1 Introduction
The impact of global climate change on water supplies is still a major concern in modern science, economics, and ecosystems and manifests to have an indirect and direct impact on natural hydrological (Sarker, 2022) and climatic circulation (Arnell and Gosling, 2013) through changes in rainfall patterns, runoff, and sea level (Honings, 2018). These changes are of great concern as the world's population grows and the current high demand for water is stressed (Vörösmarty et al., 2000), and they affect environmental integrity (Standen et al., 2022). The impact of water diversions (Gao et al., 2022) on lakes for irrigated agriculture and urban use (Wine and Laronne, 2020) has been widely exposed. In addition, rising temperatures, changing precipitation patterns (Singhal et al., 2023), and changes in extreme frequency events increase the likelihood of flooding (Sarker, 2023; Singhal et al., 2023), alter seasonal water supply (Mertz et al., 2009), and water level (Dusini et al., 2009; Yuan et al., 2015) and, as a result, have an impact on nutrient transport (Alifujiang et al., 2020). Climate change drivers such as area, location, and elevation contribute to similarities and differences, and few studies have been conducted to account for them (Lan et al., 2011). Climate and human activities influence the water balance of Lake Issyk-Kul (Romanovsky, 2002) as important ecosystem indicators and water sources in Kyrgyzstan (Matuzeviciute et al., 2018). Other recent studies, such as Alifujiang et al. (2002), Romanovsky (2002) and uulu Salamat et al. (2015), claim that the lake is experiencing water level instability. The water-level fluctuations (Alymkulova et al., 2016; Alifujiang et al., 2017) were identified by unexpected changes in runoff (Alifujiang et al., 2002) and seasonal flooding (Duan et al., 2020). For the local society, simulation of hydrological components (Uwamahoro et al., 2021), accurate forecasting of seasonal variations in the water level of Issyk-Kul Lake under various scenarios, and anthropogenic activities are essential.
Indeed, Global Circulation Model (GCMs) play an important role in predicting future climate change (Yao et al., 2020). However, due to unknown data, the interpolation of Global Circulation Model (GCM) data is required, and they must be thoroughly analyzed and verified. One way to estimate values between known data points is through interpolation (Hamed et al., 2022; Prathom and Champrasert, 2023). It entails estimating climate data values for a particular site. The interpolation methods of climate change scenarios have been widely used in climate predictions (Markovic et al., 2014), and the model simulation provides the more accurate prediction (Lee et al., 2014). Utilizing predictions under various scenarios, the Global Circulation Model (GCM) is a model used to determine the future climate situation (Chokkavarapu and Mandla, 2019). However, only at a low spatial resolution (250–600 km) does the GCM produce predictions (Kaini et al., 2020). The location of the catchment plays a role in conducting unsampled data selection and bias correction methods to determine the accuracy of hydrological modeling. The study uses a model ensemble, which is able to lower a single model's uncertainty. When creating data, interpolation is crucial in the unsampled area or in predictions by applying mathematical techniques, both geostatistical and non-geostatistical (Huerta et al., 2023). Inverse Distance Weight IDW data's performance is a non-geostatistical spatial interpolation and heavily dependent on the season (Chae et al., 2022; Adelodun et al., 2023). IDW is a well-liked interpolation technique because of its low complexity (Zhu et al., 2022). According to the literatures, the effectiveness of different spatial interpolation techniques, such as IDW, in estimating climate data demonstrates that the interpolated error values' low-level error by IDW is not significantly different from that of the other approaches (Meng et al., 2019; Tan et al., 2021; Liu et al., 2022). Therefore, our reasoning for selecting IDW is strengthened by its ability to capture local patterns and user-controlled parameters. Furthermore, Coupled Model Intercomparison Project Phase 6 (CMIP6) builds on previous CMIP simulations to address a wide range of specific questions and fill scientific gaps identified in previous CMIP phases (Eyring et al., 2016). The Model Intercomparison Project (MIP) promotes CMIP6, the so-called Shared Socioeconomic Pathways (SSPs), in order to provide more reasonable and accurate data (Voldoire et al., 2019; Tokarska et al., 2020; Zelinka et al., 2020). SSP119 is a brand-new scenario, while SSP585 is an updated version of Representative Concentration Pathway (RCP) scenarios from CMIP5 (Qing, 2012; Riahi et al., 2017). These climate scenarios may provide the most accurate and practical future projections. The SSP119 aims to keep global warming below 1.5°C in order to meet the Paris Agreement's goals (Su et al., 2002). The scenario 119 focuses on consumption with a low material growth rate and a lower resource and energy intensity (Riahi et al., 2017). Thus, because Kyrgyzstan is a landlocked country (Akiner, 2016; Rovenskaya et al., 2018) with relatively low industrialization and agriculture (Rodrik, 2017; Lee and Mah, 2020), scenario 119 was chosen to examine climate change in this study. And also, as the country is surrounded by developed countries such as China and Kazakhstan (Kembayev, 2020) with fossil-fueled development (Yang, 2010), SSP545 is recommended since it focuses on fossil-fuel production (Riahi et al., 2017).
Previous climate researches have focused on regional trends of climate patterns (Fontaine et al., 2001; Stone et al., 2001; Jha et al., 2006; Cousino et al., 2015). Most of existing climate effect studies and discharge prediction models are limited in extent and focus on specific, small locations (Fontaine et al., 2001; Stone et al., 2001; Jha et al., 2006; Cousino et al., 2015). Limited studies have examined the impacts of climate change associated with differences in elevation, location, latitude, area, slope (Luo et al., 2019b), and human activities (Alifujiang et al., 2002). However, the influence of human activities and climate change on hydrological components has yet to be recognized. Thus, there is a lack of understanding of the local impacts of climate on water resources in smaller watersheds, as well as how these small watersheds respond to changes caused by elevations, locations, latitude, and area differences, as well as anthropogenic activities. Discharge differences are influenced by the agriculture change ratio (Juahir et al., 2010). In fact, there is a link between the population and their activities (Mahmoud and Gan, 2018), which lead to increased water consumption, especially for irrigation. In a variety of catchments, the Soil and Water Assessment Tool (SWAT) has been used to forecast discharge (Abbaspour et al., 2007; Baker and Miller, 2013; Grusson et al., 2015). We used the SWAT model in this study with the general objective of quantifying the effects of climate change and land use change on total water resources based on the capacity revealed by previous researchers using this model. The specific objectives of this research are to: (1) simulate total discharges from these catchments for the period 2020–2100 based on two scenarios of greenhouse gas emissions, SSP119 and SSP585; (2) quantify the effects of climate change on water resources in the three selected catchments around Lake Issyk-Kul; and (3) use the Markov matrix and the regression model to show historical and future changes in LULC due to human activities and climate change for the periods (1992–2003), (2003–2015), and (2015–2100).
4 Discussion
4.1 Spatiotemporal characteristics under climate change and sensitivity transformation
Climate change has a broad impact on Issyk-Kul water balance across the basin, with the variations visible in the catchments that feed the lake (Alifujiang et al., 2002; Shabunin and Shabunin, 2002). The lake is surrounded by many catchments (Savvaitova and Petr, 1992; Klerx and Imanackunov, 2002). However, based on the most densely populated areas and problematic issues (lack of observed discharge), three catchments were selected (Figure 1). The main source of water for the lake is the catchments around it (Wang et al., 2013; Guo et al., 2014), and the water barriers in the catchments to the lake have an indirect impact on the basin's water level. Overall, the climate effect of the three selected catchments around Issyk-Kul Lake shows significant spatiotemporal heterogeneities. With the exception of catchment (b), which showed significant temperature differences from the other two catchments, particularly in the summer and autumn, these catchments experienced significant climate warming and wetting (Figure 5). The lake, fed by glacier water and snowmelt, is obviously affected by temperature and precipitation. Our findings are consistent with those of Luo et al. (2018) and Uwamahoro et al. (2021), who recorded decreases in summer precipitation. The catchments (a) and (c), which receive water from the glacier melt on mountain peaks such as TeskeyAla-Too Mountain, have shown less warming than the catchment (b) in the basin's north, and this is in line with Uwamahoro et al. (2021), which has shown a temperature increase (Figure 5). The altitude and elevation differences and similarities reported by Lan et al. (2011) help to clarify this. This is also consistent with previous studies (Hu et al., 2014; Luo et al., 2019b), which suggest that temperature change will be more noticeable at higher altitudes and elevations. In high peaks, the average elevation of the two catchments (a) and (c) shows slight differences (Figure 1) and thus slight warming similarities (Figure 5), whereas the catchment (b), which is~200 m lower in elevation than the two catchments, is identified differently (Figures 1, 5). The effect of altitude on warming is less than that of elevation. Moreover, our results show that minimum temperatures are rising faster than maximum temperatures, confirming observations from the world's most terrestrial regions (Donat et al., 2013; Morak et al., 2013; Feng et al., 2018). Increased vapor and aerosol content in the air is expected to allow for greater changes in minimum temperature than in maximum (Ma et al., 2013). This can influence specific outcomes according to regional and local factors.
This analysis reveals that the selected catchments experienced a strong increase in total discharge under the SSP119 scenarios and slight increase in total discharge under the SSP585 scenarios (Figure 6). Because temperature influences not only the form of precipitation but also the volume of snowmelt water in the catchments around the Issyk-Kul basin, the overall runoff is more vulnerable to rising temperatures than rising precipitation. The same situation has been observed in other catchments, such as alpine catchments in Karakoram (Liu et al., 2017a). In fact, for all the catchments (a), (b), and (c), the increases in temperature and precipitation result in an increase in total discharge under SSP119 and SSP585 (Figures 5, 6). Under SSP585, however, when the temperature rises to a very high level, the total discharge decreases (Figures 5, 6). This is in line with some studies that found a significant decrease in total discharge in some watersheds, such as Kaidu catchment in Xinjiang (Fang et al., 2015) and Athabasca catchment in Canada (Shrestha et al., 2017). The findings revealed that the rise in discharges in the study area is not sustainable. If the temperature continues to rise, the total discharge will be reduced in the future, as predicted by Fang et al. (2015). According to our results, critical temperatures exist under SSP585 for the catchments surrounding Issyk-Kul Lake. Therefore, temperature changes always have a negative impact on total discharge in catchments throughout the basin.
4.2 Variations in the impact of climate change caused by the differences in catchment characteristics
Climate change has different impacts on the overall discharge in each of the three catchments. In general, the two catchments located to the southeast of Issyk-Kul Lake would undergo greater changes in overall discharge than the catchment to the north. Under SSP119 scenario, the average variations in total discharge by 2020–2100 are 13.5, 5, and 12% for catchments (a), (b) and (c), respectively (Figure 6). These differences can be qualified depending on the location and area. The result revealed that small low-lying catchments are less vulnerable to climate change. This is demonstrated by the fact that catchment (b) has smaller average discharge changes (5%) than catchment (a) (13.5%), which is located to the Southeast near Teskey Ala-Too with the highest peak. Differences in elevation and surface area result in changes in the southeastern catchments. Our result is consistent with previous studies reported that high alpine catchments would experience the greatest hydrological changes due to the important role of glacier and snow in the water balance (Nijssen et al., 2001; Beniston et al., 2003; Lan et al., 2011).
Sensitivities were observed in the two catchments as a result of precipitation and temperature variations. The findings suggest that the slope aspect of a catchment can influence its response to climate change. In our study, the windward sloping catchments of the highest peak of Teskey Ala-Too and Kungey Ala-Too are more sensitive to climate change than the downwind sloping catchments, probably because of water vapor source, land cover, and other factors (Luo et al., 2019b). SSP119 and SSP585 both showed a downward trend in snow melt from June to August (Figure 6). This was due to the catchments' differing elevations and temperatures. Under SSP119 and SSP585, evapotranspiration is proportional to precipitation and temperature increases (Figures 5, 6). For the three catchments, the reaction of evapotranspiration in discharge changes is greater compared to those in precipitation.
4.3 Land use/cover under human activities and climate change
A historical Markov analysis of the change in LULC over the study region for the periods (1992–2003) and (2003–2015) revealed minor and major changes in LULC in three watersheds (Figure 7). Agriculture showed an increasing trend in catchments over time, with the exception for catchment (b) in the north of the Lake, which showed a decline during the periods (1992 to −2003) and (2003–2015). The big part of agriculture expanded to grasslands. Agriculture was located at a lower elevation in the catchments, and cultivation was one of the major reasons for this expansion, especially in the area near Karakol City. Furthermore, irrigation is deliberately necessary for agriculture in these areas (Alymkulova et al., 2016). Previous studies have found that water use decreased between 1990 and 2014 (Alifujiang et al., 2002). During 1980–1989, 1990–1999, and 2000–2014, agriculture water use decreased from 2029 × 106 m3yr−1 to 981 × 106 m3yr−1 and 461 × 106 m3yr−1, respectively. Human activities, such as agricultural irrigation, land use, and water-soil conservation, have transformed the spatial and temporal distribution of water resources, indirectly affecting the hydrological processes of the basins (Dong et al., 2016; Wu et al., 2017).
In general, the results showed that agriculture area increased in our study due to population food needs. For all periods in Southeast, downward changes were mainly in snow and ice, whereas the catchment (b) showed a very slight increase in snow and ice for all periods (Figure 7). Furthermore, when water leaves mountain outlets, runoff is significantly affected by anthropogenic activities, particularly agriculture that requires irrigation. Our results clearly demonstrated that the little runoff has LULC changes impacts, which is consistent with the findings of other researchers (Li and Wang, 2009). The results of this study revealed that catchment (c) had the greatest change in total discharge, especially in 1993 (−1.06 m3/s) and 2001 (−1.05 m3/s), and catchment (b) had the smallest change (−0.005 m3/s) in 2007. The results revealed that water consumption for irrigation is higher in catchment (c) than in catchments (a) and (b) due to increase in proportion of people engaged in agriculture in Karakol City (Figure 8). In comparison to the northern catchment, the southeast catchments (a) and (c) of the basin appear to have a large decrease in total discharge.
Predictions for the period 2015–2100 revealed an increase and decrease in the percentiles of LULC classes in this study (Table 4). Agriculture experienced the greatest increase, followed by bare land, with the exception of catchment (c) in the southeast of the basin. Forest had the highest decreasing percentiles (−59%), followed by grassland (−25.89%). The study of land cover changes revealed a high increase (61.25%) in agriculture on catchment (c), which is due to human activities of the population near the catchments.
4.4 Climate change and anthropogenic activities on streamflow
In hydrological science, the assessment of climate change and human activities is a critical issue. However, because of the use of different techniques (parameters) and reference periods, different locations have different impacts (Liu et al., 2020). With respect to this declaration, the catchment to the north of the lake had less human influence than the catchments to the south-east. In comparison to the two Southeast catchments, the catchment (c) showed the greatest impact of human activities. From region to region, the nuanced significance of climate and human impacts varies (Liu et al., 2017b). Similarly, when hydrological components were compared, the water discharge in catchment (b) was lower than in catchments (a) and (c). This obviously leads to the conclusion that, compared to human activities, climate change has a greater impact on the selected catchments and greatly affects Lake Issyk-Kul. This agrees with Alifujiang, Abuduwaili (Alifujiang et al., 2017), who concluded that climate change was the main factor disturbing the Issyk-Kul Lake's water levels. Similar to Cheng et al. (2016) argued that climate change was the main contributor to the reduction in runoff, accounting for 64% of the change in runoff. Topography and land use land cover change influence the discharge in catchments (de Magalhães et al., 2022; Zhang et al., 2022). Discharge on catchment c was smaller because of its physical characteristics indicated by its topography and LULC indicated by a considerable amount of impermeable which lowered infiltration and a more regulated runoff. Thus, leading to a smaller relative change in discharge.