Siqi Li, B. Zhu, Xunhua Zheng, Pengcheng Hu, Shenghui Han, Ji-hui Fan, Tao Wang, Rui Wang, Kai Wang, Z. Yao, Chunyan Liu, Wei Zhang, Y. Li
{"title":"Enabling a process-oriented hydro-biogeochemical model to simulate soil erosion and nutrient losses","authors":"Siqi Li, B. Zhu, Xunhua Zheng, Pengcheng Hu, Shenghui Han, Ji-hui Fan, Tao Wang, Rui Wang, Kai Wang, Z. Yao, Chunyan Liu, Wei Zhang, Y. Li","doi":"10.5194/bg-20-3555-2023","DOIUrl":null,"url":null,"abstract":"Abstract. Water-induced erosion and associated particulate carbon (PC), particulate nitrogen (PN)\nand particulate phosphorus (PP) nutrient losses are vital parts of biogeochemical\ncycling. Identifying their intensity and distribution characteristics is of\ngreat significance for the control of soil and water loss and nitrogen/phosphorus nonpoint\nsource pollution. This study incorporated modules of physical soil\nerosion and associated PC, PN and PP losses into a process-oriented\nhydro-biogeochemical model (Catchment Nutrients Management Model coupled with\nDeNitrification–DeComposition, CNMM-DNDC) to enable it to predict soil and\nwater loss. The results indicated that the upgraded CNMM-DNDC (i) performed\nwell in simulating the observed temporal dynamics and magnitudes of surface\nrunoff, sediment and PN/PP yields in the lysimetric plot of the\nJieliu catchment in Sichuan Province and (ii) successfully predicted the\nobserved monthly dynamics and magnitudes of stream flow, sediment yield and\nPN yields at the catchment outlet, with significant univariate\nlinear regressions and acceptable Nash–Sutcliffe indices higher than 0.74.\nThe upgraded CNMM-DNDC demonstrated that a greater proportion of PN to total nitrogen (TN) during the period with large precipitation events and amounts than that during\nthe drought period (16.2 %–26.6 % versus 2.3 %–12.4 %). The\nintensities of soil erosion and particulate nutrient yields in the Jieliu\ncatchment were closely related to land use type in the following order: sloping\ncultivated upland (SU) > residential areas (RA) > forest land (FL).\nThe scenario analysis demonstrated that high greenhouse gas (GHG) emissions\nscenarios provided a greater risk of soil erosion than did low GHG emissions\nscenarios and that land use change (i.e., from SU to FL)\ncould help to mitigate soil and water loss accelerated by climate change in\nthe future. The upgraded model was demonstrated to have the ability of\npredicting ecosystem productivity, hydrologic nitrogen loads, emissions of\nGHGs and pollutant gases, soil erosion and particulate nutrient yields,\nwhich renders it a potential decision support tool for soil erosion and\nnonpoint source pollution control coordinated with increasing production and\nreducing GHG and pollutant gases emissions in a catchment.\n","PeriodicalId":8899,"journal":{"name":"Biogeosciences","volume":" ","pages":""},"PeriodicalIF":3.9000,"publicationDate":"2023-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biogeosciences","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.5194/bg-20-3555-2023","RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Abstract. Water-induced erosion and associated particulate carbon (PC), particulate nitrogen (PN)
and particulate phosphorus (PP) nutrient losses are vital parts of biogeochemical
cycling. Identifying their intensity and distribution characteristics is of
great significance for the control of soil and water loss and nitrogen/phosphorus nonpoint
source pollution. This study incorporated modules of physical soil
erosion and associated PC, PN and PP losses into a process-oriented
hydro-biogeochemical model (Catchment Nutrients Management Model coupled with
DeNitrification–DeComposition, CNMM-DNDC) to enable it to predict soil and
water loss. The results indicated that the upgraded CNMM-DNDC (i) performed
well in simulating the observed temporal dynamics and magnitudes of surface
runoff, sediment and PN/PP yields in the lysimetric plot of the
Jieliu catchment in Sichuan Province and (ii) successfully predicted the
observed monthly dynamics and magnitudes of stream flow, sediment yield and
PN yields at the catchment outlet, with significant univariate
linear regressions and acceptable Nash–Sutcliffe indices higher than 0.74.
The upgraded CNMM-DNDC demonstrated that a greater proportion of PN to total nitrogen (TN) during the period with large precipitation events and amounts than that during
the drought period (16.2 %–26.6 % versus 2.3 %–12.4 %). The
intensities of soil erosion and particulate nutrient yields in the Jieliu
catchment were closely related to land use type in the following order: sloping
cultivated upland (SU) > residential areas (RA) > forest land (FL).
The scenario analysis demonstrated that high greenhouse gas (GHG) emissions
scenarios provided a greater risk of soil erosion than did low GHG emissions
scenarios and that land use change (i.e., from SU to FL)
could help to mitigate soil and water loss accelerated by climate change in
the future. The upgraded model was demonstrated to have the ability of
predicting ecosystem productivity, hydrologic nitrogen loads, emissions of
GHGs and pollutant gases, soil erosion and particulate nutrient yields,
which renders it a potential decision support tool for soil erosion and
nonpoint source pollution control coordinated with increasing production and
reducing GHG and pollutant gases emissions in a catchment.
期刊介绍:
Biogeosciences (BG) is an international scientific journal dedicated to the publication and discussion of research articles, short communications and review papers on all aspects of the interactions between the biological, chemical and physical processes in terrestrial or extraterrestrial life with the geosphere, hydrosphere and atmosphere. The objective of the journal is to cut across the boundaries of established sciences and achieve an interdisciplinary view of these interactions. Experimental, conceptual and modelling approaches are welcome.