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Seasonal forecasting of water resources in the aral sea basin

English title Seasonal forecasting of water resources in the aral sea basin
Applicant Schär Christoph
Number 101957
Funding scheme Project funding (Div. I-III)
Research institution Institut für Atmosphäre und Klima ETH Zürich
Institution of higher education ETH Zurich - ETHZ
Main discipline Climatology. Atmospherical Chemistry, Aeronomy
Start/End 01.12.2003 - 31.10.2007
Approved amount 191'158.00
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Keywords (6)

Atmospheric data assimilation; Seasonal forecasting; Climate variability; Runoff forecasting; Water resources; Mountain meteorology

Lay Summary (English)

Lead
Lay summary
In semi-arid mountainous regions, runoff from snowmelt represents the dominant contribution to river flow and freshwater supply during the summer season. Real-time knowledge of winter snow accumulation thus provides a solid basis for seasonal runoff forecasting. In the current project, related aspects have been investigated for the Aral Sea basin. The major rivers in this basin, the Syrdarya and Amudarya, have their source region in the high mountains of the Tian Shan, Pamir and Hindukush. The economy and ecology of the Central Asian region heavily relies on the two rivers, and the exploitation of this precious but limited resource has led to the dramatic desiccation of the Aral Sea. In a heavily overused system such as the Aral Sea basin, appropriate seasonal forecasting (lead time up to a few months) is particularly important, in order to optimize the complex water management tasks. The main challenge to seasonal forecasting in the Aral Sea basin is the estimation of winter and spring snow accumulation. In an area of approximately 500,000 km2, covered by highly rugged mountainous terrain, there are a mere 30 real-time precipitation stations. This station density is far too low to support a reliable estimate of snow water equivalent in the runoff formation region.

In response to this challenge, we have developed a seasonal runoff forecasting system for Central Asia and tested a number of precipitation data sets for estimating winter snow accumulation: (i) conventional rain-gauge data and derived precipitation analyses, (ii) the ERA-40 meteorological reanalysis data (available for the time period 1958-2001 at low spatial resolution), (iii) the ECMWF operational analysis (available in real time at high spatial resolution since 2002), and (iv) output from an extended analysis-driven regional climate model simulation covering the period since 1958. Some of these data sets are available in real time (e.g. the meteorological analyses), others can be made available in real time with comparatively small extra efforts (e.g. the regional climate simulation). The different precipitation data sets have been tested in multivariate statistical forecasting approaches. Results demonstrate that the resulting seasonal runoff forecasts are generally of high quality, albeit the quality of the forecasts strongly depends on the size of the river basin considered.

In addition to the forecast-oriented research tasks described above, we have investigated the processes that control interannual climate variations in Central Asia. This includes a detailed analysis of past precipitation observations, an assessment of the relationship between the Indian summer monsoon and the Central Asian precipitation climate, and a diagnostic study assessing the seasonality and interannual variability of the westerly jet over the Tibetan-Plateau. Results demonstrate a complex sequence of mechanisms that entails both tropical (i.e. monsoon) and extratropical (i.e. westerly jet) influences.
Direct link to Lay Summary Last update: 21.02.2013

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