synopsis ph.d research ( farooq cheema sb) 2nd
TRANSCRIPT
Ph.D THESIS (SYNOPSIS)
SEDIMENT YEILD FROM A MOUNTANIOUS WATERSHED IN PAKISTAN
(A CASE STUDY OF NARAN BASIN, A SUB-CATCHMENT OF KUNHAR RIVER)
BY:
NAME…………………………………………………...…FAROOQ AZIM CHEEMA
REGISTRATION NO…………………………………… 2007-Ph.D-WRE-03
DATE OF REGISTRATION…………………………….02 JANUARY, 2008
PART TIME/FULL TIME:……………………………....PART TIME
SUPERVISOR:
PROF. DR.MUHAMMAD LATIF (DIRECTOR)
CENTER OF EXCELLENCE IN WATER RESOURCES ENGINEERING
UNIVERSITY OF ENGINEERING AND TECHNOLOGY, LAHORE
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SEDIMENT YIELD FROM A MOUNTAINOUS WATERSHED IN PAKISTAN
(A CASE STUDY OF NARAN BASIN, A SUB-CATCHMENT OF KUNHAR RIVER)
Abstract
The high sediment yields from mountainous watersheds are threatening the storage capacities
of the reservoirs. A warming climate increases tropical cyclone intensity, causing more
intense rainfall. This creates problems for soil and water conservation and management,
particularly for countries in the western tropical and subtropical Pacific region, where
cyclones (typhoons) frequently occur. Countries located on a typhoon track and frequently
suffer from devastating floods and landslides generated by typhoons. There are speculated
impacts of global warming on the hydrological cycle and associated processes and the threats
posed to the inhabitants of the locals.
Proposed study will present qualitative and quantitative evidence for the changing
characteristics of rainfall–runoff patterns and the associated geomorphic response under a
changing climate. In this study estimates of sediment yield for watersheds will be obtained
using a physical based distributed hydrologic and sediment transport Model which will be
compared with direct measurements.
For the verification of the Model results flows and sediment concentration data will be
collected from SWHP WAPDA a data collection Authority at site, they got this data by
installing automatic water level recorders on the streams and by measuring the flow velocity
using a current meter. Stream water samples are analysed in the laboratory to obtain the
values of suspended sediment concentration required to calculate the sediment load.
This study will focuses on sediment problems in river basins and the difficulties involved.
Firstly overviews of the sediment problems experienced by individual countries or particular
issues relating to the wider region will be presented; and then case studies that deal with
specific problems and their management will be investigated. The overviews highlight the
sediment problems faced including soil erosion and reservoir sedimentation; recent changes
in the sediment loads and their wider implications; the impact of human activity on the
sediment loads of rivers; and new challenges for erosion and sedimentation research will be
linked to contemporary issues.
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1.0 INTRODUCTION
Earth's climate has undergone radical changes in the distant as well as the recent past
and is almost certain to undergo more radical changes in the not-too-distant future. As
industrialization, population, and urbanization continue to increase, so too will stressors on
the environment such as pollution. Such change in climate and environmental quality could
have huge implications for quality of life. Regardless of where we stand on the often
politically charged issue of global warming, or global climate change, we owe it to ourselves
and our children to take an intelligent look at the data and develop actionable, intelligent
alternatives.
Climate change has many origins such as; changes in solar activity, alterations in the
earth's orbit about the sun, natural variability including volcanic activity, anthropogenic (of
human origin). Changes since 1850 in the composition of the atmosphere and increases in the
principal Greenhouse gases -- Carbon Dioxide and Methane -- have been linked to human
activities.
Climate normals or average weather conditions computed from a 30-year period can
be significantly different when computed from early last century and compared to the present
time. Similarly, future climate normals may differ significantly from today's climate.
An understanding of the precipitation regimes throughout the world may allow the
definition of climatic zones based on temperature and precipitation regimes. This may permit
the definition of areas of high and low erosion rates. It is difficult to classify distinct climatic
zones as they tend to merge into one another rather than have sharp boundaries but a number
of general models have been produced. There have been many climatic classifications
produced but one of the most common is based on the original Koppen classification
(Pidwirny, 1999) with eight climatic regions based on four temperature zones and one
moisture zone and the seasonal domination of air masses.
High sediment yields are natural in the tropics and are balanced by the high rates of
erosion and soil production. When this balance is disturbed by anthropogenic activities then
the sediment yield is dramatically increased at the expense of soil renewal. The steady rise in
soil erosion in tropical countries due to increased cultivation has endangered reservoir
projects and caused doubts about the viability of existing and future schemes. The
impoundment of water for potable and irrigation supplies, hydro-power, and flood control is a
necessary step towards improved national incomes. Untimely sedimentation may reduce the
benefits and, if it is ignored, remedial measures may become prohibitively expensive.
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2.0 PROBLEM STATEMENT
2.1 Environment and motivation
Sediment yield is inextricably linked with climate, so the prospect of global climate
change has serious implications for water resources and their development. It is mentioned in
IPCC report that increased evaporation combined with regional changes in precipitation
characteristics has the potential to affect mean runoff, frequency and intensity of floods and
drought, ground water, soil moisture, and water supplies for irrigation and hydroelectric
generation. The potential for global climate changes to increase the risk of soil erosion is
clear, but actual damage is difficult to estimate. TAMS and HR Wallingford (1998) have
estimated the sediment discharge in Tarbela Reservoir as an average of 200 metric ton per
year. There are ways in which soil erosion and sediment production may be affected by
climate change:
Changes in temperatures
Changes in seasonal rainfall distribution , and
Changes in rainfall extreme
2.2 Problem Narration
Sediment problems are assuming increasing importance in many river basins and can
represent a key impediment to sustainable development. Such problems include accelerated
soil erosion, reservoir sedimentation and the wider impact of sediment on aquatic ecology,
river morphology and water resource exploitation. They are further complicated by the
impact of climate change in causing both increases and decreases in the sediment load of
many rivers in recent years. To address these problems, sediment management process must
be investigated considering factors of climate change. In perspective of recent threats of
climate change, the safe usability of existing and new development of water resources
infrastructure is not taken into account in prevailing practices of project design and appraisals
which require ascertaining quantifiable impact of local climate change.
2.3 NEED OF STUDY
Critical decisions are made on the basis of 'climate normals'. For example, reservoirs
life and their flushing capacity are designed to take into account past climates' extremes.
Changing extremes due to climate change may render some designs unfit or unable to
withstand future conditions within the design's expected lifetime. Although a factor of safety
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and future expansion margins are kept to cover up this and other unforeseen; however there is
need to assess quantifiable impact due to climate change in respect of reduction in uncertainty
and risk.
3.0 STUDY OBJECTIVES
It is aimed to estimate the effects of the anticipated changes on the stream suspended
sediment loads, exemplified on a stream draining a watershed. The overall objectives of this
research will be following:
1. Identify and evaluate basin-specific hydrologic-based rainfall and runoff factors.
2. Identify and evaluate basin-specific sediment erosion, transport and yield factors.
3. To establish the rainfall runoff relationship of the watershed
4. To establish the sediment concentration and yield relationship with the runoff
3.1 Scope of study
In attempt to solve stated problem, following work will be performed:
Exhaustive literature survey for analysis of the problem domain and factors extraction
Spatial, Physical properties and Land use data processing with GIS
Data analysis of precipitations, temperatures, flow and sediments
Rainfall runoff relationship
Runoff – sediment yield relationship
Assessing sediment yield
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4.0 LITERATURE SURVEY
4.1 Research Background
Climate change impacts on basin’s inflow supply in various ways. It may alter
seasonal temperature and precipitation, shift the timing of stream flow runoff, and reduce the
ability of existing supplies to meet water needs. The only means available to quantify the
non-linear climate response is by using numerical models of the climate system based on
well-established physical, chemical and biological principles, possibly combined with
empirical and statistical methods. These are designed mainly for studying climate processes
and natural climate variability, and for projecting the response of the climate to human-
induced forcing (Baede et al., 2001).
Shrestha et al. (1999) analysed and found maximum temperature data from 49 stations
in Nepal for the period 1971–94 reveal warming trends after 1977 ranging from 0.068 to
0.120C per year in most of the Middle Mountain and Himalayan regions, while the Siwalik
and Terai (southern plains) regions show warming trends less than 0.030C per year. The
subset of records (14 stations) extending back to the early 1960s suggests that the recent
warming trends were preceded by similar widespread cooling trends. Distributions of
seasonal and annual temperature trends show high rates of warming in the high-elevation
regions of the country (Middle Mountains and Himalaya), while low warming or even
cooling trends were found in the southern regions. This is attributed to the sensitivity of
mountainous regions to climate changes. The seasonal temperature trends and spatial
distribution of temperature trends also highlight the influence of monsoon circulation.
A study of the long-term trend in surface air temperatures in India by Hingane et al.
(1985) indicated an increase in mean annual temperature of 0.480C over the past century. A
study of changes in air temperature of Qinghai-Xizang (Tibetan) Plateau showed a decreasing
trend from 1950 to 1970 and an increase after 1970 (Li and Tang 1986).
Linear regression analysis by Archer (2003) suggests that a 1°C rise in mean summer
temperature arising from climate change would result in an increase of 17% in summer runoff
for the river Shyok (basin area 65 025 km2) and a 16% increase for the river Hunza (basin
area 13 925 km2), respectively. Fowler and Archer (2006) found that increase in winter
maximum temperature is large and statistically significant (p< 0.05) at Gilgit, Skardu, and
Dir, with increases of 0.27°, 0.55°, and 0.51°C decade-1
, respectively.
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Singh and Kumar (1997) and Bengtsson (2005) suggest through modeling studies that
increased temperature results in increased evaporative loss and since snow cover volume is
limiting in reduced runoff, with an estimated decrease of 9% for a 1°C rise in temperature for
the Satluj basin in the western Himalayas. Akhtar et al. (2008) found that the annual mean
temperature rise by the end of the century ranges from 0.3 to 4.8 ˚C. The warming is more
pronounced in the Hunza (4.5˚C) and Gilgit (4.8˚C) river basins compared to the Astore
(0.3˚C) river basin where in the summer season the temperature even decrease by 0.2˚C. The
precipitation changes in the Hunza (19%) and Gilgit (21%) river basins are somewhat similar,
while precipitation changes in the Astore (113%) river basin are comparatively large.
Archer and Fowler (2004) found the trends of rainfall from 1961 to 1999 with decadal
increases in order of 22, 103 and 120 mm at Skardu, Shahpur and Dir climate station of upper
Indus basin respectively. Khan (2001) concluded that the analysis of time series of river
flows and associated climatic data did not find any pattern of trends likely to be caused by
‘greenhouse warming’ in the Upper Indus Basin.
Wang et al (2009) found in a sub-basin of Yellow River for the period 1950–2000 that
the decrease in percentage change of run-off due to climate change impact is found to be 89%
followed by 66% and 56% in 1970s, 1980s and 1990s, respectively. Labat et al., (2004)
claimed a 4% increase in global total runoff per 1°C rise in temperature during the 20th
century.
According to White, W.R. 1990, Sediment yields vary with climate, the geology of the
catchment and land-use practices. White, W.R. 2000 investigated the sediment amount and
nature of the sediment entering or likely to enter the reservoir needs to be established. This
requires measurements over many years to establish the results with the confidence which is
required. There are various approaches to this task. Most commonly sediment transport is
measured at a gauging station not too far upstream of the reservoir and a relationship between
flow rate and sediment transport rate is established. The long hydrological record is then used
to compute the total amount of sediment passing the gauging station by integrating over the
period of the record. There are some dangers in doing this because there is no unique
relationship between flow rate and sediment transport rate for fine cohesive sediments, the
quantities of sediment being determined by the amount being washed off the catchment not
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the capability of the river to transport them. Bed load is difficult to measure and is often
estimated as 10% of the total sediment load. An alternative approach is to calculate the bed
load using established predictive techniques. In the case of existing reservoirs, information
about the amount of sediments entering the reservoir can be augmented by surveys of the
amount and nature of the material settling within the reservoir. Care is required, however, to
allow for the amount of material, mainly fine, which passes through the reservoir without
deposition. Bed material sampling should be undertaken in the reservoir and in the rivers
which feed the reservoir. A sound knowledge of the nature of these sediments, including their
size and specific gravity, is an essential requirement to provide inputs for numerical models
which simulate sediment movement.
Michael et al. (2005) projected potential increases in erosion of the order of 20 to 60%
over the next five decades for two sites in Saxony, Germany. These results are arguably
based on significant simplifications with regard to the array of interactions involved in this
type of assessment (e.g., biomass production with changing climate). Pruski and Nearing
(2002a) simulated erosion for the 21st century at eight locations in the USA using the
HadCM3 GCM, and taking into account the primary physical and biological mechanisms
affecting erosion. The simulated cropping systems were maize and wheat. The results
indicated a complex set of interactions between the several factors that affect the erosion
process. Overall, where precipitation increases were projected, estimated erosion increased
by 15 to 100%. Where precipitation decreases were projected, the results were more complex
due largely to interactions between plant biomass, runoff, and erosion, and either increases or
decreases in overall erosion could occur.
A significant potential impact of climate change on soil erosion and sediment
generation is associated with the change from snowfall to rainfall. The potential impact may
be particularly important in northern climates. Warmer winter temperatures would bring an
increasing amount of winter precipitation as rain instead of snow, and erosion by storm
runoff would increase. The results described above which use a process-based approach
incorporated the effect of a shift from snow to rain due to warming, but the studies did not
delineate this specific effect from the general results. Changes in soil surface conditions, such
as surface roughness, sealing and crusting, may change with shifts in climate, and hence
affect erosion rates.
Zhang and Nearing (2005) evaluated the potential impacts of climate change on soil
erosion in central Oklahoma. Monthly projections were used from the HadCM3 GCM, using
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the SRES A2 and B2 scenarios and GGa1 (a scenario in which greenhouse gases increase by
1%/yr), for the periods 1950 to 1999 and 2070 to 2099. While the HadCM3-projected mean
annual precipitation during 2070 to 2099 at El Reno, Oklahoma, decreased by 13.6%, 7.2%,
and 6.2% for A2, B2, and GGa1, respectively, the predicted erosion (except for the no-till
conservation practice scenario) increased by 18-30% for A2, remained similar for B2, and
increased by 67-82% for GGa1. The greater increases in erosion in the GGa1 scenario was
attributed to greater variability in monthly precipitation and an increased frequency of large
storms in the model simulation. Results indicated that no-till (or conservation tillage) systems
can be effective in reducing soil erosion under projected climates.
A more complex, but potentially dominant, factor is the potential for shifts in land use
necessary to accommodate a new climatic regime (O’Neal et al., 2005). As farmers adapt
cropping systems, the susceptibility of the soil to erosive forces will change. Farmer
adaptation may range from shifts in planting, cultivation and harvest dates, to changes in crop
type (Southworth et al., 2000; Pfeifer and Habeck, 2002). Modelling results for the upper
Midwest U.S. suggest that erosion will increase as a function of future land-use changes,
largely because of a general shift away from wheat and maize towards soybean production.
For ten out of eleven regions in the study area, predicted runoff increased from +10% to
+310%, and soil loss increased from +33% to +274%, in 2040–2059 relative to 1990–1999
(O’Neal et al., 2005). Other land-use scenarios would lead to different results. For example,
improved conservation practices can greatly reduce erosion rates (Souchere et al., 2005),
while clear-cutting a forest during a ‘slash-and-burn’ operation has a huge negative impact on
susceptibility to runoff and erosion.
Little work has been done on the expected impacts of climate change on sediment
loads in rivers and streams. Bouraoui et al. (2004) showed, for southern Finland, that the
observed increase in precipitation and temperature was responsible for a decrease in snow
cover and increase in winter runoff, which resulted in an increase in modelled suspended
sediment loads. Kostaschuk et al. (2002) measured suspended sediment loads associated with
tropical cyclones in Fiji, which generated very high (around 5% by volume) concentrations of
sediment in the measured flows. The authors hypothesized that an increase in intensity of
tropical cyclones brought about by a change in El Niño patterns could increase associated
sediment loads in Fiji and across the South Pacific.
In terms of the implications of climate change for soil conservation efforts, a
significant realisation from recent scientific efforts is that conservation measures must be
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targeted at the extreme events more than ever before (Soil and Water Conservation Society,
2003). Intense rainfall events contribute a disproportionate amount of erosion relative to the
total rainfall contribution, and this effect will only be exacerbated in the future if the
frequency of such storms increases.
4.2 Projection of Historic Trend of Climate Change / Downscaling
Outputs from general circulation models (GCMs) can be useful in getting an overview
of possible climate scenarios, but are typically too coarse in scale (250 km x 250 km) to be
useful in practical comprehensive water resource planning situations (Durman et al. 2001).
The approaches which have been proposed for downscaling GCMs could be broadly
classified into two categories: dynamic downscaling and statistical downscaling.
4.2.1 Downscaling Methods
Dynamical Downscaling (DD) method involves the development of the regional
climate model which required the user to highly understanding of the atmospheric physical
behavior and local or regional interactions and feedback. Generally, DD method is used for
regions of complex topography, coastal or island locations in the regions of highly
heterogeneous land cover.
Statistical downscaling or empirical downscaling is a tool for downscaling climate
information from coarse spatial scales to finer scales. Statistical downscaling methods rely on
empirical relationships between local-scale predictands and regional-scale predictors to
downscale GCM scenarios Successful statistical downscaling is thus dependent on long
reliable series of predictors and predictands. Statistical Downscaling (SD) methods are used
to achieve the climate change information at the fine resolution through the development of
direct statistical relationships between large scale atmospheric circulation and local variables
(such as precipitation and temperature).
Compared to dynamical downscaling, the statistical method is relatively easy to use
and provides station-scale climate information from GCM-scale outputs (Wilby et al., 2002).
Thus, statistical downscaling methods are the most widely used in anticipated hydrologic
impact studies under climate-change scenarios. The main advantages of statistical
downscaling are that they are cheap, computationally undemandable and readily transferable,
providing local information most needed in many climate change impact applications and
ensembles of climate scenarios permit risk or uncertainty analyses.
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Salathe (2005) conducted a study to simulate stream flow in the Yakima River, a
mountainous basin in Washington, USA, to illustrate how model differences affect stream
flow simulations. The downscaling is applied to the output of three models (ECHAM4,
HADCM3, and NCAR-PCM) for simulations of historic conditions (1900–2000) and two
future emissions scenarios (A2 and B2 for 2000–2100) from the IPCC assessment. The
ECHAM4 simulation closely reproduces the observed statistics of temperature and
precipitation for the 42 year period 1949–90. Stream flow computed from this climate
simulation likewise produces similar statistics to stream flow computed from the observed
data.
Charles (2007) used four climate model simulations forced by the SRES A2 emission
scenario: the CSIRO Mk3 GCM, the CSIRO Conformal-Cubic Atmospheric Model (CCAM,
run at high spatial resolution over Australia with far-field forcing from the Mk3 GCM), the
Hadley Centre HadAM3P GCM and the Max Planck Institute ECHAM4 GCM. The non-
homogeneous hidden Markov model (NHMM), a stochastic downscaling model, was used to
quantify the impacts of the projected climate change on multi-site, daily precipitation. A
catchment water balance model (LUCICAT), calibrated under existing conditions, and was
driven by the downscaled precipitation to produce runoff projections. Biases in climate model
reproduction of the season cycles of the atmospheric predictors used in downscaling are
shown to have significant impacts on simulated precipitation, and hence runoff. The
downscaled CCAM and Mk3 results project reductions in annual precipitation ranging from
12 to 14% by mid century (2035–2064), resulting in a decline in runoff ranging from 30 to
44%. Downscaling the HadAM3P output, available at the daily time step only for the period
2070–2099, produces a precipitation decline of 24% and a runoff reduction of 69%. The
ECHAM4 downscaled precipitation inadequately reproduced the observed annual cycle and
so was not used for runoff projection.
Nearing (2001) used output from two GCMs (HadCM3 and the Canadian Centre for
Climate Modelling and Analysis CGCM1) and relationships between monthly precipitation
and rainfall erosivity (the power of rain to cause soil erosion) to assess potential changes in
rainfall erosivity in the USA. The predicted changes were significant, and in many cases very
large, but results between models differed both in magnitude and regional distributions.
Zhang et al. (2005) used HadCM3 to assess potential changes in rainfall erosivity in the
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Huanghe River Basin of China. Increases in rainfall erosivity by as much as 11 to 22% by the
year 2050 were projected across the region.
Flows and sediment Modelling
Surface runoff and soil erosion as well as many of the factors controlling both will be directly or
indirectly affected by climate change impact. Increasing precipitation amounts and intensities cause
non linear responses of runoff and soil loss. The variation of local precipitation and temperature
regimes implicate shifts in vegetation cover, soil conditions, land use and management which will
affect runoff, erosion and the translocation of sediments and environmental pollutants to surface
waters. Recent concern about the impact of global change on the Earth system has
emphasized the impact of climate change resulting from the increased emission of
greenhouses gases and associated global warming, it is important to consider other measures
of the functioning of the system. Soil erosion rates and the sediment loads transported by the
world’s rivers provide an important and sensitive indicator of changes in the operation of the
Earth system and, as indicated above, widespread changes in erosion rates and sediment flux
can have important repercussions and give rise to significant socio-economic and
environmental problems.
Precipitation and runoff are direct driving forces of soil erosion and sediment
transport. Variation of precipitation will surely lead to the changes of surface runoff, soil
erosion and sediment dynamics. Response of soil erosion and sediment transport to
precipitation change has become an important issue under changing climate (West and Wali,
2002; Yang et al., 2003).
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5.0 RESEARCH METHODOLOGY
5.1 Study area
To achieve the objectives of present study, the Naran watershed is selected as study
area. It is the upper part of Kunhar River having 1036 square km basin area. The basin has
the mountainous characteristics. This river contributes water into Jhelum River and ultimately
to Mangla reservoir. Exhaustive literature will be reviewed related to climate change impact
on flows and sediment yields from mountainous watershed to get real insight to problem
causes and its assessment approaches.
5.2 Data Needed
Historic data of following parameters will be required to conduct this research. Within
study area WAPDA-SWHP has established climatological stations at Sail ul Malook and
Shogran. A hydrological station exist at Naran is collecting flows and sediment
concentrations measurements. Pakistan Meteorological Department and any other source will
also be helpful and will be contacted for more data.
Daily temperature (min. and max)
Daily precipitation data
Daily flow data
Instantaneous suspended concentration
Annual suspended load
Topographic, DEM
Soil data
Land use and land cover
Other data related with flows and sediment yield
5.3 Data Analysis
The following analysis will be performed to examine the climate change in the study area.
Minimum temperature trends
Maximum temperature trends
Precipitation trends
Flow trends
Sediment trends
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Interpretation of trends with climate change parameters
Delineate the watershed and divide into sub basins and elevation zones using GIS
tool.
Draw/develop the rainfall, land cover and soil distribution map in GIS Model.
5.4 Projection of historical trends with the climate parameters
Above determined trends will be extended using statistical downscaling techniques
for following variables:
For temperatures
For precipitation
5.5 Modelling for Flows and Sediments Yield
The flows and sediment yields will be computed in following sequence:
Selecting an appropriate hydrologic and sediment trap Model.
Calibration of the Model
Validation of the Model
Computing sediments yield with corresponding scenarios
SHETRAN Model will be initialized and input will be given for Naran basin such
as spatial data, physical properties of soil, meteorological data and simulation parameters.
Base run will be performed and result will be calibrated and will be validated with
existing collected data. Simulation of sediment yield will be performed for various
scenarios derived from interpretation and extension of climate change.
5.6 Assessment of future sediment yield
Assessment of future sediment will be extracted from above computation cycle and
will be presented as the outcome of research in an appropriate format.
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6.0 PROBABLE RESULTS AND EXPECTED BENEFITS / CONTRIBUTION OF
RESEARCH WORK
Probable outcome of this proposed research will be some quantifiable figures of
future sediment yield in view of local climate change of chosen basin. It may make planners,
decision makers and designers a bit comfortable in front of uncertainty and risk of climate
change while performing their responsibilities Present Climate Change threats are based
upon theories while this research will help in confirming some basin-specific realistic
computation which is yet a knowledge gap. It may create new dimensions of analysis for
research and provide an alternate way and approach of thinking for functioning.
Scientific Personnel
Scientific Personnel required to support research task will be handled by under scholar.
Institutional Facilities
Existing Institutional Facilities seems to be sufficient.
Research Funds
Research Funds will be required to support research task to a tune of about 120 thousands
Rupees for data purchase, soil samples collection and testing cost.
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Research Time schedule
Sr Activities 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
1 Literature survey
2 Data Collection
3 Data analysis
4 Modelling
5 Analyzing Results
6 Publication
Research
7 Thesis write up
8 Preparing for exam
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References
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19
COMMENTS OF SUPERVISOR
Signature of Supervisor Signature of Student
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No: CEWRE/SYNOP/11/ Dated: ----------------
The above proposal duly recommended by the Centre’s Board of Studies in its meeting held
on 08.02.2012 is hereby forwarded to the Director of Research, University of Engineering
and Technology, Lahore for obtaining the approval of the Vice-Chancellor.
(Prof. Dr. Muhammad Latif)
Director, CEWRE.