Land use land cover dynamics as a function of changingdemography and hydrology

Irfana Showqi • Irfan Rashid •

Shakil Ahmad Romshoo

� Springer Science+Business Media Dordrecht 2013

Abstract This paper describes the spatiotemporal

changes pertaining to land use land cover (LULC) and

the driving forces behind these changes in Doodh-

ganga watershed of Jhelum Basin. An integrated

approach utilizing remote sensing and geographic

information system (GIS) was used to extract infor-

mation pertaining to LULC change. Multi-date LULC

maps were generated by analyzing remotely sensed

images of three dates which include LandSat TM

1992, LandSat ETM? 2001 and IRS LISS-III 2005.

The LULC information was extracted by adopting on-

screen image interpretation technique in a GIS envi-

ronment at 1:25,000 scale. Based on the analysis,

changes were observed in the spatial extent of

different LULC types over a period of 13 years.

Significant changes were observed in the spatial extent

of forest, horticulture, built-up and agriculture. Forest

cover in the watershed has decreased by 1.47 %,

Agricultural by 0.93 % while as built-up area has

increased by 0.92 %. The net decrease in forest cover

and agriculture land indicate the anthropogenic inter-

ference into surrounding natural ecosystems. From the

study it was found that the major driving forces for

these changes were population growth and changes in

the stream discharge. The changes in the stream

discharge were found responsible for the conversion of

agricultural land into horticulture, as horticulture has

increased by 1.14 % in spatial extent. It has been

found that increasing human population together with

decreasing stream discharge account for LULC

changes in the watershed. Therefore, the existing

policy framework needs to focus upon mitigating the

impacts of forces responsible for LULC change so as

to ensure sustainable development of land resources.

Keywords Land cover dynamics �Population growth � Discharge �Himalayas � Geoinformatics

Introduction

The natural and socioeconomic factors and their

utilization by humans in time and space determine

the land use land cover (LULC) pattern of a region

(Zubair 2006; Rahdary 2008; Bhagawat 2011; Shife-

raw 2011). The surface of the earth has been modified

considerably over the past 50 years by human activ-

ities especially through urbanization, deforestation

and intensive agricultural practices. Changes in LULC

are among the most important changes on the earth

surface (Turner et al. 1990; Nunes and Auge 1999).

The conversion of grassland, woodland and forest into

cropland and pasture during the last few decades has

risen dramatically in the tropics (Williams 1990;

Shiferaw 2011; Lambin et al. 2003). Human impacts

on the global environment are operating at unprece-

dented magnitudes. LULC changes on the earth are so

I. Showqi � I. Rashid (&) � S. A. Romshoo

Department of Earth Sciences, University of Kashmir,

Hazratbal, Srinagar 190006, Jammu and Kashmir, India

e-mail: irfangis@gmail.com

123

GeoJournal

DOI 10.1007/s10708-013-9494-x

intense that, when aggregated globally, they signifi-

cantly affect key aspects of earth system functioning.

Such changes also determine, in part, the vulnerability

of places and people to climatic, economic or socio-

political perturbations (Kasperson et al. 1995). LULC

changes are an endless process taking place on the

surface of the earth (Reid et al. 2000). It is taken as a

serious problem in changing the environment (Shife-

raw 2011). Moreover, this change could be the result

of complicated interactions of socio economic and

biophysical situations like economic diversification,

technological advancement, demographic pressure

and many other related conditions (Reid et al. 2000).

Land is one of the important components of life

support system. Unfortunately it has been overused

and abused all through the course of human civiliza-

tions. It is beyond doubt that human activities have

modified the natural environment considerably and

nowadays the intensity and scale of these modifica-

tions has increased significantly (Goldewijk 2001).

Anthropogenic activities have profound impacts upon

the natural setting of global systems (Rashid et al.

2013; Rashid and Romshoo 2012) and the most

striking human induced changes of the current era is

because of the increase in population (Seiferling et al.

2012; Weinzettel et al. 2013). At global scale, increase

in population is characterized by the conversion of

natural land cover to anthropogenically driven land

uses like built-up and road construction. Since 1850,

the total global population has increased six times and

the earth’s urban population has increased over 100

times (Hauser et al. 1982). The impact of population

increase on economic and environmental systems is

very immense (Clarke et al. 1997). Population

dynamics is quite important since reallocation of land

is required to accommodate the ever increasing

population. Regional, national and global land con-

version and consumption rates will continue to

increase as population grows up. As the population

and standard of life improves there is an obvious

demand for producing more from natural resources

especially the land. To meet such needs, the arable

lands, built-up are bound to expand at the cost of the

natural land cover (Panahi et al. 2010). Information on

LULC and possibilities for their optimal use is

essential for the selection, planning and implementa-

tion of land use schemes to meet the increasing

demands for basic human needs and welfare (Manon-

mani et al. 2010). This information also assists in

monitoring the changes of land use resulting out of

changing demands of increasing population.

Linking socioeconomics, hydrometeorology

and remotely sensed data

Integrating remote sensing with the population dynamics

is a plausible approach to understand the impact of the

human activities on biophysical environment. Integration

between social science and natural science is important

for understanding the socioeconomic changes that dras-

tically affect the natural resources. Integration of

remotely sensed data with socioeconomic information

in GIS has widened considerably (Rindfus and Stern

1998; Fox et al. 2003). Much of the research has focused

on linking census and survey-based socioeconomic data

to remotely sensed land use data, particularly for

modeling the drivers of deforestation in rural areas (Pfaff

1999; Geoghegan et al. 2001). Researchers have inte-

grated the socioeconomic and remotely sensed data for

urban analysis (Lo and Faber 1997). Many of these

studies have employed multivariate statistics to model

land-cover change using household and census unit-level

data. Seto and Kaufmann (2003) extend this approach for

econometric modeling of rural to urban land conversion,

as indicated by Landsat TM imagery, in the area

surrounding Hong Kong, China. Multiple number of

factors such as local climate, LULC, topography, soil and

geology determines the stream discharge of watershed

(Hua et al. 2005). Most of the observed variability in the

stream discharge is caused by the climate change and the

land cover variations (Hua et al. 2005). Furthermore,

LULC alteration can also affect flood frequency and

regional climate (Greene et al. 1999). One of the major

driving forces leading to changes in land cover charac-

teristics and hydrological processes is human activity

(Mao and Cherkauer 2009).

The purpose of this paper is to examine how

increase in population growth and changes in stream

discharge affect the LULC pattern in Kashmir Hima-

laya. In this study, we used multi-date, multi-sensor

satellite data to determine the spatio-temporal changes

pertaining to the LULC in Doodhganga watershed.

The spatiotemporal changes were then related with the

changes in population and stream discharge within the

watershed. The present study demonstrates the use of

remote sensing and GIS in quantifying, correlating and

integrating the changes in the LULC with population

dynamics and stream discharge.

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Study area

Doodhganga watershed in Kashmir Himalayas is

situated between the 33�150–34�150 latitudes and

74�450–74�830 longitudes covering an area of

736.2 km2 (Fig. 1). It is one of the left bank tributaries

of the river Jhelum, originating on the eastern slopes of

the Pir Panjal mountain range below the Tatakuti peak

which is at an altitude of 4,500 m a.s.l (Hussain and

Pandit 2011a, b). The topography of the watershed

is varied and exhibits altitudinal extremes of

1,548–4,634 m a.m.s.l (Romshoo and Rashid 2012).

It is bounded by lofty Pir Panjal Mountain Range on

south. Its relief is diverse, comprising of steep slopes,

plateaus, plains, alluvial fans and meadows like

Toshmaidan, Kongwatan, Gulmarg, Yousmarg etc.

The upper reaches of the catchment that is usually snow

covered and has extremely steep slopes of more than

70 %, followed by comparatively lesser steep slopes of

60–70 % which reflect the different aspects of mainly

the Karewa formations (plateau-like features devel-

oped in thick accumulations of the Pleistocene glacial

moraines) in the middle parts of the watershed. The

downstream watershed area have very gentle slope of

0–1 % (Hussain and Pandit 2011a, b). The plains of the

watershed are very fertile, hence, ideal for agriculture,

whereas the higher reaches comprise dense pine forests

and lush green alpine pastures. Geologically the area

consists of Panjal traps, limestone, Karewa Formation

and Recent Alluvium. The characteristic Karewa

Formation in relatively lower elevations is ideal for

horticulture (Romshoo and Rashid 2012). The area

experiences temperate climatic conditions, with aver-

age winter and summer temperatures ranging from 5 to

25 �C, respectively. The average annual precipitation

is about 660 mm in the form of rain and snow (Hussain

and Pandit 2011a, b). Doodhganga stream, one of the

important perennial tributaries of river Jhelum, is the

main drainage and water resource in the watershed and

is an important source of water for the famous Hokersar

wetland (Romshoo and Rashid 2012).

Materials and methods

Data sets used

Data from various sources was used to accomplish the

research objective in order to accomplish the study.

Chiefly three kinds of data-sets were used in the

present study:

Satellite data

Multi-temporal datasets from various sources from

1992 to 2005 were used for analyzing the spatio-

temporal changes in the Doodhganga watershed. In

order to minimize the impacts of the changing season

on the mapping, it was ensured, to use the data of the

same season with minimum possible gaps between

them. Satellite imageries of Landsat TM (15 Oct,

1992) with a spatial resolution of 30 m and Path/Row-

149/36; Landsat ETM? (30 Sept, 2001), with a spatial

resolution of 30 m and Path/Row-149/36 and IRS

LISS-III (19 Oct, 2005) with a spatial resolution of

23.5 m and Path/Row-92/46 were used.

Stream discharge data

A time series of the stream discharge data from 1980 to

2010 data (Irrigation and Flood Control Department,

Government of Jammu and Kashmir) was statistically

analyzed to investigate if it has any link with the

LULC changes.

Population data

To study the population dynamics in the Doodhganga

watershed, the population data of 1981 and 2001

(Census of India, Bureau: J&K) was analyzed, to find

out the impact of the population growth on the LULC

in the watershed.

Data analysis

In order to carry out the spatial analysis, all satellite

data were converted to a common image format. The

flowchart of the methodology adopted in this study is

given in the Fig. 2. Satellite data was georeferenced,

mosaiced and the area of interest was extracted using

standard image processing algorithms (Jensen 1996;

Lillesand et al. 2004). Various image enhancement

techniques were applied to the images to increase the

interpretability of the image data (Starck et al. 1998).

In the present study, visual interpretation method was

employed keeping in view its advantages in delineat-

ing land cover types in topographically rugged terrain.

Based on certain fundamental image characteristics

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(viz; tone, texture, pattern, size, shape, shadow

coupled with site/location and associated features),

which help in interpretation of earth features, classi-

fication of digital images through on screen interpre-

tation approach was carried out. National natural

resources management system (NNRMS) standards

(ISRO 2005) were used for categorizing LULC in the

watershed. The LULC map of 2005 was validated in

the field to determine its accuracy. The accuracy

estimation is essential to assess reliability of the

classified map (Foody 2002). Kappa coefficient

(Jensen 1996) the robust indicator of the accuracy

estimation was also estimated for the final LULC map.

In addition, the overall accuracy, user’s accuracy,

producer’s accuracy, errors of omission and commis-

sion were also computed to assess the accuracy of the

LULC at the watershed scale. This was followed by

extensive ground validation in order to obtain an

accurate vegetation type map. Overall classification

accuracy is given by following formula (Veregin

1995):

q ¼ ðn=NÞ � 100

where ‘q’ is classification accuracy, ‘n’ is number of

points correctly classified on image, and ‘N’ is number

of points checked in the field.

Kappa coefficient, the robust indicator of the

accuracy estimation for the final LULC map was

estimated by the following formula (Cohen 1960):

k ¼NPr

i¼1

Xii �Pr

i¼1

ðXiþ:XþiÞ

N2 �Pr

i¼1

ðXiþ:XþiÞ

Fig. 1 Study area

Fig. 2 Methodology adopted in the study

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where r is number of rows in error matrix, xii is

number of observations in row i and column i (on the

major diagonal), xi1 is total of observations in row i

(shown as marginal total to right of the matrix), x1i

total of observations in column i (shown as marginal

total at bottom of the matrix) and N is total number of

observations included in the matrix.

In order to determine the changes in the LULC that

have occurred over the observation period from 1992

to 2005, change detection analysis was performed

(Baker et al. 2007; Schmid et al. 2005).

Trend analysis was adopted for the time series

analysis of stream discharge data, to infer the

changing climate trends from the data. Well-timed

and accurate change detection of features provides

the base for better understanding of the relationships

and interactions between human and natural phe-

nomena to better manage and use resources (Lu

et al. 2004; Canty and Nielsen 2006). In order study

the population changes within the watershed, pop-

ulation growth was analyzed at the village level

using census data of 1981 and 2001. Assuming that

in future population growth rates remain constant

within the watershed, the population of 1992 and

2005 was generated from the data of 1981 and 2001.

In Doodhganga watershed there are 284 villages and

4 urban centers as per 2001 census. Population

growth rates were used for the investigating the

changes in LULC of Doodhganga watershed.

Results and discussions

LULC change detection

In order to analyze and map the LULC within the

Doodhganga watershed, onscreen interpretation

approach was adopted. Twelve types of LULC classes

were delineated from the satellite data (1992, 2001 and

2005) at 1:25,000 scale. The LULC types are;

agriculture, barren land, built-up, dense forest, horti-

culture, pasture, plantation, scrub land, sparse forest,

snow, water body and wetland. Figure 3a shows the

thematic map of the LULC types of 1992 and Table 1

shows the spatial estimates of each LULC categories

in 1992. It is observed from the information that

agriculture was the dominant class covering an area of

44.04 % of total area. Area under dense forest was

about 12.89 %. Horticulture covered 13.07 % of the

area followed by scrub land 7.02 %, snow 6.85 %,

pastures 3.25 %, barren land 2.71 %, wetland 2.61 %,

built-up 2.39 % and water body 1.84 %. Area under

sparse forests was only 0.69 %. Figure 3b shows the

spatial distribution of the LULC data within the

watershed for the year 2001 mapped from the LandSat

ETM? data. All the twelve LULC types, mapped in

1992, are present in the watershed. From the analysis

of the data in Table 1, it is clear that agriculture is

again the most dominant land use type in the

watershed although it has decreased by -0.78 % in

area followed by dense forest, that has suffered a

greater loss and has decreased from 12.89 to 11.32 % a

decrease by 1.57 %. The LULC types that has

increased in spatial extent are horticulture, barren

land, built-up, scrub land and sparse forest The area

under built-up has increased from 2.39 % in 1992 to

2.96 % in 2001. However, the water body has shrunk

from 1.89 to 1.63 %. The details of the areal coverage

and proportion of different LULC types found in 2001

are given in the Table 1. The distribution of the LULC

types mapped during the 2005 is shown in the Fig. 3c.

The spatial extent and the proportionate statistics are

given in the Table 1. From the analysis of the data, it is

observed that the area under the Built-up has signif-

icantly increased from 2.96 % in 2001 to 3.31 % in

2005. Similarly, the horticulture is showing an

increase in area. The important Hokersar Wetland in

the watershed is showing a decrease from 2.61 to

2.33 % during 1992–2005. For the spatial statistics of

the other LULC categories, refer to Table 1.

An accuracy assessment of the LULC types derived

from the on screen interpretation of the 2005 satellite

data was also carried out. 191 sample points were

chosen for verification of the LULC map in the field.

The overall accuracy of the LULC delineated from

2005 satellite data was 96.86 % Table 2. Kappa

coefficient for the classified data of 2005 was found

to be 0.965. In addition, user’s accuracy, producer’s

accuracy was also computed to assess the accuracy of

the LULC at the watershed scale.

Stream discharge data analysis

A time series of the stream discharge data comprising

of river discharge data from 1980 to 2010 was

analyzed to investigate if, there is any link between

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these two parameters, LULC change and the declining

water extent of the Doodhganga stream. The analysis

of the time series of the discharge data of the

Doodhganga tributary from 1980 to 2010, the main

feeder tributary of the River Jhelum, indicate decreas-

ing tendency of the river discharge (Fig. 4). The

lowering of water discharge may be attributed to the

untimely precipitation and reduction in annual pre-

cipitation in Doodhganga watershed (Romshoo and

Rashid 2012). Highest discharge in the stream was

observed in spring season, this may be due to

maximum precipitation in this season and also because

of the spring thaw causing large snow melts in the

upper areas which increase discharge in the stream

(Hussain and Pandit 2011a, b). The decreasing trend of

discharge in Doodhganga stream has a direct impact

on the changing LULC in the watershed. Particularly,

agriculture lands are being converted to apple orchards

as the latter require less amount of water and hence are

climatologically more feasible (Romshoo and Rashid

2012). As it evident from the analysis that agricultural

land has decreased by -0.93 % from 1992 to 2001 and

Fig. 3 LULC types delineated from satellite data of: a 1992, b 2001 and c 2005

Table 1 Area under

different LULC classes in

Doodhganga watershed

from 1992 to 2005

-, decrease; ?, increase

Class name Area (km2) Change (km2)

1992–2005

Change %

1992–20051992 2001 2005

Agriculture 324.25 318.52 317.39 -6.86 -0.93

Barren land 19.92 23.8 20.55 ?0.63 ?0.09

Built up 17.59 21.81 24.36 ?6.77 ?0.92

Dense forest 94.91 83.34 84.12 -10.79 -1.47

Horticulture 96.21 103.16 104.63 ?8.42 ?1.14

Pasture 23.95 21.01 19.84 -4.11 -0.56

Plantation 19.39 16.92 17.19 -2.2 -0.30

Scrub land 51.7 99.13 62.1 ?10.4 ?1.41

Snow 50.44 13.11 50.45 ?0.01 0.00

Sparse forest 5.06 6.08 6.08 ?1.02 ?0.14

Water body 13.53 12 12.33 -1.2 -0.16

Wetland 19.25 17.32 17.16 -2.09 -0.28

Total area 736.2 736.2 736.2

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horticulture land has increased by 1.14 % during the

same period. The decrease in the water discharge in

the Doodhganga tributary could be one of the reasons

for this type of land transformation in the study area.

Population data analysis

Population data was analyzed in order to see the

changes in the population growth and its impact on the

LULC. Population maps for the year 1992, 2001 and

2005 are shown in Fig. 5. At watershed level, the

overall population has increased from 207,103 in 1992

to 292,072 in 2005 (Table 3). The increase in the

population in the Doodhganga watershed may be

attributed to increased life expectancy that is increase

in the birth rates and consequent decrease in the death

rates. This increase in human life expectancy can be

associated with profound changes in the human life

style (Howse 2006). The population density in the

Doodhganga watershed has increased from 282 per-

son’s km-2 in 1992 to 397 person’s km-2 in 2005

(Table 3). Similarly the number of households in the

watershed has increased from 30,953 in 1992 to

46,239 in 2005 (Table 3).

Fig. 4 Graph showing discharge of Doodhganga stream a at Head-Branwar and b at Tail-Barzulla

Table 2 Error matrix showing per class accuracy of 2005 land cover data

Sample data Reference data Row total User’s accuracy

DF SF HR AG PL PA SC WB WL BU BL SW

DF 10 – – – – – – – – – – – 10 100

SF – 10 – – – – – – – – – – 10 100

HR – – 29 – 1 – – – – – – – 30 96.7

AG – – – 29 – – – – – 1 – – 30 96.7

PL – – 1 – 19 – – – – – – – 20 95

PA – – – – – 10 – – – – – – 10 100

SC – – – – – – 10 – – – – – 10 100

WB – – – – – – – 20 – – – – 20 100

WL – – – – – – – – 5 1 – – 6 83.3

BU – – – 1 – – – – – 28 – – 29 96.6

BL – – – – 1 – – – – – 10 – 11 90.9

SW – – – – – – – – – – – 5 5 100

Column total 10 10 30 30 21 10 10 20 5 30 10 5 185

Producer’s accuracy 100 100 96.7 96.7 90.4 100 100 100 100 93.3 100 100 100

DF dense forest, SF sparse forest, HR horticulture, AG agriculture, PL plantation, PA pastures, SC scrub, WB waterbody, WL wetland,

BU built-up, BL barren land, SW snow

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The increasing trend in population density and

number of households has a direct impact on the

changing LULC in Doodhganga watershed. Particu-

larly, agriculture lands are being converted to settle-

ments and forests are converted to agriculture lands in

order to meet the demands of the increasing population

(Kombe and Kreibich 2000). Besides built-up is the

important class of almost every LULC classification

scheme, it increases because of urbanization and

increase in population (Uma and Mahalingam 2011;

Bhagawat 2011; Ifatimehin et al. 2009), as demo-

graphic growth stimulates structural change through

multiplier effects (Fazal and Amin 2011). The simul-

taneous rapid growth in population and the consequent

changes in land use pattern come at a cost to the natural

environment (Cohen 1995; Tang et al. 2005; Ifatime-

hin and Ufuah 2006; Ifatimehin and Musa 2008).

Since rapid expansion of urban areas due to rise

in population and economic growth is increasing

additional demand on natural resources thereby caus-

ing land use changes (Mohan et al. 2011). All other

anthropogenic influences within the watershed partic-

ularly in terms of increase in the infrastructure

development and increase in horticulture added by

the impacts of the deforestation have accelerated the

deterioration of the watershed structure and function

(Ray and Ray 2011; Clark 2012). Research has proved

that problems associated with environmental moni-

toring and control persists through the history of

mankind. The situation has aggravated in recent times

due to anthropogenic intervention on the environment,

hence, there remains few landscapes on the earth’s

surface that have not been significantly altered by

human beings in some ways (Bhagawat 2011; Lambin

et al. 2003; Abbas et al. 2010). The agriculture land

has shown a decreased trend in area, from output maps

it is easily inferred that most of the horticulture land

comes from agriculture land and also infrastructure

development occurs on the agriculture land. The

increasing trend in horticulture land in the area is

because of the decreasing trend in the discharge in the

said stream as the latter require less amount of water

and hence are climatologically more viable (Romshoo

and Rashid 2012). Land under forests has reduced and

could be as result of well known environmental

problems such as deforestation, urbanization etc.

(Rahdary 2008; Farooq and Rashid 2010; Clark

2012; Lambin et al. 2003; Abbas et al. 2010). The

Fig. 5 Village-wise population map of Doodhganga watershed for the year a 1992, b 2001 and c 2005

Table 3 Change in the number of households, population and

population density in Doodhganga watershed from 1992 to

2005

Year Number of

households

Total

population

Population density

(persons km-2)

1992 30,953 207,103 282

2001 41,089 263,499 359

2005 46,239 292,072 397

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main cause of deforestation in these areas is the

increased need for timber, firewood due to increase in

population as the area is predominantly a rural setting.

Pasture lands have been acclaimed as ownership land

masses and are continuously being transformed to

barren lands and scrub land at an ever faster pace due

to the over grazing of the cattle; this could be the

possible reason behind their reduction in the

watershed area (Showqi 2012). Water bodies have

decreased in spatial extent in the watershed. Normally

this result can be accepted keeping in view the general

scenario of Kashmir valley wherein numerous rivers,

river channels, lakes, ponds etc. have been totally lost

(Showqi 2012). On the other side increase in horti-

culture could result in water pollution (eutropication),

thus decreasing the quality and quantity of water in the

water bodies (Rashid and Romshoo 2012).

Linking LULC changes with population dynamics

and stream discharge

LULC changes within the Doodhganga watershed

were correlated with population increase and changes

in discharge of Doodhganga at its tail (Barzulla).

Decrease in area under agriculture was compared with

increase in population in Doodhganga watershed

(Fig. 6a) wherein the value correlation coefficient

was -0.98, depicting a near perfect negative correla-

tion. Similarly, increase in area under horticulture was

compared with increase in population in Doodhganga

watershed (Fig. 6b) wherein the value correlation

coefficient was 0.98, depicting a near perfect positive

correlation. It is hence evident that agriculture lands

have either been converted into horticulture or built-up

(Rashid and Romshoo 2012). Moreover, decrease in

area under agriculture land was compared with stream

discharge (Fig. 6c) which showed a near perfect

positive correlation (0.93). Similarly, increase in

agriculture land was compared with stream discharge

(Fig. 6d) which showed a near perfect negative

correlation (-0.93).

Conclusion

This research demonstrates the use of an integrated

approach utilizing remotely sensed data, field obser-

vations and ancillary data for determining the influ-

ence of demographic and stream discharge changes on

LULC in Doodhganga watershed. The study has

revealed that LULC conversions are taking place

especially from the last few decades which resulted

in the decline in spatial extents of agriculture land

(-0.93 %), increase in built-up area (?0.92 %),

Fig. 6 Correlation

between: a area under

agriculture and

demographic setup, b area

under horticulture and

demographic setup, c area

under agriculture and stream

discharge and d area under

horticulture and stream

discharge, from 1992 to

2005

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increase in horticulture area (?1.14 %), conversion of

pasture lands to barren land and decrease in spatial

extents of wetland (-0.28 %) and water bodies

(-0.16 %) within the watershed. An important obser-

vation from this analysis is the loss of natural land

cover in the form of forested areas (-1.47 %),

highlighting the need to protect them. The time series

analysis of the stream discharge in the Doodhganga

watershed shows a declining trend. This reduction in

stream discharge of Doodhganga, a consequence of

climate change, is responsible for the conversion of

the agricultural lands into orchards. It has been found

that increasing human population together with

decreasing stream discharge account for LULC

changes in the watershed. The conversion of natural

vegetated areas to impermeable surfaces like built-up

has direct bearing on water budget of the Doodhganga

watershed. In order to mitigate the negative impacts of

LULC conversions due to ever increasing human

population alongwith decline in stream discharge, the

existing policy framework needs to focus upon

evolving the strategies that ensure sustainable use of

our land resources.

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