Quantifying the impact of socioeconomic development and climate change on Escherichia coli concentrations in the Pakistani Kabul River

Clean water is indispensable for the sustenance of life and maintenance of health. However, water quality is threatened by changes in socio-economic developments (population growth, urbanisation, livestock increase and sanitation) and climate (surface air temperature and precipitation patterns). Major water quality contaminants include microorganisms, such as fecal coliforms, Escherichia Coli (E.coli) and pathogens. Microbial contamination poses serious health risks in developing countries like Pakistan, where people do not have access to clean water due to lack of waste water treatment and thorough manure management. Therefore, to reduce the present and future health risk, it is important to understand the impacts of socio-economic development and climate-change on microbial fate and transport in surface water resources in the Kabul River Basin in Pakistan. The objective of this study is quantifying the impact of socio-economic development and climate change on E.coli concentrations in the Pakistani Kabul River. To reach the objective, I sampled E.coli concentrations at several locations in Kabul River, applied statistical and process based modelling, developed future global change scenarios and analysed the impact of these scenarios on E.coli concentrations. I focus on E.coli rather than pathogens, because sampling of pathogens and its chemical analysis are expensive. Kabul River Basin is a tributary of the Indus river and is located in the Hindukush-Karakoram-Himalayas (HKH) and suffers from floods every year. The population suffers from a high risk of waterborne diseases. The water is contaminated by direct sewage inputs from large cities, like Peshawar, direct manure inputs from animal sheds along the river and indirect manure inputs from the land. Kabul River Basin is subjected to hazardous levels of microbiological pollution. The concentration of micro-organisms is influenced by hydro-climatic variables, such as water and surface air temperature, precipitation and discharge. However, the net effect of these variables remains thus far unclear. High concentrations of E.coli were found in the main stream and its tributaries (Chapter 2). Samples were collected along the Kabul river and drinking water samples from the city of Nowshera (April 2013 to July 2015) and all surface water samples violate the bathing water criteria and all drinking water samples violate the drinking water criteria. The correlation between hydro-climatic variables and E.coli concentration was analysed. Water temperature and surface air temperature were positively correlated, most likely because high temperatures coincide with high precipitation and discharge. Precipitation and river discharge data were also positively correlated with E.coli concentrations. This shows that precipitation, which increases the surface runoff, transports E.coli and other waterborne pathogens to the river nearby (correlation with precipitation) and further upstream (correlation with discharge). A regression model was also applied that explained 61% of the E.coli variability in surface water and 55% of E.coli variability in drinking water resources, even when other factors, such as location and land-use variables are ignored (Chapter 2). To better understand the hydrology in the basin, the current and future flows of Kabul river were modelled using the Soil and Water Assessment Tool (SWAT), which serves as a basis for the process-based E.coli model. Flash floods occur every year in the basin as a result of increased discharge due to snow and glacier melt together with monsoon precipitation. The Kabul River Basin is one of the most vulnerable regional basin to climate change. The hydrological model was calibrated and validated for the full Kabul River Basin and performed well (NSE equals 0.77 and 0.72 respectively). Flood frequency and expected return period were analysed for a contemporary period (1981-2000) and two future periods (i.e. 2031-2050 and 2081-2100) using the Representative Concentration Pathway (RCP) 4.5 and RCP8.5 scenarios based on four bias-corrected downscaled climate models (Chapter 3). The flood frequency analysis shows that the present day’s one-in-a-fifty year event could occur between once in every 3 year (EC-EARTH and MIROC climate-models) and once in every 24 years (IPSL climate-model). This study presents climate-change impact assessment in the Kabul River Basin. The selected approach is in general well accepted in the scientific community and the results can be useful in flood management in the region. Outcomes of this study can be helpful for regions that have similar hydro-climatological conditions. To better understand the fate and transport of bacteria from land to water resources and to assess source contribution, the SWAT model was calibrated and validated for E.coli. Our study is the first bacterial modelling study for the Kabul River Basin (Chapter 4). The simulated concentrations have slightly lower variability than the observed concentrations. The model performance could be improved further by using more input E.coli data, but the current model results agree well enough with our measured E.coli concentrations (NSE equals 0.69 and 0.66 for calibration and validation respectively). Based on the pathogen source estimations, point (direct) sources are identified to be the most important microbial pollution sources. Pollution from upstream areas is also important, while non-point (diffuse) sources play a role mostly during the periods with high discharge. Our study underlines the importance of wastewater treatment and manure management both in and upstream of the study area. Studies like ours were lacking in developing countries like Pakistan and can be used for scenario analyses in the region (Chapter 4). The model can be useful in microbial water quality assessments in other watersheds and for pathogenic microorganisms, such as Cryptosporidium and Rotavirus. The calibrated and validated SWAT bacterial model (Chapter 4) was used to assess E.coli concentrations in a comprehensive scenario analysis (Chapter 5). We developed two future scenarios based on state-of-the-art approaches, using the Shared Socio-economic Pathways (SSPs), RCPs and own assumptions in line with the SSP storylines. We took the modelled E.coli concentrations from Chapter 4 as baseline scenarios and defines two future scenarios as Scenario_1 (sustainability scenario) and Scenario_2 (uncontrolled scenario). These scenarios represent different socio-economic development and climate change. The two scenarios were developed by combining SSP1, a sustainable, equitable and environmentally focussed world with RCP4.5 (limed climate change) in Scenario_1, and SSP3 (a divided world, with no interest in the environment) with RCP8.5 (strong climate change) in Scenario_2. Currently, no wastewater treatment plant exists in the basin, because the 2010 floods destroyed the available plants. We assumed excellent and poor wastewater and manure treatment for 2050s and 2100s for Scenario_1 and Scenario_2 respectively, in line with the storylines. Scenario_2 resulted in higher E.coli concentrations compared to the baseline scenarios due to high population growth, poor wastewater and manure treatment and land-use changes. However, microbial water quality was found to improve under Scenario_1. This was achieved by implementing improved and technologically advanced wastewater treatment and manure management. Future concentrations were found to be between 0.6% and 7% of the baseline concentrations depending on the treatment technology used (Chapter 5). This study highlights the need for substantial improvements in wastewater and manure treatment systems in the Kabul River Basin to assure future E.coli concentrations in water sources will be within the limits of WHO and US-EPA regulations for drinking and bathing water quality. The primary treatment facility that is currently installed is a good start, but insufficient to strongly reduce concentrations. Hence major investments are required to install technologically advanced wastewater treatment and manure treatment plants to cut-down the current contamination level of Kabul river. My PhD thesis provides a base for devising optimal coping strategies that are essential for the sustainability of hydrological resources under socio-economic developments and climate-change impacts. The results of our research are helpful to further assess alternative water quality management options. The outcomes of this study also increase the knowledge in the field of microbial fate and transport in water resources in a developing country like Pakistan, where such studies are lacking. A limited number of previous studies on global change impacts on microbial contamination of surface water in other areas of the world focused only on the climate-change impacts on microbial water quality. This is the first study to evaluate the influence of combined socio-economic and climate-change impacts on E.coli concentrations in the Kabul River Basin. The developed SWAT model and scenario analysis can be used for other contaminants, such as nutrients, pesticides and heavy metals. Our study can be a first step to improve water quality of the Kabul River Basin by providing tools for water managers and health specialists to improve the water quality and reduce the risks related to the use of contaminated water resources. This study will be useful not only in this region, but also for other regions of the world with similar microbial water contamination issues.

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Bibliographic Details
Main Author: Iqbal, Shahid
Other Authors: Leemans, Rik
Format: Doctoral thesis biblioteca
Language:English
Published: Wageningen University
Subjects:climatic change, escherichia coli, health, regression analysis, rivers, socioeconomics, water pollution, water quality, gezondheid, klimaatverandering, regressieanalyse, rivieren, sociale economie, waterkwaliteit, waterverontreiniging,
Online Access:https://research.wur.nl/en/publications/quantifying-the-impact-of-socioeconomic-development-and-climate-c
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