Muhammad Awais , Yongqi Chen , Wei Zhang , Syed Muhammad Zaigham Abbas Naqvi , Hao Zhang , Vijaya Raghavan , Jiandong Hu , Iskander Tlili
{"title":"农业面源污染及营养物向水体径流土壤渗滤液自动监测系统的实验验证","authors":"Muhammad Awais , Yongqi Chen , Wei Zhang , Syed Muhammad Zaigham Abbas Naqvi , Hao Zhang , Vijaya Raghavan , Jiandong Hu , Iskander Tlili","doi":"10.1016/j.asej.2025.103713","DOIUrl":null,"url":null,"abstract":"<div><div>Despite advancements, precise on-site measurement of agricultural non-point source pollution and its impact on water quality remains challenging. Existing systems face limitations in addressing spatial variability and temporal fluctuations and accurately capturing nutrient dynamics in water bodies. This study introduces an innovative automated monitoring framework to assess nitrogen (N) and phosphorus (P) contributions from agricultural runoff. This research also presents an innovative mathematical modeling framework and experimental validation for an automated soil leachate collection system (ASLCS) designed to monitor agricultural non-point source pollution, particularly focusing on nitrogen (N) and phosphorus (P) dynamics integrating soil water dynamics, pressure variations, and sensor responses. The model demonstrated exceptional accuracy in simulating soil water content across multiple depths (30, 60, and 90 cm) with remarkably low RMSE values of 0.0038, 0.0044, and 0.0036 m<sup>3</sup>/m<sup>3</sup> respectively. The soil leachate collection rates showed a<!--> <!-->strong correlation with soil water content (R<sup>2</sup> > 0.98 across all depths), with collection efficiency peaking at soil water contents above 0.28 m<sup>3</sup>/m<sup>3</sup>. Pressure dynamics analysis revealed sophisticated relationships between normalized pressure and volume (R<sup>2</sup> = 0.9911 and 0.9977), while ultrasonic level sensor performance demonstrated high measurement accuracy (R<sup>2</sup> = 0.9902) across operational ranges. The capability of the designed model to monitor nutrient concentrations showed exceptional precision, with validation results indicating high accuracy for NH<sub>4</sub>-N (R<sup>2</sup> = 0.9968, 0–10 mg/L range), NO<sub>3</sub>-N (R<sup>2</sup> = 0.9960, 0–20 mg/L range), and phosphorus (R<sup>2</sup> = 0.9943, 0–5 mg/L range). This integrated approach represented a significant advancement in automated monitoring technology, offering real-time, high-precision tracking of agricultural nutrient leaching while minimizing soil disruption.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 11","pages":"Article 103713"},"PeriodicalIF":5.9000,"publicationDate":"2025-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Experimental validation of an automated soil leachate monitoring system for agricultural Non-Point source pollution and nutrient run-off to water bodies\",\"authors\":\"Muhammad Awais , Yongqi Chen , Wei Zhang , Syed Muhammad Zaigham Abbas Naqvi , Hao Zhang , Vijaya Raghavan , Jiandong Hu , Iskander Tlili\",\"doi\":\"10.1016/j.asej.2025.103713\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Despite advancements, precise on-site measurement of agricultural non-point source pollution and its impact on water quality remains challenging. Existing systems face limitations in addressing spatial variability and temporal fluctuations and accurately capturing nutrient dynamics in water bodies. This study introduces an innovative automated monitoring framework to assess nitrogen (N) and phosphorus (P) contributions from agricultural runoff. This research also presents an innovative mathematical modeling framework and experimental validation for an automated soil leachate collection system (ASLCS) designed to monitor agricultural non-point source pollution, particularly focusing on nitrogen (N) and phosphorus (P) dynamics integrating soil water dynamics, pressure variations, and sensor responses. The model demonstrated exceptional accuracy in simulating soil water content across multiple depths (30, 60, and 90 cm) with remarkably low RMSE values of 0.0038, 0.0044, and 0.0036 m<sup>3</sup>/m<sup>3</sup> respectively. The soil leachate collection rates showed a<!--> <!-->strong correlation with soil water content (R<sup>2</sup> > 0.98 across all depths), with collection efficiency peaking at soil water contents above 0.28 m<sup>3</sup>/m<sup>3</sup>. Pressure dynamics analysis revealed sophisticated relationships between normalized pressure and volume (R<sup>2</sup> = 0.9911 and 0.9977), while ultrasonic level sensor performance demonstrated high measurement accuracy (R<sup>2</sup> = 0.9902) across operational ranges. The capability of the designed model to monitor nutrient concentrations showed exceptional precision, with validation results indicating high accuracy for NH<sub>4</sub>-N (R<sup>2</sup> = 0.9968, 0–10 mg/L range), NO<sub>3</sub>-N (R<sup>2</sup> = 0.9960, 0–20 mg/L range), and phosphorus (R<sup>2</sup> = 0.9943, 0–5 mg/L range). This integrated approach represented a significant advancement in automated monitoring technology, offering real-time, high-precision tracking of agricultural nutrient leaching while minimizing soil disruption.</div></div>\",\"PeriodicalId\":48648,\"journal\":{\"name\":\"Ain Shams Engineering Journal\",\"volume\":\"16 11\",\"pages\":\"Article 103713\"},\"PeriodicalIF\":5.9000,\"publicationDate\":\"2025-08-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Ain Shams Engineering Journal\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S209044792500454X\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ain Shams Engineering Journal","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S209044792500454X","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
Experimental validation of an automated soil leachate monitoring system for agricultural Non-Point source pollution and nutrient run-off to water bodies
Despite advancements, precise on-site measurement of agricultural non-point source pollution and its impact on water quality remains challenging. Existing systems face limitations in addressing spatial variability and temporal fluctuations and accurately capturing nutrient dynamics in water bodies. This study introduces an innovative automated monitoring framework to assess nitrogen (N) and phosphorus (P) contributions from agricultural runoff. This research also presents an innovative mathematical modeling framework and experimental validation for an automated soil leachate collection system (ASLCS) designed to monitor agricultural non-point source pollution, particularly focusing on nitrogen (N) and phosphorus (P) dynamics integrating soil water dynamics, pressure variations, and sensor responses. The model demonstrated exceptional accuracy in simulating soil water content across multiple depths (30, 60, and 90 cm) with remarkably low RMSE values of 0.0038, 0.0044, and 0.0036 m3/m3 respectively. The soil leachate collection rates showed a strong correlation with soil water content (R2 > 0.98 across all depths), with collection efficiency peaking at soil water contents above 0.28 m3/m3. Pressure dynamics analysis revealed sophisticated relationships between normalized pressure and volume (R2 = 0.9911 and 0.9977), while ultrasonic level sensor performance demonstrated high measurement accuracy (R2 = 0.9902) across operational ranges. The capability of the designed model to monitor nutrient concentrations showed exceptional precision, with validation results indicating high accuracy for NH4-N (R2 = 0.9968, 0–10 mg/L range), NO3-N (R2 = 0.9960, 0–20 mg/L range), and phosphorus (R2 = 0.9943, 0–5 mg/L range). This integrated approach represented a significant advancement in automated monitoring technology, offering real-time, high-precision tracking of agricultural nutrient leaching while minimizing soil disruption.
期刊介绍:
in Shams Engineering Journal is an international journal devoted to publication of peer reviewed original high-quality research papers and review papers in both traditional topics and those of emerging science and technology. Areas of both theoretical and fundamental interest as well as those concerning industrial applications, emerging instrumental techniques and those which have some practical application to an aspect of human endeavor, such as the preservation of the environment, health, waste disposal are welcome. The overall focus is on original and rigorous scientific research results which have generic significance.
Ain Shams Engineering Journal focuses upon aspects of mechanical engineering, electrical engineering, civil engineering, chemical engineering, petroleum engineering, environmental engineering, architectural and urban planning engineering. Papers in which knowledge from other disciplines is integrated with engineering are especially welcome like nanotechnology, material sciences, and computational methods as well as applied basic sciences: engineering mathematics, physics and chemistry.