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.

SNOW COVER MONITORING BY REMOTE SENSING AND SNOWMELT RUNOFF CALCULATION IN THE UPPER HUANGHE RIVER BASIN

The upper Huanghe(Yellow) River basin is situated in the northeast of the Qinghai Xizang(Tibet)Plateau of China. The melt water from the snow cover is main water supply for the rivers in the region during springtime and other arid regions of the northwestern China, and the hydrological conditions of the rivers are directly controlled by the snowmelt water in spring. So snowmelt runoff forecast has importance for hydropower, flood prevention and water resources utilization. The application of remote sensing and Geographic Information System (GIS) techniques in snow cover monitoring and snowmelt runoff calculation in the upper Huanghe River basin are introduced amply in this paper. The key parameter-snow cover area can be computed by satellite images from multi platform, multi temporal and multi spectral. A cluster of snow cover data can be yielded by means of the classification filter method. Meanwhile GIS will provide relevant information for obtaining the parameters and also for zoning. According to the typical samples extracting snow covered mountainous region, the snowmelt runoff calculation models in the upper Huanghe River basin are presented and they are mentioned in detail also. The runoff snowmelt models based on the snow cover data from NOAA images and observation data of runoff, precipitation and air temperature have been satisfactorily used for predicting the inflow to the Longyangxia Reservoir , which is located at lower end of snow cover region and is one of the largest reservoirs on the upper Huanghe River, during late March to early June. The result shows that remote sensing techniques combined with the ground meteorological and hydrological observation is of great potential in snowmelt runoff forecasting for a large river basin. With the development of remote sensing technique and the progress of the interpretation method, the forecast accuracy of snowmelt runoff will be improved in the near future. Large scale extent and few stations are two objective reality situations in China, so they should be considered in simulation and forecast. Apart from dividing, the derivation of snow cover area from satellite images would decide the results of calculating runoff. Field investigation for selection of the learning samples of different snow patterns is basis for the classification.

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.

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.

Effect of climatic change on snowmelt runoffs in mountainous regions of inland rivers in Northwestern China

Climatic change has significant impacts on snow cover in mid-latitude mountainous re- gions, in the meantime, spatial and temporal changes of snow cover and snowmelt runoffs are con- sidered as sensitive indicators for climatic change. In this study, the upper Heihe Watershed in the Qilian Mountains was selected as a typical area affected by snow cover and snowmelt runoffs in northwestern China. The changes in air temperatures, precipitation, snowfall and spring snowmelt runoffs were analyzed for the period from 1956 to 2001. The results indicate that climatic warming was apparent, particularly in January and February, but precipitation just fluctuated without a clear trend. The possible changes of snowmelt runoffs in the upper Heihe watershed in response to a warming of 4℃ were simulated using Snowmelt Runoff Model (SRM) based on the degree-day factor algorithm. The results of the simulation indicate that a forward shifting of snow melting season, an increase in water flows in earlier melting season, and a decline in flows in later melting season would occur under a 4℃ warming scenario.

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.

Preliminary studies on the ionic pulse of snowmelt runoff in the Urumqi River, Xinjiang, Northwest China

IONIC pulse of snowmelt and its runoff in seasonally snow-covered alpine catchments was de-fined by Johannessen et al. When a snowpack begins melting, the first meltwater drainingthrough the pack carries a large fraction of the soluble ions with it, an ionic pulse. 10％ of thefirst meltwater may drain 80％ of the soluble contents out of the snowpack within severalhours or days. In other words, an ionic pulse designates a peak in ionic concentration duringthe initial melting process of a snowpack. The peak has been proved by a plot test 10 times

考虑融雪及土壤冻融的新安江模型及其应用——以雅砻江上游径流模拟为例

寒区为中国大江大河的主要产流区,其径流预报精度直接影响下游水利工程调度和水资源科学管理。针对传统概念性水文模型较少考虑积雪融雪及土壤冻融过程对径流的叠加影响这一问题,以新安江模型为基础,以降水量和气温为驱动数据,提出了基于“等效土壤温度”和“土壤冻融特征曲线”的概念性土壤冻融模块来刻画积雪融雪及土壤冻融共同影响下的流域产流过程,构建了考虑融雪产流和土壤冻融的新安江模型。以雅砻江甘孜水文站以上流域为典型研究区,开展了流域2017—2022年冰雪消融期逐小时的径流模拟分析。结果表明,相比于HBV模型,考虑融雪产流和土壤冻融的模型可以显著提升流域冰雪消融期的水文模拟精度,各年份消融期径流的纳什效率系数中位数由0.69提升至0.83,相关系数中位数由0.88上升至0.92。本研究所提出的考虑融雪及土壤冻融的新安江模型可以为寒区的水文业务预报提供科学支撑。

基于三维激光扫描技术的冻结黑土细沟发育模拟

为探究融雪径流与冻结状态对黑土细沟网络发育的影响,该研究开展了冻结与非冻结处理黑土坡面的融雪径流模拟冲刷试验,利用三维激光扫描技术获取多次定时径流冲刷并直至侵蚀形态稳定的坡面点云,结合数字表面模型差异(digital surface model of difference,DoD)微地形变化监测方法与点云逆向工程,获取细沟网络发育过程的侵蚀面积、侵蚀体积、细沟长度和细沟密度等侵蚀参数。结果表明,冻结因素与温度变化对细沟网络发育过程与程度有重要影响:1)冻结处理的黑土坡面更容易发展出细沟网络,达到坡面侵蚀形态基本稳定后的侵蚀面积、侵蚀体积以及侵蚀细沟长度是非冻结处理黑土坡面的291%、557%和437%。2)冻结处理与非冻结处理沿坡面细沟截面形态变化差异明显。冻结坡面细沟交叉时宽深比RW/D快速减小,下切速度加快,随后宽度与深度呈比例稳定增加;非冻结坡面汇水处的R_(W/D)随冲刷次数增加而增大,侧蚀速度加快,其他截面R_(W/D)随着冲刷次数的增加而减小,下切速度加快。3)采用ArcGIS与点云逆向工程模型联合获取的冻结状态下细沟形态参数与发育过程DoD相对误差范围为-12.70%~4.42%,提取精度在95%以上。该联合方法在冻结土体条件下获取细沟参数具有较高精度,可作为土壤侵蚀参数高精度提取的一种手段。

东北黑土区融雪径流侵蚀力时空分布

[目的]融雪侵蚀是东北黑土区主要土壤侵蚀形式之一,是该区土地退化的重要作用力,融雪径流侵蚀力是计算融雪径流侵蚀量的关键因子,因此研究融雪径流侵蚀力具有重要意义。融雪径流侵蚀力主要受积雪深度、辐射强度及升温速率影响,其主要驱动力包括融雪速率和地表径流作用。[方法]通过计算近31年日均融雪径流侵蚀力,分析东北黑土区融雪径流侵蚀力时空分布特征,并利用地理探测器辨析各区域融雪径流侵蚀力的主要影响因子。[结果]3个黑土亚区1990—2020年日均融雪径流侵蚀力均呈现先增大后减小态势,近些年逐步趋于稳定,多年日均融雪径流侵蚀力为0.01(MJ·mm)/(hm ^(2)·h·a);空间上多年日均融雪径流侵蚀力在0~0.21(MJ·mm)/(hm ^(2)·h·a)范围内,基本呈现中间小、四周大规律。融雪径流侵蚀力影响因子空间上表现为积雪深度北部大、南部小,太阳辐射强度呈现由西向东递减,升温速率值从北部向南部递减。通过地探测器辨析融雪径流侵蚀力影响因子作用强弱发现,升温速率对蒙东黑土亚区作用最强,而积雪深度对松嫩黑土亚区及三江黑土亚区作用最强。[结论]通过分析1990—2020年东北黑土区融雪径流侵蚀力时空特征及其影响因子,对于深化研究区融雪径流侵蚀特征及融雪侵蚀防控具有一定的理论和实践意义。

寒区侵蚀产沙过程及模型算法研究进展

寒区侵蚀产沙过程受到冰川消融、融雪及土壤冻融的影响。气候变化下该过程存在极大不确定性。完善现有分布式水沙模型以量化冰冻圈要素的影响是解析该过程的重要方向。基于广泛的文献调研,总结这3类要素如何影响侵蚀产沙过程及相关模型算法,并比较多个模型在寒区的适用性。发现:1)冰川主要通过冰川径流(其计算包括冰川动态算法、冰川融水量的计算及不同分配方式)和基岩侵蚀(其计算可采用经验方法得到冰川区总输沙量后与水沙模型耦合)2方面影响侵蚀产沙过程;2)融雪过程增加地表产流,因此融雪量常被视为动能为0的降雨参与侵蚀计算;3)土壤冻融作用包括冻融深度影响产流量、冻融循环增加土壤可蚀性以及冻融深度对土壤可侵蚀范围的限制;4)现有模型对冰冻圈径流过程的考虑较完善,但对冰川消融和土壤冻融影响下的侵蚀产沙考虑不足。为此,建议在现有模型基础上补充相关算法完善模型结构,从而提高模型在寒区的适用性,以期采用改进后的模型量化冰冻圈要素对侵蚀产沙过程的影响,帮助明确寒区侵蚀产沙过程机制及未来变化规律。

分布式融雪径流模型研究进展

融雪径流在寒区、干旱区对当地的水资源起着十分重要的作用,但融雪同样也会带来融雪性洪水、山体滑坡等自然灾害,因此对融雪径流的模拟一直是寒旱区的重要热点,针对近些年来融雪径流模拟研究的发展趋势,介绍融雪径流模拟的主要类型,一类是基于能量平衡的物理模型,另一类是基于气温指标的度日模型。重点阐述分布式融雪径流模型的应用情况及其进展,并对分布式融雪径流模型进行讨论与展望。

不同清雪方式对城市融雪径流调控效果研究

随着城市化进程加快、气候多变,城市雨雪冰冻灾害日趋严重。针对冬季融雪带来的地表积水问题,利用Storm Water Management Model(SWMM)研究了机械、化学、人工3种清雪措施对冬季寒区城市融雪径流规律和低影响开发(LID)效果的影响机理。研究结果发现,3种清雪措施对于冬季寒区城市地表径流调控起到了显著作用,地表径流控制率增幅为5.9%~21.8%。3种清雪措施与LID组合使用后,均可将地表径流控制率提高至85%以上,相较于未清雪情景相比,地表径流控制率提高了40.0%~44.2%;与单独采取清雪措施相比,提高了22.4%~34.1%;与单独采取LID措施相比,提高了1.5%~5.7%。因此,清雪措施与LID的结合使用可提高冬季城市地表径流调控效果,不同清雪方式与LID的组合方式,对城市融雪径流的调控效果差异显著。

基于VMD-NGO-LSTM的融雪洪水汛期非平稳性极值径流预测模型及应用

金沟河属于典型的融雪补给流域,受自然环境、气候变化和人类活动等因素的影响,汛期极值径流序列表现出非平稳性及复杂性特征,给流域内汛期极值径流精准预测带来新的挑战。为解决该地区汛期极值径流的非平稳性对于预测结果的影响,引入变分模态分解算法(Variational Mode Decomposition,VMD),提出一种基于北方苍鹰优化算法(Northern Goshawk Optimization,NGO)与长短期记忆神经网络(Long Short-Term Memory,LSTM)的组合预测模型(VMD-NGO-LSTM),应用于金沟河流域八家户水文站1964—2016年的汛期极值径流预测,采用均方根误差(RMSE)、平均绝对误差(MAE)、平均绝对百分比误差(MAPE)、Nash系数(NSE)评价模型的预测能力。结果表明:(1)根据金沟河流域融雪洪水汛期径流极值序列的周期变化和趋势变化的水文特性变化结果表明径流极大值序列和径流极小值序列均具有非平稳性;(2)VMD-NGO-LSTM预测模型的NSE均大于0.97,且RMSE、MAPE、MAE值均处于偏小状态,与VMD-LSTM模型和VMD-NGO-BP模型相比,VMD-NGO-LSTM模型能够很好地预测八家户汛期极值径流的变化过程。该研究为汛期极值径流预测工作提供了新的思路,对新疆地区防洪减灾具有一定参考价值。

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.

Snowmelt modeling using two melt-rate models in the Urumqi River watershed, Xinjiang Uyghur Autonomous Region, China

In this paper,the performance of the classic snowmelt runoff model(SRM)is evaluated in a daily discharge simulation with two different melt models,the empirical temperature-index melt model and the energy-based radiation melt model,through a case study from the data-sparse mountainous watershed of the Urumqi River basin in Xinjiang Uyghur Autonomous Region of China.The classic SRM,which uses the empirical temperature-index method,and a radiation-based SRM,incorporating shortwave solar radiation and snow albedo,were developed to simulate daily runoff for the spring and summer snowmelt seasons from 2005 to 2012,respectively.Daily meteorological and hydrological data were collected from three stations located in the watershed.Snow cover area(SCA)was extracted from satellite images.Solar radiation inputs were estimated based on a digital elevation model(DEM).The results showed that the overall accuracy of the classic SRM and radiation-based SRM for simulating snowmeltdischarge was relatively high.The classic SRM outperformed the radiation-based SRM due to the robust performance of the temperature-index model in the watershed snowmelt computation.No significant improvement was achieved by employing solar radiation and snow albedo in the snowmelt runoff simulation due to the inclusion of solar radiation as a temperature-dependent energy source and the local pattern of snowmelt behavior throughout the melting season.Our results suggest that the classic SRM simulates daily runoff with favorable accuracy and that the performance of the radiation-based SRM needs to be further improved by more ground-measured data for snowmelt energy input.

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.

Response of runoff and its components to climate change in the Manas River of the Tian Shan Mountains

A warming-wetting climate trend has led to increased runoff in most watersheds in the Tian Shan Mountains over the past few decades.However,it remains unclear how runoff components,that is,rainfall runoff(Rrain),snowmelt runoff(Rsnow),and glacier meltwater(Rglacier),responded to historical climate change and how they will evolve under future climate change scenarios.Here,we used a modified Hydrologiska Byrans Vattenbalansavdelning(HBV)model and a detrending method to quantify the impact of precipitation and temperature changes on runoff components in the largest river(Manas River)on the northern slope of the Tian Shan Mountains from 1982 to 2015.A multivariate calibration strategy,including snow cover,glacier area,and runoff was implemented to constrain model parameters associated with runoff components.The downscaled outputs of 12 general circulation models(GCMs)from the Sixth Coupled Model Intercomparison Project(CMIP6)were also used to force the modified HBV model to project the response of runoff and its components to future(2016-2100)climate change under three common socio-economic pathways(SSP126,SSP245,and SSP585).The results indicate that Rrain dominates mean annual runoff with a proportion of 42%,followed by Rsnow(37%)and Rglacier(21%).In terms of inter-annual variation,Rrain and Rsnow show increasing trends(0.93(p<0.05)and 0.31(p>0.05)mm per year),while Rglacier exhibits an insignificant(p>0.05)decreasing trend(-0.12 mm per year),leading to an increasing trend in total runoff(1.12 mm per year,p>0.05).The attribution analysis indicates that changes in precipitation and temperature contribute 8.16 and 10.37 mm,respectively,to the increase in runoff at the mean annual scale.Climate wetting(increased precipitation)increases Rrain(5.03 mm)and Rsnow(3.19 mm)but has a limited effect on Rglacier(-0.06 mm),while warming increases Rrain(10.69 mm)and Rglacier(5.79 mm)but decreases Rsnow(-6.12 mm).The negative effect of glacier shrinkage on Rglacier has outweighed the positive effect of warming on Rglaciers resulting in the tipping point(peak water)for Rglacier having passed.Runoff projections indicate that future decreases in Rglacier and Rsnow could be offset by increases in Rrain due to increased precipitation projections,reducing the risk of shortages of available water resources.However,management authorities still need to develop adequate adaptation strategies to cope with the continuing decline in Rgacier in the future,considering the large inter-annual fluctuations and high uncertainty in precipitation projection.

东北寒区SWAT模型融雪径流空间异质性参数率定方法及应用——以白山流域为例

融雪水是东北地区春季径流的重要来源,融雪径流过程的可靠模拟及预报可为科学管理和调度春汛期水资源提供参考。东北寒区年度内存在融雪径流和降雨径流两种产流模式,流域物理空间属性差异对融雪径流产流模式影响显著,为了解决东北寒区融雪径流空间异质性问题、提高SWAT模型模拟及预报精度,提出对SWAT模型采用单站点和多站点联合参数率定的策略。首先,利用白山水库入库流量进行单站初步参数率定,进而,采用多站点对融雪径流参数进行率定,并将该参数移植到单站初步率定参数集。结果表明:单站初步参数率定后模拟得到年度(1—12月)、夏季汛期(6—9月)、春季融雪期(3—5月)验证期月尺度确定系数(R^(2))分别为0.76、0.74和0.58,日尺度R^(2)分别为0.71、0.75和0.51;单站和多站点联合参数率定后模拟得到年度、夏季汛期、春季融雪期验证期月尺度R^(2)分别为0.80、0.74和0.79,日尺度R^(2)分别为0.74、0.78和0.61。在月尺度和日尺度上,单站和多站点联合参数率定较单站参数率定后春季融雪期的模拟精度分别提高了20%和10%。

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。