Climate Change Impacts on Water Resource and Air Pollution in Kabul Sub-basins, Afghanistan

Rasouli, Hafizullah

doi:10.30564/agger.v4i1.4312

Cited by 8 publications

(6 citation statements)

References 10 publications

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“…The hydrometeorological regime is characterized by rain in the spring and snow in the winter. The melting of glaciers in summer is increasing each year due to high temperatures, leading to rising water levels in the river (Rasouli 2022). In addition, rainfall in the monsoon season also affects water levels in the river.…”

Section: Description Of Datamentioning

confidence: 99%

A novel hybrid framework to model the relationship of daily river discharge with meteorological variables

Shabbir,

Chand,

Iqbal

2024

Meteorol. Hydrol. Water Manage.

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River discharge is affected by many factors, such as water level, rainfall, and precipitation. This study proposes a new hybrid framework named LAES (LASSO-ANN-EMD-SVM) to model the relationship of daily river discharge with meteorological variables. This hybrid framework is a composite of the least absolute shrinkage and selection operator (LASSO), an artificial neural network (ANN), and an error correction method. In the first stage, LASSO identifies meteorological variables that have a significant influence on the generation of river discharge. Next, the ANN model is used to predict river discharge using meteorological variables selected by LASSO, and the error series is determined. The error series is decomposed into intrinsic mode functions and residuals using empirical mode decomposition (EMD). The EMD components are modeled using the support vector machine (SVM) model, and the error predictions are aggregated. In the last stage, the LASSO-ANN predictions and the predicted error series are aggregated as the final discharge prediction. The proposed hybrid framework is illustrated on the Kabul River of Pakistan. The performance of the proposed hybrid framework is compared with six models using various performance measures and the Diebold-Mariano test. These models include multiple linear regression (MLR), SVM, ANN, LASSO-MLR, LASSO-SVM, and LASSO-ANN models. The findings reveal that the proposed hybrid model outperforms all other models considered in the study.In the testing phase, the root mean square error (RMSE), mean absolute percentage error (MAPE), and mean absolute error (MAE) of the proposed LAES hybrid model are 337.143 m 3 /s, 32.354%, and 218.353 m 3 /s which are smaller than all other models compared in the study. Our proposed hybrid system is an efficient model for river discharge prediction that will be helpful in water management and protection against floods. Long-term prediction can help to identify the major effects of climate change and to make evidence-based environmental policies.

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Section: Description Of Datamentioning

confidence: 99%

A novel hybrid framework to model the relationship of daily river discharge with meteorological variables

Shabbir,

Chand,

Iqbal

2024

Meteorol. Hydrol. Water Manage.

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“…The radiometry method found that the lifetime of these metamorphic rocks of approximately (928 ± 8) million years [21,34] . The older of the two is located in the Khair Khana Mountains while the younger one is in the Shawaky and Qorugh Mountains range [12,36,37] (Figure 1).…”

Section: Geology Of Kabulmentioning

confidence: 99%

“…The Granite in Paghman, Kabul spans from Precambrian [11] and Khengal series. To further characterize the basin, it is important to note that Kabul is surrounded by different fault systems including Chamman-moqure [12] , Sarobi, and Mahi-par faults [13] . The Kabul Basin is tectonically active in the transpressional deformation plate-bound-ary region in the areas under investigation [14,15] .…”

Section: Introductionmentioning

confidence: 99%

Groundwater Quality Assessment in Pul-e-Charkhi Region, Kabul, Afghanistan

Rasouli,

Vaseashta

2023

adv. in geol. and geotech. eng. res.

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We present the results of studies conducted on the assessment of groundwater quality observed on several water samples taken from water supply sources in the Pul-e-Charkhi region, which is located near the eastern part of Kabul and has seen steady growth in population after the U.S. completed its withdrawal from Afghanistan on 30 August 2021. The water in the basin serves as the main source of water supply and it consists of water discharge from nearby local industries, automobile repair and wash, Osman House, Gradation Place, International Standards Region, and many other regional sources that create a mix of contaminants in discharge to the basin. We collected several samples from each groundwater source for this investigation and transported them carefully to the research laboratory, maintaining the integrity of the samples. The main objective of this study is to assess groundwater quality for the determination of contaminants in groundwater to see what limitations it may pose for recycling and reuse. Such a study is necessary since the region requires persistent sources of water due to a steady increase in population and an associated shortage of water supply due to arid conditions. Furthermore, there is unavailability of similar data since the region served to support military operations since 2001. The samples were analyzed for temperature, electroconductivity, dissolved oxygen, total dissolved solids, salinity, pH, color, turbidity, hardness, chemicals, and heavy metals. The results obtained suggest that the parameters can be used efficiently to design filtration strategies based on region-specific contamination for the specific catchments located in and around the Kabul Basin. An effort to add additional characterization techniques is described to detect micro/nano plastics and new and emerging contaminants. The efforts reported here are consistent with the 2030 agenda for Sustainable Development Goals.

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“…REEs pollution into the Kor River are derived from the entry of effluent Charmineh tanning, petrochemical and Fars meat factories. Hafizullah Rasouli [2] investigated climate change impacts on water resources and air pollution, in Kabul Sub-basins, Afghanistan. Hydrometeorological and groundwater data (the year 1957 to the year 2017) were analyzed to discover natural causes of climate change effects on surface and groundwater resources and air pollutions.…”

Section: Summary Of Paper Presented In Vol 4 No 1 (2022)mentioning

confidence: 99%