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Nitrogen Leaching and Groundwater Recharge Modeling for the On-Farm Flood Flow Capture Project in Fresno, California.

机译:加利福尼亚弗雷斯诺市农场洪水流量捕获项目的氮浸出和地下水补给模型。

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摘要

Groundwater management is an important subject in California where people depend on groundwater for irrigation and drinking water. On-Farm Flood Flow Capture (OFFC) is a new method of groundwater recharge, which diverts flood flow in a river or canal to agricultural lands. OFFC's feasibility is currently investigated through an on-going project at Terranova Ranch in Helm near Fresno, CA. One of the concerns in OFFC is the groundwater pollution by nitrate (NO 3-) leaching from agricultural soils. This study is to develop a numerical model to investigate the impacts of OFFC to the NO 3- concentration and flux in the soil and groundwater recharge with different OFFC application rates, irrigation rates, and soil parameters. Also this study aims to find if NO3- can be captured by immobile pores, which reduces NO3- leaching. .;Field infiltration tests using double-ring infiltrometers were conducted to assess if immobile pores should be considered in the model. Based on the infiltration test results, a numerical model for 60 m vadose zone, which estimates groundwater recharge and NO3- leaching as its bottom water and NO3- fluxes, was developed using HYDRUS-1D considering OFFC, irrigation, precipitation, plant water uptake, plant solute uptake, evaporation and transpiration from vineyards. The model inputs were developed using surface flow and climate data from 1983 to 2002. The model was calibrated with volumetric water contents and water inflow from OFFC experiment data from 2011. The model base scenario (BASE) assumed OFFC application at 0.060 m/day when surface water was available during the non-growing season from late-October to mid-March and was only used for in-lieu recharge during the growing season from mid-March to late-October. Scenarios of an over irrigation (OI) with 1.2 times more OFFC rate from BASE and lower OFFC rate of 0.048 m/day (LOW), with 2 different longitudinal dispersivity coefficients of 1 and 0.1 m (DL1 and DL0.1) were also modeled. The model calibration data was only available for the surface 1.22 m. Therefore, the deep vadose zone soil parameters, a higher and a lower residual volumetric water contents (HthetaR and LthetaR), saturated volumetric water contents (HthetaS and LthetaS), and saturated hydraulic conductivities (HK and LK) were also used in BASE to assess their impacts to the groundwater recharge and NO3 - leaching.;The calibrated model showed low root mean square errors of less than 0.02 and high Nash-Sutcliff coefficients of above 0.65 for volumetric water contents measured at 0.15, 0.61 and 1.22 m from the soil surface. The field infiltration leached most NO3- in the 0.20m-thick soil, which cannot be explained by reasonable NO3- encapsulation in immobile regions. Therefore the model was developed with a simple equilibrium transport model without consideration of immobile pores. However, data collected from the relatively shallow depth (0.20 m) to determine the transport model type may not be able to capture preferential flow, and further investigation may be needed.;How quickly groundwater responds to surface water input varied by the quantity applied at the surface in the modeling results. However, in wet years when more than 4 m of water is applied at the surface, the groundwater recharge increased within 1 year in all tested scenarios. The modeling results showed small differences in bottom water and NO3- leaching between BASE and OI, while LOW showed lower and delayed recharge and NO 3- leaching. The root zone NO3- concentrations decreased by more than 90% at the end of the modeling period for all scenarios. NO3- concentrations at the vadose zone-groundwater interface became lower than the groundwater NO3 - concentration after 15 m of groundwater recharge in most DL0.1 scenarios, and this indicates groundwater quality improvement. However, it was not observed in any DL1 scenarios. BASE with different vadose zone parameters did not show significant differences in the recharge and timings, but showed differences in the NO3- leaching quantities and timings. HthetaR, HthetaS and LK delayed the NO3- leaching while LthetaR, LthetaS and HK accelerated NO3- leaching. Results from all scenarios and parameters showed at least 70% of initial residual soil NO3- leached to the groundwater after the modeling period.;OFFC seems to increase NO3- loads to the groundwater when applied on a soil with high residual NO3-, while it removes NO3- accumulated near the surface soil. BASE and OI showed only small differences in NO3- leaching, so irrigation rate differences may have small impacts to NO3- leaching compared to OFFC rates. The models showed that OFFC is likely to leach a high portion of the initial soil NO 3- for the study site, and NO3- reached to the groundwater from annual fertilizer application is much smaller than that from the initial soil NO3-. Therefore, initial soil NO3- concentrations and OFFC rates have more impacts to groundwater NO3- contamination than irrigation and NO3- fertilizer management for the scenarios investigated in this study.
机译:在加利福尼亚,地下水管理是重要的课题,那里的人们依靠地下水灌溉和喝水。农田洪水流量捕获(OFFC)是一种新的地下水补给方法,可将河流或运河中的洪水流量转移到农田。目前,通过加利福尼亚州弗雷斯诺附近Helm的Terranova Ranch正在进行的项目对OFFC的可行性进行了调查。 OFFC中关注的问题之一是从农业土壤中浸出的硝酸盐(NO 3-)对地下水的污染。本研究旨在建立一个数值模型,以研究OFFC对不同OFFC施用量,灌溉速率和土壤参数下土壤和地下水补给中NO 3-浓度和通量的影响。这项研究还旨在发现NO3-是否可以被固定的毛孔捕获,从而减少NO3-的浸出。使用双环渗透仪进行田间渗透试验,以评估模型中是否应考虑固定孔。根据入渗测试结果,使用HYDRUS-1D开发了一个60 m渗流带的数值模型,该模型估算了地下水的补给量和NO3-淋滤作为其底水和NO3-通量,并考虑了OFFC,灌溉,降水,植物水分吸收,葡萄园中植物溶质的吸收,蒸发和蒸腾作用。使用1983年至2002年的地表流量和气候数据开发了模型输入。使用2011年OFFC实验数据中的体积水含量和水流入量对模型进行了校准。模型基础情景(BASE)假设OFFC应用为0.060 m / day,在10月下旬至3月中旬的非生长季节可使用地表水,并且仅在3月中旬至10月下旬的生长季节用于地表补给。还模拟了过量灌溉(OI)的情景,该灌溉情景的基准是OFFC速率比BASE高1.2倍,而OFFC速率较低,为0.048 m / day(低),并且具有2个不同的纵向分散系数1和0.1 m(DL1和DL0.1) 。模型校准数据仅适用于1.22 m的表面。因此,在BASE中也使用了深层渗流带土壤参数,较高和较低的残留体积水含量(HthetaR和LthetaR),饱和体积水含量(HthetaS和LthetaS)以及饱和水力传导率(HK和LK)。校准后的模型显示,在距土壤表面0.15、0.61和1.22 m处测得的体积水含量,其均方根误差低至0.02,低Nash-Sutcliff系数高至0.65。 。田间入渗淋溶了0.20m厚土壤中的大多数NO3-,这不能用固定在不动地区的合理的NO3包裹来解释。因此,该模型是用简单的平衡输运模型开发的,而没有考虑固定的孔隙。但是,从相对浅的深度(0.20 m)收集的数据来确定运输模型类型可能无法捕获优先流量,因此可能需要进一步研究。;地下水对地表水输入的响应速度如何因施加的水量而变化建模结果中的曲面。但是,在潮湿的年份中,如果在地面上施加超过4 m的水,则在所有测试情况下,地下水的补给在1年内都会增加。模拟结果表明,BASE和OI之间的底水和NO3-淋滤差异很小,而LOW显示的补给量和NO 3-淋滤更低且延迟。在所有情景中,建模期间结束时,根区NO3-的浓度降低了90%以上。在大多数DL0.1情景中,渗流带-地下水界面的NO3-浓度低于地下水NO3-的浓度,这是在大多数DL0.1情景中补给15 m的地下水之后,这表明地下水质量有所改善。但是,在任何DL1方案中都没有观察到该现象。具有不同渗流区参数的BASE在补给和时间上没有显示出显着差异,但是在NO3的浸出量和时间上却显示出差异。 HthetaR,HthetaS和LK延迟了NO3-的浸出,而LthetaR,LthetaS和HK则加速了NO3-的浸出。所有情景和参数的结果表明,建模期后至少有70%的初始残留土壤NO3-渗入地下水。当在残留NO3-含量高的土壤上施用OFFC时,似乎增加了NO3-对地下水的负荷去除积聚在表层土壤附近的NO3-。 BASE和OI在NO3-淋洗中仅显示出很小的差异,因此与OFFC速率相比,灌溉速率的差异可能对NO3-淋洗产生较小的影响。模型显示,OFFC可能会向研究地点浸出大量初始土壤NO 3-,并且每年施肥时向地下水中排放的NO 3-比初始土壤NO 3-中的NO 3-要少得多。因此,在本研究调查的情景中,初始土壤NO3-浓度和OFFC速率对地下水NO3-污染的影响大于灌溉和NO3-肥料管理。

著录项

  • 作者

    Ariyama, Jiro.;

  • 作者单位

    University of California, Davis.;

  • 授予单位 University of California, Davis.;
  • 学科 Hydrologic sciences.;Environmental engineering.;Water resources management.
  • 学位 M.S.
  • 年度 2015
  • 页码 109 p.
  • 总页数 109
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

  • 入库时间 2022-08-17 11:52:18

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