Assessment of the Impacts of Climate Change and Human Activities on Runoff Using Climate Elasticity Method and General Circulation Model (GCM) in the Buqtyrma River Basin, Kazakhstan

Rakhimova, Moldir; Li, Shipeng; Bissenbayeva, Sanim; Mukanov, Yerbolat; Gafforov, Khusen Sh.; Bekpergenova, Zhuldyzay; Gulakhmadov, Aminjon

doi:10.3390/su12124968

Cited by 24 publications

(17 citation statements)

References 45 publications

(56 reference statements)

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“…It shows that in both upstream and downstream areas, the impact of anthropogenic intervention is a dominant factor contributing to runoff changes. Our findings are in line with the results of previous studies in the region of Central Asia including Arys and Keles River Basins in Uzbekistan, the Buqtyrma River Basin in Kazakhstan, and the Aksu River Basin in Xinjiang in Central Asia [6,30,31]. It should be noted that the climate elasticity method was also used in these basins.…”

Section: Discussionsupporting

confidence: 92%

“…The change point for the annual mean temperature occurred in the downstream in 1976 and in the upstream regions in 1996. Our results of the change points occurrences for the temperature in both the downstream and upstream parts are in line with the study by Rakhimova et al [30] and Bissenbayeva et al [31] in Central Asia. For the precipitation, the change point was detected in 1969 while for potential evapotranspiration it was in 1998 in both the upstream and the downstream parts of the KRB during 1950-2016.…”

Section: Trend and Change Point Analysis Of The Temperature Precipitation And Potential Evapotranspiration Seriessupporting

confidence: 93%

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Quantifying the Relative Contribution of Climate Change and Anthropogenic Activities on Runoff Variations in the Central Part of Tajikistan in Central Asia

Gulahmadov

Chen

Gulakhmadov

et al. 2021

Land

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Quantifying the relative contribution of climate change and anthropogenic activities to runoff alterations are essential for the sustainable management of water resources in Central Asian countries. In the Kofarnihon River Basin (KRB) in Central Asia, both changing climate conditions and anthropogenic activities are known to have caused changes to the hydrological cycle. Therefore, quantifying the net influence of anthropogenic contribution to the runoff changes is a challenge. This study applied the original and modified Mann–Kendall trend test, including the Sen’s slope test, Pettitt’s test, double cumulative curve, and elasticity methods. These methods were applied to determine the historical trends, magnitude changes and change points of the temperature, precipitation, potential evapotranspiration, and runoff from 1950 to 2016. In addition, the contributions of climate change and anthropogenic activities to runoff changes in the KRB were evaluated. The trend analysis showed a significant increasing trend in annual temperature and potential evapotranspiration, while the annual precipitation trend showed an insignificant decreasing trend during the 1950–2016 time period. The change point in runoff occurred in 1986 in the upstream region and 1991 in the downstream region. Further, the time series (1950–2016) is separated into the prior impacted period (1950–1986 and 1950–1991) and post impacted period (1987–2016 and 1992–2016) for the upstream and downstream regions, respectively. During the post impacted period, climate change and anthropogenic activities contributed to 87.96% and 12.04% in the upstream region and 7.53% and 92.47% in the downstream region of the KRB. The results showed that in runoff changes, the anthropogenic activities played a dominant role in the downstream (97.78%) and the climate change impacts played a dominant factor in the upstream region (87.96%). In the land-use type changes, the dominant role was played by construction land, which showed that the area from 248.63 km2 in 1990 increased to 685.45 km2 (175.69%) in 2015. These findings suggest that it is essential to adopt effective steps for the sustainable development of the ecological, hydrological, and social order in the KRB in Central Asia.

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Section: Discussionsupporting

confidence: 92%

Section: Trend and Change Point Analysis Of The Temperature Precipitation And Potential Evapotranspiration Seriessupporting

confidence: 93%

Quantifying the Relative Contribution of Climate Change and Anthropogenic Activities on Runoff Variations in the Central Part of Tajikistan in Central Asia

Gulahmadov

Chen

Gulakhmadov

et al. 2021

Land

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“…As a result, the GCM predicts the global scale mean surface temperature and periodical circulation of sea-ice extent of the oceans (Fang et al 2015a). The Intergovernmental Panel on Climate Change (IPCC) investigations have been revealed and suggest that climate variables, specifically precipitation and temperature, are more closely related with global warming and are mostly impacting regional-or catchment-scale hydrological processes (Rakhimova et al 2020).…”

Section: Introductionmentioning

confidence: 99%

Performance assessment of six bias correction methods using observed and RCM data at upper Awash basin, Oromia, Ethiopia

Tumsa

2021

Journal of Water and Climate Change

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Selecting a suitable bias correction method is important to provide reliable inputs for evaluation of climate change impact. Their influence was studied by comparing three discharge outputs from the SWAT model. The result after calibration with original RCM indicates that the raw RCM are heavily biased, and lead to streamflow simulation with large biases (NSE = 0.1, R2 = 0.53, MAE = 5.91 mm/°C, and PBIAS = 0.51). Power transformation and linear scaling methods performed best in correcting the frequency-based indices, while the LS method performed best in terms of the time series-based indices (NSE = 0.87, R2 = 0.78, MAE = 3.14 mm/°C, PBIAS = 0.24) during calibration. Meanwhile, daily translation was underestimating simulated streamflow compared with observed and was considered as the least performing method. The precipitation correction method has higher visual influence than temperature, and its performance in streamflow simulations was consistent and considerable. Power transformation and variance scaling showed highly qualified performance compared to others with indicated time series values (NSE = 0.92, R2 = 0.88, MAE = 1.58 mm/°C and PBIAS = 0.12) during calibration and validation of streamflow. Hence, PT and VARI were the dominant methods to remove bias from RCM models at Akaki River basin.

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“…Climate change and variability trend analyses need consistent and long-term time series climate data [1][2][3][4][5][6][7][8] that are required to study the impact of climate change on the agro-hydrological system [9][10][11]. Such climate studies can benefit from the freely available Global Climate Models (GCMs) outputs such as rainfall data.…”

Section: Introductionmentioning

confidence: 99%

Performance Evaluation and Comparison of Satellite-Derived Rainfall Datasets over the Ziway Lake Basin, Ethiopia

Hordofa

Leta

Alamirew

et al. 2021

Climate

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Consistent time series rainfall datasets are important in performing climate trend analyses and agro-hydrological modeling. However, temporally consistent ground-based and long-term observed rainfall data are usually lacking for such analyses, especially in mountainous and developing countries. In the absence of such data, satellite-derived rainfall products, such as the Climate Hazard Infrared Precipitations with Stations (CHIRPS) and Global Precipitation Measurement Integrated Multi-SatellitE Retrieval (GPM-IMERG) can be used. However, as their performance varies from region to region, it is of interest to evaluate the accuracy of satellite-derived rainfall products at the basin scale using ground-based observations. In this study, we evaluated and demonstrated the performance of the three-run GPM-IMERG (early, late, and final) and CHIRPS rainfall datasets against the ground-based observations over the Ziway Lake Basin in Ethiopia. We performed the analysis at monthly and seasonal time scales from 2000 to 2014, using multiple statistical evaluation criteria and graphical methods. While both GPM-IMERG and CHIRPS showed good agreement with ground-observed rainfall data at monthly and seasonal time scales, the CHIRPS products slightly outperformed the GPM-IMERG products. The study thus concluded that CHIRPS or GPM-IMERG rainfall data can be used as a surrogate in the absence of ground-based observed rainfall data for monthly or seasonal agro-hydrological studies.

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Assessment of the Impacts of Climate Change and Human Activities on Runoff Using Climate Elasticity Method and General Circulation Model (GCM) in the Buqtyrma River Basin, Kazakhstan

Cited by 24 publications

References 45 publications

Quantifying the Relative Contribution of Climate Change and Anthropogenic Activities on Runoff Variations in the Central Part of Tajikistan in Central Asia

Quantifying the Relative Contribution of Climate Change and Anthropogenic Activities on Runoff Variations in the Central Part of Tajikistan in Central Asia

Performance assessment of six bias correction methods using observed and RCM data at upper Awash basin, Oromia, Ethiopia

Performance Evaluation and Comparison of Satellite-Derived Rainfall Datasets over the Ziway Lake Basin, Ethiopia

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