Your search found 5 records
1 Mian, B. A.; Awan, H.; Hussain, I. 2002. Groundwater development in hard rock aquifer of Quetta valley: a case study. In Pakistan Water Partnership (PWP). Second South Asia Water Forum, 14-16 December 2002, Islamabad, Pakistan. Proceedings, vol.1. Islamabad, Pakistan: Pakistan Water Partnership (PWP). pp.369-385.
Groundwater development ; Aquifers ; Drilling ; Water supply ; Case studies / Pakistan / Balochistan / Quetta
(Location: IWMI HQ Call no: 333.91 G570 PAK Record No: H034160)
2 Usman, M.; Qasim, S. 2022. Assessment of water poverty situation in Balochistan Province of Pakistan: a case study of two tehsils of District Quetta. Pakistan Geographical Review, 77(1):80-92.
Water supply ; Poverty ; Assessment ; Water availability ; Drinking water ; Sanitation ; Households ; Case studies / Pakistan / Balochistan / Quetta
(Location: IWMI HQ Call no: e-copy only Record No: H051212)
http://pu.edu.pk/images/journal/geography/pdf/6_V77_No1_2022.pdf
https://vlibrary.iwmi.org/pdf/H051212.pdf
https://vlibrary.iwmi.org/pdf/H051212.pdf
(0.95 MB) (968 KB)
Water is essential to the survival of human beings and also for cleaning and agriculture. Pakistan being a developing country and facing water poverty. This study was conducted to analyze the water poverty status of city and Saddar tehsil of district Quetta. A water poverty index (WPI) was used to calculate the water poverty. A total of 400 participants were selected, including 300 from Quetta city tehsil (QC) and 100 from Quetta Saddar tehsil (QS). A proportional sampling technique was used to sample the participants of the study. Study design used was a descriptive one with the data being collected on structured questionnaire. Apart from the primary data, secondary was gathered from the WASA department located in Quetta. Data on the water poverty status showed that majority of the people from both tehsils (47.67% in QC and 41% in QS) were dependent on pipped water supply as their primary water source. The rest of the population were either dependent on community well (32.33% in QC and 28% in QS), borewell (11% in QC and 26% in QS) or tanker water (9% in QC and 5% in QS). Almost 90% of respondents from both tehsils reported to be using tanker water in case of water shortage from piped water supply. Interestingly, only 45.33% of respondents from QC reported clear water with no contamination while 75% respondents from QS enjoyed a clear water. Water poverty situation was found to be present in both QC and QS tehsil. Not only was water supply short but also contaminated with disposal. The development of a good policy is required for resolving the issue of water poverty in the two tehsils of Quetta.
3 Rasool, U.; Yin, X.; Xu, Z.; Rasool, M. A.; Senapathi, V.; Hussain, M.; Siddique, J.; Trabucco, J. C. 2022. Mapping of groundwater productivity potential with machine learning algorithms: a case study in the provincial capital of Baluchistan, Pakistan. Chemosphere, 303(Part 3):135265. [doi: https://doi.org/10.1016/j.chemosphere.2022.135265]
Groundwater potential ; Water productivity ; Mapping ; Machine learning ; Case studies ; Assessment ; Water quality ; Remote sensing ; Geographical information systems ; Neural networks ; Models / Pakistan / Baluchistan / Quetta
(Location: IWMI HQ Call no: e-copy only Record No: H051222)
(7.42 MB)
Although groundwater (GW) potential zoning can be beneficial for water management, it is currently lacking in several places around the world, including Pakistan's Quetta Valley. Due to ever increasing population growth and industrial development, GW is being used indiscriminately all over the world. Recognizing the importance of GW potential for sustainable growth, this study used to 16 GW drive factors to evaluate their effectiveness by using six machine learning algorithms (MLA's) that include artificial neural networks (ANN), random forest (RF), support vector machine (SVM), K- Nearest Neighbor (KNN), Naïve Bayes (NB) and Extreme Gradient Boosting (XGBoost). The GW yield data were collected and divided into 70% for training and 30% for validation. The training data of GW yields were integrated into the MLA's along with the GW driver variables and the projected results were checked using the Receiver Operating Characteristic (ROC) curve and the validation data. Out of six ML algorithms, ROC curve showed that the XGBoost, RF and ANN models performed well with 98.3%, 96.8% and 93.5% accuracy respectively. In addition, the accuracy of the models was evaluated using the mean absolute error (MAE), root mean square error (RMSE), F-score and correlation-coefficient. Hydro-chemical data were evaluated, and the water quality index (WQI) was also calculated. The final GW productivity potential (GWPP) maps were created using the MLA's output and WQI as they identify the different classification zones that can be used by the government and other agenciesto locate new GW wells and provide a basis for water management in rocky terrain.
4 Rafiq, M.; Li, Y. C.; Cheng, Y.; Rahman, G.; Ullah, I.; Ali, A. 2022. Spatial and temporal fluctuation of rainfall and drought in Balochistan Province, Pakistan. Arabian Journal of Geosciences, 15(2):214. [doi: https://doi.org/10.1007/s12517-022-09514-4]
Drought ; Rain ; Assessment ; Trends ; Precipitation ; Semiarid zones ; Meteorological stations / Pakistan / Balochistan / Barkhan / Dalbandin / Kalat / Khuzdar / Lasbella / Quetta
(Location: IWMI HQ Call no: e-copy only Record No: H051224)
(4.44 MB)
Drought is a multifaceted hydro-meteorological phenomenon that occurs due to a reduction in the amount of rainfall which increases complexity as well as scarcity in arid to semi-arid region. This research presented fluctuation in rainfall and analyzed drought conditions in Balochistan province using the standardized precipitation index (SPI). The six meteorological station (Met stations) data of rainfall were collected from the concerned stations. The data consists of 33 years of rainfall observations (1986–2018). For the data normality, skewness was applied and the results showed positive skewness at all station records with the highest variability in Kalat and Barkhan. The Mann–Kendall trend was applied on both 1-month and 12-month SPI data to assess the trend in the SPI results. In Balochistan, the SPI results detected two distinct driest drought intervals, i.e., 1998–2002 and 2014–2018. The MKT test results detected negative trend in the results of 1-month SPI at most of the selected stations with more significant results in Dalbandin. The January recorded a slight increase in rainfall in almost all weather stations with significant trend. Furthermore, the MKT results of the 12-month SPI deduced a significant positive trend in Dalbandin. Finally, the results revealed frequent drought events and it is expected that it may increase in the future.
5 Ahmad, M. B.; Muavia, A.; Iqbal, M.; Arshed, A. B.; Ahmad, M. M. 2023. Spatio-temporal drought assessment and comparison of drought indices under climatic variations in drought-prone areas of Pakistan. Journal of Water and Climate Change, 14(10):3726-3752. [doi: https://doi.org/10.2166/wcc.2023.602]
Drought ; Assessment ; Monitoring ; Precipitation ; Evapotranspiration ; Rainfall patterns ; Vegetation ; Satellites ; Water management ; Extreme weather events / Pakistan / Balochistan / Dalbandin / Jiwani / Kalat / Khuzdar / Lasbella / Quetta / Pasni / Sibi / Zhob / Panjgur
(Location: IWMI HQ Call no: e-copy only Record No: H052296)
https://iwaponline.com/jwcc/article-pdf/doi/10.2166/wcc.2023.602/1313599/jwc0143726.pdf
https://vlibrary.iwmi.org/pdf/H052296.pdf
https://vlibrary.iwmi.org/pdf/H052296.pdf
(3.15 MB) (3.15 MB)
Climatic variations cause droughts which badly affect the environment. The study focused on monitoring droughts to aid decision-making and mitigate their negative impacts on water availability for agriculture and livelihoods in the face of increasing water demand and climate change. To assess the agricultural droughts, a new agricultural Standardized Precipitation Index (aSPI) was calculated which is not used earlier in Balochistan. Widely recommended Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) were used for meteorological drought assessment. Drought indices comparison was also conducted to check the applicability. Rainfall, maximum temperature, and minimum temperature data (1992 to 2021) were utilized to calculate SPI, aSPI, and SPEI at different timescales (3, 6, 9, and 12 months) using DrinC software and SPEI calculator. Indices results revealed the following severe to extreme drought years: 1998, 1999, 2000, 2001, 2002, 2004, 2008, 2011, 2014, 2016, and 2017. It was determined that Dalbandin, Quetta, Sibi, Kalat, Khuzdar, and Zhob experienced higher extreme drought frequencies. Both long- and short-term drought durations were observed. Indices comparison showed that SPI is the most efficient drought index compared to aSPI and SPEI. This study offers valuable insights for managing water resources in the face of climate-induced droughts.
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