Please use this identifier to cite or link to this item: http://prr.hec.gov.pk/jspui/handle/123456789/20148
Title: Statistical Downscaling and Climate Change Influencing Extreme River Flows Variations of Upper Indus Basin Region
Authors: Nawaz, Faisal
Keywords: Physical Sciences
Mathematics
Issue Date: 2022
Publisher: University of Karachi, Karachi.
Abstract: As a major issue in hydrological research, the frequency of flooding on land and glaciers is increasing and has become one of the leading natural disasters in the world. It has been known for a long time that the disastrous flood occurs with combination of high strength seasonal/ excess short duration rainfall and extraordinary snow/glaciers melting. Pakistan has suffered from this disaster since 1928, especially during the monsoon (June to September) season, which disrupted livelihoods, destroyed property, infrastructure and crops, and caused more than 7,000 deaths between 1947 and 2008. Moreover, Climate change has a strong impact on water resources both locally and regionally; In order to minimize the impact on the flood risk, a comprehensive scientific analysis with mathematical modelling and subsequent efficient forecasting is inevitable for future water and environmental management scenarios. Impacts of climate change on hydrology have been extensively studied in recent decades and may lead to some revolutions in this field of research. This study investigated the relationship between climate and hydrological variables. As a preliminary analysis and to explore the insides of the data pattern using the probability distribution investigation of the rainfall and air temperature as key river flow variables illustrate that Generalized Pareto distribution is the best-fitted model. Furthermore, the trend nature of these data confirmed parametric and non-parametric investigations, of the Mann-Kendall (MK) and Augmented Dickey-Fuller (ADF). Past studies show strong correlation exists between climate and hydrological variables and flood risk assessment processes, for this, scientists relied profoundly on combined climate and hydrological models. The general circulation model (GCM) projections of future climate change cannot be used straight to consider the hydrological impacts of climate change on a regional scale due to the spatial resolution mismatch. To overcome this difficulty, the downscaling technique utilising the output of a GCM to conduct hydrological impact studies and it has a great application during the last two decades. Among numerous downscaling methods, this study utilizes the Statistical downscaling model (SDSM), and SDSM selected GCM variables based Multiple-linear regression (MLR) and Vector Autoregression (VAR) techniques to downscale the temporal variation of daily and monthly local climate of Gupis and Bonji cities and river flow at Gilgit and Chitral stations, of UIB region. It has been investigated that VAR outperforms the overall SDSM and MLR methods in all temperature, x rainfall and river flow downscaling and forecasting. Moreover, the river flow is best downscaled by utilizing the NECP global variable as predictors directly. In the family of time series investigations, a non-parametric, linear and powerful spectral estimation tool known as singular spectrum analysis (SSA) has been applied for analysis and prediction in this thesis. The results for both the calibration and validation periods were most optimal for all three (temperature, rainfall and river flow) monthly data series for both the stations. It shows that the results of SSA outcomes highly accurate than the MLR and VAR monthly downscaling methods of describe above all three data series for both the stations. The future prospects of this method can be beneficial for the allowable comparison between, stationary and non stationary time series and linear vs. non-linear time series. However, SSA may handle the coarse scale like monthly and annual data easily, for fine grade data like daily, 12, 6, and 1 hourly it is very difficult to manage this large data. This type of research typically aids governments and private organizations in keeping complete records of river flow activities that are significant under the influence of global and regional climate system. Conclusively, this work emphasizes the importance of recognizing the limitations and benefits of downscaling and various other methods mentioned in the given work. It is hoped that the results of this study will contribute significantly in current hydrological researches, in particular with reference to Upper Indus River network and Pakistan.
Gov't Doc #: 25588
URI: http://prr.hec.gov.pk/jspui/handle/123456789/20148
Appears in Collections:PhD Thesis of All Public / Private Sector Universities / DAIs.

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