Application of snowmelt runoff model(SRM) in mountainous watersheds:A review

The snowmelt runoff model （SRM） has been widely used in simulation and forecast of streamflow in snow-dominated mountainous basins around the world. This paper presents an overall review of worldwide applications of SRM in mountainous watersheds, particularly jn data-sparse watersheds of northwestern China. Issues related to proper selection of input climate variables and parameters, and determination of the snow cover area （SCA）using remote sensing data in snowmelt runoff modeling are discussed through extensive review of literature. Preliminary applications of SRM in northwestern China have shown that the model accuracies are relatively acceptable although most of the watersheds lack measured hydro-meteorological data. Future research could explore the feasibility of modeling snowmelt runoff in data-sparse mountainous watersheds in northwestern China by utilizing snow and glacier cover remote sensing data, geographic information system （GIS） tools, field measurements, and innovative ways of model parameterization.

Integration of aspect and slope in snowmelt runoff modeling in a mountain watershed

This study assessed the performances of the traditional temperature-index snowmelt runoff model(SRM) and an SRM model with a finer zonation based on aspect and slope(SRM + AS model) in a data-scarce mountain watershed in the Urumqi River Basin,in Northwest China.The proposed SRM + AS model was used to estimate the melt rate with the degree-day factor(DDF) through the division of watershed elevation zones based on aspect and slope.The simulation results of the SRM + AS model were compared with those of the traditional SRM model to identify the improvements of the SRM + AS model's performance with consideration of topographic features of the watershed.The results show that the performance of the SRM + AS model has improved slightly compared to that of the SRM model.The coefficients of determination increased from 0.73,0.69,and 0.79 with the SRM model to 0.76,0.76,and 0.81 with the SRM + AS model during the simulation and validation periods in 2005,2006,and 2007,respectively.The proposed SRM + AS model that considers aspect and slope can improve the accuracy of snowmelt runoff simulation compared to the traditional SRM model in mountain watersheds in arid regions by proper parameterization,careful input data selection,and data preparation.

Snowmelt runoff prediction under changing climate in the Himalayan cryosphere: A case of Gilgit River Basin

There are serious concerns of rise in temperatures over snowy and glacierized Himalayan region that may eventually affect future river flows of Indus river system. It is therefore necessary to predict snow and glacier melt runoff to manage future water resource of Upper Indus Basin(UIB). The snowmelt runoff model(SRM) coupled with MODIS remote sensing data was employed in this study to predict daily discharges of Gilgit River in the Karakoram Range. The SRM was calibrated successfully and then simulation was made over four years i.e. 2007, 2008, 2009 and 2010 achieving coefficient of model efficiency of 0.96, 0.86, 0.9 and 0.94 respectively. The scenarios of precipitation and mean temperature developed from regional climate model PRECIS were used in SRM model to predict future flows of Gilgit River. The increase of 3 C in mean annual temperature by the end of 21 th century may result in increase of 35-40% in Gilgit River flows. The expected increase in the surface runoff from the snow and glacier melt demands better water conservation and management for irrigation and hydel-power generation in the Indus basin in future.

Application of hydrological models in a snowmelt region of Aksu River Basin

This study simulated and predicted the runoff of the Aksu River Basin, a typical river basin supplied by snowmelt in an arid mountain region, with a limited data set and few hydrological and meteorological stations. Two hydrological models, the snowmelt-runoff model （SRM） and the Danish NedbФr-AfstrФmnings rainfall-runoff model （NAM）, were used to simulate daily discharge processes in the Aksu River Basin. This study used the snow-covered area from MODIS remote sensing data as the SRM input. With the help of ArcGIS software, this study successfully derived the digital drainage network and elevation zones of the basin from digital elevation data. The simulation results showed that the SRM based on MODIS data was more accurate than NAM. This demonstrates that the application of remote sensing data to hydrological snowmelt models is a feasible and effective approach to runoff simulation and prediction in arid unguaged basins where snowmelt is a major runoff factor.

Application of Snow Melt Runoff Model in a Mountainous Basin of Iran

Simulation and modeling the stream flow provide major data while it is a challenge in mountainous basins with regard to the important role of snowmelt runoff as well as the data scarcity in these places. The main purpose of this paper is to examine the capability of an integrated application of remote sensing data and Snowmelt Runoff Model (SRM) to simulate scheme of daily stream flow in the snow-dominated catchment, located in the North-East region of Iran. The main parameters of the model are Snow Cover Area (SCA), temperature and participation. Regarding to the lack of measured data, the input variable and parameters of the model are extracted or estimated based on accessible maps, satellite data and available meteorological and hydrological stations. The changes of snow-cover, as spatial-temporal data, which are the most effective variable in performance of SRM, are obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS) eight-day composite snow cover images. The evaluation of the model application efficiency was tested by the coefficient of determination and the volume difference, which are 0.85% and -4.6% respectively. The result depicts the relative capability of SRM though it is evident that the more accurate the estimation of model parameters, the more efficient simulation results can be obtained.

HBV模型在玛纳斯河流域的适用性

新疆天山北坡山区流域水文气象资料稀缺,融雪径流模拟比较困难。为研究HBV模型在新疆天山北坡玛纳斯河流域径流模拟的适用性,通过分析流域积雪覆盖率与径流的相关性,并基于中国地面降水与气温日值0.5°×0.5°格点数据集,经空间插值得到研究区多年平均降水和气温的空间分布,运用HBV模型模拟了玛纳斯河流域2000—2013年日尺度和月尺度径流过程,与SRM的模拟效果进行对比分析。结果表明:①多年月平均积雪覆盖率与多年月平均流量呈负相关,相关系数R^(2)=0.67,流域内积雪融水对径流的补给作用明显;②数据集经空间插值得到研究区多年平均降水和气温的空间分布能基本反映流域的垂直气候差异性,数据集可作为玛纳斯河流域缺乏气象资料的高山区径流模拟的输入数据;③HBV模型与SRM在玛纳斯河流域日尺度和月尺度的径流模拟效果评价等级均为良好,且HBV模型对洪峰流量模拟效果更好,整体的模拟值与实测值偏差更小,HBV模型在玛纳斯河流域具有较好的适用性。

A test of Snowmelt Runoff Model(SRM)for the Gongnaisi River basin in the western Tianshan Mountains,China

The Snowmelt Runoff Model (SRM) is one of a very few models in the world today that requires remote sensing derived snow cover as model input. Owing to its simple data requirements and use of remote sensing to provide snow cover information, SRM is ideal for use in data sparse regions, particularly in remote and inaccessible high mountain watersheds. In order to verify the applicability of SRM in an environment of continental climate, a test of SRM is performed for the Gongnaisi River basin in the western Tianshan Mountains, the results show that two SRM average goodness-of-fit statistics for simulations, Nash-Sutcliff coefficient (R2) and volume difference (DV), are 0.87 and 0.90%, respectively. As compared with the application results over 80 basins in 25 different countries around the world, SRM performs well in the Gongnaisi River basin. The results also show that SRM can be a validated snowmelt runoff model capable of being applied in the western Tianshan Mountains. On the basis of snowmelt runoff simulation, together with a set of simplified hypothetical climate scenarios, SRM is also used to simulate the effects of climate change on snow cover and the consecutive snowmelt runoff. For a given hypothetical temperature increase of 4℃, the snow coverage and snowmelt season shift towards earlier dates, and the snowmelt runoff, as a result, is changed significantly at the same time. The simulation results show that the snow cover is sensitive to changes of climate, especially to the increase of temperature, the major effect of climate change will be a time shifting of snowmelt runoff to early spring months, resulting in a redistribution of seasonally runoff throughout the whole snowmelt season.

Simulation of snowmelt-runoff under climate change scenarios in a data-scarce mountain environment

Pakistan is an agriculture-based economy and major proportion of irrigation water for its cultivated lands is abstracted from the Upper Indus Basin(UIB).UIB water supplies are mostly contributed from the high-altitude snow and glacier fields situated in the Hindukush–Karakoram–Himalayan ranges.Any change in the flows of these river catchments due to climate variability may result in the form of catastrophic events like floods and droughts and hence will adversely affect the economy of Pakistan.This study aims to simulate snowmelt runoff in a mountainous sub-catchment(Shyok River basin)of the UIB under climate change scenarios.Snowmelt Runoff Model(SRM)coupled with remotely sensed snow cover product(MOD10A2)is used to simulate the snowmelt runoff under current and future climate scenarios in the study area.The results indicate that(a)SRM has efficiently simulated the flow in Shyok River with average Nash–Sutcliff coefficient value(R2)of 0.8(0.63–0.93)for all six years(2000–2006)of basin-wide and zone-wise simulations,(b)an increase of 10%(by 2050)and 20%(by 2075)in SCA will result in a flow rise of∼11%and∼20%,respectively,and(c)an increase of 1℃(by 2025),2℃(by 2050),3℃(by 2075)and 4℃(by 2100)in mean temperature will result in a flow rise of∼26%,∼54%,∼81%and∼118%,respectively.This study suggests that SRM equipped with remotely sensed snow cover data is an effective tool to estimate snowmelt runoff in high mountain data-scarce environments.

SRM融雪径流模型在长江源区冬克玛底河流域的应用

冬克玛底河流域作为青藏高原腹地长江源区典型代表性高寒山区流域,有较大面积的冰川、积雪存在。本文以冬克玛底河流域2005年5￣10月的实测水文、气象资料为基础,运用SRM融雪径流模型对不同分带数对融雪径流模拟效果的影响和不同测站气温分别作为气温驱动变量对融雪径流模拟效果的影响分别进行了模拟试验。结果表明:不同分带会对SRM模型融雪径流量模拟产生一定的影响;而不同的气温作为驱动变量对模拟的效果影响很大,这表明SRM模型对气温驱动变量非常敏感。同样根据流域内径流与气温降水的相关分析看到日径流量与气温相关性较好,线性相关系数最好达到0.72,而径流与降水线性相关系数为0.20。根据以上模拟实验和相关分析选择合适的分带和具有代表性的站点气温,SRM模型模拟的两个优度指标最好可达到Nash-Sutcliffe系数(R2)=0.83和体积差(Dv)=0.95%。考虑到SRM模型对气温的敏感性,利用最终选择的模拟方案并结合气温升高1oC气候情景假设来考虑气温、降水和径流之间的关系。模拟结果表明:气温升高1oC后,(1)模拟时期内的径流总量由原来模拟的25.5×106m3增加到33×106m3;(2)冰川物质平衡线从原来的5600上升到5750米,冰川消融区从5.8km2增大到13.5km2,冰川消融量增加,对径流量的贡献明显增大。(3)气温的升高加速积雪融化并改变降水形态是径流在5￣6月变大的主导因素。7￣10月份的径流变大则主要是由于冰川消融。

SRM融雪径流模型在乌鲁木齐河源区的应用研究

乌鲁木齐河源区发育现代冰川7条,冰川面积5.6 km2,并有大范围的积雪,冰雪消融期融雪径流对乌鲁木齐河贡献显著。应用SRM(snowmelt runoff model)融雪径流模型来探讨乌鲁木齐河源区融雪期径流情况,利用度日方法,由流域本身特征及参变量获取方法的深入分析来率定模型参数,应用模拟指标Nash-Sutcliffe系数R2=0.702和积差Dv=6.81%来评价模型表现,研究发现:(1)气温、降水作为该模型的直接驱动变量对模型的模拟较为敏感。尝试对乌乌鲁木齐河源区的气温、降水数据进行IDW插值并进行修正,使得模型模拟精度提高,对模型变量的输入精度问题上提供了新的思路;(2)不同高度带上积雪的度日因子并不是稳定的,而度日因子的选取与调整对模型也非常重要;(3)模型本身的局限性也导致模拟精度的降低。结果表明SRM模型可在乌鲁木齐河流域推广应用,这必将对认识和利用乌鲁木齐河流域冰雪水资源具有重要意义。

遥感和GIS支持下的分布式融雪径流过程模拟研究

基于遥感(RS)和地理信息系统(GIS)技术,设计和构建了一个分布式融雪径流模型,整个分布式融雪径流过程的模拟计算基于能量平衡和水量平衡,由分布式栅格融雪过程、分布式栅格产流过程以及分布式栅格汇流过程组成,融雪以及产汇流过程全部基于栅格尺度,全面实现了融雪过程的分布式模拟。分布式栅格融雪过程中对"度日法"加以改进,引入了"单元时段"的概念,从而得到了"度分融雪模型";针对融雪过程中颇为复杂的冻融反复性难题,提出了旨在解释积雪冻融反复性物理机制的"冻融系数"的重要概念,对于准确把握融雪过程的物理机制具有重要意义。同时基于G IS开发了分布式融雪径流模拟系统,为分布式融雪径流模型的运行提供了平台和技术支持,二者均为融雪洪水预警决策支持系统的核心模块部分。基于由MODIS等遥感数据得到的积雪信息、地表温度等下垫面信息,基础地理信息数据如DEM及其空间分析数据和大量野外同步观测数据(积雪信息、气象数据),对典型研究区新疆军塘湖流域2006年春季典型融雪期(2006-03-06,11:00—2006-03-10,11:00)内的洪水过程进行了模拟,模拟结果精度较高,平均精度0.82,达到了融雪洪水预警预报的业务需求标准。

SRM融雪径流模型在疏勒河流域上游的应用

疏勒河是西北典型的干旱区内陆河流域,其冰雪融水是春季径流补给的重要来源之一。本文结合MODIS积雪产品MOD10A2、DEM数据和气象台站数据,构建了疏勒河流域上游SRM融雪径流模型,模拟结果的拟合优度确定系数Nash-Sutcliffe系数R2=0.834和体积差DV=1.63%。结果表明:该模型能基本上把握疏勒河流域融雪径流的趋势,达到了较好的模拟效果,可用于该流域春季径流的预测,为预防春季融雪型洪水灾害和减轻春季旱情提供了基础。

塔里木河流域积雪时空变化及融雪径流模拟

基于MODIS积雪产品分析了塔里木河流域2001-2013年间积雪覆盖(SCA)的时空变化,建立了其子流域叶尔羌河与玉龙喀什河的SRM融雪径流模型,并估算了融雪径流对总径流的贡献率(Qs)。结果表明:4-10月为塔里木河流域的融雪期,SCA在七八月达最低值;多年平均SCA为21.7%,源流区SCA高于45%;研究时段内的年均SCA呈统计不显著的波动下降趋势,年递减率为210 km^2。SRM模型能较好地模拟子流域的径流,率定期与验证期的纳什效率系数均在0.7以上,体积差的绝对值在15%以内;叶尔羌河、玉龙喀什河Q_s年际变化呈现波动状态,分别以0.3%、1.0%每年的速度缓慢上升,多年平均Qs分别为68.6%、70.2%,表明塔里木河是典型的以融雪径流为主的河流。以上研究结果对于塔河流域水资源管理具有一定的指导意义。

融雪侵蚀研究进展

融雪侵蚀在中国及世界上许多地区都有发生,其对表层土壤的破坏作用越来越为人们所认识,已成为土壤侵蚀研究中的重要问题之一。在总结相关研究成果的基础上,分析了影响积雪和融雪的气候、海拔、地形地貌及土地利用等因素。在融雪侵蚀影响因素方面,认为融雪径流、表层土壤解冻深度、解冻期表层土壤可蚀性是影响融雪侵蚀发生的特殊因素。同时指出,融雪侵蚀预报模型中冻融作用对土壤水分迁移的影响、未完全解冻层对表层土壤水分的影响以及坡面融雪过程研究是未来融雪侵蚀研究中应重点解决的问题。

水箱模型在北方寒冷湿润半湿润地区的应用探讨

依据北方寒冷地区水文特性，将水箱模型功能进行了扩充，通过在几个流域验证显示这种扩充是有效的，能够用于北方湿润半湿润地区的多年连续径流模拟，也为春汛的径流预报提供了一条途径。

APHRODITE降水数据驱动的融雪径流模拟

针对流域内气象观测站点稀少和融雪径流过程的特点,利用APHRODITE降水数据进行插值,应用日有效活动温度改进度日数;依据季节性冻土受有效活动积温影响的特点,建立有效活动积温与径流系数的关系,提高模型中融雪速率和径流系数的计算精度。结合气象、水文资料和MODIS遥感积雪产品,应用改进的融雪径流模型(SRM)对开都河流域2000年与2006年融雪期的径流进行了率定和验证模拟。改进模型在率定期和验证期的模拟结果远远优于用日平均温度作为度日数的结果。结果表明,用APHRODITE降水数据及改进的度日数和径流系数作为SRM模型参数输入,能够较好模拟开都河流域融雪径流过程,大大提高模型模拟精度。

SWAT模型融雪模块的改进

水土评价工具模型(SWAT)是一个具有物理基础的分布式水文模型,利用SCS径流曲线数方法计算地表径流,而采用相对简单的度日因子方法计算融雪径流。因此在湿润半湿润、雨量丰富的平原地区应用SWAT模型进行径流模拟时可以得到较好的模拟结果,但是在干旱半干旱、降水稀少,且春汛期间融雪径流是重要补给来源的高寒山区,模拟的融雪径流明显偏小,不能很好的反映这些地区的融雪过程,导致河道径流模拟精度偏低。FASST模型是具有物理机制的陆面过程模型,其采用能量平衡的方法计算融雪径流,能够较好的模拟复杂地形山区流域的融雪径流。以黑河山区流域为研究区,将FASST模型集成到SWAT模型,改善SWAT模型融雪径流的计算方法。通过对比SWAT模型集成前后莺落峡出山口的河道月径流、融雪径流和地表径流对河道的贡献等几个方面,表明了集成FASST融雪模块的SWAT模型能更好的反映黑河山区流域的融雪径流过程,从而提高河道径流的整体模拟精度。

基于能量平衡的分布式融雪径流模型

采用MODIS影像数据提取的积雪特征及T639L60气象预报场数据在WRF模式中的运行结果作为驱动,构造了一个以能量平衡为基础的融雪径流模型,将该融雪模型应用在天山北坡军塘湖河流域,对2010年径流模拟预报结果和实际观测数据分析显示:模型对雪深、雪水当量及融雪径流的模拟具有较好的拟合度,对提高融雪水资源管理效率及对融雪洪水预警具有一定的参考价值。

分布式融雪径流模型的设计及应用

融雪径流模型的研究对洪、旱灾害的监测与预报，对水文水资源的管理都具有重要的实用价值。本丈设计和构建了一个基于“3S”技术和DEM技术的分布式融雪径流模型，整个分布式融雪模型的计算基于能量平衡和水量平衡，由分布式栅格融雪过程到分布式橱格产流，最后是基于GIS的橱格汇流过程。融雪以及产汇流过程全部基于橱格尺度，全面实现了模型的分布式特性并具有严格的物理机制。文中提出了“单元时段”的重要概念，从而得到了“度分融雪模型”，为水文时间尺度转换难题的解决提供了新的思路；针对融雪过程中颇为复杂的冻融反复性难题提出了旨在解释积雪冻融反复性物理机制的“冻融系数”的重要概念，对于准确把握融雪过程的物理机制具有重要意义。另外，开发了B／S与C／S相结合的分布式融雪径流模拟系统，利用获取的大量实测、遥感以及气象等资料，基于橱格尺度全面实现了模型的算法，完成了对融雪径流的可视化、可控性模拟。最后。对典型研究区新疆军塘湖流域2006年春季融雪期（2006年3月6日11：00—2006年3月10日11：00的洪水过程进行了模拟．模拟结果精度较高。平均相对误差在0．18以下，达到了融雪洪水预警预报的业务需求。

基于SWAT模型的山区冰雪融水河流的日径流模拟研究

针对冰雪融水河流的产流与汇流特点,基于SWAT模型能量平衡计算原理,充分考虑地形、辐射、风、下垫面及冻土等因素对融雪的影响,研究了山区冰雪融水河流的日径流,基于遥感数据与地理信息数据得到的积雪信息,以及玛纳斯河流域1980—1995年气象、径流等实测数据,建立了适合山区融雪河流的SWAT分布式流域水文模型,并模拟了玛纳斯河流域出山口处肯斯瓦特水文站的日径流,模拟相对误差为17%、Nash Sutcliffe效率系数为0.73,模拟结果合理可靠,为研究冰雪融水河流的径流模拟提供了有效的途径。