Background: Cadmium (Cd) pollution poses a threat to human health. Examination of the spatial distribution of Cd in soils can be used to assess the risks posed to humans and the environment. Objective: This study determined the enrichment rules and factors influencing Cd pollution in Nansha, and evaluated the pollution characteristics and bioavailability of Cd in quaternary sediments through 7 deep soil profiles (0–200 cm), 4 boreholes, and 348 topsoil (0–20 cm) samples. Methods: The geo-accumulation index (Igeo) and the potential ecological risk index (Er) were used to assess ecological risk, and bioavailability was determined using multivariate, spatial distribution, and correlation matrix analyses. Results: From the Er, 52% of Nansha was classed as being at very high risk of Cd pollution; a further 36% was classed as dangerous. Cadmium was more abundant in clay soils than in sandy soils. Bioavailable Cd in quaternary sediments was significantly affected by the total Cd, and labile Cd accounted for more than half of the total Cd. Changes in pH mainly affected bioavailable Cd rather than total Cd, affecting the overall bioavailability of Cd. Conclusions: Nansha soils are commonly and seriously contaminated with Cd. An appropriate remediation treatment approach should be used to reduce Cd bioavailability. Furthermore, planting structures in farmland should be adjusted to avoid the impact of heavy metals on human health.

Karst watersheds are often treated as non-karst watersheds that can lead to several hazards. Hence, how do karst watersheds differ from non-karst watersheds and what are the effects of karstification on groundwater availability and quality? In this study, we contrast between a karst and non-karst watershed by elucidating their geomorphological peculiarities and potential impact on spatio-temporal availability and quality of groundwater. GIS morphometric mapping and hydrograph recession analysis are applied to map the watershed features and estimate hydrograph recession coefficient to define the groundwater drainage characteristics as well as the influence of karst drainage attributes (KDA). Furthermore, we characterize streamflow components based on the hydrograph recession limbs (segments) and infer their contributing geomorphological factors. Results show that the karst watershed has higher recession coefficients for successive recession limbs. Consequently, it drains larger volumes of groundwater primarily due to the KDAs, which transmit interflow and groundwater flow more rapidly through large cavities to springs as well as stream channels. The KDAs generate what we term karst drainage flow (KDF), defined by the second recession limb which has high recession coefficient as the first limb (overland flow) and strongly contrasts with the non-karst watershed from visual and ANOVA analysis. The effect is that karst aquifer yield over time is significantly lower and highly exposed to pollution compared to the non-karst aquifer. Consequently, sustainable water management practices should be adopted to ensure the availability and safety of groundwater reserves.

Solute storage and release in groundwater are key processes in solute transport for groundwater remediation and protection. In karst areas where concentrated recharge conditions exist, pollution incidents can easily occur in springs that are hydraulically connected to densely inhabited karst depressions. The intrinsic heterogeneity common in karst media makes modeling solute transport very difficult with great uncertainty. Meanwhile, it is noteworthy that solute storage and release within subsurface conduits and fissures exhibit strong controlling function on pollutant attenuation during underground floods. Consequently, in this paper, we identified and estimated the solute storage and release processes in karst water systems under concentrated recharge conditions. The methodology uses the advection–dispersion method and field tracer tests to characterize solute transport in different flow paths. Two solute transport pathways were established (i.e., linear pathway (direct transport through karst conduits) and dynamic pathway (flow through fissures)). Advection–dispersion equations were used to fit the breakthrough curves in conduit flow, while the volume of solute storage in fissures were calculated by segmenting the best fitting curves from the total breakthrough curves. The results show that, greater recharge flow or stronger dynamic conditions leads to lower solute storage rate, with the storage rate values less than 10% at high water level conditions. In addition, longer residence time was recorded for solute exchange between conduits and fissures at the low water level condition, thereby contributing to a higher solute storage rate of 26% in the dynamic pathway.