Evaluation of drought propagations with multiple indices in the Yangtze River basin.

This paper explored the drought propagation phenomenon based on meteorological, hydrological, and agricultural aspects in the Yangtze River basin (YRB), China. To evaluate meteorological, hydrological, and agricultural droughts, this paper used three drought indices, standardized precipitation evapotranspiration index (SPEI), standardized runoff index (SRI), and standardized soil moisture index (SSMI), respectively. The community land model (CLM) in the YRB to generate the monthly evapotranspiration, soil moisture, runoff data, which are required for the estimation of drought index, were applied. Different mean durations (6-and 12-month) were used for drought estimation, and propagations of meteorological to hydrological and meteorological and agricultural droughts were investigated for different durations as SPEI6-SRI6, SPEI6-SSMI6, SPEI12-SRI12, SPEI12-SSMI12. The average drought propagation between 1950 and 2010 presented the highest autocorrelation and correlation with one-month lags in four combinations of drought indices in SPEI6-SRI6, SPEI6-SSMI6, SPEI12-SRI12, and SPEI12-SSMI12. Additionally, this paper estimated the optimal lags of SPEI-SRI and SPEI-SSMI drought propagations using mean 6-and 12-month lag times for six representative drought periods. Therefore, the propagation phenomenon of meteorological to hydrological and to agricultural droughts were confirmed in the YRB.

Insights into the Pollutant Removal Performance of Stormwater Green Infrastructures: A Case Study of Detention Basins and Retention Ponds.

The quality of water has deteriorated due to urbanization and the occurrence of urban stormwater runoff. To solve this problem, this study investigated the pollutant reduction effects from the geometric and hydrological factors of green infrastructures (GIs) to more accurately design GI models, and evaluated the factors that are required for such a design. Among several GIs, detention basins and retention ponds were evaluated. This study chose the inflow, outflow, total suspended solids (TSS), total phosphorus (TP), watershed area, GI area (bottom area in detention basins and permanent pool surface area in retention ponds), and GI volume (in both detention basins and retention ponds) for analysis and applied both ordinary least squares (OLS) regression and multiple linear regression (MLR). The geometric factors do not vary within each GI, but there may be a bias due to the number of stormwater events. To solve this problem, three methods that involved randomly extracting data with a certain range and excluding outliers were applied to the models. The accuracies of these OLS and MLR models were analyzed through the percentage bias (PBIAS), Nash-Sutcliffe efficiency (NSE), and RMSE-observations standard deviation ratio (RSR). The results of this study suggest that models which consider the influent concentration combined with the hydrological and GI geometric parameters have better correlations than models that consider only a single parameter.