Modeling the Vakhsh Cascade in the Amu Darya River Basin – Implementing Future Storage Facilities in a Hydrological Model for Impact Assessment

Abstract:

In the Amu Darya River Basin in Central Asia, the Vakhsh catchment in Tajikistan is a major source of hydropower energy for the country. With a number of large dams already constructed, upstream Tajikistan is interested in the construction of one more large dam and a number of smaller storage facilities with the prospect of supplying its neighboring states with hydropower through a newly planned power grid. The impact of new storage facilities along the river is difficult to estimate and causes considerable concern and consternation among the downstream users. Today, it is one of the vexing poster child studies in international water conflict that awaits resolution.

With a lack of meteorological data and a complex topography that makes application of remote sensed data difficult it is a challenge to model runoff correctly. Large parts of the catchment is glacierized and ranges from just 500 m asl to peaks above 7000 m asl. Based on in-situ time series for temperature and precipitation we find local correction factors for remote sensed products. Using this data we employ a model based on the Budyko framework with an extension for snow and ice in the higher altitude bands. The model furthermore accounts for groundwater and soil storage. Runoff data from a number of stations are used for the calibration of the model parameters.

With an accurate representation of the existing and planned reservoirs in the Vakhsh cascade we study the potential impacts from the construction of the new large reservoir in the river. Impacts are measured in terms of a) the timing and availability of new hydropower energy, also in light of its potential for export to South Asia, b) shifting challenges with regard to river sediment loads and siltation of reservoirs and c) impacts on downstream runoff and the timely availability of irrigation water there.

With our coupled hydro-climatological approach, the challenges of optimal cascade management can be addressed so as to minimize detrimental impacts on all sides if runoff forecast information at seasonal scales is taken into account for optimal operational multi-storage management.