Inmagic DB/Text WebPublisher PRO: 6 records

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1 Malik, A. H. 2000. Integrated urban Lei River (North Pakistan) water resources management. International Journal of Water Resources Development, 16(1):97-117.

Rivers ; Catchment areas ; Watershed management ; Flood control ; Water resource management ; Aquifers ; Runoff ; Hydrology ; Monitoring ; Drought ; Wastewater ; Water quality ; Water balance ; Groundwater ; Recharge ; Geology ; Water supply ; Irrigation water / Pakistan / Lei River / Islamabad / Rawalpindi

(Location: IWMI-HQ Call no: PER Record No: H026224)

2 IPS Asia-Pacific Center Foundation Inc. 2007. Asia Water Wire: what water means for the world's most populous continent. Bangkok, Thailand: IPS Asia-Pacific Center Foundation Inc. 131p.

Dams ; Rivers ; Sanitation ; Water pollution ; Hygiene ; Poverty / Asia / Pakistan / India / Singapore / Nepal / Indonesia / Philippines / Cambodia / China / Thailand / Japan / Kalabagh Dam / Aral Sea / Buriganga River / Kathmandu / Khokana / Madhya Pradesh / Dhaka / Islamabad / Marikina City / Chhong Kneas / Beijing / Bangkok / Muzaffarabad / Tokyo

(Location: IWMI HQ Call no: 333.91 G570 IPS Record No: H042977)

http://vlibrary.iwmi.org/pdf/H042977_TOC.pdf

(0.29 MB)

3 IPS Asia-Pacific Center Foundation Inc. 2007. Asia Water Wire: what water means for the world's most populous continent. Bangkok, Thailand: IPS Asia-Pacific Center Foundation Inc. 131p.

(Location: IWMI HQ Call no: 333.91 570 IPS c2 Record No: H043901)

4 Qaiser, G.; Tariq, S.; Adnan, S.; Latif, M. 2021. Evaluation of a composite drought index to identify seasonal drought and its associated atmospheric dynamics in northern Punjab, Pakistan. Journal of Arid Environments, 185:104332. (Online first) [doi: https://doi.org/10.1016/j.jaridenv.2020.104332]

Drought ; Climate change ; Temperature ; Precipitation ; Monitoring ; Crop yield ; Normalized difference vegetation index ; Meteorological observations ; Moderate resolution imaging spectroradiometer / Pakistan / Punjab / Potwar Plateau / Islamabad / Attock / Chakwal / Jhelum / Rawalpindi

(Location: IWMI HQ Call no: e-copy only Record No: H050153)

https://vlibrary.iwmi.org/pdf/H050153.pdf

(9.72 MB)

Drought is one of the most devastating climate extremes in terms of its spatial extent and intensity. Rainfed areas are extremely vulnerable to drought, but effective monitoring may lessen the impact of such events. This study developed a composite drought index (CDI) for monitoring and assessing seasonal droughts in rainfed areas of the Potwar Plateau of Pakistan, using remotely sensed and observed meteorological datasets. We identified four severe-to-extreme drought periods in the Rabi season (wheat; 2000–01, 2001–02, 2009–10, and 2011–12) and four such events in the Kharif season (maize; 2000–2002 and 2009). An intense agro-meteorological drought was experienced in 2000, which reduced the wheat and maize yields to -54.6% and -29.9%, respectively. Our analysis revealed that these conditions could be explained by the vertically integrated moisture flux divergence (MFD), moisture transport, and total precipitable water (TPW) anomalies. For example, the presence of a strong MFD anomaly over the study area was responsible for preventing moisture transport from the Arabian Sea and Bay of Bengal, resulting in dry conditions. The index developed here can effectively monitor seasonal droughts in rainfed areas, which may help inform strategies to lessen the impact of such events.

5 Ahmed, M.; Mumtaz, R.; Zaidi, S. M. H. 2021. Analysis of water quality indices and machine learning techniques for rating water pollution: a case study of Rawal Dam, Pakistan. Water Supply, 21(6):3225-3250. [doi: https://doi.org/10.2166/ws.2021.082]

Water quality ; Water pollution ; Machine learning ; Techniques ; Monitoring ; Datasets ; Geographical information systems ; Chemicophysical properties ; Models ; Case studies / Pakistan / Islamabad / Rawal Dam

(Location: IWMI HQ Call no: e-copy only Record No: H050698)

https://iwaponline.com/ws/article-pdf/21/6/3225/933536/ws021063225.pdf
https://vlibrary.iwmi.org/pdf/H050698.pdf

(0.99 MB) (0.99 MB)

Water Quality Index (WQI) is a unique and effective rating technique for assessing the quality of water. Nevertheless, most of the indices are not applicable to all water types as these are dependent on core physico-chemical water parameters that can make them biased and sensitive towards specific attributes including: (i) time, location and frequency for data sampling; (ii) number, variety and weights allocation of parameters. Therefore, there is a need to evaluate these indices to eliminate uncertainties that make them unpredictable and which may lead to manipulation of the water quality classes. The present study calculated five WQIs for two temporal periods: (i) June to December 2019 obtained in real time (using the Internet of Things (IoT) nodes) at inlet and outlet streams of Rawal Dam; (ii) 2012–2019 obtained from the Rawal Dam Water Filtration Plant, collected through GIS-based grab sampling. The computed WQIs categorized the collected datasets as ‘Very Poor’, primarily owing to the uneven distribution of the water samples that has led to class imbalance in the data. Additionally, this study investigates the classification of water quality using machine learning algorithms namely: Decision Tree (DT), k-Nearest Neighbor (KNN), Logistic Regression (LogR), Multilayer Perceptron (MLP) and Naive Bayes (NB); based on the parameters including: pH, dissolved oxygen, conductivity, turbidity, fecal coliform and temperature. The classification results showed that the DT algorithm outperformed other models with a classification accuracy of 99%. Although WQI is a popular method used to assess the water quality, there is a need to address the uncertainties and biases introduced by the limitations of data acquisition (such as specific location/area, type and number of parameters or water type) leading to class imbalance. This can be achieved by developing a more refined index that considers various other factors such as topographical and hydrological parameters with spatial temporal variations combined machine learning techniques to effectively contribute in estimation of water quality for all regions.

6 Shah, A.; Karim, R.; Ali, K. 2022. Review of impacts of climate changes on the urban water security of Islamabad, Pakistan. Journal of Water and Land Development, 54:109-115. [doi: https://doi.org/10.24425/jwld.2022.141561]

Climate change ; Water security ; Urban areas ; Global warming ; Glaciers ; Water resources ; Water conservation ; Strategies ; Water availability ; Sustainability / Pakistan / Islamabad / Hindukush Karakoram Himalaya Region

(Location: IWMI HQ Call no: e-copy only Record No: H051464)

https://www.journals.pan.pl/Content/124441/PDF/2022-01-JWLD-13.pdf?handler=pdf
https://vlibrary.iwmi.org/pdf/H051464.pdf

(0.46 MB) (468 KB)

The global warming and subsequent climate change has seriously threatened the glaciers of the Hindukush Karakoram Himalaya (HKH) region. These glaciers provide water to more than 60% people of the 11 countries, including Pakistan. The capital city of Pakistan has witnessed unprecedented urbanisation, population increase, development of new townships and associated economic activities. These challenges, together with climate change, have created severe pressure on the water resources of the city. In this mixed mode research, including questionnaire survey of 20 questions was distributed among the residents of the city online through Google Form. The questions were related to the expected impact of climate change on the availability of water, measures for conservation of water etc. About 205 residents from various parts of the city with different demographic backgrounds responded. This was followed by Focus Group Discussions (FDGs) of the experts and the major challenges to the urban water security of Islamabad with special reference to climate change have been assessed. The research has revealed that the water resources of the city are highly unsustainable. The residents have high concerns about the availability and quality of water. The results have shown that there is a number of governance issues in water distribution systems of the city. There are no organized water conservation strategies employed by City Government. The lack of institutional and policy framework has further complicated the situation. Residents seem willing for metering of water for its conservation. Recommendations have been made to municipal authorities for rational water resource management of the city.