The Romanian Ecological Flow Method, RoEflow, Developed in Line with the EU Water Framework Directive. Concept and Case Studies

The overall purpose of the research is to develop a method to compute ecological flows in line with the EU Water Framework Directive (Directive 2000/60/EC) for the whole Romanian territory, for a variety of hydrological, morphological and ecological conditions. The method has three components: a Quantity component, a Dynamic component, and a Real-time operation component. The Quantity component is a hydrological method with elements of the aquatic fauna habitat indirectly linked to biological organisms based on the current Romanian knowledge on the linkages between hydrology and aquatic biology. The Dynamic and Real-time operation components are related to the hydrological forecast. The method is practical, robust and easy to apply. The concept and the ideas use the hydrological forecast to ensure the water dynamics required by the Water Framework Directive, and to develop the quantitative component, keeping in mind that putting it into practice might have importance for a broader audience. In order to better highlight the concept, the paper shows three practical examples of the RoEflow method’s application.

Seasonal to sub-seasonal hydrological forecast in Central Asia to improve water management and mitigate hydrometeorological risks

<p>Central Asia is facing a water shortage due to the negative impacts of climate change and demographic development. Water resources in this region originate mainly in the mountains of Pamir and Tian-Shan due to snow-and glacier melt. However, a limited observation network is available in these mountain systems and many are malfunctioning. Thus, the region needs new innovative methods to forecast seasonal and sub-seasonal water availability to ensure better water resources management and mitigate hydro-meteorological risks.</p><p>In this study, we present the results of our efforts for many years to develop a forecasting tool and implementation in the region. Since the region has limited observed meteorological data, we use primarily remote sensing data on snow cover for this purpose. We apply the MODIS snow cover data that is processed, including cloud removal, using the MODSNOW-Tool. We have applied this tool, which can be used to monitor snow cover in an operational mode and forecast water availability for the vegetation period but also for the monthly scale using the multiple linear regression method.</p><p>Our results show that snow is important in most of the river basins and can also be used as a single predictor to forecast seasonal water availability. Especially, in remote areas with limited observations, this approach gives a possibility of forecasting water availability for different time period. Besides seasonal hydrological forecast, the MODSNOW-Tool was also used to forecast water availability for upcoming months. The validity of forecasts were tested against observed discharge for the last 20 years and mostly above 70 % verification was achieved. Additionally to remote sensing based snow cover data, observed meteorological information was also used as predictors and improved the validity of forecast models in some river basins.</p><p>The implementation of the MODSNOW-Tool to improve the hydrological forecast was done for 28 river basins in Central Asia that are located in the territories of five post-Soviet countries Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan and Uzbekistan.  The MODSNOW-Tool was also implemented at the National Hydrometeorological Services (NHMS) of each post-Soviet country.</p>