• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

利用 MODFLOW 和 DRASTIC 模型模拟硝酸盐污染和地下水资源脆弱性。

Simulation of nitrate pollution and vulnerability of groundwater resources using MODFLOW and DRASTIC models.

机构信息

Department of Water Science and Engineering, College of Agriculture, Isfahan University of Technology, 8415683111, Isfahan, Iran.

出版信息

Sci Rep. 2023 May 22;13(1):8211. doi: 10.1038/s41598-023-35496-8.

DOI:10.1038/s41598-023-35496-8
PMID:37217575
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10203279/
Abstract

Groundwater assets are the foremost imperative assets of freshwater accessible to people especially in arid and semi-arid regions. For the investigation of temporal changes in groundwater nitrate pollution and the role of agriculture and other sources in the pollution of groundwater, the information on 42 drinking water wells with suitable distribution in the plain in Bouin-Daran Plain in the center of Iran was used. The results showed that the amount of hydraulic conductivity in the plain for different areas after calibration in steady state was calculated between 0.8 and 34 m/day. After calibrating the model in permanent conditions, the model was calibrated in non-permanent conditions for 2 years. The results showed that in a wide area of the region, the nitrate ion concentration has values of more than 25 mg/L. This shows that the average concentration of this ion in the region is generally high. The highest level of pollution in the aquifer of the plain is related to the southern and southeastern parts of the plain. Due to the agricultural activities with the use of large amounts of fertilizers in this plain, there is a potential for pollution in all of the places, and it requires codified and executive planning for agricultural operations as well as the use of groundwater sources. The DRASTIC vulnerability estimation method is only useful for estimating the areas that have a high potential for contamination and according to the validation tests, it has also provided a suitable estimate.

摘要

地下水资产是人们可获得的淡水首要资产,尤其是在干旱和半干旱地区。为了研究地下水硝酸盐污染的时间变化以及农业和其他来源在地下水污染中的作用,利用了伊朗中部博因-达拉恩平原上 42 口具有合适分布的饮用水井的信息。结果表明,在稳态下校准后,平原不同区域的水力传导率值在 0.8 到 34 米/天之间。在永久条件下校准模型后,对其进行了 2 年的非永久条件校准。结果表明,在该地区的广大地区,硝酸盐离子浓度值超过 25 毫克/升。这表明该地区的平均离子浓度普遍较高。平原含水层的最高污染程度与平原的南部和东南部有关。由于该平原农业活动大量使用化肥,所有地方都存在污染的可能性,因此需要对农业作业以及地下水源的使用进行规范和执行规划。DRASTIC 脆弱性评估方法仅有助于估计具有高污染潜力的区域,并且根据验证测试,它还提供了合适的估计。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d9a/10203279/8315b5a3042a/41598_2023_35496_Fig15_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d9a/10203279/3d263e1ae7e7/41598_2023_35496_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d9a/10203279/fc397d8b4654/41598_2023_35496_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d9a/10203279/7759af946b24/41598_2023_35496_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d9a/10203279/0355561efbd0/41598_2023_35496_Fig4a_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d9a/10203279/765d92816ba5/41598_2023_35496_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d9a/10203279/6798d4d55dd5/41598_2023_35496_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d9a/10203279/c7159da59be8/41598_2023_35496_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d9a/10203279/d18285ac7a9d/41598_2023_35496_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d9a/10203279/52f46a792dc6/41598_2023_35496_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d9a/10203279/17f348b8cfa8/41598_2023_35496_Fig10_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d9a/10203279/9d62ca6b7dc1/41598_2023_35496_Fig11_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d9a/10203279/fff2d989827c/41598_2023_35496_Fig12_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d9a/10203279/e7a231c66fd1/41598_2023_35496_Fig13_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d9a/10203279/8d9fff9af3b1/41598_2023_35496_Fig14_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d9a/10203279/8315b5a3042a/41598_2023_35496_Fig15_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d9a/10203279/3d263e1ae7e7/41598_2023_35496_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d9a/10203279/fc397d8b4654/41598_2023_35496_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d9a/10203279/7759af946b24/41598_2023_35496_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d9a/10203279/0355561efbd0/41598_2023_35496_Fig4a_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d9a/10203279/765d92816ba5/41598_2023_35496_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d9a/10203279/6798d4d55dd5/41598_2023_35496_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d9a/10203279/c7159da59be8/41598_2023_35496_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d9a/10203279/d18285ac7a9d/41598_2023_35496_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d9a/10203279/52f46a792dc6/41598_2023_35496_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d9a/10203279/17f348b8cfa8/41598_2023_35496_Fig10_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d9a/10203279/9d62ca6b7dc1/41598_2023_35496_Fig11_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d9a/10203279/fff2d989827c/41598_2023_35496_Fig12_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d9a/10203279/e7a231c66fd1/41598_2023_35496_Fig13_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d9a/10203279/8d9fff9af3b1/41598_2023_35496_Fig14_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d9a/10203279/8315b5a3042a/41598_2023_35496_Fig15_HTML.jpg

相似文献

1
Simulation of nitrate pollution and vulnerability of groundwater resources using MODFLOW and DRASTIC models.利用 MODFLOW 和 DRASTIC 模型模拟硝酸盐污染和地下水资源脆弱性。
Sci Rep. 2023 May 22;13(1):8211. doi: 10.1038/s41598-023-35496-8.
2
Optimization of DRASTIC method by artificial neural network, nitrate vulnerability index, and composite DRASTIC models to assess groundwater vulnerability for unconfined aquifer of Shiraz Plain, Iran.通过人工神经网络、硝酸盐脆弱性指数和综合 DRASTIC 模型优化 DRASTIC 方法,评估伊朗设拉子平原无约束含水层的地下水脆弱性。
J Environ Health Sci Eng. 2016 Aug 9;14:13. doi: 10.1186/s40201-016-0254-y. eCollection 2016.
3
Temporal and spatial assessment of groundwater contamination with nitrate by nitrate pollution index (NPI) and GIS (case study: Fasarud Plain, southern Iran).利用硝酸盐污染指数(NPI)和 GIS 对硝酸盐污染引起的地下水污染的时空评估(案例研究:伊朗南部法萨尔平原)。
Environ Geochem Health. 2020 Oct;42(10):3119-3130. doi: 10.1007/s10653-020-00546-x. Epub 2020 Mar 7.
4
Optimization of interpolation method for nitrate pollution in groundwater and assessing vulnerability with IPNOA and IPNOC method in Qazvin plain.加兹温平原地下水硝酸盐污染插值方法的优化及采用IPNOA和IPNOC方法评估脆弱性
J Environ Health Sci Eng. 2017 Nov 21;15:23. doi: 10.1186/s40201-017-0287-x. eCollection 2017.
5
Pollution Vulnerability of the Ghiss Nekkor Alluvial Aquifer in Al-Hoceima (Morocco), Using GIS-Based DRASTIC Model.利用 GIS 支持的 DRASTIC 模型评估摩洛哥豪兹尼科(Al-Hoceima)吉什内科尔冲积含水层的污染脆弱性
Int J Environ Res Public Health. 2023 Mar 12;20(6):4992. doi: 10.3390/ijerph20064992.
6
Numerical modeling of groundwater flow and nitrate transport using MODFLOW and MT3DMS in the Karaj alluvial aquifer, Iran.利用 MODFLOW 和 MT3DMS 对伊朗卡拉季冲积含水层中的地下水流动和硝酸盐运移进行数值模拟。
Environ Monit Assess. 2022 Dec 28;195(1):242. doi: 10.1007/s10661-022-10881-4.
7
Groundwater vulnerability assessment in agricultural areas using a modified DRASTIC model.利用改进的DRASTIC模型对农业地区地下水脆弱性进行评估。
Environ Monit Assess. 2016 Jan;188(1):19. doi: 10.1007/s10661-015-4915-6. Epub 2015 Dec 9.
8
Vulnerability and risk evaluation of agricultural nitrogen pollution for Hungary's main aquifer using DRASTIC and GLEAMS models.运用DRASTIC和GLEAMS模型对匈牙利主要含水层农业氮污染的脆弱性与风险评估
J Environ Manage. 2009 Jul;90(10):2969-78. doi: 10.1016/j.jenvman.2007.08.009. Epub 2007 Dec 3.
9
Tackling the salinity-pollution nexus in coastal aquifers from arid regions using nitrate and boron isotopes.利用硝酸盐和硼同位素解决干旱地区沿海含水层中的盐度-污染关系问题。
Environ Sci Pollut Res Int. 2017 May;24(15):13247-13261. doi: 10.1007/s11356-017-8384-z. Epub 2017 Jan 22.
10
Groundwater vulnerability and contamination risk mapping of semi-arid Totko river basin, India using GIS-based DRASTIC model and AHP techniques.利用 GIS 支持的 DRASTIC 模型和层次分析法技术对印度半干旱的托特科河流域的地下水脆弱性和污染风险进行制图。
Chemosphere. 2022 Nov;307(Pt 2):135831. doi: 10.1016/j.chemosphere.2022.135831. Epub 2022 Aug 6.

引用本文的文献

1
Groundwater nitrate response to hydrogeological conditions and socioeconomic load in an agriculture dominated area.农业主导地区地下水硝酸盐对水文地质条件和社会经济负荷的响应
Sci Rep. 2025 Jan 8;15(1):1315. doi: 10.1038/s41598-024-84318-y.

本文引用的文献

1
Quantify the effects of groundwater level recovery on groundwater nitrate dynamics through a quasi-3D integrated model for the vadose zone-groundwater coupled system.通过一个用于非饱和带-地下水耦合系统的准三维综合模型,量化地下水位恢复对地下水中硝酸盐动态的影响。
Water Res. 2022 Nov 1;226:119213. doi: 10.1016/j.watres.2022.119213. Epub 2022 Oct 6.
2
Investigating sources, driving forces and potential health risks of nitrate and fluoride in groundwater of a typical alluvial fan plain.研究典型冲积扇平原地下水中硝酸盐和氟化物的来源、驱动因素及潜在健康风险。
Sci Total Environ. 2022 Jan 1;802:149909. doi: 10.1016/j.scitotenv.2021.149909. Epub 2021 Aug 27.
3
Using MODFLOW and RT3D to simulate diffusion and reaction without discretizing low permeability zones.
使用 MODFLOW 和 RT3D 模拟无低渗透带离散化的扩散和反应。
J Contam Hydrol. 2021 May;239:103777. doi: 10.1016/j.jconhyd.2021.103777. Epub 2021 Jan 28.
4
Municipal drinking water nitrate level and cancer risk in older women: the Iowa Women's Health Study.城市饮用水硝酸盐水平与老年女性癌症风险:爱荷华州女性健康研究
Epidemiology. 2001 May;12(3):327-38. doi: 10.1097/00001648-200105000-00013.