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基于DRAINMOD的农田地表径流氮素流失动态模拟 总被引：2，自引：0，他引：2
为了解水旱农田地表径流氮素流失机理及过程,于2008年6～9月在湖北省漳河灌区开展了田间试验,并利用DRAINMOD模型对其进行模拟。研究结果表明:水田地表径流铵态氮和硝态氮的流失率均高于旱地,水田地表径流以铵态氮为主,而旱地以硝态氮为主。水旱农田地表径流氮素流失模拟值与实测值都非常接近,水田地表径流硝态氮和铵态氮模拟的相对误差分别为8.35%和10.99%,旱地分别为5.45%和14.11%;水田硝态氮和铵态氮模拟的效率系数分别为0.961和0.974,旱地的分别为0.993和0.938,效果都很好。因此,利用DRAINMOD模型进行该地区农田氮素流失动态模拟是可行而有效的。 相似文献
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Establishing an effective hydrological model is important for guiding the design of small-scale drainage systems. The simulation principle and the sensitivity of key parameters of DRAINMOD model were summarized from four aspects:Hydrological characteristics, nitrogen transport, salt transport and model cooperation. The research application progresses of DRAINMOD model and its coupled model at home and abroad were systematically reviewed, and the limitations and development trends of the model were discussed. It is pointed out that DRAINMOD model has good simulation performance in the fields of agricultural drainage, nitrogen removal and stain reduction. In the simulation of cold area or urban stormwater regulation, domestic research needs to reference from foreign research results. The research suggests that the key research directions of DRAINMOD model could be summarized as the following aspects:
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Global sensitivity analysis is a useful tool to understand process‐based ecosystem models by identifying key parameters and processes controlling model predictions. This study reported a comprehensive global sensitivity analysis for DRAINMOD‐FOREST, an integrated model for simulating water, carbon (C), and nitrogen (N) cycles and plant growth in lowland forests. The analysis was carried out for multiple long‐term model predictions of hydrology, biogeochemistry, and plant growth. Results showed that long‐term mean hydrological predictions were highly sensitive to several key plant physiological parameters. Long‐term mean annual soil organic C content and mineralization rate were mainly controlled by temperature‐related parameters for soil organic matter decomposition. Mean annual forest productivity and N uptake were found to be mainly dependent upon plant production‐related parameters, including canopy quantum use efficiency and carbon use efficiency. Mean annual nitrate loss was highly sensitive to parameters controlling both hydrology and plant production, while mean annual dissolved organic nitrogen loss was controlled by parameters associated with its production and physical sorption. Parameters controlling forest production, C allocation, and specific leaf area highly affected long‐term mean annual leaf area. Results of this study could help minimize the efforts needed for calibrating DRAINMOD‐FOREST. Meanwhile, this study demonstrates the critical role of plants in regulating water, C, and N cycles in forest ecosystems and highlights the necessity of incorporating a dynamic plant growth model for comprehensively simulating hydrological and biogeochemical processes. Copyright © 2013 John Wiley & Sons, Ltd. 相似文献
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Osvaldo Salazar Abraham Joel Ingrid Wesström Harry Linnér R. Wayne Skaggs 《水文研究》2010,24(26):3837-3851
The field hydrology model DRAINMOD integrated with Arc Hydro in geographical information system (GIS) framework (Arc Hydro–DRAINMOD) was used to simulate the hydrological response of a coastal watershed in southeast Sweden. Arc Hydro–DRAINMOD uses a distributed approach to route water from each field edge to the watershed outlet. In the framework the Arc Hydro data model was used to describe the stream network in the watershed and to connect the individual simulated DRAINMOD‐field outflow time series from each plot using Arc Hydro schema‐links features, which were summed at Arc Hydro schema‐nodes features along the stream network to generate the stream network flow. Hydrology data collected during six periods between 2003 and 2008 were used to test Arc Hydro–DRAINMOD and its performance was evaluated by considering uncertainties in model inputs using generalized likelihood uncertainty estimation (GLUE). The GLUE estimates obtained (uncertainty bands 5% and 95%) agreed satisfactorily with measured monthly discharges. The percentage of time in which the observed discharges were bracketed by the uncertainty bands was 88% in calibration periods and 75% in validation periods. Although monthly time step simulations showed good agreement with observed discharges during the two main discharge events in spring, the contradictory daily time step results indicate that the watershed response simulations on a daily basis need to be improved. The uncertainty analysis showed that in periods of higher discharge, such as spring periods, the uncertainty in prediction was higher. It is important to note that these uncertainty estimations using the GLUE procedure include the uncertainties in measured discharge values, model inputs, boundary conditions and model structures. It was estimated that stream baseflow represented 42% of the total watershed discharge, but further research is needed to confirm this. These results show that the new Arc Hydro–DRAINMOD framework is applicable for predicting discharge from artificially drained watersheds in southeast Sweden. Copyright © 2010 John Wiley & Sons, Ltd. 相似文献
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Good modelling practice requires the incorporation of uncertainty analysis into hydrologic/water quality models. The generalized likelihood uncertainty estimation procedure was used to evaluate the uncertainty in DRAINMOD predictions of daily, monthly, and yearly subsurface drain flow. A variance‐based sensitivity analysis technique, the extended Fourier amplitude sensitivity test, was used to identify the main sources of prediction uncertainty. The analysis was conducted for the experimental drainage field at the Southeast Purdue Agricultural Center in Indiana. Six years of data were used and the uncertainties in eight model parameters were considered to analyse how uncertainties in input parameters propagate to model outputs. The width of 90% confidence interval bands of drain flow ranged from 0 to 0·6 cm day?1 for daily predictions, from 0 to 3·1 cm month?1 for the monthly predictions, and from 7·6 to 12·4 cm year?1 for yearly predictions. Annual drain flow predicted by DRAINMOD fell well within the 90% confidence bounds. Model results were most sensitive to the vertical saturated hydraulic conductivity of the restrictive layer and the lateral hydraulic conductivity of the deepest soil layer, followed by the lateral hydraulic conductivity of the top soil layer and surface micro‐storage. Parameter interactions also contributed to the prediction uncertainty. Copyright © 2006 John Wiley & Sons, Ltd. 相似文献
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为研究雨水花园对暴雨径流水文调控效果受不同设计参数的影响,在试验研究的基础上,利用排水模型DRAINMOD分析了雨水花园长期运行效果受其蓄水层深度、汇流面积比以及降雨特征等因素的影响。模型测试结果显示,DRAINMOD可以较好地模拟雨水花园内部水文过程;长序列（1951—2007年）模拟结果发现,试验雨水花园对暴雨径流量削减率的年均值为18.5%,经介质净化的水量占雨水径流总量的76.1%;雨水花园蓄水层深度超过某一临界值后对其滞留效果没有影响;汇流面积比增大,排水量和溢流量均增大;在雨水花园内部增加30 cm反硝化作用蓄水层后,排水量下降了19.2%,雨水花园对径流量的削减率提高到33.5%。可见,增加内部蓄水层后雨水花园对水量削减和污染物浓度去除都具有积极作用。 相似文献
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Hydrologic models often require correct estimates of surface macro‐depressional storage to accurately simulate rainfall–runoff processes. Traditionally, depression storage is determined through model calibration or lumped with soil storage components or on an ad hoc basis. This paper investigates a holistic approach for estimating surface depressional storage capacity (DSC) in watersheds using digital elevation models (DEMs). The methodology includes implementing a lumped DSC model to extract geometric properties of storage elements from DEMs of varying grid resolutions and employing a consistency zone criterion to quantify the representative DSC of an isolated watershed. DSC obtained using the consistency zone approach is compared to DSC estimated by “brute force” (BF) optimization method. The BF procedure estimates optimal DSC by calibrating DRAINMOD, a quasi‐process based hydrologic model, with observed streamflow under different climatic conditions. Both methods are applied to determine the DSC for relatively low‐gradient coastal plain watersheds on forested landscape with slopes less than 3%. Results show robustness of the consistency zone approach for estimating depression storage. To test the adequacy of the calculated DSC values obtained, both methods are applied in DRAINMOD to predict the daily watershed flow rates. Comparison between observed and simulated streamflow reveals a marginal difference in performance between BF optimization and consistency zone estimated DSCs during wet periods, but the latter performed relatively better in dry periods. DSC is found to be dependent on seasonal antecedent moisture conditions on surface topography. The new methodology is beneficial in situations where data on depressional storage is unavailable for calibrating models requiring this input parameter. Copyright © 2012 John Wiley & Sons, Ltd. 相似文献
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