Distributed Estimation and Analysis of Precipitation Recharge Coefficient in Strongly-exploited Beijing Plain Area, China

The precipitation recharge coefficient(PRC), representing the amount of groundwater recharge from precipitation, is an important parameter for groundwater resources evaluation and numerical simulation. It was usually obtained from empirical knowledge and site experiments in the 1980 s. However, the environmental settings have been greatly modified from that time due to land use change and groundwater over-pumping, especially in the Beijing plain area(BPA). This paper aims to estimate and analyze PRC of BPA with the distributed hydrological model and GIS for the year 2011 with similar annual precipitation as long-term mean. It is found that the recharge from vertical(precipitation + irrigation) and precipitation is 291.0 mm/yr and 233.7 mm/yr, respectively, which accounts for 38.6% and 36.6% of corresponding input water. The regional mean PRC is 0.366, which is a little different from the traditional map. However, it has a spatial variation ranging from –7.0% to 17.5% for various sub-regions. Since the vadose zone is now much thicker than the evaporation extinction depth, the land cover is regarded as the major dynamic factor that causes the variation of PRC in this area due to the difference of evapotranspiration rates. It is suggested that the negative impact of reforestation on groundwater quantity within BPA should be well investigated, because the PRC beneath forestland is the smallest among all land cover types.

Integrating Smart Building Energy Data into Smart Grid Applications in the Intelligent Secondary Substations

Automation has arrived in the low voltage grid domain. In the next few years, the secondary substation—at the barriers of medium and low voltage grids—will thus be upgraded to enable novel functions. In this paper, we present various smart grid applications running on such intelligent secondary substations(iSSN) including their interaction with each other. We integrate energy consumption and production data, as well as forecasts, sensed from the smart buildings’ energy management systems(BEMSs) into the operation of the low voltage grid. A suitable framework for those modular applications includes features to initiate their installation, update, removal, the remote operator site, and not requiring staff on-site for such typical reappearing maintenance tasks.