Influence of Headwater Reservoirs on Climate Change Impacts and Flood Frequency in the Kabul River Basin

While climate change impacts vary globally, for the Kabul River Basin (KRB), concerns are primarily associated with frequent flooding. This research describes the influence of headwater reservoirs on projections of climate change impacts and flood frequency, and how the riparian countries can benefit from storing of floodwaters for use during dry seasons. Six climate change scenarios and two Representative Concentration Pathways (RCPs) are used in three periods of a quarter-century each. The Soil and Water Assessment Tool (SWAT) is used to assess how the proposed reservoirs will reduce flooding by ~38% during the wet season, reduce the flood frequency from five to 25 years return period, and increase low flows by ~110% during the dry season, which reflect an ~17.5% reduction in the glacier-covered area by the end of the century. The risks and benefits of reservoirs are highlighted in light of the developmental goals of Afghanistan and Pakistan.

Flood Hazard Zonation Using an Artificial Neural Network Model: A Case Study of Kabul River Basin, Pakistan

Floods are the most frequent and destructive natural disasters causing damages to human lives and their properties every year around the world. Pakistan in general and the Peshawar Vale, in particular, is vulnerable to recurrent floods due to its unique physiography. Peshawar Vale is drained by River Kabul and its major tributaries namely, River Swat, River Jindi, River Kalpani, River Budhni and River Bara. Kabul River has a length of approximately 700 km, out of which 560 km is in Afghanistan and the rest falls in Pakistan. Looking at the physiography and prevailing flood characteristics, the development of a flood hazard model is required to provide feedback to decision-makers for the sustainability of the livelihoods of the inhabitants. Peshawar Vale is a flood-prone area, where recurrent flood events have caused damages to standing crops, agricultural land, sources of livelihood earnings and infrastructure. The objective of this study was to determine the effectiveness of the ANN algorithm in the determination of flood inundated areas. The ANN algorithm was implemented in C# for the prediction of inundated areas using nine flood causative factors, that is, drainage network, river discharge, rainfall, slope, flow accumulation, soil, surface geology, flood depth and land use. For the preparation of spatial geodatabases, thematic layers of the drainage network, river discharge, rainfall, slope, flow accumulation, soil, surface geology, flood depth and land use were generated in the GIS environment. A Neural Network of nine, six and one neurons for the first, second and output layers, respectively, were designed and subsequently developed. The output and the resultant product of the Neural Network approach include flood hazard mapping and zonation of the study area. Parallel to this, the performance of the model was evaluated using Root Mean Square Error (RMSE) and Correlation coefficient (R2). This study has further highlighted the applicability and capability of the ANN in flood hazard mapping and zonation. The analysis revealed that the proposed model is an effective and viable approach for flood hazard analysis and zonation.

CHANGE DETECTION IN LAND USE AND LAND COVER OF DISTRICT CHARSADDA PAKISTAN ALONG RIVER KABUL (2010 FLOOD): TAKING ADVANTAGE OF GEOGRAPHIC INFORMATION SYSTEM AND REMOTE SENSING

This study aims to quantify land use and land cover changes before and after the 2010 flood in district Charsadda, Pakistan. Advanced geographic information systems (GIS) and remote sensing techniques (RST) evaluate land use and land cover changes. The purpose of this research is to estimate and compare the pre-and post-flood changes and their influences on land use and land cover changes. Land use land cover data studies are important for sustainable management of natural resources; they are becoming increasingly important for assessing the environmental impacts of economic development. Moreover, some remedial measures are adopted to develop the area’s land cover to overcome future problems. Land use and land cover changes are measured using satellite images. Two instances, i.e., pre-flood and post-flood, are compared to analyze the change in land use and land cover of district Charsadda within 5 km along the Kabul River. Comparative analysis of pre-flood and post-flood imageries highlighted some drastic changes over the water body, built-up area, agricultural land, and bare land during flood instances. The study area is rural and agricultural land is dominant as compared to other land uses. We evaluated the percentage of different land use and land cover within our study area. The agricultural land found about 68.5%, barren land 22.5%, and the water body 8.8% before the flood. After inundation, the water body raised to 16.4%, bare soil increased to 26.3%, agricultural land degraded up to 57.0%, and settlements (villages) along the Kabul River were severely damaged and finished by this flood. 2010’s flood heavily damaged approximately four villages in district Nowshera, six in district Peshawar, and twenty-seven Charsadda District villages.

Evaluation of fish diversity and abundance in the Kabul River with comparisons between reaches above and below Kabul City, Afghanistan

The fish fauna of the Kabul River downstream of the City of Kabul face threats from increasing human population such as pollution, overfishing, and increased development. Despite the rapid increase of these activities leading to threats to fishes in the Kabul River, no studies have examined the changes in diversity, distribution, and abundance of fish fauna in the Kabul River surrounding of Kabul City. In this study, the Kabul River was divided into two zones (upstream and downstream) consisting of six sampling sites (3 sites per zone). Of the total of 1,190 fishes collected, Cypriniformes was the dominant order with one family, six genera, and eight species. Cyprinidae was the dominant family of that order with 81.4% (n= 969) of total individuals. Species abundance was higher in the upstream reaches in almost all analyses. Upstream sites recorded 11 species, while seven species were recorded from downstream sites. Fish species richness was significantly higher upstream versus downstream reaches (9.67 ± 1.53 vs. 6.33 ± .58; U= .00, z= -1.99, p= .04, r= .81). Species diversity upstream was significantly higher than downstream (H’= 1.90 ± 0.15, D1= 0.81 ± 0.02). Similarly, species evenness was also higher upstream than downstream (J’= 0.84 ± 0.01). Low diversity, abundance, and evenness in downstream reaches are likely due to anthropogenic activities affecting the river in and around Kabul City.

Kabul River Flow Prediction Using Automated ARIMA Forecasting: A Machine Learning Approach

The water level in a river defines the nature of flow and is fundamental to flood analysis. Extreme fluctuation in water levels in rivers, such as floods and droughts, are catastrophic in every manner; therefore, forecasting at an early stage would prevent possible disasters and relief efforts could be set up on time. This study aims to digitally model the water level in the Kabul River to prevent and alleviate the effects of any change in water level in this river downstream. This study used a machine learning tool known as the automatic autoregressive integrated moving average for statistical methodological analysis for forecasting the river flow. Based on the hydrological data collected from the water level of Kabul River in Swat, the water levels from 2011–2030 were forecasted, which were based on the lowest value of Akaike Information Criterion as 9.216. It was concluded that the water flow started to increase from the year 2011 till it reached its peak value in the year 2019–2020, and then the water level will maintain its maximum level to 250 cumecs and minimum level to 10 cumecs till 2030. The need for this research is justified as it could prove helpful in establishing guidelines for hydrological designers, the planning and management of water, hydropower engineering projects, as an indicator for weather prediction, and for the people who are greatly dependent on the Kabul River for their survival.

The Role of Large Dams in a Transboundary Drought Management Co-Operation Framework—Case Study of the Kabul River Basin

Hydrologic drought is a frequent phenomenon in the transboundary Kabul River Basin (KRB), the vital resource shared between the two nations of Afghanistan and Pakistan. While the KRB has vast water resources, these resources are subject to extreme hydrologic events and, as a result, are not adequately managed to deal with the stress during drought conditions in the transboundary setting with no formal agreement or treaty. Rapid population growth and increases in agricultural land will require balanced water distribution to meet the array of needs. The Soil and Water Assessment Tool (SWAT) is used to evaluate distribution options for flow frequencies under existing and proposed large dams in the headwaters of the KRB. The calibrated SWAT streamflow results are employed for statistical analyses of the Standardized Streamflow Index (SSI) and Annual Cumulative Deficit Volume (ACDV) to investigate hydrologic drought time series and identify the role of proposed dams to be used for drought mitigation. Based on the SSI, proposed dams can provide additional storage that will partially address hydrologic droughts in the future. At the same time, restrictions on agricultural land expansion and water intakes are other measures to facilitate balanced water resource availability. This study discusses the intricacies of transboundary conflict and cooperation, water rights, and drought risk management; as well, recommendations for a KRB transboundary Drought Task Force (DTF) between Afghanistan and Pakistan are provided, to develop a science-based policy for using the stored waters in large dams for drought relief, fairly and transparency.

The genus Pelophylax (Amphibia, Ranidae) in Pakistan: museum collections and possible distribution

We provide the first comprehensive data on the questionable distribution of the genus Pelophylax and the family Ranidae from Pakistan. Based on a literature review and two specimens of the genus from Tasp, Panjgur District in Pakistani Balochistan (USNM 26194–95), stored in the Smithsonian National Museum of Natural History, Washington, DC, USA, we discuss the possible occurrence and affiliation of these frogs in the context of Central Asia. Our comparison shows that the nearest records of Pelophylax in relation to the Tasp specimens are reported from more than 280 km (air-line) away in Iran and Afghanistan, which are currently separated by hot and mostly desert environments. We suggest that possible surviving populations of this genus may still be present in Balochistan (Rakhshan River) or Khyber Pakhtunkhwa (Kabul River) Provinces of Pakistan. This would, however, need further field investigations.

Potential Implications of Future Climate Change And Extremes On Health, Agriculture, Water, And Cryosphere Sectors In The Kabul River Basin

Increasing temperature and variability in precipitation are affecting different sectors in the Himalayan region. This study aims to quantify the future scenario and related extreme indices in the Kabul River Basin of the western Himalaya using high-resolution climate data sets. We selected the representative global climate model simulations for RCP4.5 and 8.5, based on their abilities to represent the historical climate cycle. By using a three-step methodology, we selected four models for RCP4.5 and four for RCP8.5. The analysis shows that, overall, precipitation will increase by 4 and 12 per cent for RCP4.5 and 8.5 respectively by the end of the 21st century, and the seasonal analysis shows decreasing pattern during the winter and pre-monsoon seasons. However, temperatures will increase consistently by 3OC to 5OC in RCP4.5 and 8.5 scenarios. The extreme indices were calculated based on the selected models. The extremes, like consecutive summer days, warm days, and heatwave will increase, whereas the frost days, cold nights, and cold waves will decrease towards the end of this century. Notably, more warm days and heatwaves than the baseline period are projected in future scenarios. Besides, the extremes are not homogenous in time and space. We also discussed the potential implications of these climatic extremes as related to human health, agricultural productivity, water availability, and the cryosphere. We strongly urge prompt climate actions in order to increase the adaptive capacity against these extreme changes and to build a resilient livelihood in the Kabul River Basin.

Flood Risk Management with Transboundary Conflict and Cooperation Dynamics in the Kabul River Basin

The Kabul River, while having its origin in Afghanistan, has a primary tributary, the Konar River, which originates in Pakistan and enters Afghanistan near Barikot-Arandu. The Kabul River then re-enters Pakistan near Laalpur, Afghanistan making it a true transboundary river. The catastrophic flood events due to major snowmelt events in the Hindu Kush mountains occur every other year, inundating many major urban centers. This study investigates the flood risk under 30 climate and dam management scenarios to assess opportunities for transboundary water management strategy in the Kabul River Basin (KRB). The Soil and Water Assessment Tool (SWAT) is a watershed-scale hydraulic modeling tool that was employed to forecast peak flows to characterize flood inundation areas using the river flood routing modelling tool Hydrologic Engineering Center - River Analysis System -HEC-RAS for the Nowshera region. This study shows how integrated transboundary water management in the KRB can play a vital catalyst role with significant socio-economic benefits for both nations. The study proposes a KRB-specific agreement, where flood risk management is a significant driver that can bring both countries to work together under the Equitable Water Resource Utilization Doctrine to save lives in both Afghanistan and Pakistan. The findings show that flood mitigation relying on collaborative efforts for both upstream and downstream riparian states is highly desirable.