impacts of land use-land cover change and …impacts of land use–land cover change and...

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Impacts of land useland cover change and urbanization on ooding: A case study of Oshiwara River Basin in Mumbai, India P.E. Zope, T.I. Eldho , V. Jothiprakash Department of Civil Engineering, Indian Institute of Technology Bombay, Mumbai 400076, India abstract article info Article history: Received 13 June 2015 Received in revised form 14 May 2016 Accepted 6 June 2016 Available online 9 June 2016 In the present study, the impact of land useland cover (LULC) change and urbanization on oods are investigat- ed for an expanding urban catchment of the Oshiwara River in Mumbai, India. For the study area, the land use change was estimated between 1966, 2001 and 2009 by using the topographic map and satellite images. The analysis of LULC change revealed that the change between 1966 and 2001 was slower than that between 2001 and 2009. The LULC analysis revealed a 74.84% increase in the built up area with a 42.8% decrease in open spaces between the years 1966 and 2009, with substantial increase in urbanization. The impact of LULC on ood hydrograph for different return periods was ascertained by using the HEC-GeoHMS and HEC-HMS models. In the past 43 years, the increase in peak runoff and runoff volume is marginally varied by 3.0% and 4.45% for the 100-year return period and 10.4% and 12.2% for the 2-year return period respectively, although the built-up area increased by 74.84%. The ood inundation area is increased by 5.61% for the 100-year return period and 6.04% for the 10-year return period between the same time period. The results showed that lower return periods led to a maximum change in peak discharge/volume of runoff compared to higher return periods for change in land use conditions. Further, a ood hazard analysis has been carried out and it showed that the area in highly hazardous zone is increased by 64.29% as compared to less hazardous zone where it is decreased by 32.14%. Over- all, the total ood hazard area is increased by 22.27%. The developed ood plain and ood hazard maps can be used by the local Municipal body to prepare ood mitigation and early evacuation management plans during oods and as a criteria for insurance of any property by insurance organizations. © 2016 Elsevier B.V. All rights reserved. Keywords: Land useland cover change Flood plain Urbanization Hazard map Hydrologic model Mitigation 1. Introduction Migration of people from rural to urban areas causes an increase in population and urbanization. Urbanization is the main cause of changes in hydrologic and hydraulic processes, loss of existing drainage capacity and ooding in urban areas. It increases the total runoff volume and peak discharge of storm runoff events (Dewan and Yamaguchi, 2009; Ali et al., 2011; Sayal et al., 2014; Miller et al., 2002). The LULC change is inuenced by humans trying to meet various needs such as residen- tial, industrial, agricultural, mining and other infrastructural facilities and are major concerns associated with the economic and sustainable growth of an area (Zubair, 2006; Rawat et al., 2013). Correct use of every part of available land is very essential to improve the economic condition of an area without further deterioration (Chaurasia et al., 1996; Rawat et al., 2013). LULC change and its implication on hydrolog- ical processes have been prominent research topics in the recent times (Amini et al., 2011; Chen et al., 2009; Fox et al., 2012). Sayal et al. (2014) concluded that for the entire study area of Konar catchment, in- crease in peak discharge for the LULC scenario from the year 1976 to 2004 was 1023.3 m 3 /s to 1194.7 m 3 /s and decrease in the time to peak was 1 h and 10 min. Owrangi et al. (2014) developed a method which can be effectively used to raise early land use change awareness and facilitate ood risk management. Urban ooding has become a haz- ard globally and inuences the future development. The major changes in the rainfall pattern occurring due to climate change will further in- crease the ood risk (Guhathakurta et al., 2011; Kulkarni et al., 2013). Integration of hydrological models such as HEC-HMS and traditional statistical tests, where data is available, is useful for analyzing the im- pact of LULC (Lambin, 1997; Lopez et al., 2001; Lorup et al., 1998; Legesse et al., 2003; Saghaan et al., 2008; Zope et al., 2015). Most of urban cities in the coastal regions of India, such as Mumbai and Chennai, are vulnerable to ooding because of increased frequency of heavy rain- fall for a short duration coinciding with the tidal variations (Kulkarni et al., 2014a). Satellite images are the important source of data to monitor LULC with remote sensing (Coppin and Bauer, 1996; Galford et al., 2008; Jensen et al., 1995; Seto et al., 2002; Woodcock et al., 2001; Zhu and Woodcock, 2014). The accuracy of the terrain model depends on the Catena 145 (2016) 142154 Corresponding author. E-mail addresses: [email protected] (P.E. Zope), [email protected] (T.I. Eldho), [email protected] (V. Jothiprakash). http://dx.doi.org/10.1016/j.catena.2016.06.009 0341-8162/© 2016 Elsevier B.V. All rights reserved. Contents lists available at ScienceDirect Catena journal homepage: www.elsevier.com/locate/catena

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Page 1: Impacts of land use-land cover change and …Impacts of land use–land cover change and urbanization on flooding: A case study of Oshiwara River Basin in Mumbai, India P.E. Zope,

Catena 145 (2016) 142–154

Contents lists available at ScienceDirect

Catena

j ourna l homepage: www.e lsev ie r .com/ locate /catena

Impacts of land use–land cover change and urbanization on flooding: Acase study of Oshiwara River Basin in Mumbai, India

P.E. Zope, T.I. Eldho ⁎, V. JothiprakashDepartment of Civil Engineering, Indian Institute of Technology Bombay, Mumbai 400076, India

⁎ Corresponding author.E-mail addresses: [email protected] (P.E. Zope), eldh

[email protected] (V. Jothiprakash).

http://dx.doi.org/10.1016/j.catena.2016.06.0090341-8162/© 2016 Elsevier B.V. All rights reserved.

a b s t r a c t

a r t i c l e i n f o

Article history:Received 13 June 2015Received in revised form 14 May 2016Accepted 6 June 2016Available online 9 June 2016

In the present study, the impact of land use–land cover (LULC) change and urbanization on floods are investigat-ed for an expanding urban catchment of the Oshiwara River in Mumbai, India. For the study area, the land usechange was estimated between 1966, 2001 and 2009 by using the topographic map and satellite images. Theanalysis of LULC change revealed that the change between 1966 and 2001 was slower than that between 2001and 2009. The LULC analysis revealed a 74.84% increase in the built up area with a 42.8% decrease in open spacesbetween the years 1966 and 2009, with substantial increase in urbanization. The impact of LULC on floodhydrograph for different return periods was ascertained by using the HEC-GeoHMS and HEC-HMS models. Inthe past 43 years, the increase in peak runoff and runoff volume is marginally varied by 3.0% and 4.45% for the100-year return period and 10.4% and 12.2% for the 2-year return period respectively, although the built-uparea increased by 74.84%. The flood inundation area is increased by 5.61% for the 100-year return period and6.04% for the 10-year return period between the same time period. The results showed that lower return periodsled to a maximum change in peak discharge/volume of runoff compared to higher return periods for change inland use conditions. Further, a flood hazard analysis has been carried out and it showed that the area in highlyhazardous zone is increased by 64.29% as compared to less hazardous zonewhere it is decreased by 32.14%. Over-all, the total flood hazard area is increased by 22.27%. The developed flood plain and flood hazard maps can beused by the local Municipal body to prepare flood mitigation and early evacuation management plans duringfloods and as a criteria for insurance of any property by insurance organizations.

© 2016 Elsevier B.V. All rights reserved.

Keywords:Land use–land cover changeFlood plainUrbanizationHazard mapHydrologic modelMitigation

1. Introduction

Migration of people from rural to urban areas causes an increase inpopulation and urbanization. Urbanization is themain cause of changesin hydrologic and hydraulic processes, loss of existing drainage capacityand flooding in urban areas. It increases the total runoff volume andpeak discharge of storm runoff events (Dewan and Yamaguchi, 2009;Ali et al., 2011; Sayal et al., 2014; Miller et al., 2002). The LULC changeis influenced by humans trying to meet various needs such as residen-tial, industrial, agricultural, mining and other infrastructural facilitiesand are major concerns associated with the economic and sustainablegrowth of an area (Zubair, 2006; Rawat et al., 2013). Correct use ofevery part of available land is very essential to improve the economiccondition of an area without further deterioration (Chaurasia et al.,1996; Rawat et al., 2013). LULC change and its implication on hydrolog-ical processes have been prominent research topics in the recent times(Amini et al., 2011; Chen et al., 2009; Fox et al., 2012). Sayal et al.

[email protected] (T.I. Eldho),

(2014) concluded that for the entire study area of Konar catchment, in-crease in peak discharge for the LULC scenario from the year 1976 to2004 was 1023.3 m3/s to 1194.7 m3/s and decrease in the time topeak was 1 h and 10 min. Owrangi et al. (2014) developed a methodwhich can be effectively used to raise early land use change awarenessand facilitate flood riskmanagement. Urban flooding has become a haz-ard globally and influences the future development. The major changesin the rainfall pattern occurring due to climate change will further in-crease the flood risk (Guhathakurta et al., 2011; Kulkarni et al., 2013).Integration of hydrological models such as HEC-HMS and traditionalstatistical tests, where data is available, is useful for analyzing the im-pact of LULC (Lambin, 1997; Lopez et al., 2001; Lorup et al., 1998;Legesse et al., 2003; Saghafian et al., 2008; Zope et al., 2015). Most ofurban cities in the coastal regions of India, such asMumbai and Chennai,are vulnerable to flooding because of increased frequency of heavy rain-fall for a short duration coinciding with the tidal variations (Kulkarni etal., 2014a).

Satellite images are the important source of data to monitor LULCwith remote sensing (Coppin and Bauer, 1996; Galford et al., 2008;Jensen et al., 1995; Seto et al., 2002; Woodcock et al., 2001; Zhu andWoodcock, 2014). The accuracy of the terrain model depends on the

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143P.E. Zope et al. / Catena 145 (2016) 142–154

interpolation mechanism adopted (Arun, 2013; Eldho et al., 2006).Geospatial Information System (GIS) and remote sensing together areused as an effective tool for flood hazard delineation. They are alsoused to assess the spatial variability of flood hazard (Qi and Altinakar,2011; Pramojanee et al., 1997). River flood hazard mapping preventsloss of human life and minimizes damages to property and social dis-ruption (Alaghmand et al., 2010). In coastal cities such as Mumbai,land is scarce because they are surrounded by sea. LULC change rapidlyalters the hydrologic process with an increase in urbanization. Whenhigh-intensity rainfall coincides with high tide, the existing drainagesystem losses its capacity, thereby resulting in flood (Gupta, 2007).There are limitations in increasing the capacity of the existing drainagebecause of land availability and high tide levels (Zope et al., 2015).Storm and catchment characteristics influence the hydrological re-sponse (Yeo et al., 2004; Kalantari et al., 2014). Sharma et al. (2001)evaluated the hydrological response on runoff considering the impact

Fig. 1. (a) Location map of the study area; (b) Geometr

of soil, water conservation, alternative land use and management prac-tices by prioritizing watersheds on the basis of runoff generated. Theyfound 42.88% decrease in the runoff yield. Flood hazard maps can beused as an effective tool for water resource as well as urban planningby design engineers to assess the vulnerability of the infrastructureand residents of that area to flood events (Fernandez and Lutz, 2010).Approximately 40% of the total natural disasters worldwide are due toflooding (Ohl and Tapsell, 2000). The LULC change is the main causeof ecosystem change (Waroux, 2011; Owrangi et al., 2014). Althoughthe flood hazard disasters caused by natural calamities cannot beprevented, the magnitude of impact can be reduced (Dewan et al.,2006).Mumbai being a coastal island city, faces scarcity of land and lim-itations on horizontal growth. A small intensity of rainfall coincidingwith high tide causes major part of the city to get flooded, during therainy season, because it is influenced by the tidal effects. To overcomethese difficulties, and for the effective design of drainage system, the

y of River with tributaries and HEC-RAS Geometry.

Page 3: Impacts of land use-land cover change and …Impacts of land use–land cover change and urbanization on flooding: A case study of Oshiwara River Basin in Mumbai, India P.E. Zope,

Fig. 2. Flow chart of the methodology for flood plain and hazard analysis.

144 P.E. Zope et al. / Catena 145 (2016) 142–154

flood prone areas in the catchment have to be identified. For theflood mitigation and evacuation system planning, preparation offlood hazard maps for the maximum flood extent of different flowconditions is necessary. Tingsanchali and Karim (2005) developed

Fig. 3. DEM of the Osh

flood hazard maps for the southwest region of Bangladesh for100 year return period storm depth and found that 54% of thestudy area are in medium hazard zone, 26% in higher and 20% inlower hazard zone.

iwara River Basin.

Page 4: Impacts of land use-land cover change and …Impacts of land use–land cover change and urbanization on flooding: A case study of Oshiwara River Basin in Mumbai, India P.E. Zope,

Fig. 4. Stream ordering: (a) Strahler method; (b) Shreve method.

145P.E. Zope et al. / Catena 145 (2016) 142–154

The main objective of the present study is to assess the LULC changebetween 1966, 2001 and 2009 for the Oshiwara River catchment area inMumbai, India. The impact of the LULC on flood hydrographs for differ-ent return periods was ascertained using the HEC-GeoHMS and HEC-HMSmodels. Flood plain and flood hazardmaps for the land use patternof 1966 and 2009, with 2-, 10-, 25-, 50- and 100-year return periodswere developed. HEC-GeoRAS and HEC-RAS models were integratedwith GIS and remote sensing data.

2. Study area

The Oshiwara River and its catchment lies between the latitude 19°06′0″N to 19°12′0″N and longitude 72°48′0″E to 72°55′0″E (Fig. 1(a))inMumbai city region, India. The Oshiwara River originates from SanjayGandhi National Park and Aarey colony. This river has twomain streams

known asWalbhat Nallah and Janata Nallah. Oshiwara River consists offour tributaries, two major and two minor tributaries as shown in Fig.1(b).The total length of the main river is 7.126 km. The bed slope ofthe river from Aarey colony to the Western express highway is steep(approximately 1 in 143), and the average bed slope at the downstreamtowards outlet is relatively flat (approximately 1 in 600) (WAPCOS,2007). Encroachment along the river bank by narrowing the flow pathis the main cause of flooding. The Oshiwara River meets the ArabianSea through the Malad creek. The location of the Oshiwara River catch-mentwith other details is shown in Fig. 1(a). The total area of the catch-ment considered is 25.67 km2. The average annual rainfall for thecatchment is 2129.8 mm (FFC, 2006).

Mumbai, the financial capital of India and capital of Maharashtra isthe main trading and economic center and is developing rapidly. Withthe increasing pressure of population growth due to people migrating

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Table 1Morphological parameters of the study area.

Sr. no Morphological parameters Values

General parameters1 Area (km2) 25.672 Perimeter (km) 33.363 Length of basin (Lb) (km) 8.5

Shape parameter4 Form factor (Rf) (km2/km) 0.0915 Elongation ratio (Re) 0.676 Circularity ratio (Rc) 0.547 Compactness coefficient (Cc) 0.063

Drainage parameters8 Total stream length (km) 31.569 Total number of stream order (∑Nu) 410 Total length of all stream order (∑Lu) 31.5611 Bifurcation ratio (Rb) 312 Drainage density (Dd) 1.2313 Stream frequency (Fs) (Nu/km2) 0.7414 Length of overland flow (Lo) (km) 0.6115 Texture ratio (T) (No/km) 0.12

146 P.E. Zope et al. / Catena 145 (2016) 142–154

from all over the country, there is severe stress on land, infrastructureand water resources (Samant and Subramanyan, 1998; Gupta, 2007;Zope et al., 2015). Horizontal growth and infrastructural facilities thathelp to copewith the needs of the increasing population are limited be-cause the city faces a scarcity of land as it is surrounded by sea, hills, andcreek (Bhagat and Guha, 2006). The needs of the population are metthrough LULC change and encroachments along the flow path of rivers,thereby leading to increase in urbanization. Being a coastal city, thedrainage outlet of the main river is into the creek, which is influencedby the tidal effects. On July 26, 2005, Mumbai experienced extremelyheavy and high-intensity rainfall of 190 mm/h coinciding with hightide. The entire suburban part of the city was flooded and there washuge loss of property, lives and animals (FFC, 2006; Gupta, 2007;Gupta and Lokanadham, 2008; Zope et al., 2015).

3. Material and methods

For the study area considered, the required rainfall data were col-lected from the Indian Metrological department (IMD) and the localself–governing body, and statistical analysis was performed to estimaterainfall depths for various return periods (Kulkarni et al., 2014b). In thepresent study, the rainfall depths corresponding to 2-, 10-, 25-, 50- and100 year return periods were used for hydrologic and flood plain analy-sis. The data collected include satellite images, toposheet, and actualsurveyed data from the local self-governing body. The methodologyused is illustrated in the flow chart, given in Fig. 2. The following sec-tions describe the methodology in detail.

3.1. Rainfall runoff modeling

3.1.1. Development of digital elevation modelSince the toposheet (no. 47A/16) containing the study area does not

contain elevation contours over the catchment, the digital elevationmodel (DEM) could not be developed using the toposheet alone. There-fore Advanced Space borne Thermal and Reflection Radiometer

Table 2Runoff curve number for the study area.

Sr. no Land use types

Runoff curve number for various soilgroups

A B C D

1 Open land 49 69 76 842 Built-up area 69 76 84 923 Vegetation 35 70 79 824 Water body 100 100 100 100

(ASTER), Global Digital Elevation Model (GDEM) of Terra satellite(htpp://asterweb.jpl.nasa.gov) and the Shuttle Radar Topography Mis-sion (SRTM) (htpp://srtm.csi.cgiar.org) DEMwere used for the delinea-tion of the watershed boundary of the study area. The stream networkgenerated from the SRTM DEM gives better results than that from theASTER DEM (Kulkarni et al., 2014a). The actual surveyed data were col-lected from theMunicipal Corporation of Greater Mumbai to generate abetter geometric profile along the river cross sections. From the SRTMDEM, the points along the river alignmentwere replacedwith the actualsurveyed data points to generate a new DEM (Fig. 3). The stream net-work generated from this newDEM coincidedwith the present positionof the river alignment, and thus, accurate geometric profiles were gen-erated. Catchment and drainage networks were generated using theArc GIS extension of HEC-GeoHMS software. Using the tool terrain pro-cessing of HEC-GeoHMS software, based on the flow accumulation andproject point at outlet, sub basin delineation has been carried out. Thesub basins having common confluence are merged and thus total 17sub basins are delineated. The total area of catchment is 25.67 km2.The basin model which is the input requirement for HEC-HMS softwarewas generated by HEC-GeoHMS software with integration of Arc GIS.

3.1.2. Geomorphologic analysisThe Shrevemethod gives the total count of tributaries present in the

basin. Stream ordering was conducted using the Strahler and Shrevemethod (Singh Savindra, 1998) and is shown in Fig. 4(a) and (b).

The estimated shape and drainage parameters of the catchment areaare tabulated in Table 1.

3.1.3. Land use classification and curve number generationIn the present study, LULC changewas assessed between 1966, 2001

and 2009. The land usemap of 1966was prepared by digitizing the Sur-vey of India Toposheet No. A-47/16 surveyed in 1966 and published in1976. Arc Map 9.3.1 was used for digitization and this map was consid-ered as the base map when compared with land use change. The LULCclasses observed for the analysis were open land, built-up land, waterbody and vegetation (consisting grass cover between 50% to 85%).Landsat/ETM satellite image of 2001 and Indian Remote Sensing satel-lite P6/L-4 image of March 2009 were used to extract the LULC data.The maximum likelihood classification method was used and analysiswas conducted using ERDAS Imagine 9.0 software. The base soil mapwas obtained from the National Bureau of Soil Survey and Land UsePlanning, Nagpur and soil maps for the study area for 1966 and 2009were developed accordingly. Composite curve numbers extractedfrom the curve number maps generated for 1966 and 2009 were themain input to hydrologic analysis in HEC-HMS software. The curvenumber for different soil groups and land use types are listed in Table 2.

3.1.4. Hydrologic modeling using HEC HMSHEC-HMS model has options for infiltration, base flow, runoff and

river routing (Ali et al., 2011; USACE, 2000; Saghafian et al., 2008).The HEC-HMS model has three main models of simulation, basinmodel, metrological model and control specification (Ali et al., 2011).The catchment model containing the delineation of sub watershed,area of sub watershed, stream length, longest flow path, elevation, andslope were developed by using HEC-GeoHMS (USACE, 2003) and thesaid catchment model was then exported to the HEC-HMS model. TheSCS curve number method was adopted for infiltration. The SCS-Unithydrograph method was used for transformation and kinematic wavemethod was used for flood routing. A 24 h storm rainfall depth having2-, 10-, 25-, 50- and 100-years return periods was given as input tothe hydrological model in the HEC-HMS model. At each junction, theflood hydrograph and peak discharge were determined for differentland use conditions which will be the main input for the hydraulicmodel HEC-RAS.

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Fig. 5. Land use maps for (a) 1966; (b) 2001; (c) 2009.

147P.E. Zope et al. / Catena 145 (2016) 142–154

3.1.5. Hydraulic modeling using the 1D model (HEC-RAS)The geometry of the river was generated in Arc GIS by integrating

HEC-GeoRAS software with version 4.3.93 as a pre processer (Lastra etal., 2008). In HEC-RAS geometry data, the entire main course is dividedinto upper reach, middle reach 1, middle reach 2, lower reach 1, andlower reach 2 along with four tributaries as shown in Fig. 1(b). The ge-ometry consists of left bank, right bank, and flow paths. The cut lines

Table 3LULC changes for the study area with changes between 1966, 2001 and 2009.

S. no Land use

Area in km2 % change

1966 2001 2009 1966–20

1 Built-up land 4.73 6.79 8.27 +43.552 Vegetation 5.6 8.01 8.72 +43.043 Open land 14.84 10.64 8.49 −28.34 Water body 0.5 0.28 0.19 −44.0

were generated at equal intervals of 100 m. All these layers were thenextracted from the triangulated irregular network (TIN) generatedfrom the DEM of the study area (USACE, 2011). The geometry for theOshiwara River with the tributaries is shown in Fig. 1(b).

The Manning's roughness coefficient “n” map was prepared fromland use map by assigning the individual Manning's “n” as per landuse type. Manning's “n” were assigned for built-up land as 0.015,

in LULC

01 2001–2009 1966–2009Rate of change in LULC (%/year)

1966–2009

+31.29 +74.84 +1.7412.67 +55.71 +1.30

−14.49 −42.79 −0.99−18.0 −62.00 −1.44

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Fig. 6. Flood hydrographs at outlet for 2-, 10-, 25-, 50- and 100-year return periods forLULC of 1966.

Fig. 7. Flood hydrographs at outlet for 2-, 10-, 25-, 50- and 100-year return periods forLULC of 2009.

148 P.E. Zope et al. / Catena 145 (2016) 142–154

water body as 0.03, vegetation as 0.10 and for open land as 0.15 (Vieux,2001; Kalyanapu et al., 2009; Zope et al., 2015). Geometry data werethen exported into HEC-RAS 1-D hydrodynamic model for further hy-draulic analysis. The Saint Venant equations were used in the HEC-RAS model to generate water surface profiles at the point of interest(Root and Papakos, 2010; USACE, 2010). As the Oshiwara River dis-charge its flow in the Malad creek of the Arabian Sea, tidal depth varia-tion was given as the boundary condition at the outlet point. Theupstream boundary condition is considered as normal depth. The rivercross sections were modified as per the geometric profile. The modelcan be simulated for subcritical, supercritical or mixed flow conditionsdepending upon the boundary conditions (USACE, 2010). Mixed flowconditions were used for simulation. The hydraulic simulation was per-formed corresponding to 2-, 10-, 25-, 50- and 100-year return periodprofiles. The results of the water surface profiles and water surface ex-tent obtained from HEC-RAS were then exported to Arc GIS. The floodplain extent and depths for different flow conditions and land use con-ditionswere generated by integrating theHEC-GeoRASmodel for differ-ent flow and land use conditions (Alaghmand et al., 2010; Suriya andMudgal, 2012).

3.2. Flood plain and flood hazard maps

Flood plain maps for different flow conditions can be developed toestimate the flood extent and flood depth. The generated flood plainand depth maps are used as the main input for developing the floodhazard maps. The step-wise methodology used for generating theflood plain and flood hazard maps is described below.

3.2.1. Flood plain mapsFollowing steps are used to generate the flood plain map.

• Provision of flood hydrograph and flood peak discharge for differentflow conditions as input to generatewater surface extent and profiles.

• Extraction of flood depth from triangulated irregular network (TIN).• Export of water surface extent and profiles for post processing in ArcGIS by integrating HEC-GeoRAS.

• Development of flood plain and depth maps for different flowconditions.

The results of the hydraulic analysis from the one dimensional hy-draulic HEC-RASmodel used in this study are exported as GIS format ex-port file in ArcGIS containing centerline and cross section alignments,water surface elevations at the cross sections and a boundary polygondefining themaximum extent of the floodplain. HEC-GeoRAS, an exten-sion of the ArcGIS, was used to conduct post processing of theseimported GIS export file by creating the water surface TIN from thebuilding polygon, cross section alignment and water surface elevations(Hernandez and Zhang, 2007). Then the water surface TIN was com-pared with the terrain TIN to create the floodplain polygon. This poly-gon denotes the maximum possible extent of the flood plainaccording to the cross section limit (Maidment and Djokic, 2000; Zopeet al., 2015). The flood inundation depth grid denotes the flood risk(Suriya andMudgal, 2012). The results of theflood plainmap developedare discussed in Section 4.3.

3.2.2. Flood hazard mapsHere a new methodology was developed to generate the flood haz-

ardmaps for the coastal urban areas. In thismethod, the various param-eters considered are: generated flood plain map, slope, distance fromthe river to various locations obtained from the DEM and distancefrom the coast bank and flood escape. Following steps are used to gen-erate the flood hazard map.

• All the flood extent maps for different flow conditions are merged toobtain maximum flood extent as input for the flood hazard map.

• Generation of a rastermap to calculate the cell-wise distance from theriver considering the terrain elevation by using the cost distance toolin Arc GIS.

• Generation of the raster map to calculate the cell-wise distance fromthe river to the catchment boundary by using the Euclidean distancetool in Arc GIS.

• Generation of the raster map to calculate the cell-wise distance fromthe coast bank by using the Euclidean distance tool in Arc GIS.

• Clipping of all these rastermaps to themaximummerged flood extentmap.

• Generation of zones 1–100 to bring all the rastermaps at one standardlevel by using the Slice tool in Arc GIS.

• Weightage overlay analysis using the Delphi technique (Lee et al.,2013) by giving 0.5 weightage to the raster generated considering

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Table 4Peak discharge and volume of runoff for different return periods.

Sr. no Flow eventPeak discharge (m3/s)

% change

Volume of discharge at outlet(m3 × 106) % change

LULC 1966 LULC 2009 LULC 1966 LULC 2009

1 2 year return period 357.6 394.8 10.4 76.65 86.00 12.202 10 year return period 771.0 817.9 6.09 163.15 175.95 7.853 25 year return period 1056.9 1105.7 4.62 233.77 248.02 6.104 50 year return period 1359.4 1407.4 3.53 289.02 304.36 5.315 100 year return period 1683.0 1730.7 2.83 359.89 375.89 4.45

149P.E. Zope et al. / Catena 145 (2016) 142–154

the river and slope, 0.4 weightage to the raster for distance from theriver and 0.1 weightage to the raster generated for distance from thecoast bank.

• Generation of flood hazard maps.

The flood plain extent generated for different return period stormevents are merged to obtain the maximum flood extent polygon be-cause it differed in different periods. The spatial analysis tool, cost dis-tance of Arc GIS software was used to generate the cost distanceraster. This raster calculate the last accumulated shortest distance ofeach cell to the catchment boundary. To generate the cost distance ras-ter, slopemap and river line in vector formatwas given as input. The Eu-clidean distance tool from Arc GIS software was used to calculate theEuclidean distance-river raster by using the river vector file as input. Itcalculates the cell-wise distance from the centerline of the river to thecatchment boundary. Because the area near the river bank is most vul-nerable for flooding, this raster layer was considered for the analysis.The Euclidian distance tool in Arc GIS was used and the Euclidean dis-tance-coast raster was generated to calculate the distance from thecoastal line. Thus, flood hazard maps are developed by merging theflood extent derived for different return periods to obtain themaximumaerial extent of flood, distance from the river, coast, and slope of thecatchment. The results of the flood hazard map developed for thestudy area are discussed in Section 4.4.

Fig. 8. Flood hydrographs at outlet for 2 year return period under LULC of 1966 and 2009.

4. Results and discussion

4.1. LULC change

The resulting LULCmaps generated for the study area for 1966, 2001and 2009 are shown in Fig. 5(a), (b) and (c) respectively. The percent-age LULC change from 1966 to 2001, 2001 to 2009 and 1966 to 2009is shown in Table 3.

The aforementioned results revealed that there is steady change inLULC from 1966 to 2001 compared with that between 2001 and 2009.A drastic land use change and ultimately growth in the urban areawere observed in the study area from 2001. About 43.55% increase inthe built-up area, and 28.3% and 44% reduction in open spaces andwater body respectively were observed over 35 years (between 1966and 2001). However, 31.29% increase in the built up area, and 14.49%and 18% reduction in open space and water body were observed withina short period of 8 years between 2001 and 2009. Overall, 74.84% in-crease in the built-up area and 42.79% and 62% reduction in openspace and a water body respectively, were observed in the past43 years. The rate of change in LULC between the year 1966 and 2009is estimated by assessing percentage change in LULC between these pe-riods divided by number of years (43 years). The increase in rate ofchange in built-up area was 1.74% and decrease in water body was1.44% per year which can be considered as very high, indicating rapidurban growth in the catchment with spatial and temporal change inland use over the four decades. During this period, encroachment wasalso observed along the bank of the river alignment reducing the flowpath substantially. In this study, there are limitations in assessment ofaccuracy of LULC for years 1966, 2001 and 2009 as there are no grounddata or documents that were available.

4.2. Effect of LULC change on flood peak

The present study is focused on the impact of LULC change on theflood peak discharge, and the flood hydrograph, by using the rainfall-runoff modeling with storm rainfall depth for different return periods,to and land use conditions of 1996 and 2009. Storm rainfall depths fordifferent return periods were derived by using Gumbell distributionmethod for statistical analysis of rainfall data. Daily rainfall data fromyear 1951 to 2009 and hourly rainfall data from year 1969 to 2009from the nearest rain gauge station (Santacruz) was used for the statis-tical analysis (Zope et al., 2015). In this study, the SCS-CN loss methodhas been used in the HEC-HMS model for calculating the runoff. Thesoil type, land use and hydrological condition of the land cover are themajor factors while deriving the curve numbers (CN). Land use andsoil maps are coupled and hydrological soil group was assigned as perthe soil cover (Zope et al., 2015). With reference to the hydrologicalsoil group and land use cover, CN number assigned is given in Table 2.Composite CN for each sub basin were derived and used as input inthe SCS-CN modeling in HEC-HMS. Fig. 6 (for 1966) and Fig. 7 (for2009) show the graphical representation of the results obtained from

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Fig. 9. Flood plain maps for LULC of 1966 – (a) 10 years; (b) 25 years; (c) 50 years; (d) 100 years.

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the hydrologic modeling with 1-min time step for the storm rainfalldepth for these return periods at the outlet point of the basin for theLULC condition change in 1966 and 2009. Table 4 shows the change inpeak runoff discharge at the outlet for different return periods for theland use conditions of 1966 and 2009.

From the analysis and aforementioned results, it was observed thatfor the lower return period of 2 years, peak discharge and the volumeof runoff at the outlet was higher than those for high return period of100 years. Furthermore, it can be concluded that in the past 43 years,the increase in peak runoff is marginally varied by about 3.0% for the100-year return period compared to 10.4% for the 2-year return period,although the built-up area increased by 74.84%. In addition, an increasein the total volume of runoff for the 2-year return period was 12.2% be-tween year 1966 and 2009. The flood hydrograph at the outlet for the2 year return period for the LULC of 1966 and 2009 is shown in Fig. 8.

Here it may be noted that thewater table inMumbai is high becauseit was formed by the reclamation of seven islands and is a coastal city. Ahigh saturation level resulting in less infiltration was observed for thehigh return periods. These are the main reasons for a marginal increasein the percentage change of peakdischarge for the higher return periodsfor change in land use conditions (Zope et al., 2015). The drainage sys-tem of Mumbai was designed for a rainfall intensity of 25 mm/h,

which was changed to 50 mm/h after deluge on July 26, 2005 (FFC,2006). In addition Mumbai being a coastal city, it is affected by tidal ef-fects, therefore when low intensity rainfall coincides with high tide, theexisting drainage system losses its capacity and flooding occurs inmanyparts of the city (Zope et al., 2015).

4.3. Generation of flood plain maps

The flood inundation maps for the study area for the years 1966 and2009 which are obtained through modeling the land use conditions for10-, 25-, 50- and 100-year storm rainfall depths are shown in Fig. 9(a) to(d) and in Fig. 10(a) to (d) respectively. The areal extents of these inun-dation areas are prescribed in Table 5.

For land use condition of the year 1966, the percentage flood inun-dated area of total sub basin for 10 year return period was 7.09 andfor 100 year return period was 11.10. For land use condition of year2009, it was observed as 7.52 and 11.73 respectively for 10 year and100 year return periods. While analyzing, the percentage change inthe flood inundated area between the years 1966 and 2009, it is ob-served that for 10 year return period, it is 6.04 and for 100 year returnperiod is 5.61. Thus from the aforementioned results, it is revealedthat the flood inundation area is higher for the LULC conditions for

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Fig. 10. Flood plain maps for LULC of 2009 – (a) 10 years; (b) 25 years; (c) 50 years; (d) 100 years.

Table 5Flood inundation areas estimated for the case study area, for different years return periodstorm events.

Returnperiodstormevent

LULC - year 1966 LULC - 2009% change in theflood inundationarea (1966–2009)

Floodinundationarea (km2)

% area oftotal subbasin

Floodinundationarea (km2)

% area oftotal subbasin

10 year 1.82 7.09 1.93 7.52 6.0425 year 2.22 8.65 2.31 9.00 4.0650 year 2.53 9.86 2.70 10.52 6.71100 year 2.85 11.10 3.01 11.73 5.61

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2009 as compared to 1966. Furthermore, it can be concluded that thepercentage change in the flood extent area between four decades(1966–2009), for the lower return periods, it is marginally more com-pared with that for the higher return periods. The depth of flooding in-creased in 2009 compared to the land use condition of 1966. In Arc GIS,the first order standard deviation was used to classify the flood depthinto the number of classes. The downstream part of the catchment ismore vulnerable than the upstream area.

4.4. Delineation of flood hazard maps

In this study, thematic maps of maximum flood extent for differentflow conditions, slope distance, distance from river, and distance fromcoast bank are prepared for the study area, by using Arc GIS software9.3.1 to generate the flood hazard maps.

The Oshiwara River discharges its flow into the Malad creek andtherefore the area near the creek at some distance from the river is af-fected by tidal influence. All the raster cells are clipped to the polygongenerated for themergedmaximum flood extent of different return pe-riods. All the three raster grids which are cost distance–slope and river,Euclidean distance–coast, and Euclidean distance–river for the LULCcondition of 1966 are shown in Fig. 11(a), (b), and (c) respectively

and for the LULC condition for 2009 in Fig. 12(a), (b), and (c) respective-ly. The entire clipped rastermapswere standardized using the Slice toolin Arc GIS. The equal area method was used for classification and thetotal area was divided into 100 zones with a similar number of cells ineach zone. In the weighted overlay analysis, a weightage of 0.5 wasgiven to cost distance-slope and the river raster grid because of topo-graphical reasons and the movement of water from a lower to higherslope. The weightage of 0.4 was given to Euclidean distance from theriver raster grid as the flood depth and extent will be closer to theriver regime. The weightage of 0.1 was given to the Euclidean distance

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Fig. 11. Flood hazard maps for LULC of 1966–(a) Cost distance–Slope and river; (b) Euclidean distance–coast; (c) Euclidean distance-river; (d) flood hazard map.

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from the sea raster grid as only some parts of the catchment near thecreek were influenced by tides. In addition, the Delphi technique wasused to decide the weights (Lee et al., 2013). The flood hazard map of1966 and 2009 is shown in Figs. 11(d) and 12(d) respectively.

The flood hazard is classified in five categories (very low, low, mod-erate, high and very high) by using the first order standard deviationmethod of classification. Lower value indicates higher vulnerabilityand vice versa (Suriya andMudgal, 2012). The categorywise vulnerabil-ity area for the LULC conditions of 1966 and2009 is presented in Table 6.

For land use conditions of the year 1966, the area of flood hazard ex-tent in low hazard category was 0.74 km2, in very high hazard categorywas 0.14 km2 and total flood hazard extent area was 2.47 km2. For landuse condition of the year 2009, it was observed that 0.56 km2 in lowhazard category, 0.23 km2 in very high hazard category and total floodhazard extent area was 3.02 km2. From the aforementioned results, itcan be concluded that, the flood hazard extent area has increased by64.29% in very high-hazard zones, whereas, the flood hazard extentarea has decreased by 32.14% in low-hazard zones for 2009 comparedto the LULC conditions of 1966. The flood hazard maps prepared forthe study area can be used to take precautionarymeasures in highly vul-nerable area during the rainy season.

5. Conclusions

The migration of people from rural to urban area has led to rapidLULC changes to satisfy the population's needs, and thus there is tre-mendous growth in urban areas in the developing countries all overthe world. Mumbai, being an island city, faces scarcity of land andhave limitations for horizontal development as well as increasing thecapacity of existing storm water drainage system and is prone to fre-quent flooding in all monsoon seasons. In this study, the impacts ofLULC and urbanization on flooding have been investigated for aMumbaicatchment of Oshiwara River by considering the changes for 43 years.The integrated approach of hydrologic and hydraulic models of theHEC-HMS, HEC-GeoHMS, HEC-RAS, HEC-GeoRAS with GIS and remotesensing has beenused in the rainfall runoff and in theflood plainmodel-ing. The LULC analysis of the Oshiwara River catchment showed 43.55%increase in the built-up area and 28.3% and 44% reduction in openspaces and water body respectively over 35 years (between 1966 and2001). However, a 31.29% increase in built-up area and 14.49% and18% reduction in open spaces and water body respectively, were ob-servedwithin a short period of 8 years between 2001 and 2009. Overall,for the past period of 43 years, 74.84% increase in the built-up area, and

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Fig. 12. Flood hazard maps for LULC of 2009–(a) Cost distance–Slope and river; (b) Euclidean distance–coast; (c) Euclidean distance-river; (d) flood hazard map.

Table 6Flood hazard extent for LULC 1966 and 2009.

Type of hazard

Area of flood hazard extent(km2) % change between 1966 and 2009

LULC - 1966 LULC - 2009

Very low 0.19 0.21 10.53Low 0.74 0.56 −32.14Moderate 0.88 1.04 18.18High 0.7 0.8 14.29Very high 0.14 0.23 64.29Total area 2.47 3.02 22.27

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42.79% and 62% reduction in open space andwater bodywere observed,respectively. Thus there have been spatial and temporal changes in theland use over the four decades. The results obtained from the presentstudy revealed that there is an increase in the runoff peak and volume,although the increase is marginal in comparison to change in LULC. Fur-ther the flood plain and hazard maps for different flow and land useconditions were generated. The flood hazard analysis of the study arearevealed that the very high-hazard zone extent area was increased sub-stantially up to 64%, whereas the low-hazard zone extent area was de-creased to 32% between 1966 and 2009. The flood plain and flood

hazard maps developed in this study can be used by the local Municipalbody to prepare flood mitigation and early evacuation managementplan duringfloods and as criteria for insurance of any property by insur-ance organizations.

Acknowledgement

The authors are grateful for the data from the India Metrological De-partment and the co-operation from the Municipal Corporation ofGreater Mumbai for this study. Authors are also thankful to the anony-mous reviewer/s and Editorial board members for their constructivecomments and suggestions.

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