Impacts of climate change on the water resources and irrigation water demand in the Upper Indus River Basin, Pakistan | |
| Author | Khattak, Muhammad Shahzad Khan |
| Call Number | AIT Diss. no.WM-10-01 |
| Subject(s) | Climatic changes--Pakistan Irrigation water--Pakistan Water-supply--Pakistan |
| Note | A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Engineering in Water Engineering and Management, School of Engineering and Technology |
| Publisher | Asian Institute of Technology |
| Series Statement | Dissertation ; no. WM-10-01 |
| Abstract | Some of the most affected areas by climate change are hydrology, water resources and agriculture. Changes in climate alter a wide range of characteristics of a river basin: the snow accumulation, melting and hence, seasonal flows and crop and inigation requirements. An understanding of the likely trajectories of climate in a basin is thus a prerequisite for management and adaptation strategies for water sector. The overall objective of this study is to assess the impacts of climate change on the hydrology, water resources and irrigation water demand in the Upper Indus River Basin (UIRB). The specific objectives include assessment of past trends in hydro-climatic variables, selection of suitable GCMs, and impacts of future climate on streamflow and irrigation water demand in the study basin. Trend analysis of hydro-climatic variables is perfo1med in the portion of the UIRB lying in Pakistan. Due to high variability of climate, the study area is divided into three regions, the upper, middle and lower. A combination of non-parametric statistical approaches has been used to assess the trends in the historical hydro-meteorological data. The techniques include, Mann-Kendall and Sen's slope methods in combination with Trend Free PreWhitening approach to remove the effect of serial conelation, and then binomial and quantile-quantile tests are applied to the Mann-Kendall statistics to evaluate whether the trend is significant or not. For maximum coverage of the study area, and to ensure a common period for all data types, an analysis period of 39 years (l 967-2005) is chosen. A year is divided into four seasons of three months each, namely winter (Dec-Feb), spring (Mar-May), summer (Jun-Aug) and autumn (Sep-Nov). The meteorological variables, minimum temperature, maximum temperature, and precipitation and the hydrological variable, streamflow are considered. A total of 20 meteorological and eight hydrometric stations are used for the trend analysis. The decadal trend of hydro-climatic data is also performed. For several of the variables, many more trends are identified than can be expected to occur by chance. Winter TMX has revealed a significant increasing trends (p < 0.10) with a trend slopes of 1.79, 1.66 and l.2°C per 39 years for the upper, middle and lower regions, respectively. All the three regions show increasing trends for the spring season with p-value > 0.10. For the summer and autumn season, mixed trends are observed. Summer TMN has shown a statistically significant (p < 0.10) decreasing trends of 2.08, 1.05 and 2.11 °C for the three regions, respectively. No conclusive trends are observed in precipitation except increasing trend in autumn season. The summer season flow has decreased in six out of eight stations. The concurrent trend results show that winter and spring temperature and autumn precipitation have increased runoff in the study area during those seasons. The two decades 1967-1976 and 1997-2005 are the warmest and driest in the analysis period. The perfo1mance of various GCMs is evaluated based on statistical parameters of observed and simulated time series of temperature and precipitation at gauging stations and grid nodes. A considerable variability in different GCMs simulations for the observed climate was observed. The HadCM3, SRNIES, ECHAM4, and NCAR models could simulate the spatial variability of mean temperature well. All the models substantially underestimated the magnitude of temperature on a monthly basis. The estimated precipitation showed much higher variations compared to mean temperature for all GCMs and at all stations. None of the models could represent the observed magnitude and spatial variability of precipitation in the study area. However, on the basis of similar statistics of the observed |
| Year | 2010 |
| Corresponding Series Added Entry | Asian Institute of Technology. Dissertation ; no. WM-10-01 |
| Type | Dissertation |
| School | School of Engineering and Technology |
| Department | Department of Civil and Infrastucture Engineering (DCIE) |
| Academic Program/FoS | Water Engineering and Management (WM) |
| Chairperson(s) | Babel, Mukand S.; |
| Examination Committee(s) | Clemente, Roberto S. ;Perret, . Sylvain ;Honda, Kiyoshi ;Tachikawa, Yasuto; |
| Scholarship Donor(s) | N.W.F.P. University of Engineering &Technology, Peshawar, Pakistan - AIT Fellowship ; |
| Degree | Thesis (Ph.D.) - Asian Institute of Technology, 2010 |