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A Deterministic Approach for Approximating the Diurnal Cycle of Precipitation for Use in Large-Scale Hydrological Modeling

机译:大规模水文模拟中近似沉淀昼夜循环的确定性方法

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Accurate characterization of precipitation P at subdaily temporal resolution is important for a wide range of hydrological applications, yet large-scale gridded observational datasets primarily contain daily total P. Unfortunately, a widely used deterministic approach that disaggregates P uniformly over the day grossly mischaracterizes the diurnal cycle of P, leading to potential biases in simulated runoff Q. Here we present Precipitation Isosceles Triangle (PITRI), a two-parameter deterministic approach in which the hourly hyetograph is modeled with an isosceles triangle with prescribed duration and time of peak intensity. Monthly duration and peak time were derived from meteorological observations at U.S. Climate Reference Network (USCRN) stations and extended across the United States, Mexico, and southern Canada at 6-km resolution via linear regression against historical climate statistics. Across the USCRN network (years 2000-13), simulations using the Variable Infiltration Capacity (VIC) model, driven by P disaggregated via PITRI, yielded nearly unbiased estimates of annual Q relative to simulations driven by observed P. In contrast, simulations using the uniform method had a Q bias of -11%, through overestimating canopy evaporation and underestimating throughfall. One limitation of the PITRI approach is a potential bias in snow accumulation when a high proportion of P falls on days with a mix of temperatures above and below freezing, for which the partitioning of P into rain and snow is sensitive to event timing within the diurnal cycle. Nevertheless, the good overall performance of PITRI suggests that a deterministic approach may be sufficiently accurate for large-scale hydrologic applications.
机译:精确表征沉淀P在副时期的沉淀P对于各种水文应用是重要的,但是大规模网格化的观察数据集主要含有每日总P.不幸的是,广泛使用的确定性方法在当天均匀地将P均匀地分解差价P的循环导致模拟径流中的潜在偏差问题。在这里,我们呈现沉淀等腰三角形(PITRI),这是一种双参数确定方法,其中每小时职业图与等级三角形建模,具有规定的峰值强度的规定持续时间和时间。每月持续时间和高峰时间源于美国气候参考网(USCRN)站的气象观测,并在美国,墨西哥和加拿大南部的延伸,通过针对历史气候统计的线性回归在6公里的分辨率下。跨越USCRN网络(2000-13岁),采用V通过PITRI分列的P驱动的可变渗透能力(VIC)模型的模拟,相对于由观察到的P.相反,使用该模拟的模拟产生几乎没有偏见的年度Q估计。相反,使用该模拟通过估计冠层蒸发和低估渗透率,均匀的方法具有-11%的Q偏差。 Pitri方法的一个限制是雪积累的潜在偏差,当高比例的P落在冰冻和低于冻结的温度下的天数时,P进入雨雪和雪的分区对日期内的事件定时敏感循环。然而,Pitri的良好整体性能表明,对于大规模的水文应用,确定性方法可能足够准确。

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