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Overview of mean temperature (T) and sum precipitation (P) in Kazakhstan over the vegetation growing seasons in 2000–2016 for three main distinct sub-regional landscapes calculated from Climate Research Unit data: (A) northern semi-steppe and steppe sub-region, (B) central semi-desert/desert sub-region, and (C) mountainous sub-region
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Droughts have significant negative impacts on livelihoods and economy of Kazakhstan. In this study, we assessed and characterized drought hazard events in Kazakhstan using satellite Remote Sensing time series for the period between 2000 and 2016. First, we calculated Vegetation Condition Index (VCI) and Standardized Enhanced Vegetation Index anomal...
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... Droughts are most frequent during the growing season and generally show an increasing trend over time. Dubovyk et al. (2019) found that Kazakhstan experienced drought every year from 2000 to 2016. The 2021 drought in the southern and south-western regions of Kazakhstan significantly impacted the country's agricultural sectors. ...
... The primary factor driving these changes is the increasing incidence of drought in the region. Dubovyk et al. (2019) found that in the years 2000, 2008, 2012, and 2014, over 50% of the republic's territory experienced droughts of varying intensities. Notably, the most extensive droughts, in terms of geographic coverage, occurred in 2012 and 2014. ...
Kazakhstan’s insufficient food production contributes to its dependency on food imports, highlighting the need for science-based technologies to address land degradation and boost domestic production. The privatisation of land and the establishment of a market economy led to the division of collective farms and significant land fragmentation, resulting in a reduction of agricultural land by 10.6 million ha in the West Kazakhstan region, particularly between 1991 and 2000. Desertification and soil degradation have led to decreased soil fertility, adversely affecting the agricultural industry. Over the last 30 years, the area of eroded soils has increased by 5–9%. As of 2022, over 16.7% of agricultural land remains unused, a substantial rise from 1991. This study aims to investigate the qualitative and quantitative transformations of agricultural land in the region over the past three decades and to assess the impact of climate change on land degradation processes. To achieve this, cartographic analysis of NDVI3g (Global Inventory Monitoring and Modelling System [GIMMS]) data for 1990–2022 was conducted, employing linear ordinary least squares and median Theil–Sen trend methods to identify long-term vegetation trends. The results showed a negative trend in agricultural lands with a decline rate of 0.0025 per year (P = 0.009). However, in the past 13 years, a positive trend was observed in only three regions, with an average increase of 0.007 per year (P = 0.03). These findings are statistically significant and highlight the growing impact of climatic factors on agricultural and natural ecosystems.
... The existing spectral drought indices can be classified into four groups (Hao and Singh, 2015) including (1) soil drought indices, such as Soil Moisture Index (SMI) (Esch et al., 2018) and Ratio Dryness Monitoring Index (RDMI) ; (2) vegetation drought indices, such as Vegetation Condition Index (VCI) and Enhanced Vegetation Index (EVI) (Ha et al., 2023;Shi et al., 2022;Dubovyk et al., 2019); (3) temperature drought indices, such as Land Surface Temperature (LST) (Gutman, 1990) and Thermal Condition Index (TCI) obtained from longterm LST (Kogan, 1995). Soil-vegetation drought indices such as Visible and Short-wave infrared Drought Index (VSDI) (Zhang et al., 2013), Normalized Multi-band Drought Index (NMDI) (Wang et al., 2008), and Short-wave Infrared Water Stress Index (SIWSI) (Fensholt and Sandholt, 2003) have been proposed to address the monitoring challenges in semiarid regions with sparse vegetation. ...
... It is a long-term hydro-meteorological event affecting large regions and different development sectors, especially in Botswana, where the effects are the most noticeable in water resources. There is decreased rainfall, increased cases of drought [16,17] , and increased temperatures, leading to stress on evapotranspiration rates [18,19] . Severe droughts are common in Botswana due to erratic, strongly below-average rainfall. ...
Climate change and variability pose significant threats to southern Africa, with projected continuous drought in Botswana. This study examines the causal relationships between African-Indian monsoon systems (East Africa, West Africa, and Peninsula India), the Mascarene High, and interannual rainfall variability over Botswana. Using statistical analysis and mapping techniques (Pearson correlation statistics and convergent cross mapping (CCM)), the authors analysed the impact of these weather systems on rainfall variability from 1979 to 2021. The findings reveal significant negative associations between these weather systems and interannual rainfall variability in Botswana, shedding light on their crucial roles in shaping the region's rainfall patterns. Bidirectional causation between different regions and the Mascarene High was observed, emphasising the interconnectedness of rainfall patterns. Significant findings include the bidirectional causation between Botswana and West Africa rainfall during March–May (MAM) and October–December (OND) seasons. In addition, the authors also observed bidirectional causation between Botswana and Peninsula Indian rainfall during the OND season. The study highlights the potential of these factors in predicting extreme events and assists in planning for potential risks associated with rainfall variability in Botswana to promote community awareness and education on climate change and variability, water conservation, and sustainable livelihood.
... In general, irrigation practices contribute to alleviating the impact of drought on irrigated crops, as supported by numerous studies (Geng et al., 2022;Li et al., 2020c). However, when drought occurs suddenly and with significant intensity, or during critical growth stages of crops, delayed irrigation may prove ineffective in mitigating the adverse effects on irrigated croplands (Dubovyk et al., 2019;Li et al., 2022a). Furthermore, during prolonged and extreme drought periods that affect local water resource availability, the insufficient supply of water for irrigation can lead to drought-related losses in irrigated croplands Vicente-Serrano et al., 2019). ...
... The subsequent increase in human population in the catchment, which has accelerated since land use intensification associated with Chinese Belt and Road initiatives, has significantly increased both surface and groundwater consumption for industrial and domestic use (De Boer et al., 2021). Extended periods of droughts (e.g., in the year 2000, 2008, 2010, 2012, 2014, and 2021) have further reduced the availability of surface water and inflow to the lake (Dubovyk et al. , 2019;De Boer et al., 2021;Farooq et al., 2023). At the same time, there has been an increase in the amount of sediments, salts, and other solutes entering the system; these remain and become concentrated due to evaporation, increasing salinity and pollution (Kaushal et al., 2021;Abdelbaki, 2022) using point source datasets. ...
Lake Balkhash is Asia’s third-largest lake and an endorheic basin. The lake and its contributing tributaries provide essential water and ecosystem services to the surrounding population, particularly in the Kazakh region. With approximately 2.5 million people living in the areas such as Almaty oblast, Zhetisu oblast, several districts of Karagandy oblast, and Abay province, monitoring and maintaining the lake’s health and water quality is essential for the sustainable management of water resources. The hydrology of Lake Balkhash has been significantly impacted in recent decades by a warming climate, landuse landcover changes, and water-consuming economic activities, the latter of which are driven by population growth and expansion. Turbidity—the measurement of water clarity—serves as a major indicator of water health. Here, we analyze spatial and temporal variability in turbidity across Lake Balkhash by mapping the normalized difference turbidity index (NDTI) based on Landsat data for 1991–2022. We consider major exploratory variables such as precipitation, near-surface temperature, wind speed and direction, water level, and landuse landcover (LULC) within the catchment. We find an overall decrease in turbidity over interannual and seasonal timescales. We observe significant negative correlations between NDTI, near-surface temperature, and water level at both scales but no clear relationship between turbidity and precipitation or wind variables. Among the LULC variables, grassland and bareland near Lake Balkhash showed a positive correlation with NDTI but have spatially decreased over time. Conversely, shrubland and wetland exhibit a negative correlation with NDTI; however, this has spatially increased with time. Our results highlight the significant impact of rising temperatures, anthropogenically influenced water levels, and the LULC variables on turbidity. The turbidity dynamics, in turn, influence the circulation, oxidation, and overall health of Lake Balkhash’s water. Therefore, the study emphasizes that the warming climate and alterations in the lake’s hydrology have a considerable impact on water quality. This suggests that monitoring water health alone may not suffice to mitigate the impacts of climate change and human activities. However, a more comprehensive approach is needed to sustainably manage and conserve dryland water resources.
... In recent decades, the EAR has experienced frequent droughts 13,[21][22][23] and increased land-use pressure (such as overgrazing) 24,25 following economic and sociopolitical changes in countries in the EAR. During the transition phase (the 1990s), the livestock number significantly decreased, but it has rapidly increased in the last two decades, resulting in vegetation productivity loss 13,[26][27][28] and rangeland degradation 25,29,30 . ...
Drought risk threatens pastoralism in rangelands, which are already under strain from climatic and socioeconomic changes. We examine the future drought risk (2031–2060 and 2071–2100) to rangeland productivity across Eurasia (West, Central, and East Asia) using a well-tested process-based ecosystem model and projections of five climate models under three shared socioeconomic pathway (SSP) scenarios of low (SSP1−2.6), medium (SSP3−7.0), and high (SSP5−8.5) warming relative to 1985–2014. We employ a probabilistic approach, with risk defined as the expected productivity loss induced by the probability of hazardous droughts (determined by a precipitation-based index) and vulnerability (the response of rangeland productivity to hazardous droughts). Drought risk and vulnerability are projected to increase in magnitude and area across Eurasian rangelands, with greater increases in 2071–2100 under the medium and high warming scenarios than in 2031–2060. Increasing risk in West Asia is caused by longer and more intense droughts and vulnerability, whereas higher risk in Central and East Asia is mainly associated with increased vulnerability, indicating overall risk is higher where vulnerability increases. These findings suggest that future droughts may exacerbate livestock feed shortages and negatively impact pastoralism. The results have practical implications for rangeland management that should be adapted to the ecological and socioeconomic contexts of the different countries in the region. Existing traditional ecological knowledge can be promoted to adapt to drought risk and embedded in a wider set of adaptation measures involving management improvements, social transformations, capacity building, and policy reforms addressing multiple stakeholders.
... Central Asia is classified as drought-prone and is one of the most vulnerable areas to moisture deficit in the world (Dubovyk et al. 2019;Guo 2018). Based on the findings of foreign scientists, rising temperatures, decreasing precipitation, and increasing evaporation in Central Asia (Lioubimtseva and Henebry 2009;Yin et al. 2016) heighten the vulnerability of ecosystems to droughts due to limited water resources, low adaptive capacity, and a growing population (Zheleznova et al. 2022). ...
... Droughts have occurred throughout the country with varying frequency and intensity, with the highest frequency during the growing season. Dubovyk et al. (2019) reported that Kazakhstan experienced drought every year between 2000 and 2016. ...
... The primary cause of this decline is the drought trend in the area. Dubovyk et al. (2019) found that between 2000 and 2014, over 50% of the country's territory experienced varying degrees of drought, with the most widespread droughts occurring in 2012 and 2014. Bolatova et al. (2022) also reported that the severe drought in 2021 resulted in significant economic losses and changes in cropped areas. ...
Сельское хозяйство - один из наиболее чувствительных к изменению климата секторов экономики, поскольку сельскохозяйственное производство в значительной степени зависит от погодных условий, особенно от жары и осадков. Эксперты Международной продовольственной организации пришли к выводу, что после 2030 года во многих регионах планеты урожайность сельскохозяйственных культур будет снижаться из-за изменений климата. Для сельского хозяйства наибольшую опасность представляют такие проявления изменения климата, как повышение температуры, изменение режима распределения осадков, подъём уровня моря (для прибрежных низменностей) и частые засухи и наводнения, особенно в областях, предрасположенных к стихийным бедствиям. Эти изменения влияют на сельское хозяйство, всё более острой становится проблема обеспечения продовольственной безопасности. В данной статье проанализировано современное состояние земель сельскохозяйственного назначения в западном регионе Казахстана в условиях изменения климата, особенности использования их в сельскохозяйственной сфере, в частности, в растениеводческих отраслях, а также рассматриваются вопросы их рационального использования. Основной акцент делается на необходимости адаптации сельского хозяйства к новым климатическим условиям и эффективному использованию доступных земельных ресурсов. В работе представлены ключевые аспекты данной проблемы, анализируются возможные решения и предлагаются рекомендации для устойчивого развития сельского хозяйства в регионе.
... In January, the range of average temperatures is from À5°C in the south to À20°C in the north. On the contrary, in July, the range of temperatures is from 18°C (in the north) to 29°C (south) (Dubovyk et al. 2019), which can be observed in Figure 1. The study area and Walter-Lieth climate graphs for various locations across the country. ...
... To be able to provide improved operational monitoring and drought event forecasting, the present system needs to advance its technological capabilities. Responsible authorities should consider tools like ML forecasting to provide accurate and timely information for knowledge-driven decisions related to droughts in the country's various social and economic sectors considering the rising risks associated with the impacts of climate variability and climate change in the region (Dubovyk et al. 2019). ...
Kazakhstan is recently experiencing an increase in drought trends. However, low-capacity probabilistic drought forecasts and poor dissemination have led to a drought crisis in 2021 that resulted in the loss of thousands of livestock. To improve drought forecasting accuracy, this study applies Machine Learning and Deep Learning (ML and DL) algorithms to capture the sequences of drought events using a non-contiguous drought analysis (NCDA). Precipitation, 2-m temperature, runoff, solar radiation, relative humidity, and evaporation were collected from the ERA5 database as input variables. Combinations of inputs were used to build ML models, including seven classifiers (Logistic, K-NN, Kernel SVM, Decision Tree, Random Forest, XGBoost, and GRU). The output events were defined by standardized precipitation index (SPI) and SPEI indicators as binary classes. Weekly time series from 1991 to 2021 for each cell were used to forecast a lead time from 1 week to 6 months. GRU provided 97–99% accuracy in more volatile regions while Random Forest and XGBoost showed 94–99% accuracy at a lead time of 6 months. The accuracy evaluation was based on the confusion matrix and F1 score to analyze the stage change capture. This study demonstrates the effectiveness of using ML and DL algorithms for drought forecasting, with potential applications for other regions.
... For this reason, the findings obtained in this study were also compared with the findings obtained near Kazakhstan and Central Asia Region. Despite limited opportunities, researchers studied different aspects of climate change in the region by using alternative methods and techniques (Öztürk et al. 2012;2017;Russell et al. 2018;Dubovyk et al. 2019;Faruq et al. 2021). According to the IPCC 6th Assessment Report (AR-6) (IPCC 2021), the ecological and socio-economic systems of Central Asia, where Kazakhstan is located, are seriously threatened by climate change due to the semi-arid nature of the region. ...
... The current study was inconsistent with Salnikov's study in terms of strong warming in the spring due to the variable time scale considered by the two studies. The results related to spring temperature in this study are in agreement with the findings referred to by Faruq et al. (2021), Dubovyk et al. (2019), and Karatayev et al. (2022). According to Karatayev et al. (2022), as for seasonal changes, the highest and the lowest rates of increase in the mean annual temperature were observed in spring (0.59 °C/ per decade) and winter Fig. 5 Inter-annual and longperiod variations, and long-term linear trends in summer meanair temperature series of two (Taraz and Kyzylorda) stations characterized with a required statistically significant persistence in Kazakhstan. ...
The annual, seasonal, and monthly trends of air temperatures were analyzed for thirteen urban and five rural meteorological stations in Kazakhstan for the 1963–2020 period. The non-parametric Mann–Kendall (M–K) rank correlation and Sen’s slope estimator methods and the parametric least-squares linear regression (LSLR) were used to determine whether there were positive or negative statistically significant trends in mean, average maximum, and minimum air temperature time series along with diurnal temperature ranges (DTRs), and temperature differences between five large and small cities. In addition, Kazakhstan’s annual and seasonal air temperature series were analyzed in terms of autocorrelation (serial correlation) coefficients. Coefficients of variations indicated that mean annual temperature variability is the highest in northern cities. Results of the M–K trend test indicated that the highest and lowest increases in the mean air temperatures were observed in spring and autumn, respectively. The magnitudes of the significant increasing trends in annual air temperature ranged between 0.23 °C/decade at Karagandy and 0.54 °C/decade at Kyzylorda. Annual and seasonal diurnal temperature ranges (DTRs) reveal insignificantly decreasing and increasing trends at most of the stations characterized by urbanization. According to the results of both M–K and LSLR tests, annual and winter air temperature differences of some station pairs tend to significantly increase, which may mean that the differences in the calculated temperature range between large and small cities might have widened significantly. However, significance test for the calculated autocorrelation coefficients of the annual and seasonal air temperature data showed that most of the series clearly appear as a low-frequency variability on the significantly increased long-term averages.
... Moreover, severe and recurrent droughts can also have dramatic negative impacts on near-natural ecosystems, such as forests and grasslands (Senf, Buras, Zang, Rammig, & Seidl, 2020). Therefore, drought assessment, monitoring, and predictions have become urgent scienti c topics (Dubovyk, 2019;Graw et al., 2020). In acknowledgment of this problem, the United Nations Convention to Combat Deserti cation (UNCCD) has recently launched the drought initiative (https://www.unccd.int/actions/drought-initiative) to address the far-reaching consequences of droughts. ...
... , which is computed using near-infrared and red spectral bands, is an indicator of vegetation health; consequently, anomalies in the NDVI may be indicative of drought conditions(Dubovyk, 2019;Ghazaryan, König, et al., 2020). NDWI is an index that is very effective for drought monitoring as it is related to the moisture condition of vegetation canopies(Ghazaryan, Dubovyk, Graw, Kussul, & Schellberg, 2020). ...
Severe droughts have had unprecedented impacts on vegetation in German ecosystems in recent years. Accurate assessment of the temporal and spatial dynamics of vegetation affected by drought stress requires high to medium spatial resolution images (10-m) and frequent in-situ observations. However, the lack of dense long-term 10-m image time series hinders remote sensing-based high spatial resolution drought assessments. The objective of this study was to evaluate drought conditions in Central Germany using a multi-sensor satellite time series with varying spatial and temporal resolutions. We calculated several drought indices, including the Vegetation Condition Index (VCI), anomalies of the Normalized Vegetation Index (NDVI) and Normalized Water Index (NDWI), and anomalies of land surface temperature (LST), from pre-processed 250m-1km MODIS (Moderate Resolution Imaging Spectroradiometer)-time series and a regular synthetic Sentinel-2 time series. Overall, the spatial patterns of drought were similar between the same drought index time series from both sensors, while variations were observed in the identified severity levels of drought and the level of spatial detail in the mapped drought patterns. Our findings indicated that the study area was predominantly affected by drought during the 2018 growing season, with less extensive drought-affected areas also observed in 2017 and 2020. In-situ drought index time series consistently recorded the presence of drought conditions throughout the summer seasons of 2018–2020, confirming the results of our satellite-based analysis. Future research should explore the feasibility of employing fusion techniques to downscale moderate-resolution drought analysis to a spatial resolution of 10m while maintaining a long-term image time series. The integration of such datasets holds significant implications for environmental monitoring and assessment, enabling more accurate and timely interventions in the face of severe climatic events.
