Flood Modelling of the Zhabay River Basin Under Climate Change Conditions

Flood modelling in snow-fed river basins is critical for understanding the impacts of climate change on hydrological extremes. The Zhabay River in northern Kazakhstan exemplifies a basin highly vulnerable to seasonal floods, which pose significant risks to infrastructure, livelihoods, and water reso...

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Main Authors: Aliya Nurbatsina, Zhanat Salavatova, Aisulu Tursunova, Iulii Didovets, Fredrik Huthoff, María-Elena Rodrigo-Clavero, Javier Rodrigo-Ilarri
Format: Article
Language:English
Published: MDPI AG 2025-02-01
Series:Hydrology
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Online Access:https://www.mdpi.com/2306-5338/12/2/35
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author Aliya Nurbatsina
Zhanat Salavatova
Aisulu Tursunova
Iulii Didovets
Fredrik Huthoff
María-Elena Rodrigo-Clavero
Javier Rodrigo-Ilarri
author_facet Aliya Nurbatsina
Zhanat Salavatova
Aisulu Tursunova
Iulii Didovets
Fredrik Huthoff
María-Elena Rodrigo-Clavero
Javier Rodrigo-Ilarri
author_sort Aliya Nurbatsina
collection DOAJ
description Flood modelling in snow-fed river basins is critical for understanding the impacts of climate change on hydrological extremes. The Zhabay River in northern Kazakhstan exemplifies a basin highly vulnerable to seasonal floods, which pose significant risks to infrastructure, livelihoods, and water resource management. Traditional flood forecasting in Central Asia still relies on statistical models developed during the Soviet era, which are limited in their ability to incorporate non-stationary climate and anthropogenic influences. This study addresses this gap by applying the Soil and Water Integrated Model (SWIM) to project climate-driven changes in the hydrological regime of the Zhabay River. The study employs a process-based, high-resolution hydrological model to simulate flood dynamics under future climate conditions. Historical hydrometeorological data were used to calibrate and validate the model at the Atbasar gauge station. Future flood scenarios were simulated using bias-corrected outputs from an ensemble of General Circulation Models (GCMs) under Representative Concentration Pathways (RCPs) 4.5 and 8.5 for the periods 2011–2040, 2041–2070, and 2071–2099. This approach enables the assessment of seasonal and interannual variability in flood magnitudes, peak discharges, and their potential recurrence intervals. Findings indicate a substantial increase in peak spring floods, with projected discharge nearly doubling by mid-century under both climate scenarios. The study reveals a 1.8-fold increase in peak discharge between 2010 and 2040, and a twofold increase from 2041 to 2070. Under the RCP 4.5 scenario, extreme flood events exceeding a 100-year return period (2000 m<sup>3</sup>/s) are expected to become more frequent, whereas the RCP 8.5 scenario suggests a stabilization of extreme event occurrences beyond 2071. These findings underscore the growing flood risk in the region and highlight the necessity for adaptive water resource management strategies. This research contributes to the advancement of climate-resilient flood forecasting in Central Asian river basins. The integration of process-based hydrological modelling with climate projections provides a more robust framework for flood risk assessment and early warning system development. The outcomes of this study offer crucial insights for policymakers, hydrologists, and disaster management agencies in mitigating the adverse effects of climate-induced hydrological extremes in Kazakhstan.
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spelling doaj-art-863b6a2352bd4d3d8a524186df92c1ca2025-08-20T03:12:05ZengMDPI AGHydrology2306-53382025-02-011223510.3390/hydrology12020035Flood Modelling of the Zhabay River Basin Under Climate Change ConditionsAliya Nurbatsina0Zhanat Salavatova1Aisulu Tursunova2Iulii Didovets3Fredrik Huthoff4María-Elena Rodrigo-Clavero5Javier Rodrigo-Ilarri6Institute of Geography and Water Security, Ministry of Education and Science of the Republic of Kazakhstan, Almaty 050010, KazakhstanInstitute of Geography and Water Security, Ministry of Education and Science of the Republic of Kazakhstan, Almaty 050010, KazakhstanInstitute of Geography and Water Security, Ministry of Education and Science of the Republic of Kazakhstan, Almaty 050010, KazakhstanPotsdam Institute for Climate Impact Research (PIK) e. V., 14473 Potsdam, GermanyIHE Delft Institute for Water Education, 2601 Delft, The NetherlandsInstituto de Ingeniería del Agua y del Medio Ambiente (IIAMA), Universitat Politècnica de València, 46022 Valencia, SpainInstituto de Ingeniería del Agua y del Medio Ambiente (IIAMA), Universitat Politècnica de València, 46022 Valencia, SpainFlood modelling in snow-fed river basins is critical for understanding the impacts of climate change on hydrological extremes. The Zhabay River in northern Kazakhstan exemplifies a basin highly vulnerable to seasonal floods, which pose significant risks to infrastructure, livelihoods, and water resource management. Traditional flood forecasting in Central Asia still relies on statistical models developed during the Soviet era, which are limited in their ability to incorporate non-stationary climate and anthropogenic influences. This study addresses this gap by applying the Soil and Water Integrated Model (SWIM) to project climate-driven changes in the hydrological regime of the Zhabay River. The study employs a process-based, high-resolution hydrological model to simulate flood dynamics under future climate conditions. Historical hydrometeorological data were used to calibrate and validate the model at the Atbasar gauge station. Future flood scenarios were simulated using bias-corrected outputs from an ensemble of General Circulation Models (GCMs) under Representative Concentration Pathways (RCPs) 4.5 and 8.5 for the periods 2011–2040, 2041–2070, and 2071–2099. This approach enables the assessment of seasonal and interannual variability in flood magnitudes, peak discharges, and their potential recurrence intervals. Findings indicate a substantial increase in peak spring floods, with projected discharge nearly doubling by mid-century under both climate scenarios. The study reveals a 1.8-fold increase in peak discharge between 2010 and 2040, and a twofold increase from 2041 to 2070. Under the RCP 4.5 scenario, extreme flood events exceeding a 100-year return period (2000 m<sup>3</sup>/s) are expected to become more frequent, whereas the RCP 8.5 scenario suggests a stabilization of extreme event occurrences beyond 2071. These findings underscore the growing flood risk in the region and highlight the necessity for adaptive water resource management strategies. This research contributes to the advancement of climate-resilient flood forecasting in Central Asian river basins. The integration of process-based hydrological modelling with climate projections provides a more robust framework for flood risk assessment and early warning system development. The outcomes of this study offer crucial insights for policymakers, hydrologists, and disaster management agencies in mitigating the adverse effects of climate-induced hydrological extremes in Kazakhstan.https://www.mdpi.com/2306-5338/12/2/35climate changefloodshydrological modellingKazakhstanSWIM modelZhabay River
spellingShingle Aliya Nurbatsina
Zhanat Salavatova
Aisulu Tursunova
Iulii Didovets
Fredrik Huthoff
María-Elena Rodrigo-Clavero
Javier Rodrigo-Ilarri
Flood Modelling of the Zhabay River Basin Under Climate Change Conditions
Hydrology
climate change
floods
hydrological modelling
Kazakhstan
SWIM model
Zhabay River
title Flood Modelling of the Zhabay River Basin Under Climate Change Conditions
title_full Flood Modelling of the Zhabay River Basin Under Climate Change Conditions
title_fullStr Flood Modelling of the Zhabay River Basin Under Climate Change Conditions
title_full_unstemmed Flood Modelling of the Zhabay River Basin Under Climate Change Conditions
title_short Flood Modelling of the Zhabay River Basin Under Climate Change Conditions
title_sort flood modelling of the zhabay river basin under climate change conditions
topic climate change
floods
hydrological modelling
Kazakhstan
SWIM model
Zhabay River
url https://www.mdpi.com/2306-5338/12/2/35
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AT iuliididovets floodmodellingofthezhabayriverbasinunderclimatechangeconditions
AT fredrikhuthoff floodmodellingofthezhabayriverbasinunderclimatechangeconditions
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