Exploring the multiscale hydrologic regulation of multipond systems in a humid agricultural catchment

The role of ponds in pesticide dissipation at the catchment scale: The case of the Save agricultural catchment (Southwestern France)

Pesticides are a major source of pollution for ecosystems. In agricultural catchments, ponds serve as buffer areas for pesticide transfers and biogeochemical hotspots for pesticide dissipation. Some studies have highlighted the specific impact of ponds on the dynamics of pesticides, but knowledge of their cumulative effect at the watershed scale is scarce. Hence, using a modelling approach, we assessed the cumulative role of ponds in pesticide transfer in an agricultural basin (Southwest of France, 1110 km2). The Soil and Water Assessment Tool (SWAT) model was used to model the Save basin, including 197 ponds selected with a Multi-Criteria Decision Aiding Model based on their pesticide interception capacities. The daily discharge, the suspended sediment loads and two herbicide loads (i.e. S-metolachlor and aclonifen) in dissolved and particulate phases were accurately simulated from January 2002 to July 2014 at a daily time step. The presence of ponds resulted in a yearly mean reduction at the watershed outlet of respectively 61 % and 42 % of aclonifen and S-metolachlor fluxes compared to the simulations in the absence of ponds. Sediment-related processes were the most efficient for pesticide dissipation, leading to a mean dissipation efficiency by ponds of 51.0 % for aclonifen and 34.4 % for S-metolachlor. This study provides a first quantification of the cumulative role of ponds in pesticide transfer at the catchment scale in an intensive agricultural catchment.

Assessing hydrological connectivity for natural-artificial catchment with a new framework integrating graph theory and network analysis

Anthropogenic activities alter the underlying surface conditions and arrangements of landscape features in a drainage basin, interfering with the pollutant (e.g., dissolved nitrogen, phosphorus) transport network configuration and altering the hydrological response. Assessing the impact of anthropogenic activities on hydrological connectivity for natural-artificial catchment is critical to understand the hydrological-driven ecosystem processes, services and biodiversity. However, quantifying this impact at catchment scale remains challenging. In this study, a new framework was proposed to quantify the impact of anthropogenic activities on hydrological connectivity combined with graph theory and network analysis. This framework was exemplified in a natural-artificial catchment of the Yangtze River basin of China. Based on remote sensing and field-investigated data, three transport networks were constructed, including natural transport network (N1), ditch-road transport network (N2), and terrace-dominated transport network (N3), which reflected the different human intervention. The results showed that human intervention improved the connectivity of the nodes and enhanced the complexity of the catchment transport network structure. Anthropogenic activities significantly decreased the hydrological structural connectivity of the catchment. In particular, compared with the N1 network, the critical nodes for hydrological connectivity which were judged by connectivity indexes were reduced by 92.94% and 95.29% in the N2 and N3 network, respectively. Furthermore, the ditch-road construction had a greater impact than terraces in decreasing hydrological structural connectivity at catchment scale. This framework has proven effective in quantifying the hydrological connectivity analysis under different human intervention at the catchment scale and facilitates the improvement of catchment management strategies.

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.

Exploratory Analysis on the Spatial Distribution and Influencing Factors of Beitang Landscape in the Shangzhuang Basin

Beitang landscape is a production system and land use pattern that ancient people created to adapt to droughts and floods during a long traditional farming culture. It has a critical reference meaning for water resource use and water systems protection in modern cities. Taking the Shangzhuang Basin (China) as an example, this study used multi-source data, such as remote sensing images, Beitang vector dataset, land-use dataset, elevation, slope, river, road, and field survey, to investigate the spatial distribution and influencing factors Beitang landscape. Results showed that in a typical small watershed basin, an area of ponds accounted for 1.0%, about 12 ponds per square kilometer—the average area of ponds is 814 m2, of which the vast majority is less than 1000 m2. The study found that the spatial distribution of Beitang in the Shangzhuang Basin has cluster characteristics, influenced by elevation, slope, aspect, river, roads, villages, farmland, woodland, and other factors, all of which have closely related to the natural environment development and human activities. The upstream, middle, and downstream of three Beitang landscapes were coordinated to support the Beitang landscape system in the small watershed of the basin. Findings provided a model for protecting and utilizing natural water systems in rural areas during the construction of sponge cities.

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

Understanding wetland water quality dynamics and associated influencing factors is important to assess the numerous ecosystem services they provide. We present a combined self-organizing map (SOM) and linear mixed-effects model (LMEM) to relate water quality variation of multipond systems (MPSs, a common type of non-floodplain wetlands in agricultural regions of southern China) to their extrinsic and intrinsic influences for the first time. Across the 6 test MPSs with environmental gradients, ammonium nitrogen (NH₄⁺-N), total nitrogen (TN), and total phosphate (TP) almost always exceeded the surface water quality standard (2.0, 2.0, and 0.4 mg/L, respectively) in the up- and midstream ponds, while chlorophyll-a (Chl-a) exhibited hypertrophic state (≥28 μg/L) in the midstream ponds during the wet season. Synergistic influences explained 69±12% and 73±10% of the water quality variations in the wet and dry season, respectively. The adverse, extrinsic influences were generally 1.4, 6.9, 3.2, and 4.3 times of the beneficial, intrinsic influences for NH₄⁺-N, nitrate nitrogen (NO₃^--N), TP, and potassium permanganate index (COD_Mn), respectively, although the influencing direction and degree of forest and water area proportion were spatiotemporally unstable. While COD_Mn was primarily linked with rural residential areas in the midstream, higher TN and TP concentrations in the up- and midstream were associated with agricultural land, and NH₄⁺-N reflected a small but non-negligible source of free-range poultry feeding. Pond surface sediments exhibited consistent, adverse effects with amplifications during rainfall, while macrophyte biomass can reflect the biological uptake of COD_Mn and Chl-a, especially in the mid- and downstream during the wet season. Our study advances nonpoint source pollution (NPSP) research for small water bodies, explores nutrient "source-sink" dynamics, and provides a timely guide for rural planning and pond management. The modelling procedures and analytical results can inform refined assessment of similar NFWs elsewhere, where restoration efforts are required.

The Role of Ponds in Pesticide Dissipation at the Agricultural Catchment Scale: A Critical Review

Ponds in agricultural areas are ubiquitous water retention systems acting as reactive biogeochemical hotspots controlling pesticide dissipation and transfer at the catchment scale. Several issues need to be addressed in order to understand, follow-up and predict the role of ponds in limiting pesticide transfer at the catchment scale. In this review, we present a critical overview of functional processes underpinning pesticide dissipation in ponds. We highlight the need to distinguish degradative and non-degradative processes and to understand the role of the sediment-water interface in pesticide dissipation. Yet it is not well-established how pesticide dissipation in ponds governs the pesticide transfer at the catchment scale under varying hydro-climatic conditions and agricultural operation practices. To illustrate the multi-scale and dynamic aspects of this issue, we sketch a modelling framework integrating the role of ponds at the catchment scale. Such an integrated framework can improve the spatial prediction of pesticide transfer and risk assessment across the catchment-ponds-river continuum to facilitate management rules and operations.