Yale CEO Syr-Darya / Chu Watershed  
 
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Information on River Basins

River Basin Data (IWMI)

World Water and
Climate Atlas (IWMI)

Central Asia
Regional Water Info Base

Watersheds of the World  

 

 

With more than 90% of the watershed being classified as dry-lands almost any agricultural activity depends on irrigation. Waters from the Syr-Darya River are intensively used for crop irrigation as well as for the generation of hydroelectric power. From its origin in the Tian Shan to the Aral Sea, its waters have been dammed in ten reservoirs with more under construction. Water withdrawal for agricultural use far exceeds domestic and industrial use (14% to 86% of total water withdrawal). The agricultural areas of the Ferghana Valley, the Syr-Darya Province and the river flood plain, are the main water consumers.

The mild climates in the Ferghana Valley and the Syr-Darya Province allow the growing of two crops per year. With most of the crops under irrigation, this is putting pressure on water- and soil-resources. Cotton, corn, and winter wheat are the dominant crops. Crop rotation is commonly practiced. Seeding and consequently crop peaking and harvesting, occurs over a time range of up to three months, triggering substantial shifts in growing cycles.

Different sources display the Syr-Darya Basin as covering slightly different areas. This is partly due to the quality of topographic data used for watershed delineation. In our study we included the Chu River (separated from the Syr-Darya in the south by the Khrebet Karatau) which strictly does not discharge into the Syr-Darya.

 

Data

National Climate
Data Center

SRTM (seamless data)

SRTM (individual tiles)

Global Surface Summary
of the Day

Khrebet Karatau Khrebet Nuratau Lake Aydarkul Lake Issykul Pamir Takla Makan Ferghana Valley Kara Kum Kyzyl Kum Peski Muyunkum Lake Balkash Aral Sea Tian Shan Tashkent Gulistan Dzhizak Shimkent Ferghana Andizhan Samarkhand Chardzhev Bukhara Karsi Dushanbe Dzhambul Bishkek Alamaty Kashi Osh Namangan Zezkazgan Kyzyl-Orda Kasachstan Steppe

 

 

Shaded relief map of the
Syr-Darya / Chu basin

Watershed and country boundaries. The watershed, as displayed, has a number of internal basins that do not discharge into the Aral Sea.

Move cursor over map for names of geographic locations and cities  

 

 

Umbet Naryn Dzhusaly Kyzyl Kum Dzhizak Tashkent Fergana

Mean Annual Total Precipitation

Mean annual precipitation, calculated from years 1994-2004, using daily station data from the GCOS Surface Network (GSN).

Click on marked locations for a graph of annual total precipitation.

 

 

Class 2 Class 4 Class 5 Class 6 Class 7 Class 8 Class 9 Class 10 Class 10 Class 10 Class 9 Class 1 Class 3 Class 1 Class 8

10-Day Mean Annual Temperature Classes

Unsupervised classification of the mean "10-day Temperature". The mean was calculated from years 1994-2004. 10-day gridded mean temperature layers (1km resolution) were aggregated and interpolated using daily station data from the GCOS Surface Network (GSN). The chosen number of classes is ten.

Click on map for "Class Mean Signatures" of mean, maximum, and minimum temperatures.

 

 

Variations in hue are indicative for different vegetation types or cropping cycles, variations in intensity indicate variations in vegetation coverage (dark colors representing low, bright colors high coverage).

 

Vegetation Cover

A color composite of the first three Fourier magnitudes (here calculated from a 36 NDVI layer stack) is an efficient way to reduce the information contained in cyclic NDVI data, making it suitable for visualization, while preserving most of the vegetation diagnostic details.

 Click on marked locations for examples of growing cycles (NDVI-cycles)
 

 

   

 

Trends in green biomass (NDVI)

The interpretation of green biomass trends needs to be done with care. An increasing or decreasing trend can have manifold causes and may indicate both improvement or deterioration. 

 

 

 

  1. In this region, trends, particularly those of natural vegetation covers, will be strongly influenced by inter-annual climate variations.

  2. Subtle human induced trends in green biomass, may not show without the removal of the climate signal (Evans and Geerken, 2005).

  3. Calculated trends for a specific period may be influenced by the climate situation at the end and at the beginning of that period.

  4. The length of the period an area is snow-covered, will have an impact, particularly on the accumulated NDVI.

  5. Switching from single cropping to double cropping is often accompanied by a decrease in the NDVImax, however, the total green biomass produced (NDVIacc) typically increases.

 

From the drop down boxes below maps can be displayed showing trends in annual total green biomass production (accumulated NDVI) or in annual green biomass maximum (maximum NDVI). Trends were calculated for various periods between 1982 and 2004.

Positive trends

 

Negative trends

 

 

 

 

Distinct trends

  1. Strongest trends, positive and negative, are mostly related to changes in agricultural activities.

  2. Positive biomass trends (82-01) in the Pamir Mts. may indicate an increasingly shorter period of snow-cover.

  3. Negative trends East and Northeast of Lake Aydarkul (82-01), falling into the agricultural area of the Syr-Darya province, are related to irrigation water shortages during summer and to a rapid deterioration of soils due to salinization.

  4. In contrast, positive trends along the Southern shore line of Lake Aydarkul (82-01), mostly coinciding with rangeland vegetation, suggest a slight improvement of the natural vegetation cover.