Multi-site and long-term estimation of phosphorus dynamics for paddy surface water in China based on new MLEpaddy-P.

Paddy surface water serves as the primary source of artificial drainage and rainfall runoff leading to phosphorus (P) loss from paddy fields. The quantification of P dynamics in paddy surface water on a large scale is challenging due to the spatiotemporal heterogeneity of influencing factors and the limitations of field measurements. Based on 1226 data sets from 33 field sites covering the three main rice-growing regions of China (the Southeast Coast, the Yangtze River Basin, and the Northeast Plain), we analyzed the spatiotemporal characteristics of P attenuation in paddy surface water and its influencing factors. A new multi-site and long-term phosphorus estimation model for paddy (MLEpaddy-P) was proposed to evaluate the total phosphorus (TP) dynamics at national scale by improving the initial concentration (C0) and attenuation coefficient (k) of the first-order kinetic model (Ct=C0∙e-k(t-1)). Our study showed that: (1) Fertilizer amounts, soil organic matter content, soil Olsen-P content, soil pH, and soil total phosphorus are the primary factors affecting the variation of C0 and k; (2) Yangtze River Basin possessed the highest C0 (6.87 ± 12.97 mg/L) and high k ≤ 7 (0.262 in 1-7 days after fertilization), followed by Southeast Coast (4.15 ± 5.33 mg/L; 0.263) and Northeast Plain (1.33 ± 1.50 mg/L; 0.239), respectively; (3) MLEpaddy-P performed well in daily TP dynamics estimation at national scale with R2 of 0.74-0.85; (4) Middle and lower reaches of the Yangtze River Basin were the critical regions with high TP concentration due to high fertilizer amount and soil Olsen-P content. The new universal model realizes the multi-site and long-term estimation of P dynamics while greatly saving multi-site monitoring costs. This study provides a basis for early warning and targeted control of P loss from paddies.

Phosphorus use efficiency has crossed the turning point of the environmental kuznets curve: Opportunities and challenges for crop production in China.

The overuse of phosphate fertilizer causes waste of resources and is detrimental to the sustainability of agriculture and aquatic systems. Effective management of phosphorus (P) in agricultural systems is important. Lack of understanding on the temporal and spatial variations of P utilization in farmland systems would constrain the development of more precise and effective policies as well as management practices. Here, we used two indicators, P use efficiency (PUE) and P surplus (Psur), to evaluate changes in P utilization in crop production on both national and regional scale in China during 2005-2018. Great heterogeneity of PUE and Psur were found across different regions, with Northeast of China showing the highest PUE (0.67) and lowest Psur (11.0 kg/ha). For temporal trends, our study showed that China crossed the turning point of the environmental Kuznets curve in 2007, which indicates that China has reached a new development stage of P use that is resource-saving and environmentally friendly. Along with the processes of industrialization and urbanization in China, the development of agricultural mechanization has further resulted in an increase of PUE and decrease of Psur. Although great efforts were made, China still has a relative low PUE and high Psur compared to developed countries. Our results suggest a regionalized perspective for developing policies for the sustainable use of P resources.

Improved estimation of nitrogen dynamics in paddy surface water in China.

Paddy surface water is the direct source of artificial drainage and surface runoff leading to N loss from rice paddy fields. Quantifying the N dynamics in paddy surface water on a large scale is challenging because of model deficiencies and the limitations of field measurements. This study analyzed the N dynamics and the influencing factors in paddy surface water in the three main Chinese rice-growing regions: Northeast Plain, Yangtze River Basin, and Southeast Coast. An improved first-order kinetic model was proposed to evaluate the total nitrogen (TN) dynamics at a countrywide scale by improving the calculation method of the initial TN concentration (C0) and providing the optimum value of attenuation coefficient (k). The results show that: (1) the average reduction rate of TN concentration on the 7th day after fertilization increased with the growth period (85%, 90%, and 95% during the basal, tillering, and panicle fertilization periods, respectively); (2) the attenuation coefficient k for the growth periods was ranked as follows: panicle fertilization period > tillering fertilization period > basal fertilization period. The Yangtze River Basin had the highest average k value (0.31-0.34), followed by the Southeast Coast (0.24-0.41) and Northeast Plain (0.22-0.30); and (3) the improved first-order kinetic model performed well in the N dynamics estimation (R2 > 0.6). High TN concentration with high fertilizer application amounts and precipitation caused the Yangtze River Basin to have a high N runoff loss risk. The proposed universal model realizes the simulation of N dynamics from a single site to multi-sites while greatly saving multi-site monitoring costs. This study provides a basis for effectively optimizing N management and preventing N loss in rice paddies.

Evolution and restoration of water quality in the process of urban development: a case study in urban lake, China.

Urban development has positive and negative effects on the evolution of enclosed lake water quality. This study aims to quantitatively analyze the water quality evolution of a typical urban lake, the Sha Lake, in the process of urban development. The land use degree comprehensive index (I) was calculated to reveal the level of urban development; water quality index (Smid) and eutrophication index (Tmid) were used to evaluate the water quality changes by fuzzy comprehensive-quantifying assessment (FCQA) method. The urban construction process and the water quality changes in 2000-2018 in the Sha Lake Basin were divided into three stages: (1) in 2000-2006, with the slow urban development, water quality remained stable and the degree of eutrophication improved slightly; (2) in 2007-2009, I increased rapidly to reach 300, Smid and Tmid increased from 90.62 to 92.83 and 75.06 to 87.52, respectively. Water quality deteriorated because of the failure to implement environmental protection measures in time; (3) in 2010-2018, although urban development reached a high level (I > 300), the water network connection project, dredging project, exogenous pollutant control, and sewage pipe network renovation since 2009 were critical measures to improve water quality for a long time. Due to the lag effect on improving water quality, the implementation of environmental protection measures should be synchronized with or even before urban construction. The research results can provide a scientific basis for the urban lake water environment protection in the process of urban development.

Influencing factor analysis of phosphorus loads from non-point source: a case study in central China.

The influence factor analysis for non-point source (NPS) pollution is very important to taking effective water pollution control measures. In this study, the self-organizing map (SOM) and linear model analysis were used to analyze the relationships between total phosphorus (TP) loads and influencing factors, both qualitatively and quantitatively. The land-use type, topography, and vegetation coverage were the main factors influencing the export of TP loads in Tangxun watershed. Slope and normalized difference vegetation index (NDVI) were chosen as characteristic indices of topography and vegetation coverage, respectively. For the whole watershed, the high TP loads were mainly distributed in areas with high slope and low vegetation coverage for a specific land-use type. For different land types, the slope significantly influenced the export of TP loads in waste/bare land and forest/green land while NDVI influenced the export of TP loads in forest/green land and farmland. In terms of multi-factor analysis, the comprehensive influence of slope and NDVI on TP loads showed as waste/bare land>forest/green land>farmland>rural/urban construction land.

Enhancing nitrate removal from small wetlands via regulating bacterial-algal symbiosis with macrophyte coverage.

With increasing land resource constraints, wetlands, as ecological hotspots, are expected to enhance biogeochemical processes to mitigate nitrogen (N) pollution, particularly nitrate-nitrogen (NO3--N). However, the interactions among bacteria, algae, and macrophytes in wetlands, which are crucial for N removal, remain largely unknown. This study explored how macrophyte coverage influences bacterial-algal interactions, shifting from mutualism to inhibition, thereby affecting N removal. Moderate coverage enhanced NO3--N and total nitrogen (TN) removal (P < 0.05), which was correlated with increased microbial abundance (P < 0.05). This may have resulted from moderate algal photosynthesis, reduced physiological stress, and the expansion of ecological niches for microbes. Insufficient coverage promoted algal growth (chlorophyll-a > 31.8 µg·L-1), leading to increased competition for substrates and elevated pH, which further inhibited bacterial activity. Excessive coverage also inhibited bacterial activity by reducing illumination and oxidation-reduction potential. Consequently, insufficient and excessive coverage decreased N removal efficiencies by 2.7-15.7 % (NO3--N) and 3.7-11.1 % (TN) while increasing methane emission potential by 1.4-6.9 times compared with moderate coverage. These findings offer insights into solving NO3--N contamination using near-natural methods and balancing the ecological and practical considerations for small wetlands.

Universal high-frequency monitoring methods of river water quality in China based on machine learning.

The in-situ high-frequency monitoring of total nitrogen (TN) and total phosphorus (TP) in rivers is a challenge and key to instant water quality judgment and early warning. Based on the physical and chemical association between TN/TP and sensor-measurable predictors, we proposed a novel "indirect" measurement method for TN and TP in rivers. This method combines the timeliness of multi-sensor and the accuracy of intelligent algorithms, utilizing 188,629 data sets from 131 water monitoring stations across China. Under 5 algorithms and 4 predictor group scenarios, the results showed that: (1) extra tree regression (ETR) with 6 predictors exhibited the best precision, and the mean determination coefficient (R2) of TN and TP inversion across 131 stations reached 0.78 ± 0.25 and 0.79 ± 0.22 respectively; (2) among 6 potential predictors, the importance degrees of temperature, electrical conductivity, NH4-N, and turbidity were greater than that of pH and DO, and >80 % of stations exhibited acceptable prediction accuracy (R2 > 0.6) when the number of predictors (P) ranged from 4 to 6, which showed good tolerability to predictor variations; (3) the accurate classification rates of water quality standard (ACRws) of all stations based on TN and TP reached 90.41 ± 6.96 % and 92.33 ± 6.41 %; (4) in 9 regions/basins of China, this method showed universal application potential with no significant prediction difference. Compared with laboratory test, water quality automatic monitoring station, and remote sensing inversion, the proposed method offers high-frequency, high-precision, regional adaptability, low cost, and stable operation under rainy, cloudy, and nighttime conditions. The new method may provide important technological support for timely pollutant tracing, pre-warning, and emergency control for river pollution.

Potential to mitigate nitrogen emissions from paddy runoff: A microbiological perspective.

Ditches and ponds are the basic units of agroecosystems that serve irrigation and drainage and also perform the natural ecological function of reducing nitrogen (N) emissions. To better enhance the design and advance management strategies in the paddy field ecosystem to minimize N emission, the N cycling microorganism in the paddy field ecosystem including interconnected fields with rice-wheat rotation, ditches, and ponds in central China was investigated by metagenomic techniques. Our results showed that ditches and ponds may be N removal hotspots by microorganisms in the rice and wheat seasons respectively. Given seasonal variation, the abundance of N-related microorganisms was high during the rice season. However, the Shannon and Simpson indices were lower and the microbial co-occurrence network was destabilized, which could make microbes in the rice season fragile and sensitive. Phytoplankton as key environmental factors affecting the N cycling microbial could promote more stable microbial communities through maintaining a good mutualistic symbiosis. While high algae concentration significantly promotes the abundance of norB than nosZ (P < 0.05), which may result in more N2O production. To trade off N removal and N2O emission, the algae concentration needs to be controlled. Our findings provide a systematic profile of N-related microorganisms in the paddy field ecosystem, and it would benefit in developing effective strategies for limiting N pollution in agriculture.

Enhancing rice production sustainability and resilience via reactivating small water bodies for irrigation and drainage.

Rice farming threatens freshwater resources, while also being increasingly vulnerable to drought due to climate change. Rice farming needs to become more sustainable and resilient to climate change by improving irrigation drainage systems. Small water bodies, used to store drainage water and supply irrigation in traditional rice farming systems have gradually been abandoned in recent decades. This has resulted in a higher water footprint (WF) associated with rice farming due to increased freshwater usage and wastewater release, also leaving rice production more vulnerable to extreme weather events. Here, we propose how protecting and reactivating small water bodies for rice irrigation and drainage can decrease rice production WF in China by 30%, save 9% of China's freshwater consumption, increase irrigation self-sufficiency from 3% to 31%, and alleviate yield loss in dry years by 2-3%. These findings show that redesigning rice irrigation drainage systems can help meet water scarcity challenges posed by climate change.

Synthesis and Modification of Tetrahedron Li10.35Si1.35P1.65S12 via Elemental Doping for All-Solid-State Lithium Batteries.

Solid-state electrolyte (SSE), as the core component of solid-state batteries, plays a critical role in the performance of the batteries. Currently, the development of SSE is still hindered by its high price, low ionic conductivity, and poor interface stability. In this work, we report the tailored synthesis of a high ionic conductive and low cost sulfide SSE for all-solid-state lithium batteries. The Li10.35Si1.35P1.65S12 with favorable tetragonal structure was synthesis by increasing the concentration of Si4+, which shows an ionic conductivity of 4.28 × 10-3 S cm-1 and a wide electrochemical stability window of up to 5 V. By further modifying the composition of the electrolyte via ionic doping, the ionic conductivity of Li10.35Si1.35P1.65S12 can be further enhanced. Among them, the 1% Co4+-doped Li10.35Si1.35P1.65S12 shows the highest ionic conductivity of 6.91 × 10-3 S cm-1, 40% higher than the undoped one. This can be attributed to the broadened MS4 - tetrahedrons and increased Li+ concentration. As a demonstration, an all-solid-state Li metal battery was assembled using TiS2 as the cathode and 1% Co4+-doped Li10.35Si1.35P1.65S12 as the electrolyte, showing capacity retention of 72% at the 110th cycle. This strategy is simple and can be easily extended for the construction of other high-performance sulfide SSEs.

Identifying key drivers of harmful algal blooms in a tributary of the Three Gorges Reservoir between different seasons: Causality based on data-driven methods.

Intense harmful algal blooms (HABs) can occur in the backwaters of tributaries supplying large-scale reservoirs. Due to the characteristics of process-based models and difficulties in modelling complex nonlinear processes, traditional models have difficulties disentangling the driving factors of HABs. In this study, we used data-driven methods (i.e., correlation analysis and machine-learning models) to identify the most important drivers of HABs in the Xiangxi River, a tributary of the Three Gorges Reservoir, China (2017-2018), for the dry season (from October to mid-April) and wet season (from April to September). We utilized the maximal information coefficient (MIC) combined with a time lag strategy and prior knowledge to quantitatively identify the driving variables of HABs. An extra trees regression (ETR) model was developed to assess the relative importance of causal variables driving algal blooms for the different periods. The results showed that water temperature was the most important driver for the duration of the study, followed by total nitrogen. Nitrogen had a stronger effect on algal blooms than phosphorus during both the wet and dry seasons. HABs were mainly affected by ammonia nitrogen in the wet season and by other forms of nitrogen in the dry season. In contrast, rather than the water temperature and nutrients, the operation of the Three Gorges Dam (difference between inflow and outflow discharge rate) was the most significant factor for algal blooms during the dry season, but its influence sharply declined during the wet season. This study showed that the key drivers of HABs can differ between seasons and suggests that HAB management should take seasonality into account.

Real-time measurement of total nitrogen for agricultural runoff based on multiparameter sensors and intelligent algorithms.

Real-time monitoring of non-point source (NPS) pollution is challenging owing to the minute-scale change in runoff flow and concentration under rainfall condition. In this study, we proposed a real-time measurement method for total nitrogen (TN) by combining the timeliness of sensor detection and the accuracy of intelligent algorithms, based on the physical and chemical relationships between TN and sensor-measured indexes. Extra tree regression was selected as the TN inversion algorithm, which has high precision, high computational efficiency, and better ability in over-fitting control. The results show that: (1) the real-time inversion algorithm of TN can achieve the monitoring frequency at the minute scale (<5 min); (2) the method performs well (R2>0.9) when the training and testing datasets are from similar environmental backgrounds (fields or ditches); (3) in the case of partial variable missing, this method can still realize TN inversion, and the prediction accuracy is acceptable (R2>0.7) under the number of missing variables (n) ≤ 2, which makes up for the flaws of missing or abnormal data caused by sensor malfunctions. Overall, the proposed real-time measurement method of TN has stable data acquisition, high precision, and high monitoring frequency. In addition, the method is not limited by cloudy, rainy, or nighttime conditions. Compared with methods such as laboratory test, remote sensing inversion, and water quality automatic monitoring station, our method has obvious advantages in runoff monitoring of NPS pollution, which mainly occurs in small and micro water bodies. The new real-time measurement of TN for runoff may provide important technological support for pre-warning and emergency control of NPS pollution.

Exposure and Inequality of PM2.5 Pollution to Chinese Population: A Case Study of 31 Provincial Capital Cities from 2000 to 2016.

Fine particulate matter (PM2.5) exposure has been linked to numerous adverse health effects, with some disadvantaged subgroups bearing a disproportionate exposure burden. Few studies have been conducted to estimate the exposure and inequality of different subgroups due to a lack of adequate characterization of disparities in exposure to air pollutants in urban areas, and a mechanistic understanding of the causes of these exposure inequalities. Based on a long-term series of PM2.5 concentrations, this study analyzed the spatial and temporal characteristics of PM2.5 in 31 provincial capital cities of China from 2000 to 2016 using the coefficient of variation and trend analyses. A health risk assessment of human exposure to PM2.5 from 2000 to 2016 was then undertaken. A cumulative population-weighted average concentration method was applied to investigate exposures and inequality for education level, job category, age, gender and income population subgroups. The relationships between socioeconomic factors and PM2.5 exposure concentrations were quantified using the geographically and temporally weighted regression model (GTWR). Results indicate that the PM2.5 concentrations in most of the capital cities in the study experienced an increasing trend at a rate of 0.98 µg m-3 per year from 2000 to 2016. The proportion of the population exposed to high PM2.5 (above 35 µg m-3) increased annually, mainly due to the increase of population migrating into north, east, south and central China. The higher educated, older, higher income and urban secondary industry share (SIS) subgroups suffered from the most significant environmental inequality, respectively. The per capita GDP, population size, and the share of the secondary industry played an essential role in unequal exposure to PM2.5.

Preferred hierarchical control strategy of phosphorus from non-point source pollution at regional scale.

Spatiotemporal heterogeneity poses challenges on prevention and control of non-point source (NPS) pollution. Treating pollution sources sequentially by prioritizing the critical periods (CPs) and critical source areas (CSAs) is essential for effective control of regional NPS pollution. In this study, the gird-based dual-structure export empirical model (DSEEM) was used to simulate phosphorus losses in the Danjiangkou Reservoir Basin (DRB) on a monthly scale. Based on the co-analysis of CPs and CSAs coupled with the point density analysis (PDA), a preferred hierarchical control strategy, which was connected with regional management units, was proposed to improve the pertinence for phosphorus loss control. CPs, sub-CPs, and non-CPs were identified on the temporal scale; CSAs, sub-CSAs, and non-CSAs were identified on the spatial scale. The results showed that CPs (July, April, and September), sub-CPs (May, March, and August), and non-CPs contributed 62.8%, 31.1%, and 6.1% of the annual TP loads, respectively. Furthermore, we proposed a hierarchical control strategy for NPS pollution: class I (CSAs in CPs) → class II (sub-CSAs in CPs, CSAs in sub-CPs) → class III (non-CPs, non-CSAs, sub- and non-CSAs in sub-CPs). Class I covered the periods and areas with the highest loads, contributing 26.2% of the annual loads within 14.5% of the area and 25.0% of the time. This study provides a reference for the targeted control of NPS pollution at regional scale, especially in environmental protection with limited funds.

A framework for evaluating county-level non-point source pollution: Joint use of monitoring and model assessment.

It is believed that non-point source (NPS) pollution threatens the regional environment. Because of the disconnection between the hydrological scale and the administrative scale of implementing feasible management policies in existing research, watershed-based management measures have limited application in current NPS control. In this study, a framework for county-level monitoring and evaluation is proposed, which contains a cascade monitoring scheme and an adaptable assessment scheme. The cascade monitoring scheme is based on the principle of "pollution source-transport pathways-receiving waters" layout method and the adaptable assessment scheme makes full use of monitoring data in the model. A set of processes was designed to monitor and assess county-level NPS pollution, from the initial step of county basic situation investigations to the final step of NPS pollution assessment. Two schemes are included in the process to improve the feasibility of the results. Here, the importance of the joint use of monitoring and simulation for environmental policy and management is stressed, and focus is on the characteristics of administrative boundaries. A case study involving Nanle County is presented, and a detailed layout scheme and the assessment results are given in this paper.

Cooperative identification for critical periods and critical source areas of nonpoint source pollution in a typical watershed in China.

Critical periods (CPs) and critical source areas (CSAs) refer to the high-risk periods and areas of nonpoint source (NPS) pollution in a watershed, respectively, and they play a significant role in NPS pollution control. The upstream Daning River Basin is a typical watershed in the Three Gorges Reservoir area. In this study, a Hydrological Simulation Program-Fortran (HSPF) model was used to simulate phosphorus loss in the upstream Daning River Basin. Co-analysis of critical periods and critical source areas (CACC) is a quantitative collaborative analysis method for the identification of CSAs in CPs, and it was used to classify the periods and areas of NPS pollution as CPs, sub-CPs, non-CPs, CSAs, and non-CSAs. The CPs occurred in months 5-7 and accounted for 53.7% of the total phosphorus (TP) loads, and the sub-CPs occurred in months 1, 3, 4, and 8 and accounted for 29.2% of the TP loads. In CSAs, 49.4% of the TP loads occurred in 26.8% of the basin. Furthermore, we proposed the following multilevel priority control measure for NPS pollution in the upstream Daning River Basin: CSAs in CPs (with load-area rate of 1.4), CSAs in sub-CPs (0.7), CSAs in non-CPs (0.4), non-CSAs in CPs (0.3), non-CSAs in sub-CPs (0.2), and non-CSAs in non-CPs (0.1). CSAs in CPs accounted for 25.8% of the TP loads from 19.0% of the areas in only 3 months while 49.4% of the TP loads from similar areas over an entire year. These findings indicated that the CSAs in CPs located in farmland along the Daning, Dongxi, and Houxi Rivers should be prioritized for pollution management measures.

Potential nutrient removal function of naturally existed ditches and ponds in paddy regions: Prospect of enhancing water quality by irrigation and drainage management.

Conventionally, paddy fields are regarded as important non-point sources of nutrient pollution, while ecological ditches and ponds are developed to reduce or retain nutrient export from agricultural fields. To quantify the potential nutrient removal function of ditches and ponds that naturally existed in rice growing regions, a representative paddy irrigation and drainage unit (IDU) composed of fields, ditches and a pond in the one-season rice region of the middle Changjiang River basin, China was monitored for two years. With data and knowledge gained, a Water Quantity and Quality Model for Paddy IDUs (WQQM-PIDU) is developed and applied for 30 years simulation to produce a general view. The monitored and modelled results showed that nutrient concentration peaks after fertilization was delayed and lowered in ditches and ponds, compared to those in paddy fields. Concentrations of runoff from the IDU outlet were generally lower than from the field during the whole rice growing season except the transplanting period. If fully utilized as temporary reservoirs, ditches and ponds naturally existed in a typical paddy IDU would reduce 39% nitrogen loads from field edges with a range of 17%-93% and 28% phosphorus loads with a range of 12%-92%. Although typical paddy IDUs discharge fewer nutrient loads than the content input into them, the discharge concentrations may be risky to surface waters. For their nutrient removal function, natural ditches and ponds are recommended to be included into irrigation and drainage management with accurate water level management during drainage, which is a promising and cost-effective approach to enhance surface water quality in rice growing regions.

Galectin-3 may serve as a marker for poor prognosis in colorectal cancer: A meta-analysis.

Galectin-3 has an important function in the development of tumors. The purpose of this meta-analysis was to explore the relationships between the expression of galectin-3 on clinicopathological features and prognosis of colorectal cancer (CRC). A comprehensive literature search was used to identify eligible studies, and Stata software was conducted using in this meta-analysis. A total of 15 studies, including 1661 cases, were matched in the inclusion criteria. The pooled analysis indicated that galectin-3 expression was related to the poor overall survival (OS) in CRC patients (HR: 1.77, 95% CI: 1.36-2.31, P < 0.0001). Our meta-analysis also showed that cancerous tissues have higher levels of galectin-3 expression than normal tissues. Besides, positive galectin-3 expression was also related to advanced TNM stages(III/IV vs. I/II: OR 5.30, 95% CI: 2.42-11.61, P < 0.0001), higher Duke's stages (C/D vs. A/B: OR 4.00, 95% CI: 2.22-7.22, P < 0.0001), venous invasion (venous invasion vs. not: OR 3.02, 95%CI: 1.75-5.22, P < 0.0001) and higher CEA level (CEA≥5 ng/ml vs. ≤ 5 ng/ml: OR 2.09, 95% CI: 1.09-4.03, P = 0.03). In summary, our results indicated that overexpression of galectin-3 is significantly related to the tumor progression and could be a efficient in predicting the prognosis of patients with CRC.

Evaluating the risk of phosphorus loss with a distributed watershed model featuring zero-order mobilization and first-order delivery.

Many semi-distributed models that simulate pollutants' losses from watersheds do not handle well detailed spatially distributed and temporal data with which to identify accurate and cost-effective strategies for controlling pollutants issuing from non-point sources. Such models commonly overlook the flow pathways of pollutants across the landscape. This work aims at closing such knowledge gap by developing a Spatially and Temporally Distributed Empirical model for Phosphorus Management (STEM-P) that simulates the daily phosphorus loss from source areas to receiving waters on a spatially-distributed grid-cell basis. STEM-P bypasses the use of complex mechanistic algorithms by representing the phosphorus mobilization and delivery processes with zero-order mobilization and first-order delivery, respectively. STEM-P was applied to a 217km2 watershed with mixed forest and agricultural land uses situated in southwestern China. The STEM-P simulation of phosphorus concentration at the watershed outlet approximated the observed data closely: the percent bias (Pbias) was -7.1%, with a Nash-Sutcliffe coefficient (ENS) of 0.80 on a monthly scale for the calibration period. The Pbias was 18.1%, with a monthly ENS equal to 0.72 for validation. The simulation results showed that 76% of the phosphorus load was transported with surface runoff, 25.2% of which came from 3.4% of the watershed area (classified as standard A critical source areas), and 55.3% of which originated from 17.1% of the watershed area (classified as standard B critical source areas). The standard A critical source areas were composed of 51% residences, 27% orchards, 18% dry fields, and 4% paddy fields. The standard B critical source areas were mainly paddy fields (81%). The calculated spatial and temporal patterns of phosphorus loss and recorded flow pathways identified with the STEM-P simulations revealed the field-scale critical source areas and guides the design and placement of effective practices for non-point source pollution control and water quality conservation.