land cover map is developed. In this study area, there are five classes: (1) Agriculture (2) Built-up (3) Prosophis (4) Wastelands (5) Water bodies as shown in Figure 2. Digital Elevation Model (DEM)/Slope A study area with a greater slope will have more runoff and thus a higher runoff coefficient than a study area with a lower slope. The probability of a flood increases with decreasing elevation and hence is a strong indicator for flood susceptibility. In this study, DEM was converted in percentage slope by using GIS application. In accordance with standardized tables for calculating runoff coefficient, the slope map was reclassified into three classes; (1) areas with slope less than 2%; (2) areas with slope between 2% and 6% and (3) areas with slope greater 6% as shown in Figure 3. The Digital Elevation Model data is available at BISAG have been incorporated in ArcGIS software and slope map is developed. Soil Type and Texture Soils that have a high clay content do not allow very much infiltration and thus have relatively high runoff coefficients, while soils with high sand content have higher infiltration rates and low runoff coefficients. The Natural Resource Conservation Service of the United States has classified four broad hydrological soil groups that provide useful information in determining study area runoff coefficients. Based on the soil texture attribute information, the extracted soil maps of the study areas were reclassified into the four main soil hydrological groups (A to D) defined by the United States Soil Conservation Service [6]. The soil data is available at BISAG have been incorporated in ArcGIS software and soil map is developed and reclassified into four hydrological soil groups: (A) sandy loamy (B) fine sand (C) fine loamy (D) clayey as shown in Figure 4. Rainfall Heavy rainfall is one of the major causes of floods. The probability of a flood increases with increasing rainfall within a specified time period. The daily Rainfall data of three rain gauge stations i.e., Vadodara, Pilol and Wadala Tank, are collected from State Water Data Centre (SWDC) and used for determining maximum rainfall intensity for this study. The maximum rainfall intensity map is developed in ArcGIS using Thiessen Polygon tool.

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Recent Advances in Civil Engineering (RACE 2016)

Assessment Of Flood Potential In Vishwamitri River Basin Using Remote Sensing & GIS,Gujarat

Figure 2. Land use/ Land cover map of study area

Figure 3. Slope map of study area 558 5

Recent Advances in Civil Engineering (RACE 2016)

Assessment Of Flood Potential In Vishwamitri River Basin Using Remote Sensing & GIS,Gujarat

Figure 4. Soil map of study area

Development of Peak Runoff Map

In this study area, different land cover type, slope and soil group exists. In order to find representative runoff coefficients within a given land cover, runoff coefficient is determined using the areas of the different LULC type and then the hydrologic soil group, and slope. The classical application of the rational model requires treating the entire catchment as a single unit and thus, does not lead to spatial variability of the runoff and for that matter, flood risk within catchment. In this study, however, a technique is introduced where the various classes of LULC type within the catchment is used as the unit of analysis to ensure spatially explicit assessment of flood risk. In brief, the area of the various LULC classes was computed and peak runoff estimated for each cover type. Although this approach has some limitation especially regarding catchment boundaries where a land use/cover type crosses the boundaries, it was found to be conceptually and operationally better than implementing the rational model in its raw form which can only give single peak runoff. A runoff coefficient map is first generated by vectoring the reclassified layers of LULC, slope and soil layers and overlaying them in a GIS. The overlay resulted in multiple polygons each having a unique LULC, soil and slope class. Table 1 specifies a runoff coefficient for a combination of LULC, soil type and slope. The runoff coefficient map is developed as a 559 6

Recent Advances in Civil Engineering (RACE 2016)

Assessment Of Flood Potential In Vishwamitri River Basin Using Remote Sensing & GIS,Gujarat

resultant of overlay layers of LULC, slope and soil type. This layer of runoff coefficient is eventually rasterized for subsequent analysis. A vector later of the catchment consisting the areas of each runoff coefficient value is rasterized. Once the raster layers of the runoff coefficient (C), rainfall intensity (I) and areas of the polygon for runoff coefficient value (A) is ready, the runoff peak layer is calculated by implementing Equation (1) in a GIS using raster algebra. The Peak runoff map derived as above is shown in Figure 5. The peak runoff map so generated shows the flood (runoff) potential of the vishwamitri river basin. LULC Slope (%)

Table 1. Runoff coefficient Table (Source: Knox County Tennessee)[4] Runoff Coefficient Soil Group A 6

Soil Group B 6

Soil Group C 6

Soil Group D 6

Agricultural

0.14

0.18

0.22

0.16

0.21

0.28

0.20

0.25

0.34

0.24

0.29

0.41

Prosophis

0.15

0.25

0.37

0.23

0.34

0.45

0.30

0.42

0.52

0.37

0.50

0.62

1

1

1

1

1

1

1

1

1

1

1

1

Builtup

Wasteland

Water bodies

0.33

0.65

0.37

0.67

0.40

0.69

0.35

0.66

0.39

0.68

0.44

0.70

0.38

0.68

0.42

0.70

Figure 5. Runoff Potential Map of study area 560 7

0.49

0.72

0.41

0.69

0.45

0.72

0.54

0.75

Recent Advances in Civil Engineering (RACE 2016)

Assessment Of Flood Potential In Vishwamitri River Basin Using Remote Sensing & GIS,Gujarat

RESULT AND CONCLUSION

The study has applied flood modeling approaches to demonstrate the feasibility of flood modeling in data scarce environments and limited resources. In this study, the maps for flood casual factors, namely, slope, land use/land cover, characteristics of soil have been developed in ArcGIS. The runoff coefficient map is first generated by vectoring the reclassified layers of LULC, slope and soil layers and overlaying them in a GIS. The rainfall intensity map is also developed in ArcGIS using Thiessen Polygon tool.

The peak runoff map is generated by allowing integration of the generated runoff coefficient map and the rainfall intensity map using equation (1) in Raster algebra. The peak runoff map so generated shows various flood potential areas (flood pockets) in the city of vadodara and the entire vishwamitri river basin. This map will help to prepare the flood action plan of a city of vadodara in vishwamitri basin. REFERENCES

1. ArcGIS Desktop Help 9.3, Contents-Mapping and visualization in ArcMap. 2. Daniel Asare-Kyei, Gerald Forkuor, Valentijn Venus, Modeling Flood Hazard Zones at the Sub- District Level with the Rational Model Integrated with GIS and Remote Sensing Approaches. 3. Knox County Tennessee. Stormwater Management Manual, section on the Rational Method, Volume 2 Technical Guidance. 4. Uwem J. Ituen, Imoh Johnson, Ndifreke Nyah, flood hazard assessment and decisions support using geographic information system: a case study of uyo capital city, akwa ibom state, Nigeria. 5. United States Department of Agriculture (USDA). Hydrologic Soil Groups. In Part 630: National Engineering Handbook; USDA: Washington, DC, USA, 2007. 6. V.H.Pancholi, Dr.P.P.Lodha, Dr.Indraprakash, Khalid M., J.C.Songara, Estimation of Soil Erosion for Vishwamitri River Watershed Using Universal Soil Loss Equation and GIS.

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