Facts and Perspectives of Water Reservoirs in Central Asia: A Special Focus on Uzbekistan

Rakhmatullaev, Shavkat; Huneau, Frédéric; Coustumer, Philippe Le; Motelica-Heino, Mikaël; Bakiev, Masharif

doi:10.3390/w2020307

Cited by 34 publications

(15 citation statements)

References 7 publications

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“…This difference is assumed to result from the number of regulation constructions (e.g., dams) along the Syr Darya, which is higher compared to the Amu Darya [4]. For the course of the Amu Darya, the Tuyamuyun Reservoir with a total volume of approximately 4.5 km 3 is stated to be the only remarkable artificial water storage [78]. However, its impact is indicated by the comparatively high MR-CI values in its upstream locations of CZ 8 leading to a second gradient of CI in the river system (Figure 8).…”

Section: Assessment Of CI In the Asb (2000-2012)mentioning

confidence: 99%

Cropping Intensity in the Aral Sea Basin and Its Dependency from the Runoff Formation 2000–2012

Conrad

Schönbrodt-Stitt

Löw³

et al. 2016

Remote Sensing

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This study is aimed at a better understanding of how upstream runoff formation affected the cropping intensity (CI: number of harvests) in the Aral Sea Basin (ASB) between 2000 and 2012. MODIS 250 m NDVI time series and knowledge-based pixel masking that included settlement layers and topography features enabled to map the irrigated cropland extent (iCE). Random forest models supported the classification of cropland vegetation phenology (CVP: winter/summer crops, double cropping, etc.). CI and the percentage of fallow cropland (PF) were derived from CVP. Spearman's rho was selected for assessing the statistical relation of CI and PF to runoff formation in the Amu Darya and Syr Darya catchments per hydrological year. Validation in 12 reference sites using multi-annual Landsat-7 ETM+ images revealed an average overall accuracy of 0.85 for the iCE maps. MODIS maps overestimated that based on Landsat by an average factor of~1.15 (MODIS iCE/Landsat iCE). Exceptional overestimations occurred in case of inaccurate settlement layers. The CVP and CI maps achieved overall accuracies of 0.91 and 0.96, respectively. The Amu Darya catchment disclosed significant positive (negative) relations between upstream runoff with CI (PF) and a high pressure on the river water resources in 2000-2012. Along the Syr Darya, reduced dependencies could be observed, which is potentially linked to the high number of water constructions in that catchment. Intensified double cropping after drought years occurred in Uzbekistan. However, a 10 kmˆ10 km grid of Spearman's rho (CI and PF vs. upstream runoff) emphasized locations at different CI levels that are directly affected by runoff fluctuations in both river systems. The resulting maps may thus be supportive on the way to achieve long-term sustainability of crop production and to simultaneously protect the severely threatened environment in the ASB. The gained knowledge can be further used for investigating climatic impacts of irrigation in the region.

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Section: Assessment Of CI In the Asb (2000-2012)mentioning

confidence: 99%

Cropping Intensity in the Aral Sea Basin and Its Dependency from the Runoff Formation 2000–2012

Conrad

Schönbrodt-Stitt

Löw³

et al. 2016

Remote Sensing

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“…Climate change as well as human interaction have altered the water balance of the region, causing serious water shortages, retreat of glaciers, desertification, and the drying-up of the Aral Sea [4][5][6][7][8][9]. Population growth and the intensifying demand on more water for irrigation and the production of hydropower stand in contrast to the decline of the resource [10,11], causing also political tensions to arise [8,12]. Against this background a detailed analysis of processes like changing snow cover duration, onset, or melt of snow-covered areas becomes more important.…”

Section: Introductionmentioning

confidence: 99%

Identifying Changing Snow Cover Characteristics in Central Asia between 1986 and 2014 from Remote Sensing Data

et al. 2014

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Central Asia consists of the five former Soviet States Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan, and Uzbekistan, therefore comprising an area of ~4 Mio km 2 . The continental climate is characterized by hot and dry summer months and cold winter seasons with most precipitation occurring as snowfall. Accordingly, freshwater supply is strongly depending on the amount of accumulated snow as well as the moment of its release after snowmelt. The aim of the presented study is to identify possible changes in snow cover characteristics, consisting of snow cover duration, onset and offset of snow cover season within the last 28 years. Relying on remotely sensed data originating from medium resolution imagers, these snow cover characteristics are extracted on a daily basis. The resolution of 500-1000 m allows for a subsequent analysis of changes on the scale of hydrological sub-catchments. Long-term changes are identified from this unique dataset, revealing an ongoing shift towards earlier snowmelt within the Central Asian Mountains. This shift can be observed in most upstream hydro catchments within Pamir and Tian Shan Mountains and it leads to a potential change of freshwater availability in the downstream regions, exerting additional pressure on the already tensed situation.

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“…Yet, following independence from the Soviet Union, this centrally managed "water-energy-food/livelihood nexus" collapsed. Currently, large quantities of water are released by the upstream countries during winter for generating their highly needed electric power to satisfy their own heating demands during this peak season [50,51]. However, while doing so, less water remains to satisfy the water demand in the downstream countries, particularly during the summer irrigation seasons.…”

Section: Description Of the Study Area And River Network Schemementioning

confidence: 99%

The Effect of Energy Constraints on Water Allocation Decisions: The Elaboration and Application of a System-Wide Economic-Water-Energy Model (SEWEM)

Bekchanov

Lamers²

2016

Water

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Worldwide, demand for water, energy, and food are on the rise due to population and industrial growth. Because of such increasing demands and in spite of the limitedness of key resources, more efficient ways to meet these demands become obligatory. Especially considering the multiple interlinkages between water, energy, and food/livelihood systems, an integrated management of key resources such as water, land, and energy deems essential for realizing synergetic efficiencies, for consistent policy decisions, and for sustainable development, in particular across the river basins of the world. Therefore, the general framework of a system-wide economic-water-energy model (SEWEM), which is applicable across river basins and adjustable to different spatial scales such as sub-catchments, is presented here to meet the demands for an effective analytical tool in dealing with water-energy-food/livelihood nexus challenges. Previous hydro-economic models often ignored energy requirements, for instance, for irrigation water supply, as well as energy supply constraints, which recurrently might have led to an overestimation of the optimal levels of ground and surface water uses. The SEWEM was developed to address this gap and analyze how optimal levels of surface and groundwater uses, as well as on irrigation and power production benefits, change in response to the consideration of energy supply constraints and energy requirements for water pumping and other agricultural production operations. This is illustrated for the case of the Aral Sea Basin (ASB) in Central Asia, where surface and groundwater supplies heavily depend on pumping and thus on energy availability. The findings underlined the overestimations of optimal water uses by a hydro-economic model that neglects energy constraints. Moreover, geographical conditions have affected the changes in optimal ratios of surface and groundwater uses and water distributions across the river basin when energy restrictions are taken into account. The results confirmed the importance of the consideration of energy constraints for the assessment of optimal water and land uses, and the essential role of an integrated analysis of water, energy, and food/livelihood systems for better-informed policy-making. Despite the added value of the SEWEM that can consider energy system constraints, further fine-tunings would make it even more relevant for addressing additional questions related to basin management. For example, improvements can be expected through considering the system dynamics, ecological aspects, income distribution effects, trade relationships, and institutional restrictions.

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Facts and Perspectives of Water Reservoirs in Central Asia: A Special Focus on Uzbekistan

Cited by 34 publications

References 7 publications

Cropping Intensity in the Aral Sea Basin and Its Dependency from the Runoff Formation 2000–2012

Cropping Intensity in the Aral Sea Basin and Its Dependency from the Runoff Formation 2000–2012

Identifying Changing Snow Cover Characteristics in Central Asia between 1986 and 2014 from Remote Sensing Data

The Effect of Energy Constraints on Water Allocation Decisions: The Elaboration and Application of a System-Wide Economic-Water-Energy Model (SEWEM)

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