Assessment of extrinsic and intrinsic influences on water quality variation in subtropical agricultural multipond systems

A new framework to model the distributed transfer and retention of nutrients by incorporating topology structure of small water bodies

Small water bodies such as interval water-flooded ditches, ponds, and streams serve as important nutrient sinks in many landscapes, especially in the multi-water continuum system. Yet watershed nutrient cycling models often fail to or insufficiently capture these waters, resulting in great uncertainty in quantifying the distributed transfer and retention of nutrients across diverse landscapes in a watershed. In this study, we present a network-based predictive framework of the nutrient transport process in nested small water bodies, which incorporates topology structure, hydrological and biogeochemical processes, and connectivity to perform a nonlinear and distributed scaling of nutrient transfer and retention. The framework was validated and applied to N transport in a multi-water continuum watershed in the Yangtze River basin. We show that the importance of N loading and retention depends on the spatial context of grid source and water bodies because of the great variation in location, connectivity, and water types. Our results demonstrate that hotspots in nutrient loading and retention could be accurately and efficiently identified through hierarchical network effects and spatial interactions. This offers an effective approach for the reduction of watershed-scale nutrient loads. This framework can be used in modeling to identify where and how to restore small water bodies for reduced non-point pollution from agricultural watersheds.

Spatiotemporal variation evaluation of water quality in middle and lower Han River, China

As the water source for the middle route of the South-to-North Water Transfer Project, the Han River in China plays a role of the world’s largest inter-basin water transfer project. However, this human-interfered area has suffered from over-standard pollution emission and water blooms in recent years, which necessitates urgent awareness at both national and provincial scales. To perform a comprehensive analysis of the water quality condition of this study area, we apply both the water quality index (WQI) and minimal WQI (WQI_min) methods to investigate the spatiotemporal variation characteristics of water quality. The results show that 8 parameters consisting of permanganate index (PI), chemical oxygen demand (COD), total phosphorus (TP), fluoride (F-), arsenic (As), plumbum (Pb), copper (Cu), and zinc (Zn) have significant discrepancy in spatial scales, and the study basin also has a seasonal variation pattern with the lowest WQI values in summer and autumn. Moreover, compared to the traditional WQI, the WQI_min model, with the assistance of stepwise linear regression analysis, could exhibit more accurate explanation with the coefficient of determination (R²) and percentage error (PE) values being 0.895 and 5.515%, respectively. The proposed framework is of great importance to improve the spatiotemporal recognition of water quality patterns and further helps develop efficient water management strategies at a reduced cost.