Source-sink relationships of anthropogenic metal(loid)s from urban catchment to waterway in relation to spatial pattern of urban green infrastructures.

Surface sediment in urban waterways originates from fine topsoil particles within catchments via surface erosion, often bonded with non-degradable metal(loid)s. This study posited that urban green infrastructures (UGIs) can influence anthropogenic metal(loid) transport from catchment topsoil to waterway sediment by retaining moveable particles. In multiply channeled downtown Suzhou, China, UGIs' spatial patterns were examined in relations to metal(loid)s source (catchment topsoil) - sink (waterway surface sediment) dynamics. Anthropogenic metal(loid)s - As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn - were spatially quantified in sediment at 144 waterway points and in topsoil at 154 UGIs' points across 7 subwatersheds. Integrated metal(loid) loads revealed significantly higher sediment loads (except for As) than topsoil, varying with element specificity and spatial unmatching across the subwatersheds. Loads of metal(loid)s in topsoil showed no significant differences among UGI types, but sediment loads of As, Cr, and Ni correlated positively with topsoil loads in roadside and public facility UGIs within 100 m- and 200 m-wide riparian buffer zones. However, waterfront UGIs negatively impacted on these correlations for Cr, Hg, and Ni loads within the riparian buffer zones. These findings highlight metal(loid) specificity and UGIs' spatial pattern effects on anthropogenic metal(loid) loads between catchment topsoil (source) and waterway surface sediment (sink), offering valuable guidelines for UGIs' design and implementation.

Can flood resilience of green-grey-blue system cope with future uncertainty?

Urban flooding is becoming a great global concern due to growing cities, while climate change and urbanization may pose daunting challenges to both environment and humans. The integrated green-grey-blue (IGGB) system has gained interests worldwide to mitigate flood issues, however, how IGGB system acts in urban flood resilience and whether it can address future uncertainties have not been fully understood. In this study, a new framework, which combined an evaluation index system and coupling model, was constructed to quantify urban flood resilience (FR) and its responses to future uncertainties. The results showed that higher FR upstream than downstream; however, upstream FR declined approximately twice as much as downstream when faced with climate change and urbanization. Generally, climate change appeared to have a greater impact on urban flood resilience than urbanization, resulting to 3.20%-4.28% and 2.08%-4.09% FR reduction, respectively. The IGGB system could greatly improve robustness against future uncertainty, due to the fact that the IGGB without low impact development facilities (LIDs) was about 2 times in FR decline compared with IGGB with LIDs. The increase of LIDs proportion could diminish the impact of climate change, which shifted the dominant factor affecting FR from the interaction between urbanization and climate change to urbanization. Notably, a threshold of 13% construction land increase was quantified, beyond which negative effects of rainfall become dominant again. The results could guide IGGB design and urban flooding management in other similar regions.

Spatiotemporal variations in the soil quality of agricultural land and its drivers in China from 1980 to 2018.

Soil quality is essential for maintaining the sustainability of agroecosystems, especially under intensified agricultural activities and rapid land use change. The sampling and analysis of soil properties to assess the status of agricultural land is widely practiced at the field scale; however, the spatiotemporal variations in soil quality and its influencing factors at a large scale remain unclear. Here, we quantified spatiotemporal variations in the soil quality of agricultural land in China during 1980-2018 by using the soil quality index (SQI) area approach, and explored the drivers with a geographical detector method. The results showed that the distribution of the SQI in the two periods had a similar spatial trend, except for that in the southwest (SWC), and the SQI decreased from north to south regardless of land use type. The soil quality of woodland was comparatively good with mean SQI values of 1.55 and 1.53 in 1980 and 2018, respectively, followed by that in grassland and cropland. Soil organic carbon, total nitrogen and cation exchange capacity were the dominant soil indicators explaining the spatial heterogeneity of the SQI in all land uses; moreover, climatic factors (i.e., temperature and precipitation) showed a stronger effect on woodland. From 1980 to 2018, the SQI of grassland decreased deeply, especially in the SWC, which showed a severe decline of 12.5 %. The changes in precipitation and temperature were identified as the largest drivers of SQI temporal changes in woodland and grassland, respectively, and their interaction achieved the highest impact across all land uses. In addition, the bidirectional conversion between cropland and grassland in recent decades has aggravated the deterioration of soil quality. Therefore, quantifying spatiotemporal changes in the SQI and elucidating the role of factors influencing soil quality in agroecosystems can provide a guide for designing sustainable agriculture policies and improving environmental quality.

Spatial effects of urban green infrastructure on instream water quality assessed by chemical and sensory indicators.

Urban green infrastructure has been simulated effectively and economically to reduce volume and pollutants of stormwater runoffs but its spatial effects remain unclear. A snap sampling campaign was carried out for surface water quality in the downtown waterway network of a pilot sponge city (Suzhou) in China, dividing into 7 subwatersheds according to the digital elevation map. In total, 144 sampling points were investigated and measured for chemical quality of surface water while 68 out of the sampling points had a sensory evaluation questionnaire interview for water quality with 321 respondents, in whom the native residents scored a significant spatiality of water quality. The downtown waterway network had phosphorus-limited eutrophic surface water with total nitrogen worse than Class V of the national guidelines. Chemical and sensory evaluation indexes of surface water quality had significant spatial consistency (p < 0.001). All types of green spaces (%) in subwatershed, especially along the urban waterway network (waterfront) and roadside, and in the 100 m riparian buffer zone, significantly influenced nutrient loads in surface water. Findings of the present study suggest that the 100 m riparian buffer zone would be priority areas and the waterfront and roadside should be the highly efficient spots for planning strategy on urban green infrastructure implementation to reduce nutrient loads in surface water and to improve urban landscape aesthetics.

Incorporating receiving waters responses into the framework of spatial optimization of LID-BMPs in plain river network region.

Deep insights into the receiving waters responses to optimal spatial allocation of LID-BMPs are considered extremely important. This study addressed the urgent need to incorporate receiving waters responses into the spatial allocation optimization of LID-BMPs and demonstrated the efficiency of the approach to guide watershed management. The integration of an overland-river coupling model and the NSGA-III algorithm resulted in the proposal of a general simulation-optimization framework for the optimal layout of LID-BMPs. The coupled model was swapped out for the surrogates to increase computational efficiency. When 40.71%, 36.06%, and 61.80% reductions in runoff volume, flood volume, and TP concentration are achieved, the newly proposed framework can save 34.44% and 16.31% cost compared to the approach that does not consider receiving waters responses and refined spatial allocation, respectively. Results indicate that the incorporation of receiving waters responses and refined spatial allocation are essential for the optimal design of LID-BMPs. This new framework offers the potential for more cost-effective high-cost solutions. The results of spatial optimization are significantly influenced by imperviousness.