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首页> 外文期刊>Hydrological ProcHydrological Processesrnesses >Application of a GIS‐based distributed hydrology model for prediction of forest harvest effects on peak stream flow in the Pacific Northwest
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Application of a GIS‐based distributed hydrology model for prediction of forest harvest effects on peak stream flow in the Pacific Northwest

机译:基于GIS的分布式水文模型在西北太平洋西北地区森林采伐对峰值水流影响的预测中的应用

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摘要

Spatially distributed rainfall–runoff models, made feasible by the widespread availability of land surface characteristics data (especially digital topography), and the evolution of high power desktop workstations, are particularly useful for assessment of the hydrological effects of land surface change. Three examples are provided of the use of the Distributed Hydrology-Soil–Vegetation Model (DHSVM) to assess the hydrological effects of logging in the Pacific Northwest. DHSVM provides a dynamic representation of the spatial distribution of soil moisture, snow cover, evapotranspiration and runoff production, at the scale of digital topographic data (typically 30–100 m). Among the hydrological concerns that have been raised related to forest harvest in the Pacific Northwest are increases in flood peaks owing to enhanced rain-on-snow and spring radiation melt response, and the effects of forest roads. The first example is for two rain-on-snow floods in the North Fork Snoqualmie River during November 1990 and December 1989. Predicted maximum vegetation sensitivities (the difference between predicted peaks for all mature vegetation compared with all clear-cut) showed a 31% increase in the peak runoff for the 1989 event and a 10% increase for the larger 1990 event. The main reason for the difference in response can be traced to less antecedent low elevation snow during the 1990 event. The second example is spring snowmelt runoff for the Little Naches River, Washington, which drains the east slopes of the Washington Cascades. Analysis of spring snowmelt peak runoff during May 1993 and April 1994 showed that, for current vegetation relative to all mature vegetation, increases in peak spring stream flow of only about 3% should have occurred over the entire basin. However, much larger increases (up to 30%) would occur for a maximum possible harvest scenario, and in a small headwaters catchment, whose higher elevation leads to greater snow coverage (and, hence, sensitivity to vegetation change) during the period of maximum runoff. The third example, Hard and Ware Creeks, Washington, illustrates the effects of forest roads in two heavily logged small catchments on the western slopes of the Cascades. Use of DHSVM's road runoff algorithm shows increases in peak runoff for the five largest events in 1992 (average observed stream flow of 2·1 m s) averaging 17·4% for Hard Creek and 16·2% for Ware Creek, with a maximum percentage increase (for the largest event, in Hard Creek) of 27%. © 1998 John Wiley & Sons, Ltd.
机译:空间分布的降雨径流模型,由于广泛获得的地表特征数据(尤其是数字地形)以及大功率台式工作站的发展而变得可行,对于评估地表变化的水文影响尤其有用。提供了三个使用分布式水文-土壤-植被模型(DHSVM)评估西北太平洋地区伐木的水文影响的例子。 DHSVM以数字地形数据(通常为30–100 m)的规模来动态表示土壤水分,积雪,蒸散量和径流的空间分布。与西北太平洋地区森林采伐有关的水文问题包括由于雪上雨水和春季辐射融化反应的增强以及森林道路的影响而导致的洪峰增加。第一个例子是在1990年11月至1989年12月在北福克斯诺夸尔米河上两次下雪雨洪水。预测的最大植被敏感性(所有成熟植被的峰值与所有明晰峰值之间的差异)显示为31% 1989年事件的最高径流量增加,而1990年事件的最大径流量增加10%。响应差异的主要原因可以追溯到1990年事件期间较低的低海拔降雪。第二个例子是华盛顿Little Naches河的春季融雪径流,该河排水了华盛顿喀斯喀特山脉的东坡。对1993年5月至1994年4月春季融雪高峰径流的分析表明,相对于所有成熟植被而言,目前的植被,整个流域的春季高峰春季水流量只增加了约3%。但是,对于最大可能的收成方案,将有更大的增加(最多30%),并且在小水源流域中,其较高的海拔高度会导致最大积雪期的积雪(并因此对植被变化敏感)。径流。第三个例子是华盛顿州的Hard和Ware Creeks,它说明了喀斯喀特山脉西坡上两个密集采伐的小集水区的林道的影响。 DHSVM的道路径流算法的使用显示了1992年的五个最大事件的峰值径流增加(平均观测到的流量2·1 ms),对于Hard Creek平均为17·4%,对于Ware Creek平均为16·2%,最大百分比(对于最大的事件,在Hard Creek)增加了27%。 ©1998 John Wiley&Sons,Ltd.

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