Related Experiment Video
Updated: Jan 12, 2026

Continuous Instream Monitoring of Nutrients and Sediment in Agricultural Watersheds
Published on: September 26, 2017
Effect of sampling frequency and streamflow on nutrient source apportionment in subtropical rivers
Yajing Sheng1, Wei Gao2, Min Cao1
1Guangdong Basic Research Center of Excellence for Ecological Security and Green Development, School of Ecology, Environment and Resources, Guangdong University of Technology, Guangzhou, China.
None:
Accurate estimation of nutrient contributions is essential for effective pollution control, yet remains challenging due to substantial uncertainties arising from limited sample sizes and dynamic hydrological regimes. This study employs a process-based load apportionment model (LAM), integrating daily flow records and high-resolution water quality data from 41 monitoring stations across the Pearl River Basin (PRB), to quantitatively distinguish point-source versus non-point-source contributions to total nitrogen (TN) and total phosphorus (TP) loads. Statistical T-tests were systematically applied to evaluate the sensitivity of source apportionment results to monitoring frequency and streamflow variability. The results indicate that: (1) Non-point sources dominate nutrient fluxes, contributing 85.95 and 92.13% of annual TN and TP loads respectively, acting as the largest sources averaging 83.41% (TN) and 90.88% (TP) of the period (average R2 > 0.70); (2) Regional heterogeneity exists, with the Beijiang sub-basin exhibiting significantly lower non-point-source TN contributions (66.15%) compared to other sub-basins; (3) Monitoring frequency exerts greater influence on TN source partitioning (P < 0.05 at 65.85% stations) than TP (46.34% stations). These findings highlight the necessity of region-specific management strategies and underscore the value of high-frequency monitoring coupled with multi-source data fusion to enhance the robustness of pollution source identification.
Related Concept Videos
Sampling Plans
Random sampling is a method where each member of the population has an equal chance of being selected for the sample. It involves selecting individuals randomly, often using random number generators or lottery-type methods. For example, when analyzing the properties of a...
Rapidly Varying Flow
Primary Production
Upsampling

