Landscape patterns of catchment and land-use regulate legacy phosphorus releases in subtropical mixed agricultural and woodland catchments

Influence of climate and land use on watershed anthropogenic phosphorus inputs and riverine phosphorus export dynamics: A global analysis

Many studies have found predictive relationships between riverine phosphorus (P) export and net anthropogenic P inputs (NAPI) at the watershed scale, but the global or regional extent of these relationships has not been empirically quantified. Herein, we present a data-driven global assessment of the response of riverine total P (TP) fluxes to NAPI based on 358 watersheds. NAPI exhibited high spatial heterogeneity (2-12,085 kg P km-2 yr-1) and was well correlated with riverine TP fluxes. Riverine TP export fractions of NAPI were primarily regulated by NAPI components, hydroclimate factors, and land-use as determined through a random-forest meta-analysis. In watersheds dominated by disturbed land-use (e.g., agricultural and developed lands), runoff emerged as pivotal climate-related factors influencing riverine export fractions of NAPI. In watersheds dominated by natural land-use, runoff, precipitation and temperature were identified as the most critical factors. We developed a mixed-effects meta-regression model (R2 = 0.63-0.70, RMSE = 19-78 %, n = 87-202) to examine the quantitative relationship between riverine TP fluxes and NAPI, which avoids subjectivity in selecting influencing factors and regression forms. The model estimated that legacy P contributed 14-17 % of annual riverine TP fluxes in Chinese watersheds, 25 % in North American watersheds and 11-27 % in European watersheds. Annual NAPI contributions to annual riverine TP flux were 83-86 % in China, 75 % in North America and 73-89 % in Europe. The model forecasted 52-67 %, 69-71 % and 74-77 % reductions in riverine TP fluxes across Chinese, North American, and European watersheds by 2050 under five shared socio-economic pathway scenarios compared to 2010 baseline conditions, respectively. This study provides a straightforward and reliable method for quantifying anthropogenic P input and riverine P export dynamics within an acceptable error range. It provides guidance for developing phosphorus pollution control strategies to counter potential increases in phosphorus inputs due to expected changes in climate and land use.

Legacy phosphorus delays the accomplishment of expected phosphorus management object

Legacy phosphorus (P) in watersheds continuously affects the water quality. The time lag between anthropogenic P input and algal bloom has made P dynamics prediction in aquatic ecosystems more challenging. Whether the legacy P in the Yangtze River Watershed (YRW) exceeds its storage threshold remains unknown, and the continuous impact of legacy P on the water quality has not been analyzed. This study aimed to evaluate variation trends (1970-2018) and influencing factors for accumulated P in the YRW under different economic development periods, quantitatively identify the watershed P storage threshold based on the two split line models and estimate the time required for the return of legacy P to the baseline level using an exponential decay process. The results showed that the P storage threshold of the YRW was surpassed due to intense anthropogenic activities, and the residual P still had an impact on aquatic ecosystems for a long time. The dissolved total P loadings may become the top priority to achieve better P management goals. The time lags for the legacy P restoration would require for about 1000 years to be exhausted. The legacy P in the YRW would continuously undermine the restoration efforts of the water quality. The combined effects of watershed P surplus reductions and depletion of residual P may become essential to better manage P in the future. We still need to strengthen our efforts to make soil legacy P more absorbed by crops and improve sewage treatment capacity to achieve sustainable development of YRW.

Effects of comprehensive landscape patterns on water quality and identification of key metrics thresholds causing its abrupt changes

Comprehensive landscape patterns influence water quality with multiple factors, complex processes, and scale dependence. However, studies identifying landscape thresholds causing abrupt water quality changes and characterizing the contribution of topography to water quality are still limited. Exploring the impact mechanisms of natural geographical and landscape characteristics on spatial and seasonal water quality variations is conducive to watershed water resource protection and ecosystem restoration. Based on water quality monitoring data of Minjiahe River in the typical headwater area of the upstream Dan River in China from 2019 to 2021, we employed redundancy analysis, partial redundancy analysis, and nonparametric change-point analysis to analyze the relationship between stream water quality and multi-spatial scale comprehensive landscape patterns, to obtain the interactive and independent contributions of different landscape categories at multi-spatial scales on water quality, and to find the key landscape threshold leading to abrupt changes in water quality. Results showed that landscape configuration, landscape composition, and topographic factors collectively explain over 89.1% of water quality variation. Most seasonal variations in water quality were primarily caused by landscape configuration. The landscape composition was mainly responsible for the differences in water quality variations among spatial scales. The topographic factors made the least independent contribution and had a potential impact on overall water quality variation. In order to protect the water quality of streams, it is more reasonable to regulate the landscape at different scales. At the sub-catchment scale, interspersion and juxtaposition index (IJI) and landscape shape index (LSI) should be controlled below 82% and 22. At the 100 m riparian scale, farmland, urban land, IJI, and LSI should be controlled below 29%, 6.5%, 92%, and 26, respectively. Our results provide important guidance for optimizing landscape patterns and water conservation in the watershed.

A raster-based estimation of watershed phosphorus load and its impacts on surrounding rivers based on process-based modelling

Quantifying phosphorus (P) load from watersheds at a fine scale is crucial for studying P sources in lake or river ecosystems; however, it is particularly challenging for mountain-lowland mixed watersheds. To address this challenge, we proposed a framework to estimate the P load at the grid scale and assessed its risk to surrounding rivers in a typical mountain-lowland mixed watershed (Huxi Region in Lake Taihu Basin, China). The framework coupled three models: the Phosphorus Dynamic model for lowland Polder systems (PDP), the Soil and Water Assessment Tool (SWAT), and the Export Coefficient Model (ECM). The coupled model performed satisfactory for both hydrological and water quality variables (Nash-Sutcliffe efficiency >0.5). Our modelling practice revealed that polder, non-polder, and mountainous areas had P load of 211.4, 437.2, and 149.9 t yr^-1, respectively. P load intensity in lowlands and mountains was 1.75 and 0.60 kg ha^-1 yr^-1, respectively. A higher P load intensity (>3 kg ha^-1 yr^-1) was mainly observed in the non-polder area. In lowland areas, irrigated cropland, aquaculture ponds and impervious surfaces contributed 36.7%, 24.8%, and 25.8% of the P load, respectively. In mountainous areas, irrigated croplands, aquaculture ponds, and impervious surfaces contributed 28.6%, 27.0%, and 16.4% of the P load, respectively. Rivers with relatively high P load risks were mainly observed around big cities during rice season, owing to a large contribution of P load from the non-point source pollution of urban and agricultural activities. This study demonstrated a raster-based estimation of watershed P load and their impacts on surrounding rivers using coupled process-based models. It would be useful to identify the hotspots and hot moments of P load at the grid scale.

Legacy contributions to diffuse water pollution: Data-driven multi-catchment quantification for nutrients and carbon

Legacy pollutants are increasingly proposed as possible reasons for widespread failures to improve water quality, despite the implementation of stricter regulations and mitigation measures. This study investigates this possibility, using multi-catchment data and relatively simple, yet mechanistically-based, source distinction relationships between water discharges and chemical concentrations and loads. The relationships are tested and supported by the available catchment data. They show dominant legacy contributions for total nitrogen (TN), total phosphorus (TP) and total organic carbon (TOC) across catchment locations and scales, from local to country-wide around Sweden. Consistently across the study catchments, close relationships are found between the legacy concentrations of TN and TOC and the land shares of agriculture and of the sum of agriculture and forests, respectively. The legacy distinction and quantification capabilities provided by the data-driven approach of this study could guide more effective pollution mitigation and should be tested in further research for other chemicals and various sites around the world.

Sources and migration similarly determine nitrate concentrations: Integrating isotopic, landscape, and biological approaches

Rapid land use change has significantly increased nitrate (NO₃^-) loading to rivers, leading to eutrophication, and posing water security problems. Determining the sources of NO₃^- to waters and the underlying influential factors is critical for effectively reducing pollution and better managing water resources. Here, we identified the sources and influencing mechanisms of NO₃^- in a mixed land-use watershed by integrating stable isotopes (δ¹⁵N-NO₃^- and δ¹⁸O-NO₃^-), molecular biology, water chemistry, and landscape metrics measurements. Weak transformation processes of NO₃^- were identified in the river, as evinced by water chemistry, isotopes, species compositions, and predicted microbial genes related to nitrogen metabolism. NO₃^- concentrations were primarily influenced by exogenous inputs (i.e., from soil nitrogen (NS), nitrogen fertilizer (NF), and manure & sewage (MS)). The proportions of NO₃^- sources seasonally varied. In the wet season, the source contributions followed the order of NS (38.6 %) > NF (31.4 %) > atmospheric deposition (ND, 16.2 %) > MS (13.8 %). In the dry season, the contributions were in the order of MS (39.2 %) > NS (29.2 %) > NF (29 %) > ND (2.6 %). Farmland and construction land were the original factors influencing the spatial distribution of NO₃^- in the wet and dry seasons, respectively, while slope, basin relief (HD), hypsometric integral (HI), and COHESION, HD were the primary indicators associated with NO₃^- transport in the wet and dry seasons, respectively. Additionally, spatial scale differences were observed for the effects of landscape structure on NO₃^- concentrations, with the greatest effect at the 1000-m buffer zone scale in the wet season and at the sub-basin scale in the dry season. This study overcomes the limitation of isotopes in identifying nitrate sources by combining multiple approaches and provides new research perspectives for the determination of nitrate sources and migration in other watersheds.

Influence path identification of topography, soil, hydrology and landscape on phosphorus buffering capacity in typical agricultural catchments in central subtropical China

The catchment phosphorus buffering capacity (PBF) determines the pressure-state-response relationship between anthropogenic P inputs and aquatic ecosystems at a catchment scale, and is affected by biogeochemical, hydrological, and ecological catchment characteristics. However, the complex relationship between these catchment characteristic factors and their impact pathways on PBF remains ambiguous, leading to large uncertainty in balancing agricultural productivity and water conservation via improving BF through management practices. In this study, the short-term buffering index, calculated from net anthropogenic P input and riverine P exports, was used to quantify the spatiotemporal variations in PBF in source agricultural catchments in the Dongting Lake basin. Partial least squares structural equation modeling was used to investigate the relationship between the PBF and the catchment characteristics. The results indicate that catchment PBF was directly determined by soil properties and hydrological conditions, while landscape patterns significantly mediated the effects of topography on soil and hydrology. Considering the pathway preferences of the model, landscape patterns could be the priority for characterizing and regulating PBF. According to a change-point analysis, the probability of PBF weakening increases dramatically when the proportion of farmland (Farm%) > 24.6%, degree of patch interspersion (Contagion index) < 64.5%, and Perimeter-Area Ratio Distribution (PARA) > 348.7. These findings provide new insights into catchment buffering mechanisms and can be used to promote the simultaneous achievement of agricultural production and environmental conservation goals.