Irrigation expansion and dynamics of desertification in the Circum-Aral region of Central Asia

Saiko, T. A.; Zonn, Igor S.

doi:10.1016/s0143-6228(00)00014-x

Cited by 160 publications

(85 citation statements)

References 4 publications

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“…Precipitation in the mountains can exceed 1,000 mm. Because of the aridity, agriculture in the study area is fully dependent on a dense irrigation and drainage network [13], which was extensively developed during the Soviet era [54]. Therefore, agricultural land is predominantly located downstream of the Amudarya and Syrdarya Rivers.…”

Section: Study Areamentioning

confidence: 99%

Mapping Cropland Abandonment in the Aral Sea Basin with MODIS Time Series

Löw¹,

Prishchepov

Waldner

et al. 2018

Remote Sensing

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Abstract:Cropland abandonment is globally widespread and has strong repercussions for regional food security and the environment. Statistics suggest that one of the hotspots of abandoned cropland is located in the drylands of the Aral Sea Basin (ASB), which covers parts of post-Soviet Central Asia, Afghanistan and Iran. To date, the exact spatial and temporal extents of abandoned cropland remain unclear, which hampers land-use planning. Abandoned land is a potentially valuable resource for alternative land uses. Here, we mapped the abandoned cropland in the drylands of the ASB with a time series of the Normalized Difference Vegetation Index (NDVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) from [2003][2004][2005][2006][2007][2008][2009][2010][2011][2012][2013][2014][2015][2016]. To overcome the restricted ability of a single classifier to accurately map land-use classes across large areas and agro-environmental gradients, "stratum-specific" classifiers were calibrated and classification results were fused based on a locally weighted decision fusion approach. Next, the agro-ecological suitability of abandoned cropland areas was evaluated. The stratum-specific classification approach yielded an overall accuracy of 0.879, which was significantly more accurate (p < 0.05) than a "global" classification without stratification, which had an accuracy of 0.811. In 2016, the classification results showed that 13% (1.15 Mha) of the observed irrigated cropland in the ASB was idle (abandoned). Cropland abandonment occurred mostly in the Amudarya and Syrdarya downstream regions and was associated with degraded land and areas prone to water stress. Despite the almost twofold population growth and increasing food demand in the ASB area from 1990 to 2016, abandoned cropland was also located in areas with high suitability for farming. The map of abandoned cropland areas provides a novel basis for assessing the causes leading to abandoned cropland in the ASB. This contributes to assessing the suitability of abandoned cropland for food or bioenergy production, carbon storage, or assessing the environmental trade-offs and social constraints of recultivation.

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Section: Study Areamentioning

confidence: 99%

Mapping Cropland Abandonment in the Aral Sea Basin with MODIS Time Series

Löw¹,

Prishchepov

Waldner

et al. 2018

Remote Sensing

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“…Water originating from snow melting in the mountains is provided to the lowland lakes by rivers, with upstream storage reservoirs used for agricultural irrigation. However, more than half of inland lakes have experienced significant decreases since 1975 [29], exacerbating serious environmental issues such as soil salinization, pollution of water sources [30], frequent drought, and land degradation [11].…”

Section: Study Areamentioning

confidence: 99%

Climate Contributions to Vegetation Variations in Central Asian Drylands: Pre- and Post-USSR Collapse

et al. 2015

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“…From a water management point of view, it is therefore a key point of interaction in the nexus between water, food, and energy. The history of drivers of irrigation area and intensity in Central Asia has been a focus of research attention, particularly in the Aral Sea basin [56,66]. Irrigation is essential because of the aridity of the area.…”

Section: Irrigationmentioning

confidence: 99%

Transferable Principles for Managing the Nexus: Lessons from Historical Global Water Modelling of Central Asia

Guillaume

Kummu

Eisner

et al. 2015

Water

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Abstract:The complex relationships within the water-energy-food security nexus tend to be place-specific, increasing the importance of identifying transferable principles to facilitate implementation of a nexus approach. This paper aims to contribute transferable principles by using global model data and concepts to illustrate and analyze the water history of Central Asia. This approach builds on extensive literature about Central Asia and global change as well as recent advances in global water modeling. Decadal water availability and sectorial water consumption time series are presented for the whole 20th century, along with monthly changes in discharge attributable to human influences. Concepts from resilience and socio-ecological system theory are used to interpret the results and identify five principles relevant to managing the transboundary nexus: (1) the subsystems included/excluded from the nexus are case-specific and should be consciously scrutinized; (2) consensus is needed on what boundaries can acceptably be crossed within the nexus; (3) there is a need to understand how reducing trade-offs will modify system dependencies; (4) global stakeholders have both a responsibility and right to contribute to the shaping of the nexus; (5) combining data with global and local perspectives can help to enhance transferability and understanding of shared problems in our globalized world.

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Irrigation expansion and dynamics of desertification in the Circum-Aral region of Central Asia

Cited by 160 publications

References 4 publications

Mapping Cropland Abandonment in the Aral Sea Basin with MODIS Time Series

Mapping Cropland Abandonment in the Aral Sea Basin with MODIS Time Series

Climate Contributions to Vegetation Variations in Central Asian Drylands: Pre- and Post-USSR Collapse

Transferable Principles for Managing the Nexus: Lessons from Historical Global Water Modelling of Central Asia

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