In this study, the spatiotemporal changes in the land cover system within a Himalayan wetland and its catchment were assessed and correlated using a time series of satellite, historical, and field data. Significant changes in the spatial extent, water depth, and the land system of the Hokersar wetland were observed from the spatiotemporal analysis of the data from 1969 to 2008.
Impacts of Changing land cover and Climate on Hokersar wetland in Kashmir
Research Work on Hokersar
1. Assessing the impacts of changing land
cover and climate on Hokersar wetland in
Indian Himalayas
Shakil Ahmad Romshoo & Irfan Rashid
Arabian Journal of Geosciences
ISSN 1866-7511
Arab J Geosci
DOI 10.1007/s12517-012-0761-9
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DOI 10.1007/s12517-012-0761-9
ORIGINAL PAPER
Assessing the impacts of changing land cover and climate
on Hokersar wetland in Indian Himalayas
Shakil Ahmad Romshoo & Irfan Rashid
Received: 31 March 2012 / Accepted: 31 October 2012
# Saudi Society for Geosciences 2012
Abstract Monitoring the spatiotemporal changes in wet- Keywords Spatiotemporal changes . Catchment . Remote
lands and assessing their causal factors is critical for devel- sensing . Biodiversity . Hydrometeorology
oping robust strategies for the conservation and restoration
of these ecologically important ecosystems. In this study, the
spatiotemporal changes in the land cover system within a Introduction
Himalayan wetland and its catchment were assessed and
correlated using a time series of satellite, historical, and field Wetlands occupy about 7 % of the Earth’s land surface (MEA
data. Significant changes in the spatial extent, water depth, 2005; Mitsch and Gosselink 1986); and in the mountainous
and the land system of the Hokersar wetland were observed region of Kashmir Himalayas alone, there are 3,813 wetlands
from the spatiotemporal analysis of the data from 1969 to and water bodies (Romshoo et al. 2010). Sustainable manage-
2008. The wetland area has shrunk from 18.75 km2 in 1969 ment of these wetland ecosystems is necessary as wetlands
to 13 km2 in 2008 with drastic reduction in the water depth provide a variety of services and functions and contribute
of the wetland. The marshy lands, habitat of the migratory tremendously to the livelihoods and human wellbeing in the
birds, have shrunk from 16.3 km2 in 1969 to 5.62 km2 in region. Most important wetland ecosystem services affecting
2008 and have been colonized by various other land cover the human wellbeing involve fisheries, food products, fresh-
types. The land system and water extent changes within the water supplies, water purification and detoxification, and
wetland were related to the spatiotemporal changes in the global climate change regulation (Costanza et al. 1997; Davis
land cover and hydrometeorological variables at the catch- 1993; Hruby 1995; MEA 2005). Wetlands deliver a wide
ment scale. Significant changes in the forest cover (88.33– array of hydrological services, for instance, flood regulation,
55.78 km2), settlement (4.63–15.35 km2), and water bodies promote groundwater recharge, and regulate river flows
(1.75–0.51 km2) were observed in the catchment. It is con- (Bullock and Acreman 2003). Further, wetlands are among
cluded that the urbanization, deforestation, changes in the the most productive ecosystems and a rich repository of
hydrologic and climatic conditions, and other land system biodiversity and are known to play significant role in carbon
changes observed in the catchment are the main causes sequestration (Kraiem 2002). The world’s wetlands are
responsible for the depleting wetland extent, water depth, degrading at an alarming rate, more than other ecosystems
and biodiversity by adversely influencing the hydrologic seriously affecting their biodiversity (Vorosmarty et al. 2010).
erosion and other land surface processes in the catchment. Due to accelerated rate of human intervention and human-
All these causes and effects are manifest in the form of induced modification of natural processes, natural wetland
deterioration of the water quality, water quantity, the biodi- landscapes also are today under acute seasonal water scarcity.
versity changes, and the decreasing migratory bird popula- Wetland areas have been gradually squeezing, permanent
tion in the wetland. wetland areas have transmuted into semipermanent wetlands
with groundwater table slashing down rapidly (Pal and
Akoma 2009). Permanent and seasonal changes within wet-
S. A. Romshoo (*) : I. Rashid
lands occur in response to a range of external factors, such as
Department of Earth Sciences, University of Kashmir, Hazratbal,
Srinagar Kashmir 190006, India the changes in the land systems at the catchment scale
e-mail: shakilrom@yahoo.com (Dooner 2003; Gillies et al. 2003), fluctuations in water table
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(Funk et al. 1994), climate change (Kraiem 2002), or other Worldwide, the lack of understanding of the values and
associated human activities. Climate change may exacerbate functions of the wetlands have led to their conversion for
impacts of threats to wetlands through predicted reductions in agriculture, settlements, plantations, and other development
rainfall and increased temperature, decreasing flow, and altering activities (Joshi et al. 2002; Wetlands International 2007).
timing and variability of flow regimes (Kingsford 2011). The Similar scenario is being witnessed in the mountainous
timing, magnitude, and frequency of rainfall or snowmelt in Himalayan region where unplanned urbanization, reckless
many wetland catchments is predicted to change (Klausmeyer deforestation, and the depleting snow and glacier resources
and Shaw 2009; Palmer et al. 2009; Viers and Rheinheimer are the major causes of the wetland depletion.
2011), with increasing temperatures predicted to augment flows The need for management, protection, and restoration of
early in spring as snow melt and produce flow reductions in these valuable systems, as well as the need to understand the
summer (Aldous et al. 2011). wetland hydrology and ecology, have spurred the investigation
Fig. 1 Study area
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of new technologies for mapping and monitoring of wetlands In the present study, time series multisensor satellite data
(Gondwe et al. 2010; Hess et al. 1995; Lyon 2001; Tanis et al. was used to determine the spatiotemporal changes in Hoker-
1994). Though the entire wetlands in the Indian Himalayas sar wetland that has tremendous ecohydrological and socio-
have been mapped at 1:50,000 scale (Romshoo et al. 2010), economic importance. These spatiotemporal changes were
there is very little information, if at all, on how they have been related with the changes at the catchment scale and hydro-
changing over the time in response to the changes in the meteorology. Most of the studies conducted on the Hoker-
climatic variables and the land system changes occurring at sar, the Queen of wetlands in Kashmir Himalayas are either
the catchment level (Anonymous 1990; Bourgeau-Chavez et focused on the hydrobiology or hydrochemistry (Gangoo
al. 2001; Garg et al. 1998). It is therefore essential to use a time and Makaya 2000; Handoo and Kaul 1982; Handoo 1978;
series of satellite data for assessing the spatiotemporal changes Kak 1990; Khan 2000; Kaul and Zutshi 1967; Kaul 1982;
within the wetlands and the catchment areas to determine the Pandit 1980; Pandit and Kumar 2006; Rather et al. 2001).
cause–effect relationship so that robust strategy for the man- However, very few studies have used the geoinformatics
agement, conservation, and restoration of the wetland is devel- approach to study spatiotemporal dynamics and limnologi-
oped. Multitemporal monitoring of wetlands using remote cal variables of the Hokersar wetland (Humayun and Joshi
sensing and geographic information systems gives a complete 2000; Joshi et al. 2002; Romshoo et al. 2011). The present
understanding of distribution, structure, and functionality of study assumes significance, in view of the fact that a longer
wetland ecosystem (Munyati 2000; Ramsey 1998; Romshoo time series of satellite and other spatial data stretching from
2004; Touzi et al. 2007) and the spatiotemporal dynamics of 1969 to 2008 has been used to monitor and assess the
various variables in the catchment areas (Basnyat et al. 2000; spatiotemporal evolution of the wetland for the last four
Omernik et al. 1981; Saxena et al. 2000; Rashid et al. 2011). A decades and the changes that have occurred in the land use
number of studies related to limnological variables in lakes and and land cover types within the catchment spread over an
wetlands have been attempted using remote sensing (Birkett area of about 732 km2. Further, the linkages between the
1995; Kapetsky 1987; Olmanson et al. 2002; Ozesmi and observed changes in the wetland have been correlated with
Bauer 2002; Roeck et al. 2008; Romshoo and Sumira 2010; the hydrometeorological data to investigate if there are any
Romshoo and Muslim 2011). impacts of the changing climate on the wetland.
Fig. 2 Scheme of methodology
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Table 1 Spatial extent Karewa Formation, and Recent Alluvium. The characteristic
of the Hokersar wetland Year Area (km2)
Karewa Formation in relatively lower elevations is ideal for
at different points in
time 1969 18.75 horticulture. The study area experiences temperate climate
1992 14.94 with the average winter and summer temperatures ranging
2001 14.71 from 5 to 25 °C, respectively. The average annual precipita-
2005 14.33 tion is about 660 mm in the form of rain and snow. Doodh-
2008 13.00 ganga stream, one of the important perennial tributaries of
river Jhelum, is the main drainage and water resource in the
catchment. Doodhganga stream flows for a course of about
Study area 56 km before emptying into Hokersar wetland.
Hokersar wetland (34° 06′ N latitude, 74° 05′ E
Doodhganga, located in Kashmir Himalaya, India is one of longitude) lying in the Northern most part of Doodh-
the major left-bank catchments of Jhelum River. It is situat- ganga catchment is a protected wildlife reserve and a
ed between 33° 15′–34° 15′ latitudes and 74° 45′–74° 83′ Ramsar site at an altitude of 1,584 m (amsl). The
longitudes covering an area of 732.6 km2. It is bounded by wetland harbors about two million migratory waterfowl
lofty Pir Panjal Mountain Range on south. The catchment during winter that migrate from Siberia and the Central
has a varied topography and exhibits altitudinal extremes of Asian region. The wetland is fed by two inlet streams—
1,548 to 4,634 m (above mean sea level (amsl)). Its relief is Doodhganga (from east) and Sukhnag Nalla (from
diverse, comprising of steep slopes, plateaus, plains, and west). The wetland attains a maximum depth of 2.5 m
alluvial fans. The plains of the catchment are very fertile, in spring due to appreciation in discharge from the
hence, ideal for agriculture, whereas the higher reaches snow-melt water in the upper reaches of Doodhganga
comprise dense pine forests and lush green alpine pastures. catchment. The water depth in autumn is minimum at
Geologically, the area consists of Panjal traps, limestone, 0.7 m. Figure 1 shows the location of the study area.
Fig. 3 Hokarsar boundary extents at different points in time
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Materials and methods Datasets used for changes in the catchment of Hokersar
Datasets used for changes in Hokersar wetland Time series of satellite data (1972–2005) from various sat-
ellites was used to analyze changes at catchment level.
Multitemporal datasets from various sources from 1969 to Landsat MSS (17 Nov 1972) with a spatial resolution of
2008 were used for analyzing changes in Hokersar wetland. 57 m and Path/Row 160/36; Landsat TM (15 Oct 1992) with
Survey of India (SOI) topographical maps of 1969 at 1:50,000 a spatial resolution of 30 m and Path/Row 149/36; IRS
scale were used for generating the base map of the Hokersar LISS-III (19 Oct 2005) with a spatial resolution of 23.5 m
wetland. Time series of satellite data from various satellites and Path/Row-92/46, 92/47 were used.
was chosen for monitoring the spatial and temporal changes in
the wetland. In order to minimize the impacts of the changing Hydrometeorological data
season on the mapping, it was ensured, wherever possible, to
use the data of the same season with minimum possible gaps A time series of the hydrometeorological data comprising of
between them. Landsat TM (15 Oct 1992) with a spatial precipitation and river discharge data from 1979 to 2009 was
resolution of 30 m and Path/Row 149/36; Landsat ETM+ (30 statistically analyzed to investigate if there is any link between
Sept 2001), with a spatial resolution of 30 m and Path/Row- the changing climate and the declining water extent of the
149/36; IRS LISS-III (19 Oct 2005) with a spatial resolution of Hokersar wetland.
23.5 m and Path/Row-92/46 and IKONOS (11 Jan 2008) with For accomplishing the research objectives, the multi-
a spatial resolution of 1 m were used. Though, all the satellite source and multitemporal satellite data was used at two
data, except IKONOS, pertain to the autumn season, when the spatial scales; at the catchment scale and the wetland scale.
discharge and water depth of the wetland is at the minimum, The flowchart of the methodology adopted in this research
however, due to unavailability of the cloud-free satellite data in is given in Fig. 2. In this research, we adopted two
autumn, the January IKONOS data was used for monitoring approaches for extracting the information from the images;
the changes in the wetland up to 2008. (a) onscreen digitization of the image data to delineate the
Fig. 4 Land use and land cover types delineated from the scanned topographic map of 1969
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Table 2 Land use and likelihood classifier was used (Fu 1976; Tso and Mather
land cover types delin- Class name Area (km2)
2001). National Natural Resources Management System
eated from the scanned
topographic map of Marshy 16.30 (NNRMS) standards (ISRO 2005) were used for cate-
1969 Open water 1.74 gorizing land use and land cover in the Doodhganga
Plantation 0.64 catchment that drains into the Hokersar wetland. While
Road 0.05 choosing various training samples for the maximum
likelihood classifier, homogeneity of the samples was
ensured for achieving higher classification accuracy.
wetland boundaries and for mapping the land use and land The land use and land cover map of 2005 at the
cover within the wetland boundary and (b) digital image catchment scale was validated in the field to determine
classification for extracting land use and land cover infor- its accuracy. Seventy-one sample points were chosen for
mation at the catchment scale. verification of the land use and land cover map in the
For delineating the wetland boundary from the topo- field. The accuracy estimation is essential to assess
graphic map, onscreen digitization method was employed. reliability of the classified map (Foody 2002). Kappa
Using the digitized boundary of the wetland from SOI map coefficient, the robust indicator of the accuracy estima-
as the base map, the wetland boundary extents at different tion for the final land use and land cover map, was
points in time were delineated from the satellite images. The estimated by the following formula:
land use and land cover types within the wetland boundary
were also digitized from the scanned map and the satellite
images in order to determine the spatiotemporal changes P
r P
r
N Xii À ðXiþ :Xþi Þ
that have occurred during the observation period (1969– i¼1 i¼1
2008). For extracting the land use and land cover informa- k¼ P
r
tion in the catchment of the Hokersar wetland, supervised N2 À ðXiþ :Xþi Þ
i¼1
image classification technique based on the maximum
Fig. 5 Land use and land cover types delineated from 1992 satellite data
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Table 3 Area covered by different land use and land cover types from 1992 to 2008 within Hokersar wetland
Class name Area 1992 (km2) Area 2001 (km2) Area 2005 (km2) Area 2008 (km2) Change from 1992 to 2008 (km2) % Change
Agriculture 4.26 3.69 3.23 4.95 0.69 3.69
Aquatic vegetation 2.5 3.48 4.56 4.46 1.96 10.73
Built up 0.01 0.05 0.12 0.11 0.1 0.55
Fallow 0.88 0.21 0.27 0.48 −0.4 −2.22
Marshy 7.74 8.06 7.27 5.62 −2.12 −11.86
Open water 0.85 0.43 0.31 0.36 −0.49 −2.72
Plantation 1.82 2.18 2.32 2.16 0.34 1.83
Road 0.03 0.03 0.03 0.03 0 0
where r is number of rows in error matrix also computed to assess the accuracy of the land use and
xii is number of observations in row i and land cover at the catchment scale. The wetland boundary
column i (on the major diagonal) and the land use and land cover types within the wetland
xi+ is total of observations in row i (shown as were extensively verified on the ground with respect to
marginal total to right of the matrix) 2008 data only as the ground truth was not available for
x+i total of observations in column i (shown as the other time periods. In order to determine the changes in
marginal total at bottom of the matrix) the land use and land cover within the wetland, that
N is total number of observations included in have occurred over the observation period from 1969
the matrix to 2008, change detection analysis was performed (Bak-
er et al. 2007; Schmid et al. 2005). Similarly, the
In addition, the overall accuracy, user’s accuracy, pro- change detection analysis was also performed at the
ducer’s accuracy, errors of omission and commission were catchment scale between 1972 and 2005.
Fig. 6 Spatial distribution of the land use and land cover data for the year 2001
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Results and discussion from the images, image elements and other contextual infor-
mation was used for improved accuracy. Figure 4 shows the
Wetland depletion land use and land cover types delineated from the scanned
topographic map that has symbols for these types. From the
The wetland has shrunk and depleted over a period of time. analysis of Fig. 4 and Table 2, we can see that the area under
During the observation period from 1969 to 2008, the spatial marshes was 16.30 km2, plantation was 0.64 km2, and open
extents of wetland have reduced from 18.75 km2 in 1969 to water was 1.74 km2 (which includes flood channel 0.07 km2)
13.00 km2. The extent of the wetland area at different points in out of the total area of 18.75 km2. There is no built up,
time is given in Table 1. As is evident from the data, an area of agriculture, fallow, and aquatic vegetation category shown
5.75 km2 has been lost during the last four decades. Figure 3 on the topographic map and hence these three categories are
shows the thematic representation of the Hokersar boundary missing in Fig. 4. It could be assumed that there was no built-
extents at different points in time. There is progressive deple- up, agriculture and fallow within the wetland in 1969. How-
tion of the wetland area from 1969 to 2008. ever, the marshy land category shown on the map may con-
stitute some aquatic vegetation as well that has been shown
Land use and land cover changes within the wetland under marshy land.
From analysis of the 1992 data, as shown in Fig. 5 and
To analyze and map the land use and land cover within the Table 3, all the eight categories of the land use and land
wetland area, onscreen digitization approach was adopted. cover are present in the wetland. Marshy lands dominate the
Eight types of land use and land cover classes were delineated wetland area covering an area of 7.74 km2 that constitutes
from the satellite data (1992, 2001, 2005, and 2008) and the 42.7 % of the wetland area. Agriculture, that was non-
scanned topographical map (1969) at a 1:25,000 scale. The existent in 1969, is the second major land use type in the
land use and land cover types are agriculture, fallow, planta- wetland covering about 23.51 % of the wetland area. Sim-
tion, marshy lands, aquatic vegetation, built up, open water, ilarly, the built up has emerged within the wetland that was
and road. For delineating the land use and land cover types not present before 1969 and covers an area of 0.01 km2
Fig. 7 Distribution of the land use and land cover types mapped during the 2005
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(0.09 %). The area under the open waters has also drastically gives the area estimates and the proportionate spatial statistics
reduced in 1992 compared to the baseline data (1969). The for each of the land use and land cover type observed within
open water body within the wetland has drastically reduced the wetland. From the analysis of the data, it is observed that
from 1.74 km2 in 1969 to 0.85 km2 in 1992. the area estimates of the land use and land cover types derived
Figure 6 shows the spatial distribution of the land use and from 2008 high-resolution IKONOS data are not showing
land cover data within the wetland for the year 2001 mapped consistent trend as observed from 1969 to 2005 except for
from the LANDSAT ETM+ data. From the analysis of the marshy and aquatic vegetation categories. In fact, due to dif-
data in Table 3, we observe that marshy lands are predom- ferent image acquisition date of 2008 data, i.e., January, when
inant in the wetland followed by agriculture. The area under the water discharge is usually a bit higher than the autumn
built up has increased from 0.01 km2 in 1992 to 0.05 km2 in when it is at the minimum, there is increase in the water extent
2001. However, the open water body has shrunk by more observed from the 2008 data. However, compared to the area
than a half from 0.85 to 0.43 km2. estimates of the dominant land cover types observed in 1969,
The distribution of the land use and land cover types there are sharp changes in the open water body, marshy lands,
mapped during the 2005 is shown in Fig. 7 and the propor- aquatic vegetation, and built-up area observed in 2008.
tionate spatial statistics are given in Table 3. From the
analysis of the data, it is observed that the area under the Land use and land cover change in the catchment
aquatic vegetation has significantly increased from 3.48 km2
in 2001 to 4.56 km2 in 2005. Similarly, the built-up is In order to analyze the causes of this deterioration and
showing an increase. Marshy lands that have tremendous depletion of the Hokersar wetland, multitemporal land use
ecological importance for the migratory birds as they nest and land cover of the Doodhganga catchment of the wet-
and breed in these areas are showing a decrease from 8.06 to land, spread over an area of 732.6 km2, was determined
7.27 km2 during the 2001–2005 period. using the three date satellite data from 1972 to 2005. Thir-
Figure 8 shows the areal distribution of the land use and teen land use and land cover classes were delineated based
land cover types delineated from 2008 IKONOS data. Table 3 on NNRMS standards; agriculture, exposed rock, fallow,
Fig. 8 Spatial distribution of the land use and land cover types delineated from 2008 IKONOS data
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Fig. 9 Spatial distribution of
land use and land cover types in
1972
forests, orchards, pasture, plantation, river, riverbed, scrub, fallow was the dominant class covering 38.59 % area.
settlement, snow, and water body from all the satellite data. Agriculture covered 20.6 % of the area followed by forest
Figure 9 shows the thematic map of the land use and land (11.37 %), snow (11 %) while as the area under orchards
cover types of 1972. It is observed from the information that and settlements was 2.79 and 0.63 %, respectively (Table 4).
Table 4 Area under different land use and land cover classes from 1972 to 2005 of Doodhganga catchment
Class Name Area 1972 (km2) Area 1992 (km2) Area 2005 (km2) Change from 1972 to 2005 (km2) % Change
Agriculture 150.92 140.42 130.67 −20.25 −2.76
Exposed rocks 27.66 49.18 61.58 33.92 4.63
Fallow 282.71 246.51 200.16 −82.55 −11.27
Forest 83.33 78.44 55.78 −27.55 −3.76
Horticulture 20.46 70.88 99.44 78.98 10.78
Pasture 11.3 10.74 7.54 −3.76 −0.51
Plantation 29.71 31.22 55.3 25.59 3.49
River 6.96 5.93 5.93 −1.03 −0.14
River bed 12.42 9.65 9.65 −2.77 −0.38
Settlement 4.63 12.4 15.35 10.72 1.46
Scrub 20.13 40.6 49.99 29.86 4.08
Snow 80.62 36.03 40.7 −39.92 −5.45
Water body 1.75 0.6 0.51 −1.24 −0.17
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The land use and land cover map of 1992 is shown in An accuracy assessment of the land use land cover types
Fig. 10. From the analysis of the thematic and the tabular derived from the supervised classification of the 2005 satel-
data, it is observed that the area under agriculture and lite data was also carried out. The accuracy of the land use
fallow, taken together, has marginally decreased between land cover delineated from 2005 satellite data was 94.09 %
1972 and 1992 (Table 4). Similarly, the area under the (Table 5). The error of omission, i.e., probability of exclud-
pasture and plantation has almost remained static. The areas ing a pixel that should have been included in the class was
under snow and forest have shown a decline. The built-up highest for river bed (0.30) followed by exposed rock (0.11),
area has significantly increased from 4.63 to 12.4 km2. plantation (0.272), scrub (0.087), horticulture (0.066), and
Similarly, the land under orchards, scrub, and exposed rock fallow (0.076). Similarly, the error of commission which is
has shown marked increase in area. the probability of including a pixel in a class when it should
Figure 11 shows the spatial distribution of the land use have been excluded was highest for river bed (0.125) fol-
and land cover types in the catchment delineated from the lowed by exposed rock (0.11), scrub (0.087), fallow (0.076),
2005 IRS LISS-III data. From the analysis of the data, it is and pasture (0.071).
evident that the agriculture and fallow, taken together, show Kappa is lower than overall accuracy and differences in
a significant decrease in areal extent. Similar trend is ob- these two measures are to be expected in that each incorpo-
served in case of forest, which has decreased by about rates different forms of information from the error matrix.
22.66 km2 compared to 1992 data. The area under settle- While overall accuracy only includes the data along the
ments has increased to 15.35 km2 in comparison to 12.4 km2 major diagonal and excludes the errors of omission and
in 1992 (Table 4). Plantation, orchards, and exposed rock commission, kappa incorporates the non diagonal elements
are also showing increase in their spatial extents. of error matrix as a product of row and column marginal.
Fig. 10 Spatial distribution of
land use and land cover types in
1992
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Fig. 11 Distribution of the land
use and land cover types
delineated from 2005 IRS
LISS-III data
Kappa coefficient for the classified data of 2005 was found tributary from 1970 to 2009, the main feeder tributary of
to be 0.935. the wetland, at both the head (Branwar) and tail (Barzulla)
indicate decreasing tendency of the river discharge with r2
Hydrometeorological data analysis of 0.26 and 0.15 respectively (Fig. 13a, b). The lowering of
water discharge may be attributed to the depleting snow
A time series of the hydrometeorological data comprising of cover and reduction in annual precipitation in Doodhganga
temperature, precipitation, and river discharge data from catchment. The decreasing extent of water spread and depth
1979 to 2009 was analyzed to investigate if there is any link of the Hokersar could partly be attributed to the changing
between these parameters and the declining water extent of climate in the Himalayan region (Akhtar et al. 2008; Dahal
the Hokersar wetland. Temperature data shows an increas- 2005; ICIMOD 2009). The decreasing trend in precipitation
ing trend Fig. 12a with r2 of 0.08. Lowest temperatures was and discharge of Doodhganaga stream has a direct bearing
recorded in 1991 (10.63 °C) while as highest temperature on the changing land use land cover in Doodhganga catch-
was recorded in 2001 (14.73 °C). The last decade (2000– ment. Particularly, agriculture lands are being converted to
2009) was the hottest decade with an average temperature of apple orchards as the latter require less amount of water and
13.75 °C as compared to average of 12.74 °C from 1979 to hence are climatologically more viable.
1999. The precipitation data shows a declining trend, even The depletion in the wetland extent are mainly attributed
though weak, as seen from the Fig. 12b with r2 of 0.14. to the encroachment by the farmers, increase in the settle-
Highest precipitation of 943 mm has been recorded in 1983 ments, conversion of wetland area into agriculture, planta-
while 2000 recorded the lowest precipitation of 423 mm. tion and built-up, and climate change (Joshi et al. 2002;
Relatively low precipitation has been recorded in late 2000s Kraiem 2002). From the data, it is evident that the open
as compared to that in early 1980s. Similarly, the analysis of water extent in the wetland has receded from 1.74 km2 in
the time series of the discharge data of the Doodhganga 1969 to 0.31 km2 in 2005 (Fig. 14a). However, the 2008
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Table 5 Accuracy assessment of land use land cover delineated from 2005 satellite data
Reference data
AG ER FA FO HO PA PL RI RB SE SC SN WB Row User’s
total accuracy
(%)
Classification data
AG 19a 0 0 0 1 0 0 0 0 0 0 0 0 20 95.00
ER 0 8a 1 0 0 0 0 0 0 0 0 0 0 9 88.89
FA 0 0 12a 0 0 0 0 0 1 0 0 0 0 13 92.31
FO 0 0 0 32a 0 0 2 0 0 0 0 0 0 34 94.12
HO 0 0 0 0 14a 0 1 0 0 0 0 0 0 15 93.33
PA 0 0 0 0 0 13a 0 0 0 0 1 0 0 14 92.86
PL 0 0 0 0 0 0 8a 0 0 0 0 0 0 8 100.00
RI 0 0 0 0 0 0 0 12a 0 0 0 0 0 12 100.00
RB 0 0 0 0 0 0 0 0 7a 0 1 0 0 8 87.50
SE 0 0 0 0 0 0 0 0 1 16a 0 0 0 17 94.12
SC 0 1 0 0 0 0 0 0 1 0 21a 0 0 23 91.30
SN 0 0 0 0 0 0 0 0 0 0 0 6a 0 6 100.00
WB 0 0 0 0 0 0 0 0 0 0 0 0 7a 7 100.00
Column total 19 9 13 32 15 13 11 12 10 16 23 6 7 186
Producer’s 100.00 88.89 92.31 100.00 93.33 100.00 72.73 100.00 70.00 100.00 91.30 100.00 100.00
accuracy (%)
a
Overall accuracy = [(19 + 8 + 12 + 32 + 14 + 13 + 8 + 12 + 7 + 16 + 21 + 6 + 7)/186] × 100 = 94.09 %
AG agriculture, ER exposed rock, FA fallow, FO forest, HO horticulture, PA pasture, PL plantation, RI river, RB river bed, SE settlement, SC scrub,
SN snow, WB waterbody
high-resolution IKONOS data shows an increase of structure and functions. There are umpteen studies that
0.05 km2 in the water extent with respect to the 2005 data have demonstrated the adverse impacts of the human influ-
mainly due to its acquisition in winter when the discharge ences on the wetlands all over the world (UNEP 2007)
from the feeder stream is higher compared to the autumn Further, the land use and land cover dynamics in the
season when all other images, used in the spatiotemporal catchment of the wetland have profound impacts on the
analysis, were acquired. Similarly, the marshy lands that functionality and health of the wetland. From the spatial
have tremendous ecological importance for the migratory and temporal analysis of the land use and land cover in the
birds, serving as the nesting and breeding grounds, have catchment, it is observed that there have been significant
showed consistent decline from 16.3 km2 in 1969 to changes from 1972 to 2005. There is marked increase in
5.62 km2 in 2008. The marshy land was the predominant the horticulture, plantation, scrub, settlements, and exposed
land cover in 1969 covering more than 85 % of the wetland rock while as the area under agriculture, fallow, forest,
area. The depletion of the marshy lands within the wetland pasture, and water resources has decreased. Settlements
has adversely affected the breeding patterns of the migra- have increased about four times from 4.63 km2 in 1972
tory birds. The emergence of the built-up areas within the to 15.35 km2 in 2005. Similarly, horticulture and plantation
wetland and its immediate surroundings has also responsi- show a significant increase in area from 1972 to 2005.
ble for the destruction of the wetland ecology and func- Permanent snow cover has decreased by about 40 km2
tionality (Fig. 14b). The built up, that was non-existent resulting in increase in the area of exposed rock. Area
within the wetland in 1969, has emerged and has colonized under agriculture and fallow has decreased by about
almost 0.11 km2 of the wetland in 2008. Due to these 100 km2 responsible for increase in spatial extent of horti-
encroachments and human settlements, the agriculture and culture and plantation. Similarly, forest and pasture areas
olericulture activity has got a boost within the wetland have been transformed into scrub because of deforestation
boundary and large areas of the wetland, spread over an from the past 33 years. These changes observed in the
area of 5.40 km2, have come under agriculture/fallow since catchment have adverse impacts on the wetland ecology
1969. All these anthropogenic influences within the wet- and hydrology. The impacts of these changes in the catch-
land have accelerated the deterioration of the wetland ment and those in the vicinity of the wetland are reflected
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Arab J Geosci
Fig. 12 a Graph showing
average annual temperature
from 1979 to 2009. b Graph
showing total annual
precipitation from 1979 to 2009
in the form of changes in the marshy and aquatic vegeta- flora and fauna. This nutrient enrichment boosts the
tion within the wetland. Increase in spatial extent of ex- growth of aquatic vegetation (Fig. 14c) found in the
posed surfaces is responsible for enhanced silt load in wetland like Nymphoides peltatum, Myriophyllum verticil-
Doodhganga stream which finds its entry into the Hokersar latum, Trapa natans, Typha angustata, and Phragmites
wetland thereby decreasing the depth and water retention australis (Dar et al. 2002).
capacity. The changes in the composition and distribution Within the wetland, various changes have been ob-
of marshy land and aquatic vegetation are showing adverse served in the composition and distribution of the aquatic
impacts on the migratory birds, hydrobiology, and hydro- vegetations. Some macrophytes like Nelumbo nucifera,
chemistry of the wetland (DEARS 2001; Khan 2000; Euryale ferox, and Acorus calamus have disappeared
Pandit and Kumar 2006). and some new species have been observed like Meny-
Further, the symptoms of the wetland deterioration are nanthese trifoliate (Kaul and Zutshi 1967). The main
attributed to the reckless use of fertilizers and pesticides reason for the disappearance of these macrophytes is
for agriculture and horticulture in the catchment, which attributed to the increase of silt load to the wetland
ultimately find their way into wetland through Dudhganga brought from the catchment by Doodhganga Nallah. An
River. This fact has been substantiated by the physico- increase in the number of macrophytic species from 24
chemical characteristics of the wetland as reported by (Pandit 1980) to 46 (Pandit and Kumar 2006) has been
Pandit and Kumar (2006). The analysis shows an increase reported. A possible reason for this may be the improve-
for nitrate and ammonical nitrogen from 1978 to 2002. ment in the flood situation following dry weather con-
Due to the increase of these nutrients, the ecology of the ditions leading mostly to summer draw-down during the
wetland is changing and adversely affecting the aquatic recent years (Pandit and Kumar 2006). As a result of this
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Arab J Geosci
Fig. 13 a Graph showing
discharge of Doodhganga
stream at head (Branwar). b
Graph showing discharge of
Doodhganga stream at Tail
(Barzulla)
increased aquatic vegetation, a drop in the oxygen con- 2009 shows a declining trend. This means that the re-
tent has been observed causing eutrophication which has duction of the water inflow to the wetland, as a conse-
direct effects on aquatic fauna like fishes. Vegetable quence of climate change, is responsible for the reduction
gardens and paddy fields, that have come up in the in the depth and spread of the water level of the wetland.
vicinity of the wetland since 1969, have also increased Wetland biodiversity, ecosystem, and services are indeed
the nutrient loading to the wetland as the use of fertil- under threat from the impacts of the climate change but
izers and irrigation in large quantities is practiced in proper management of the wetlands can reduce these
these vegetation gardens and paddy fields. impacts (O’Reilly et al. 2003; Verburg et al. 2003). The
The massive deforestation in the upper reaches of the drastic reduction in the area of marshy lands, the water
catchment has increased the silt load to the downstream depth, and the water spread, have changed the ecological
water bodies including Hokersar wetland. Due to the in- conditions within the lake and thus, adversely affected
creased siltation, the predominant land cover type in the the arrival of migratory birds, as less number of water
wetland, the marshy lands, has fragmented and is replaced fowl has been reported since the past few years. Analysis
by several land use and land cover classes, particularly of time series temperature data of Doodhganga catchment
aquatic vegetation. Excess load of siltation has also adverse- from 1979 to 2009 showed an increasing trend. The
ly affected the depth of the wetland which was 1.12 m increasing temperatures are possibly cause for bloom of
(Pandit 1980) and has reduced to 0.63 m only (Rather and alien aquatic invasive tropical water fern Azolla sp. in
Pandit 2002). Currently, the depth of the water has further Hokersar wetland which causes decrease in light penetra-
reduced resulting in decrease in the water spread. tion, dissolved oxygen content of Hokersar wetland be-
The time series analysis of the precipitation and dis- sides competing with the macrophytic species within the
charge data of the Doodhganga catchment from 1979 to wetland (Uheda et al. 1999). Dissolved oxygen shows an
18. Author's personal copy
Arab J Geosci
wetland. The construction of the network of roads around
the wetland and the proliferation of the willow planta-
tions within the wetland has hampered the natural flow
of the drainage adversely affected the wetland hydrology
and the environmental flows. Willows have been recog-
nized as a serious threat to wetland as they cause a range
of deleterious morphological and ecological changes to
wetlands and aquatic ecosystems (Poppe et al. 2006).
Conclusion
Various land use and land cover changes within the
wetland and its catchment have tremendous ecological
and socio-economic importance and it aptly depicts the
way people are treating the wetland ecosystems in the
mountainous Himalayan region. The water quality of the
wetland has deteriorated and changes in the vegetation
composition and distribution have been very significantly
affecting the biodiversity of the wetland. The wetland
depletion has serious implications not only on our flora
and fauna but also on livelihood of the people dependent
on the service and goods provided by the wetland. The
depletion and degradation of this wetland shall have
adverse impacts on the efficacy of the wetland in retain-
ing flood waters during peak discharge and flash floods
and thus endanger the lives and property of the Srinagar
city dwellers. The degradation of the marshy habitat of
the millions of the migratory birds from Siberia and
Central Asia has affected the arrival of these birds as
noticed by their less numbers in the recent years. De-
creasing trend in the precipitation has a direct bearing on
land use land cover dynamics in Doodhganga catchment.
Agriculture lands are getting converted in orchards main-
ly because less amount of water is required in the latter
case. Increase in temperature causes interference in the
hatching of eggs of birds besides disturbing the species
composition of natural vegetation. From the analysis and
discussion of the results, it is thus concluded that the
Fig. 14 a Loss in water spread due to ingress of silt from Doodhganga
main reasons for the deterioration of the Hokersar wet-
catchment and partly because of the encroachment. b Built-up areas land are increase in the nutrient and silt load from the
coming-up just around the main wetland body as a consequence of catchment due to deforestation and reckless use of pesti-
faulty regulatory framework. c Reckless growth of macrophytes within cides and fertilizers, encroachment, unplanned urbaniza-
the main wetland body as a consequence of urbanization and agricul-
tural practices around Hokersar
tion in the vicinity of the wetland, and the decreased
discharge to climate change observed in the region. It is
suggested that an appropriate mechanism is established
inverse relationship with temperature as per Henry’s Law for continuous monitoring of the wetland, its immediate
(IUPAC 1997, b). Hence, the increasing temperatures are surrounding and the catchment for land system changes,
also responsible for reduction in dissolved oxygen con- hydrochemistry, biodiversity, and wetland hydrology so
tent in the Hokersar wetland. Further, the direct discharge that a robust strategy and action plan is developed for
of the effluents and sewage from the surrounding areas the conservation and restoration of this important wet-
into the wetland because of increase in spatial extent of land, commonly called the Queen of Wetlands in
settlements has increased the nutrient loading of the Kashmir Himalayas.
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