WATERSHED AREA OF RAWAL LAKE
ABSTRACT
Over the years, several natural and anthropogenic activities have brought significant changes in the environmental conditions and land use activities of the Rawal Lake watershed. The change in land use/ land cover has resulted in deforestation, land degradation, landslides, and associated environmental changes. In this research/ study, spatial and temporal changes in land use and land cover are investigated Using Geographical Information System (GIS) and Remote Sensing (RS) techniques. Satellite images of Landsat 8 are used to assess the land use land cover changes for the years 2013 and 2021. Spatial and temporal changes in the land use/ cover were calculated using ArcGIS and ERDAS software. Results of the investigation revealed significant changes in the area, with 8% decrease in the scrub forest area from 2013 – 2021. The area of settlements has doubled during the study period and in total 533.829 hectares of land of scrub and conifer forest have been converted to settlements. The total shift in land area from scrub to agricultural land is 1976.1253 hectares (ha). Rapid Urbanization years may result in the degradation of forest cover in the watershed area. The research also evaluates the significant impacts of the changes on lake water capacity. The findings of the study could help in developing strategies to control, manage, and conserve watersheds.
1- INTRODUCTION
The Rawal Lake was constructed in1960s as an artificial reservoir that has been a supreme factor in contributing water to the locality of Rawalpindi and Islamabad. It is a key source in fulfilling the water needs for drinking purposes, household work and it also supplies water for irrigation purposes for the water needs of Rawalpindi and Islamabad.
The watershed area of Rawal Lake stretches over an area of 272 sq. km. The major streams or tributaries that comprise Rawal Watershed are Shahdara, Chatter, Bari Imam, KorangRiver and Quaid-e-Azam University stream. Among these, the main channel flowing in the watershed is the Korang River. Land use of the watershed is classified into agricultural land, settlements, rangeland, and forest area. Rawal watershed is Rawalpindi’s main source of water supply. It generates almost 33,995 hectares feet of water in an average rainfall/year and 83 million liters/day to fulfill drinking and other household needs (IUCN, 2005). It also provides water for irrigation to the downstream areas. The forest of the watershed is mainly natural and comprises conifer species and scrub forest.
Rawal Lake watershed is rich in biodiversity and is of significant importance for a number of species. The mammals in the area include pangolin, porcupine, jungle cat, jackal, wild bear, Common Fox, and yellow-throated marten. Reptile species Include Russell’s Viper and Indian cobra. Rawal Lake inhabits a diversity of 15 fish species that belong to 11 genera.
Rawal watershed has also been a fundamental site concerning tourism. It always presents an eye-catching view for all the people. As a new picnic spot, Rawal Lake in Islamabad fascinates many domestic and international tourists (Kausar et al., 2013). It has become a newly established amusement place for the folks of Islamabad and Rawalpindi in particular (Umaire, 2017). Murree Hills being the water source of some of the tributaries of Rawal Lake, is one of the most visited and loved tourist sites. It is Pakistan’s most established and famous hill station located at an altitude of 6000 to 7000 feet above sea level. Chattar Park, situated on the road to Murree is also part of the Rawal watershed and is a great stop to relax. It is a beautiful place with amazing surroundings and shining water.
Shahdara is another tourist spot in the watershed area which is well well-known amusement spot situated in the sub-rubs of Margalla Hills of Islamabad. It is 10 km away from President House in the North-East and the North of Barakhao (also a watershed area). The shrine of Bari Imam situated in the suburbs of Islamabad is also a fundamental source of religious importance. It presents a mystic atmosphere that is of great importance in promoting religious tourism. So in all, we can get a clear picture of how the Rawal watershed has been an essential element in promoting tourism. All the places discussed earlier are important and famous points for tourist attractions and millions and thousands of people visit these places to travel and explore nature’s beauty.
The spatial and temporal dimensions of the land cover and land use in the Rawal watershed are not well explored. The most recent information on land cover and use
changes of rawal watershed available is 9 years old.
Thus the primary objective of this study is to investigate the spatial and temporal change in land cover and land use changes over 8 years i.e 2013-2021. The study focuses to evaluate and asses the spatial and temporal urban and forest land use/ landcover changes. Furthermore, this research evaluates the significant impacts of the changes detected and the potential effect on the lake water capacity.
Deteriorating Landuse change land cover change in the watershed will not only bring the loss of useful natural resources but can also lead to several other environmental, social and economic issues such as wildlife destruction, soil erosion, flooding, reduced tourist attraction, reduced water capacity and above all, climate change. All things considered, the watershed has been perceived as the fundamental unit of land use recognized by both established researchers and by environmental policy directives in law (Trancoso et al., 2010).
2- LITERATURE REVIEW
Throughout the time, man has modified the framework of land use, changing whole biomes over to other utilities, mainly the Forest biome. Any modifications to the land use can bring about critical changes to the water balance elements of a watershed (Pires and Costa, 2013).
Satellite imagery is a useful source of landcover information, and urban landcover has been identified and mapped using remotely sensed data with a fine spatial resolution (Yang, 2002; Tapiodor and Casanova, 2003). In recent years, there has been an increasing awareness of the effects of geographical variables in ecosystems. In particular, fundamental variables, such as scale and spatial patterns, have become increasingly important in a vast array of ecological research (Drakare Lennon and Hillebrand, 2006; Agrawal, et al., 2007). RS now regularly provides agricultural scientists and ecologists with information on the earth and its environment at scales from local to global. GIS provides, among other things, a means to store analyze, and visualize spatial data including those derived from remote sensing together with associated advancements in computational facilities and specialist tools, such as methods for spatial analysis (Austin, 2007; Osborne, Foody and Seoane, 2007).
Considering the spectral resolution for monitoring landcover/land use behavior, natural resource environment, and risk of land degradation at the watershed area in Pakistan. RS and GIS can contribute to monitoring land use/land cover in a wide variety of ways. RS has frequently been used to derive landcover information. Changes in land use and land cover are major variables affecting ecological systems. Landcover types, for example, differ greatly in their biogeochemical cycling, and thus knowledge of their distribution is important in many environmental modeling studies. Landcover change has major impacts on issues ranging from climate change to biodiversity conservation. Given that the remotely sensed response is essentially a function of landcover type, there has been considerable interest in using remotely sensed data as a source of information on landcover.
Rawal watershed has been reported to have undergone significant changes in its environmental conditions and land use activities due to numerous socio-economic
and natural factors. A study conducted by Saeed et al. (2011) reported significant changes in the coverage of conifer forests (34 % decrease), scrub forests (29 % decrease), and settlement (231 % increase) during the decade 1992-2010. The rate of decline in the conifer class is about 19 ha/annum while that of the scrub class is 223 ha/annum. The findings indicated that there were accelerated land transformations and Changes in the process of evapotranspiration, soil water penetration, erosion, and runoff are the principal outcomes of land use changes in the watershed.
The land change such as deforestation and increased agriculture in the Rawal watershed can lead to soil erosion, land sliding, and surface runoff which can ultimately result in more flooding in low-lying areas, deteriorated water quality of dam, and reduced water holding capacity of the dam as a result to siltation. According to 2018 estimates, there are currently 14,000 acre-foot of water in Rawal Lake and authorities are concerned there will be more silt and sediments in the lake with time. The last sedimentation survey at Rawal Lake was conducted in 2000 and all the current water capacity estimates for the lake are based on old figures. The original water capacity of the lake was 47,000 acre-foot which has been decreased; due to increasing sedimentation generated from natural and anthropogenic factors in the catchment area of the watershed.
Comprehensive information on the spatial and temporal distribution of land use/landcover is essential for planning, utilization, and better management of land resources, especially for developing countries. Monitoring of land use/land cover is useful to plan development activities, such as major schemes for community requirements and sustainable watershed management. This information is also helpful in monitoring the dynamics of land use resulting from the growing needs of the population growth. There is a need to carry out a new systematic study carried out to document the land use variability in the Rawal watershed.
Zafar, Baig, and Irfan (2011) studied land use changes using satellite RS data for management zoning of the Margalla Hills National Park based on different environmental factors. Wheat yield was estimated based on the interpretation and analysis of the. Ashraf, Naz, and Mustafa (2011) studied satellite image data of drought (2001) and post-drought (2006) periods to assess changes in land use and vegetation cover through hybrid (visual and digital) interpretation techniques.
Diallo and Zhengyu (2010) used RS technology to assess Bamako’s landcover change in China within 20 years. Issa (2009) utilized change detection techniques to assess land development achievements on Al Sammalyah Island, off the coast of Abu Dhabi, the capital city of the United Arab Emirates. Kamran and Jamil (2008) used RS and GIS techniques for the detection of urban growth in Islamabad and its impacts on climate. Malik and Husain (2006) used SPOT XS (multi-spectral) satellite image data for mapping different land use/land cover in the suburbs of Rawalpindi to assess the impact of urbanization on the scrub forest dominated by Acacia modesta.
Roohi, Ashraf, and Ahmed (2004) conducted a study to evaluate the capability of LANDSAT-TM data for the identification of various land use and vegetation covers, like forests, crops, shrubs, and grasses near Fatehjang area. Singh and Khanduri (2011) studied land/landcover of Pathankot and Dhar Kalan Tehsil using RS data from the 1991, 2002, and 2006 periods to detect changes that had taken place, particularly in the built-up and forest areas and evaluate socio-economic implications of the predicted changes
Detecting the change in the pattern of land cover and land use can help in the proper monitoring and management of the watershed area and is also required for future planning and monitoring (Ashraf, 2013). Satellite imagery has been used as a major data source to detect or analyze the temporal changes in wetlands, coastal areas, watersheds, lakes, playas etc. since the 1980s.
Major sources for such analysis include Landsat (TM and ETM), Radio Detection And Ranging (RADAR), and Advanced Very High Resolution Radiometer (AVHRR). Various studies have attempted to address land use and land cover change in watersheds through different methods. Nagarajan and Poongothai (2012) exposed the impact of land cover/land use changes in the Manimuktha subwatershed of the Vellar basin, Tamil Nadu. Hu et al. (2012) analyzed land use change characteristics in the Jiuxiang River watershed from 2003 to 2009. Bazgeera et al. (2008) made an assessment of land use changes (1984 to 2003) and their implications on climatic variability for the Balachaur watershed in Punjab, India.
3- MATERIALS AND METHOD
3.1- Study Area
Study Area The study area covers the Rawal Lake watershed situated in the Pothwar plateau that begins at lake in Islamabad and is 10 km from Rawalpindi. The area comprises a surface area of about 8.8 km2 (at latitude 33°42´ N, longitude 73°07´ E, and altitude of 1,800 m). It has an undulatory topography with terraced land for agriculture, high slopes, and dissected patches under natural vegetation Five major and forty-three small streams run off into the lake. Physiographically, the watershed region includes 34 % sloping region (2000 m). The altitude goes from 480 m to 2,168 meters above ocean level. The vegetation in the watershed area has xeric characteristics, with broad-leaved deciduous, evergreen trees and diverse shrubs on the southern slopes. The dominating plant species are (Wild Olive), (Granda) and (Sanatha). Vegetation is open with scattered patches of pine trees. Sub-tropical pine zone stretches over higher elevations. The dominant plant species present are Pinus Roxburghi, Quercus Incana, and Myrsina Africana. Over the past years, several natural and anthropogenic sources have resulted in the degradation of the watershed and have significantly reduced the lake’s water quality and storage capacity
3.2- Data Acquisition
The data in this study included four multispectral satellite images of Landsat 8 having path-row 150-36, and 150-37 to assess LULC changes for the years 2013 and 2021. The Landsat 8 images are freely available and were acquired in September from the Landsat archive of the United States Geological Survey (USGS).
3.3- Image Pre-Processing
Pre-processing of the satellite images is required before detection of change with the primary objective of establishing a more accurate affiliation between the acquired data and biophysical phenomena. The satellite images were geo-referenced to the Universal Transverse Mercator (UTM) coordinate system and World Geodetic System (WGS) 1984 datum with the help of image processing and GIS software. Data was processed in ERDAS Imagine for mosaicking and sub-setting of the image based on Area of Interest (AOI).
3.4- Image Enhancement and Visual Interpretation
The goal of image enhancement is to improve the visual interpretability of an image by increasing the apparent distinction between the features. The process of visually interpreting digitally enhanced imagery attempts to optimize the complementary abilities of the human mind and the computer. The mind is excellent at interpreting spatial attributes on an image and is capable of identifying obscure or subtle features (Lillesand and Kiefer, 1994). Contrast stretching was applied to the two images and two false color composites (FCC) were produced.
3.5- Image Classification
Land cover classes are typically mapped from digital remotely sensed data through the process of supervised digital image classification (Campbell, 1987). The overall objective of the image classification procedure is to automatically categorize all pixels in an image into land cover classes or themes (Lillesand and Kiefer, 1994). Supervised classification was done of the study area maps for each year. The images were classified by assigning per-pixel signatures and differentiating the watershed into five classes based on the specific Digital Number (DN) value of different landscape elements. These seven major land use classes were selected based on their distinct reflectance characteristics and ecological importance in the watershed area. The delineated classes were Forest, Scrub forest, Agriculture, Settlements, Water, and Bare soil/rocks (Table). The following maximum likelihood algorithm was used for the supervised classification of the images. For the enhancement of classification accuracy and therefore the quality of the land cover/ use maps produced, visual interpretation was very important. Thus, visual analysis, reference data, as well as local knowledge, considerably improved the results obtained using the supervised algorithm.
Table 3.1: Classes set out for Supervised Classification
| Sr. No | Class name | Description |
| 1. | Agriculture | Crop Fields and Fallow lands |
| 2. | Settlements | Residential, Commercial, Industrial, Transportation, |
| Roads, mixed urban Land areas. | ||
| 3. | Scrub forest | Shrubland, scrubland, scrub, brush, or bush, plant including grasses, herbs, and geophytes |
| 4. | Forest | A large area of land that’s covered in trees. |
| 5. | Water | River, open water, Lakes, Ponds and reservoirs. |
| 6. | Barren land | landscape is dry and bare, and has very few plants and no trees |
3.6- Accuracy Assessment
Accuracy assessment of the classified data is very useful in the detection of change analysis, it is essential to perform accuracy assessment for individual classification (Owojori and Xie, 2005). For the accuracy assessment of the classified maps, 35 points were chosen using the random stratified method to represent different land cover classes of the area. The comparison of ground truth (Google Earth Pro) and classification results was carried out statistically. In addition, an overall accuracy test was also performed to measure the extent of classification accuracy.
3.7- Land use/cover change detection
Changes occurring on the earth’s surface can be credited to either natural or anthropogenic forces. Natural changes are related to both seasonal and annual variations in climatic conditions and are often reflected by variations in natural land cover. The impacts of human-induced changes are not necessarily limited to areas where intentional modification of the landscape has taken place. The success of change detection from imagery relies upon both the nature of the change involved and the success of the image preprocessing and classification procedures. (Milne, 1988)
The change detection procedures assume that a change in surface cover or surface material will produce a corresponding change in the reflectance of the study area. Spatial–temporal changes in land use/cover were calculated using ArcGIS software and ERDAS software. Many change detection techniques have developed recently; the most commonly used are image differencing, principal component
analysis, and post-classification comparison (Lu et al., 2004). The post-classification change detection technique, performed in ArcGIS was employed for the study because it does not only give the size and distribution of changed areas (either negative or positive), but it also gives the percentages of other land cover classes that share in the change in each land cover class individually. Post-classification has been successfully used by various researchers in urban environments due to its efficiency in detecting the location, nature, and rate of change (Hardin et al., 2007).
4- RESULTS AND DISCUSSION
The land use/landcover condition of the watershed was estimated for different periods, i.e. 2013 and 2021. The classified LULC maps of the Rawal watershed for the years 2013 and 2021 are given in Fig. These maps help to determine the quality of information derived from the data. Image analysis is performed through visual and digital interpretation of the RS data. Through visual interpretation of RS data, different land features such as settlements, agricultural land areas, forest cover, and drainage pattern of the study area are investigated. Assessment of classification accuracy of 2013 and 2021 images was carried out to determine the quality of information derived from the data. The results showed that the achieved overall classification accuracies were 95% and 92% for 2013 and 2021 classified maps. Lea and Curtis (2010) stated that accuracy assessment reporting requires the overall classification accuracy above 90% which were successfully achieved in the present research.
In the year 2013, conifer forest was found dominant over 42 % of the total watershed area. Scrub forest indicated coverage of about 28 % in the watershed area (Table) and the Settlements class stretched over 7 % area mainly in patches and scattered form. Agriculture was practiced in small to medium farms in plains and in patches over hill terraces in the watershed area.
Table 4.1: Land cover/use classes of Rawal watershed and area calculated from classified image
| Land Use/Land Cover Class | 2013 Area (ha) | % | 2021 Area (ha) | % | 2013-2021 Changed Area % | Result |
| Scrub Forest | 7633.98 | 28.6 | 5311.62 | 20 | 8 | Decrease |
| Settlements | 2003.67 | 7.5 | 4097.88 | 15.4 | -7.9 | Increase |
In the year 2021, the forest is still dominant in coverage of the study area. The scrub forest was found in over 20% area and the Settlement class stretched over 15 % of the watershed area. The spatial and temporal change results show a major decline of 2300 hectares in the scrub forest area of the rawal watershed. The scrub wood is mostly used
as fuel at the local level due to the non-availability of other energy sources in the area. Due to extensive wood cutting, the scrub forest has changed into settlements and a major part of it has been converted into agriculture.
According to the results of the change detection (Shown in Table), the total shift in land area from scrub to agricultural land is 1976.1253 hectares (ha). The reason behind this increase in the agriculture class is the rapidly growing population of twin cities resulting in demand for more food.
| From Class | To Class | 2013-2021 Area (ha) |
| Agriculture | Settlements | 8.5792 |
| Forest | Agriculture | 579.8654 |
| Scrub | Agriculture | 1976.1253 |
| Scrub | Settlements | 331.8679 |
| Forest | Settlements | 201.9611 |
Two main approaches are being adopted in Pakistan to increase agricultural food production. Bringing more area under cultivation can be done by converting the area covered by other classes into agricultural areas. The major class subjected to loss of area for this purpose is scrub forest. A similar study conducted previously on the Rawal Watershed also reinforces the findings that agricultural area has increased in past decades in the area and also that over the years, forest, scrub, water, and range land cover shifted to agricultural land cover (Ashraf, 2013). The results also found that 579.8654 hectares of forest have been converted into agricultural land.
The second class which showed a significant increase during the study period was Settlements. The area of settlements has doubled during the study period of eight years. The reason behind this rapid increase in area under the settlement class is deforestation. A total of 533.829 hectares of land of scrub and conifer forest has been converted to settlements. Over the past two decades several new housing schemes, farmhouses, and recreational pursuits e.g. Murree resorts, Valley parks, etc. have been developed in the watershed.
Along with these developments, there is an incline towards the construction of new pavements, highways, roads, and other structures to access these areas, especially in the Murree region. Another reason is the increase in a number of houses due to the
intensification in local inhabitants and partly due to government and private agencies’ investment in developing educational institutions, guesthouses and hotels, military colonies, offices, and residential areas which are often occupied only seasonally. In addition, the improvement of roads and transport facilities e.g. the development of the new Murree motorway has significantly increased the number of tourists in the area. Along with these, the mushrooming growth of commercial buildings has also been observed in the area from Islamabad to Murree. Overall scrub class has shown the highest conversion to the agriculture class, of the total watershed area, followed by an increase in settlements.
The increase in construction activities, deforestation, and increase of extensive agricultural practices in the watershed area can lead to soil degradation and soil loss due to erosion. According to Gliessman (2006) soil erosion has a direct cause-effect relationship with soil agriculture practices. Conventional agricultural practices such as monoculture, short rotations, and intensive tillage leave the soil exposed to erosion by wind.
Similarly ineffective irrigation practices cause water erosion of agricultural soil and thus every year tons of soil is lost to either air or water. The forest area has been subjected to deforestation due to an ever-increasing population rate which in turn requires increased agriculture production. Hence, it has been observed that the vegetation class in the watershed area was reduced and replaced by either the Settlement or Agriculture class which continued to increase.
As discussed in the above sections the watershed has witnessed a rapid increase in deforestation, urbanization, and agriculture, all of which affect the water class in a variety of ways. The major impact of these land cover and land use changes is on the water quality and availability and water capacity of the dam.
In 2016 it was reported by Dawn News that according to a WAPDA survey, Rawal Lake has lost around 35% of its designed storage capacity of 42,000 acre feet, which has been reduced to around 27,000 acre feet. Another Dawn article revealed that According to 2018 estimates, there were 14,000 acre feet of water in Rawal Lake and officials are worried there will be more silt and sediments in the lake with time.
Officials of the Punjab Irrigation Department said that the torrential rains in the watershed area are bringing in silt and sediment; this compromises the storage
capacity in the lake. The officials fear a significant reduction in the water-holding capacity of the lake due to extraordinary sediment deposits since the year 2000. Major infrastructure development and massive construction activities have occurred upstream after the year 2000. The official said, adding that this led to a massive flow of heavy silts such as waste construction material, pebbles, etc along the fast-flowing seasonal springs.
Cement and sand have been flowing into the lake during the rainy seasons for the past 18 years and construction and deforestation have devoid the catchment areas of full-grown trees that were holding thin soil along the slopes. This has triggered the flow of mud and soil during monsoon rains into Rawal Lake.
Hence, proper management of the watershed resources is required because, without proper management, these resources will soon be lost or will no longer be able to play their important role in the sustainable socioeconomic development of the area. What is required here is an adequate knowledge of land use/land cover, requirements, and productive and efficient watershed management.
Also read: http://www.dailytimes.com.pk/default.asp…009_pg11_1
CONCLUSION AND RECOMMENDATIONS
Recent natural and anthropogenic activities have brought substantial changes in the land use/land cover of the Rawal Lake watershed. The changes considerably include the degradation of the forest area in the watershed. This has been caused due haphazard expansion of settlement and agriculture and mainly due to a lack of proper management and land use planning in these areas and the major impact of this expansion was the subjection of forests.
The increase in settlements and decrease in forest cover is a result of uncontrolled socioeconomic practices in the watershed area. Unplanned and uncontrolled Urbanization and illegal wood-cutting practices must be eliminated.
All the stakeholders including local communities must be aware of environmental issues. The rapid growth in urbanization must be monitored using Remote Sensing techniques. Environmental laws must be enforced to prevent the damage to an extent. Risk-prone areas can be managed through effective soil water conservation techniques.
Stakeholder awareness and media campaigns should be launched to educate people to protect their natural environment. GIS and RS techniques can be used for continuous monitoring of land use/land cover changes in the watershed area. These techniques can be very helpful in studying the impacts of the changes as well as in planning their mitigation measures that will ultimately reduce the degradation.
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