Simulation of sponge city landscape pattern optimization based on the storm water management model (SWMM).

With the rapid urbanization and increasing urban impervious areas in China, urban water-logging has become increasingly serious. The concept of sponge city was proposed based on the low impact development (LID) idea. We analyzed the impacts of landscape pattern optimization scenario on urban surface runoff and rainwater control ability in central urban area of Shen-Fu New Town in Liaoning Province. The storm intensity formula was used to construct rainfall process in different return periods. The landscape patterns of the study area were optimized based on sponge city concept. The storm water management model (SWMM) was used to simulate the differences of surface runoff and rainwater regulation ability under the pre-planning scenario and the landscape pattern optimization scenario. The results showed that total runoff and runoff coefficient of the study area were increased with increasing rainfall return period. In the same rainfall return period, the runoff coefficient was significantly reduced. The reduction of total runoff gradually increased, being 2.94, 3.58, 3.72, and 4.19 mm during the 1-year, 3-year, 5-year and 50-year return period under landscape pattern optimization scenario. The corresponding reduction rate was gradually reduced, being 23.9%, 16.4%, 14.3%, and 9.3%, respectively. Landscape pattern optimization scenario could meet the requirements that the rainfall was controlled at 20.8 mm when the rainfall return period p=1 year, the rainwater pipe network would not overload when p=3 years, and the river channel would not overflow when p=50 years.

[Carbon footprint of buildings in the urban agglomeration of central Liaoning, China]. / 辽宁中部城市群建筑碳足迹.

With the development of urbanization in China, buildings consumed lots of material and energy. How to estimate carbon emission of buildings is an important scientific problem. Carbon footprint of the central Liaoning agglomeration was studied with carbon footprint approach, geographic information system (GIS) and high-resolution remote sensing (HRRS) technology. The results showed that the construction carbon footprint coefficient of central Liaoning urban agglomeration was 269.16 kg·m-2. The approach of interpreting total building area and spatial distribution with HRRS was effective, and the accuracy was 89%. The extraction approach was critical for total carbon footprint and spatial distribution estimation. The building area and total carbon footprint of central Liaoning urban agglomeration in descending order was Shenyang, Anshan, Fushun, Liao-yang, Yingkou, Tieling and Benxi. The annual average increment of footprint from 2011 to 2013 in descending order was Shenyang, Benxi, Fushun, Anshan, Tieling, Yingkou and Liaoyang. The accurate estimation of construction carbon footprint spatial and its distribution was of significance for the planning and optimization of carbon emission reduction.