Snowmelt runoffis an important component of water resources in the Northwest China(NWC).With global cli-mate warming and the increasing frequency of extreme events,snowmelt floods have caused significant damage.Howeve...Snowmelt runoffis an important component of water resources in the Northwest China(NWC).With global cli-mate warming and the increasing frequency of extreme events,snowmelt floods have caused significant damage.However,current studies lack comprehensive research and systematic risk assessments of snowmelt floods across the NWC.Based on the snowmelt runoffsimulated by GLDAS-NOAH model(1948-2022),the multiple indicators of snowmelt floods were retrieved by Peaks Over Threshold(POT)model in the NWC,and comprehensive risk assessment was conducted by integrating socio-economic data.The results indicated that the snowmelt runoffin the NWC shows a significant increasing trend and exhibits a spatial pattern of being more abundant in the northwest and southwest edges while less in the central and eastern regions.In Northern Xinjiang,snowmelt floods occurred relatively infrequently but with large magnitudes,while around the Qilian Mountains,snowmelt floods were more frequent but of smaller magnitudes.The longest duration of snowmelt floods was observed in the Kashgar and Yarkant River.Basins near mountainous areas are prone to snowmelt floods,especially the Tongtian and Lancang River basins,as well as the Ebinur Lake,Ili River basin,and the rivers south of the Altai Mountains,which face the highest risk of snowmelt floods.Based on comprehensive assessment of hazard,expo-sure,vulnerability and adaptability,high and very high-risk areas account for 15.5%of the NWC.It is urgent to enhance monitoring,early warning systems,and implement corresponding disaster prevention and mitigation measures in large mountainous basins.展开更多
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. T...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.展开更多
[Objective] The study aimed to apply energy balance snowmelt model for estimating the snowmelt runoff generated by seasonal snow in Tianshan Mountains. [Method] Three snow water collecting sites were set on a sunny sl...[Objective] The study aimed to apply energy balance snowmelt model for estimating the snowmelt runoff generated by seasonal snow in Tianshan Mountains. [Method] Three snow water collecting sites were set on a sunny slope in western Tianshan Mountains to measure the snowmelt rates at hourly interval. The positive sensible heat and negative latent heat fluxes were calculated by the energy balance snowmelt model; the snowmelt rate was also estimated by the model. Finally, the ac- curacy for the model was investigated in detail. [Result] The results indicated that sensible heat fluxes and latent heat fluxes accounted for 13.4% of total energy input and 15.1% of energy output, respectively. A good agreement between observed and estimated SWE was proved by low volume difference and the high Nash-Sutcliff coef- ficients（R2） which were 0.86, 0.92 and 0.91, respectively. [Conclusion] The energy balance snowmelt model has been proved to be a powerful tool for snowmelt estimation.展开更多
Water resources in the arid land of Northwest China mainly derive from snow and glacier melt water in mountainous areas. So the study on onset, cessation, length, tempera- ture and precipitation of snowmelt period is ...Water resources in the arid land of Northwest China mainly derive from snow and glacier melt water in mountainous areas. So the study on onset, cessation, length, tempera- ture and precipitation of snowmelt period is of great significance for allocating limited water resources reasonably and taking scientific water resources management measures. Using daily mean temperature and precipitation from 8 mountainous weather stations over the pe- riod 1960-2010 in the arid land of Northwest China, this paper analyzes climate change of snowmelt period and its spatial variations and explores the sensitivity of runoff to length, temperature and precipitation of snowmelt period. The results show that mean onset of snowmelt period has shifted 15.33 days earlier while mean ending date has moved 9.19 days later. Onset of snowmelt period in southern Tianshan Mountains moved 20.01 days earlier while that in northern Qilian Mountains moved only 10.16 days earlier. Mean precipitation and air temperature increased by 47.3 mm and 0.857~C in the mountainous areas of Northwest China, respectively. The precipitation of snowmelt period increased the fastest, which is ob- served in southern Tianshan Mountains, up to 65 mm, and the precipitation and temperature in northern Kunlun Mountains increased the slowest, an increase of 25 mm and 0.617~C, respectively, while the temperature in northern Qilian Mountains increased the fastest, in- creasing by 1.05~C. The annual runoff is also sensitive to the variations of precipitation and temperature of snowmelt period, because variation of precipitation induces annual runoff change by 7.69% while change of snowmelt period temperature results in annual runoff change by 14.15%.展开更多
Spring snowmelt peak flow （SSPF） can cause serious damage. Precipitation as rainfall directly contributes to the SSPF and influences the characteristics of the SSPF, while temperature indirectly impacts the SSPF by ...Spring snowmelt peak flow （SSPF） can cause serious damage. Precipitation as rainfall directly contributes to the SSPF and influences the characteristics of the SSPF, while temperature indirectly impacts the SSPF by shaping snowmelt rate and determining the soil frozen state which partitions snowmelt water into surface runoff and soil infiltration water in spring. It is necessary to identify the important and significant paths of climatic factors influencing the SSPF and provide estimates of the magnitude and significance of hypothesized causal connections between climatic factors and the SSPF. This study used path analysis with a selection of five factors - the antecedent precipitation index （API）, spring precipitation （SP）, winter precipitation as snowfall （WS）, 〈0℃ temperature accumulation in winter （[ATNI）, and average 〉0℃temperature accumulation in spring （AT） - to analyze their influences on the SSPF in the Kaidu River in Xinjiang, China. The results show that {ATN}, AT and WS have a significant correlation with the SSPF, while API and SP do not show a significant correlation. AT and WS directly influence the SSPF, while as the influence of[ATN] on SSPF is indirect through WS and AT. The indirect influence of [ATN[ on SSPF through WS accounts for 69% of the total influence of [ATN] on SSPF. Compared to the multiple linear regression method, path analysis provides additional valuable information, including influencing paths from independent variables to the dependent variable as well as direct and indirect impacts of external variables on the internal variable. This information can help improve the description of snow melt and spring runoff in hydrologic models as well as the planning and management of water resources.展开更多
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...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.展开更多
In order to predict long-term flooding under extreme weather conditions in central Asia, an energy balance-based distributed snowmelt runoff model was developed and coupled with the Soil and Water Assessment Tool(SWAT...In order to predict long-term flooding under extreme weather conditions in central Asia, an energy balance-based distributed snowmelt runoff model was developed and coupled with the Soil and Water Assessment Tool(SWAT) model. The model was tested at the Juntanghu watershed on the northern slope of the Tian Shan Mountains, Xinjiang,China. We compared the performances of temperature-index method and energy balanced method in SWAT model by taking Juntanghu river basin as an application example(as the simulation experiment was conducted in Juntanghu River, we call the energy balanced method as SWAT-JTH). The results suggest that the SWAT snowmelt model had overall Nash-Sutcliffe efficiency(NSE) coefficients ranging from 0.61 to 0.85 while the physical based approach had NSE coefficients ranging from 0.58 to0.69. Overall, on monthly scale, the SWAT model provides better results than that from the SWAT-JTH model. However, results generated from both methods seem to be fairly close at a daily scale. Thestructure of the temperature-index method is simple and produces reasonable simulation results if the parameters are well within empirical ranges. Although the data requirement for the energy balance method in current observation is difficult to meet and the existence of uncertainty is associated with the experimental approaches of physical processes, the SWAT-JTH model still produced a reasonably high NSE. We conclude that using temperature-index methods to simulate the snowmelt process is sufficient, but the energy balance-based model is still a good choice to simulate extreme weather conditions especially when the required data input for the model is acquired.展开更多
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 radiat...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.展开更多
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 ...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.展开更多
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...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.展开更多
Microwave radiometer SSM/I data and scatterometer QuikSCAT data have been widely used for the icesheet near-surface snowmelt detection based on their sensitivity to liquid water present in snow. In order to improve th...Microwave radiometer SSM/I data and scatterometer QuikSCAT data have been widely used for the icesheet near-surface snowmelt detection based on their sensitivity to liquid water present in snow. In order to improve the Antarctic ice-sheet near-surface snowmelt detection accuracy, a new Antarctic icesheet near-surface snowmelt synergistic detection method was proposed based on the principle of complementary advantages of SSM/I data(high reliability) and QuikSCAT data(high sensitivity) by the use of edge detection model to automatically extract the edge information to get the distribution of Antarctic snowmelt onset date, snowmelt duration and snowmelt end date. The verification result shows that the proposed snowmelt synergistic detection method improves the detection accuracy from about 75% to 86% based on AWS(Automatic Weather Stations) Butler Island and Larsen Ice Shelf. The algorithm can also be applied to other regions, which provides methodological support and supplement for the global snowmelt detection.展开更多
In this study, meteorological factors and snowmelt rate at an open site on sunny slope(OPS) and beneath forest canopy openness on shady slope(BFC) were measured using an automatic weather station and snow lysimeter du...In this study, meteorological factors and snowmelt rate at an open site on sunny slope(OPS) and beneath forest canopy openness on shady slope(BFC) were measured using an automatic weather station and snow lysimeter during the snowmelt period in 2009, 2010 and 2013. The energy budget over snow surface was calculated according to these meteorological datasets. The analysis results indicated that the net shortwave radiation(K) and sensible heat flux(H) were energy sources, and the latent heat flux(LVE) was energy sinks of snow surfaces at all sites. The net longwave radiation(L) was energy sink at OPS and 80% BFC, but energy source at 20% BFC. The gain of K, H, and the loss of LVE at BFC were obviously lower than those at OPS. The L was the maximum difference of energy budget between snow surface at BFC and OPS. In warm and wet years, the most important factor of the energy budget variation at OPS was air humidity and the second mostimportant factor was air temperature. However, the ground surface temperature on the sunny slope was the most important factor for L and energy budget at BFC. With the increases in forest canopy openness and the slope of adjacent terrains, the influences of ground surface temperature on the sunny slope on L and the energy budget over snow surface at BFC increased, especially when the snow cover on the sunny slope melts completely.展开更多
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 a...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.展开更多
The main goal of this study has been to map flood and assess land surface short-term dynamics in relation with snowy weather. The two recent snowfall events, which happened in, February 14<sup>th</sup> and...The main goal of this study has been to map flood and assess land surface short-term dynamics in relation with snowy weather. The two recent snowfall events, which happened in, February 14<sup>th</sup> and 15<sup>th</sup>, of year 2021, and February 3<sup>rd</sup> and 4<sup>th</sup>, of year 2022, were chosen. A pre-analysis correlation was assumed between, the snow events, recurrency of floods, and changes in the land surface characteristics (i.e., wetness, energy, temperature), in a “Before-During-After” scenario. Active and passive microwave satellites data such as, Sentinel-1 synthetic aperture radar (SAR), Sentinel-2 multispectral instrument (MSI) and Landsat-9 Operation Land Imager-2/Thermal Infrared Sensors-2 (OLI-2/TIRS-2), as well as cloud databased global models for water and urban layers were used. The first step of processing was thresholding of SAR image, at 0.25 cutoff, based on bimodal histogram distribution, followed by the change analysis. The following processing consisted in the images transformation, by computing the tasseled cap transformation wetness (TCTw) and the surface albedo on MSI image. In addition, the land surface temperature (LST) was modeled from OLI-2/TIRS-2 image. Then, a 5<sup>th</sup> order polynomial regression was computed, between TCTw as dependent variable and, albedo and LST as independent variables. As a first result, an area of 5.6 km<sup>2</sup> has been mapped as recurrently flooded from the two years assessment. The other output highlighted a constant increase of wetness (TCTw), considered most influential on land surface dynamics, comparatively to energy exchange (albedo) and temperature (LST). The “After” event dependency between the three indicators was highest, with a correlation coefficient, R<sup>2</sup> = 0.682, confirming the persistence of wetness after-snowmelt. Validation over topographic layers confirmed that, recurrently flooded areas are mostly distributed on, lowest valley depth points, farthest distances from channel network (i.e., from perennial waters), and lowest relative slope position areas. Whereas, 88.9% of the validation sampling were confirmed in the laboratory, and 86.7% of urban validation points were assessed as recurrently flooded when combining pre-/post-field-work campaign.展开更多
Southeast China,a densely populated and economically developed region,has experienced an increase in extreme precipitation in recent years.However,the current understanding of the influencing factors and related mecha...Southeast China,a densely populated and economically developed region,has experienced an increase in extreme precipitation in recent years.However,the current understanding of the influencing factors and related mechanisms of extreme precipitation remains incomplete.This study investigates the possible impact of spring Eurasian snowmelt on July extreme precipitation in Southeast China,using observational and reanalysis datasets.Singular Value Decomposition(SVD)analysis was used to explore the relationship between spring snowmelt and July extreme precipitation.The dominant SVD mode reveals that significantly increased snowmelt over the high latitudes of Eurasia and decreased snowmelt over the western and eastern sides of the midlatitudes of Eurasia tend to be accompanied by a meridional dipole pattern of extreme precipitation anomalies over Southeast China,with a positive center over the Yangtze River basin(YRB)and a negative center over South China(SC),and vice versa.Further analysis indicates that the soil moisture anomaly induced by the spring snowmelt anomaly can persist until July,modulating the land surface energy budget and atmospheric circulation conditions.When a snowmelt anomaly occurs,a distinct wave train type anomalous circulation develops over Eurasia,propagating southeastward from mid–high latitudes to South China,resulting in an anomalous cyclonic circulation around the Sea of Japan and North China,and an intensified western North Pacific subtropical high(WNPSH).The anomalous sinking motion related to the strengthened WNPSH inhibits water vapor convergence and results in reduced extreme precipitation over SC.In contrast,the anomalous southwesterly winds on the western flank of the WNPSH transport warm and moist air northward and converge with the anomalous northerly flow over the YRB,contributing to intense moisture convergence,which increases precipitation potential and the likelihood of extreme rainfall.Our findings provide valuable insights for improving the understanding and prediction of July extreme precipitation in Southeast China.展开更多
Some analytical results of the measured runoff during 1950s to 1980s at outlet hydrological stations of 33 main rivers and climatic data collected from 84 meteorological stations in Xinjiang Autonomous Region are pres...Some analytical results of the measured runoff during 1950s to 1980s at outlet hydrological stations of 33 main rivers and climatic data collected from 84 meteorological stations in Xinjiang Autonomous Region are presented.Comparison of hydrological and climatic parameters before and after 1980 shows that the spring runoff for most rivers after 1980s increased obviously at a rate of about 10％, though the spring air temperature did not rise very much. Especially,an increment by 20％ for alpine runoff is observed during May when intensive snow melting occurred in the alpine region. To the contrary, the runoff in June decreased about 5％. When the summer or annual runoff is taken into account,direct relationship can be found between the change in runoff and the ratio of glacier-coverage, except the runoff in August when the glacier melting is strong, indicating that climatic warming has an obvious effect on the contribution of glacier melting to the runoff increase.展开更多
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 cl...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.展开更多
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 fract...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展开更多
基金supported by China-Pakistan joint program of the Chi-nese Academy of Sciences(Grant No.046GJHZ2023069MI)National Natural Science Foundation of China(Grant No.42371145)the program of the Key Laboratory of Cryospheric Science and Frozen Soil Engineering,CAS(Grant No.CSFSE-ZZ-2402).
文摘Snowmelt runoffis an important component of water resources in the Northwest China(NWC).With global cli-mate warming and the increasing frequency of extreme events,snowmelt floods have caused significant damage.However,current studies lack comprehensive research and systematic risk assessments of snowmelt floods across the NWC.Based on the snowmelt runoffsimulated by GLDAS-NOAH model(1948-2022),the multiple indicators of snowmelt floods were retrieved by Peaks Over Threshold(POT)model in the NWC,and comprehensive risk assessment was conducted by integrating socio-economic data.The results indicated that the snowmelt runoffin the NWC shows a significant increasing trend and exhibits a spatial pattern of being more abundant in the northwest and southwest edges while less in the central and eastern regions.In Northern Xinjiang,snowmelt floods occurred relatively infrequently but with large magnitudes,while around the Qilian Mountains,snowmelt floods were more frequent but of smaller magnitudes.The longest duration of snowmelt floods was observed in the Kashgar and Yarkant River.Basins near mountainous areas are prone to snowmelt floods,especially the Tongtian and Lancang River basins,as well as the Ebinur Lake,Ili River basin,and the rivers south of the Altai Mountains,which face the highest risk of snowmelt floods.Based on comprehensive assessment of hazard,expo-sure,vulnerability and adaptability,high and very high-risk areas account for 15.5%of the NWC.It is urgent to enhance monitoring,early warning systems,and implement corresponding disaster prevention and mitigation measures in large mountainous basins.
基金supported by the National Basic Research Program of China(Grant No.2006CB400502)the World Bank Cooperative Project(Grant No.THSD-07)the 111 Program of the Ministry of Education and the State Administration of Foreign Expert Affairs,China(Grant No.B08048)
文摘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.
基金Supported by the Knowledge Innovation project of Chinese Academy of Sciences(CAS)(KZCX2-YW-334)Initiative Project of State Key Basic Research and Development Program of China(973Program,2009CB426309)~~
文摘[Objective] The study aimed to apply energy balance snowmelt model for estimating the snowmelt runoff generated by seasonal snow in Tianshan Mountains. [Method] Three snow water collecting sites were set on a sunny slope in western Tianshan Mountains to measure the snowmelt rates at hourly interval. The positive sensible heat and negative latent heat fluxes were calculated by the energy balance snowmelt model; the snowmelt rate was also estimated by the model. Finally, the ac- curacy for the model was investigated in detail. [Result] The results indicated that sensible heat fluxes and latent heat fluxes accounted for 13.4% of total energy input and 15.1% of energy output, respectively. A good agreement between observed and estimated SWE was proved by low volume difference and the high Nash-Sutcliff coef- ficients（R2） which were 0.86, 0.92 and 0.91, respectively. [Conclusion] The energy balance snowmelt model has been proved to be a powerful tool for snowmelt estimation.
基金National Basic Research Program of China (973 Program), No.2010CB951003National Natural Science Foundation of China, No.40901105Knowledge Innovation Program of the CAS, No.KZCX2-YW-Q10-3-4
文摘Water resources in the arid land of Northwest China mainly derive from snow and glacier melt water in mountainous areas. So the study on onset, cessation, length, tempera- ture and precipitation of snowmelt period is of great significance for allocating limited water resources reasonably and taking scientific water resources management measures. Using daily mean temperature and precipitation from 8 mountainous weather stations over the pe- riod 1960-2010 in the arid land of Northwest China, this paper analyzes climate change of snowmelt period and its spatial variations and explores the sensitivity of runoff to length, temperature and precipitation of snowmelt period. The results show that mean onset of snowmelt period has shifted 15.33 days earlier while mean ending date has moved 9.19 days later. Onset of snowmelt period in southern Tianshan Mountains moved 20.01 days earlier while that in northern Qilian Mountains moved only 10.16 days earlier. Mean precipitation and air temperature increased by 47.3 mm and 0.857~C in the mountainous areas of Northwest China, respectively. The precipitation of snowmelt period increased the fastest, which is ob- served in southern Tianshan Mountains, up to 65 mm, and the precipitation and temperature in northern Kunlun Mountains increased the slowest, an increase of 25 mm and 0.617~C, respectively, while the temperature in northern Qilian Mountains increased the fastest, in- creasing by 1.05~C. The annual runoff is also sensitive to the variations of precipitation and temperature of snowmelt period, because variation of precipitation induces annual runoff change by 7.69% while change of snowmelt period temperature results in annual runoff change by 14.15%.
基金financially supported by the Project of State Key Basic R & D Program of China (973 Program, Grant No. 2010CB951002)the key deployment project of Chinese Academy of Sciences (Grant No. KZZD-EW-12-2)Chinese Academy of Sciences Visiting Professorship for Senior International Scientists (Grant No. 2011T2Z40)
文摘Spring snowmelt peak flow （SSPF） can cause serious damage. Precipitation as rainfall directly contributes to the SSPF and influences the characteristics of the SSPF, while temperature indirectly impacts the SSPF by shaping snowmelt rate and determining the soil frozen state which partitions snowmelt water into surface runoff and soil infiltration water in spring. It is necessary to identify the important and significant paths of climatic factors influencing the SSPF and provide estimates of the magnitude and significance of hypothesized causal connections between climatic factors and the SSPF. This study used path analysis with a selection of five factors - the antecedent precipitation index （API）, spring precipitation （SP）, winter precipitation as snowfall （WS）, 〈0℃ temperature accumulation in winter （[ATNI）, and average 〉0℃temperature accumulation in spring （AT） - to analyze their influences on the SSPF in the Kaidu River in Xinjiang, China. The results show that {ATN}, AT and WS have a significant correlation with the SSPF, while API and SP do not show a significant correlation. AT and WS directly influence the SSPF, while as the influence of[ATN] on SSPF is indirect through WS and AT. The indirect influence of [ATN[ on SSPF through WS accounts for 69% of the total influence of [ATN] on SSPF. Compared to the multiple linear regression method, path analysis provides additional valuable information, including influencing paths from independent variables to the dependent variable as well as direct and indirect impacts of external variables on the internal variable. This information can help improve the description of snow melt and spring runoff in hydrologic models as well as the planning and management of water resources.
基金supported by the National Natural Science Foundation of China(Grant No51069017)the Special Fund for Public Welfare Industry of Ministry of Water Resources of China(Grant No201001065)+1 种基金the Open-End Fund of Key Laboratory of Oasis Ecology,Xinjiang University(Grant No XJDX0206-2010-03)the Open-End Fund of the China Institute of Water Resources and Hydropower Research(Grant NoIWHR-SKL-201104)
文摘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.
基金financially supported by the Ministry of Water Resources (MWR) public sector research and special funds-the most stringent in arid zone water resources management key technologies (201301103)National Nature Science Foundation of China (NSFC) under Grant No. 41130641, 41201025+1 种基金Ministry of Education Key Laboratory of Eco-Oasis Open Topic-Moisture change in Central Asia and its influence on precipitation in Xinjang Province (XJDX0201-2013-07)the Tianshan Scholar Start-up Fund provided by Xinjiang University
文摘In order to predict long-term flooding under extreme weather conditions in central Asia, an energy balance-based distributed snowmelt runoff model was developed and coupled with the Soil and Water Assessment Tool(SWAT) model. The model was tested at the Juntanghu watershed on the northern slope of the Tian Shan Mountains, Xinjiang,China. We compared the performances of temperature-index method and energy balanced method in SWAT model by taking Juntanghu river basin as an application example(as the simulation experiment was conducted in Juntanghu River, we call the energy balanced method as SWAT-JTH). The results suggest that the SWAT snowmelt model had overall Nash-Sutcliffe efficiency(NSE) coefficients ranging from 0.61 to 0.85 while the physical based approach had NSE coefficients ranging from 0.58 to0.69. Overall, on monthly scale, the SWAT model provides better results than that from the SWAT-JTH model. However, results generated from both methods seem to be fairly close at a daily scale. Thestructure of the temperature-index method is simple and produces reasonable simulation results if the parameters are well within empirical ranges. Although the data requirement for the energy balance method in current observation is difficult to meet and the existence of uncertainty is associated with the experimental approaches of physical processes, the SWAT-JTH model still produced a reasonably high NSE. We conclude that using temperature-index methods to simulate the snowmelt process is sufficient, but the energy balance-based model is still a good choice to simulate extreme weather conditions especially when the required data input for the model is acquired.
基金funded by the National Natural Science Foundation of China (41771470, 51069017 and 41261090)
文摘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.
文摘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.
基金supported by the National Natural Science Foundation of China(Grant No.51069017)the International Collaborative Research Program of Xinjiang Science and Technology Commission(Grant No.20126013)
文摘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.
基金supported by National Natural Science Foundation of China(Grant No. 41606209)supported by National Key Research and Development Program of China (Grant No. 2016YFB0501501)+3 种基金supported by Fujian Provincial Key Laboratory of Photonics Technology, Key Laboratory of Optoelectronic Science and Technology for Medicine of Ministry of Education, Fujian Normal University, China(Grant No. JYG1707)supported by Polar Science Strategic Research Foundation of China (Grant No. 20150312)supported by the Fundamental Research Funds for the Henan Provincial Colleges and Universities (Grant No. 2015QNJH16)supported by Science and technology project of Zhengzhou Science and Technology Bureau(Grant No. 20150251)
文摘Microwave radiometer SSM/I data and scatterometer QuikSCAT data have been widely used for the icesheet near-surface snowmelt detection based on their sensitivity to liquid water present in snow. In order to improve the Antarctic ice-sheet near-surface snowmelt detection accuracy, a new Antarctic icesheet near-surface snowmelt synergistic detection method was proposed based on the principle of complementary advantages of SSM/I data(high reliability) and QuikSCAT data(high sensitivity) by the use of edge detection model to automatically extract the edge information to get the distribution of Antarctic snowmelt onset date, snowmelt duration and snowmelt end date. The verification result shows that the proposed snowmelt synergistic detection method improves the detection accuracy from about 75% to 86% based on AWS(Automatic Weather Stations) Butler Island and Larsen Ice Shelf. The algorithm can also be applied to other regions, which provides methodological support and supplement for the global snowmelt detection.
基金funded by the National Natural Science Foundation of China (41271098, 41171066)the National Key Technology Research and Development Program of the Ministry of Science and Technology of China (2012BAC23B01)
文摘In this study, meteorological factors and snowmelt rate at an open site on sunny slope(OPS) and beneath forest canopy openness on shady slope(BFC) were measured using an automatic weather station and snow lysimeter during the snowmelt period in 2009, 2010 and 2013. The energy budget over snow surface was calculated according to these meteorological datasets. The analysis results indicated that the net shortwave radiation(K) and sensible heat flux(H) were energy sources, and the latent heat flux(LVE) was energy sinks of snow surfaces at all sites. The net longwave radiation(L) was energy sink at OPS and 80% BFC, but energy source at 20% BFC. The gain of K, H, and the loss of LVE at BFC were obviously lower than those at OPS. The L was the maximum difference of energy budget between snow surface at BFC and OPS. In warm and wet years, the most important factor of the energy budget variation at OPS was air humidity and the second mostimportant factor was air temperature. However, the ground surface temperature on the sunny slope was the most important factor for L and energy budget at BFC. With the increases in forest canopy openness and the slope of adjacent terrains, the influences of ground surface temperature on the sunny slope on L and the energy budget over snow surface at BFC increased, especially when the snow cover on the sunny slope melts completely.
文摘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.
文摘The main goal of this study has been to map flood and assess land surface short-term dynamics in relation with snowy weather. The two recent snowfall events, which happened in, February 14<sup>th</sup> and 15<sup>th</sup>, of year 2021, and February 3<sup>rd</sup> and 4<sup>th</sup>, of year 2022, were chosen. A pre-analysis correlation was assumed between, the snow events, recurrency of floods, and changes in the land surface characteristics (i.e., wetness, energy, temperature), in a “Before-During-After” scenario. Active and passive microwave satellites data such as, Sentinel-1 synthetic aperture radar (SAR), Sentinel-2 multispectral instrument (MSI) and Landsat-9 Operation Land Imager-2/Thermal Infrared Sensors-2 (OLI-2/TIRS-2), as well as cloud databased global models for water and urban layers were used. The first step of processing was thresholding of SAR image, at 0.25 cutoff, based on bimodal histogram distribution, followed by the change analysis. The following processing consisted in the images transformation, by computing the tasseled cap transformation wetness (TCTw) and the surface albedo on MSI image. In addition, the land surface temperature (LST) was modeled from OLI-2/TIRS-2 image. Then, a 5<sup>th</sup> order polynomial regression was computed, between TCTw as dependent variable and, albedo and LST as independent variables. As a first result, an area of 5.6 km<sup>2</sup> has been mapped as recurrently flooded from the two years assessment. The other output highlighted a constant increase of wetness (TCTw), considered most influential on land surface dynamics, comparatively to energy exchange (albedo) and temperature (LST). The “After” event dependency between the three indicators was highest, with a correlation coefficient, R<sup>2</sup> = 0.682, confirming the persistence of wetness after-snowmelt. Validation over topographic layers confirmed that, recurrently flooded areas are mostly distributed on, lowest valley depth points, farthest distances from channel network (i.e., from perennial waters), and lowest relative slope position areas. Whereas, 88.9% of the validation sampling were confirmed in the laboratory, and 86.7% of urban validation points were assessed as recurrently flooded when combining pre-/post-field-work campaign.
基金Supported by the National Key Research and Development Program of China(2022YFF0801603)。
文摘Southeast China,a densely populated and economically developed region,has experienced an increase in extreme precipitation in recent years.However,the current understanding of the influencing factors and related mechanisms of extreme precipitation remains incomplete.This study investigates the possible impact of spring Eurasian snowmelt on July extreme precipitation in Southeast China,using observational and reanalysis datasets.Singular Value Decomposition(SVD)analysis was used to explore the relationship between spring snowmelt and July extreme precipitation.The dominant SVD mode reveals that significantly increased snowmelt over the high latitudes of Eurasia and decreased snowmelt over the western and eastern sides of the midlatitudes of Eurasia tend to be accompanied by a meridional dipole pattern of extreme precipitation anomalies over Southeast China,with a positive center over the Yangtze River basin(YRB)and a negative center over South China(SC),and vice versa.Further analysis indicates that the soil moisture anomaly induced by the spring snowmelt anomaly can persist until July,modulating the land surface energy budget and atmospheric circulation conditions.When a snowmelt anomaly occurs,a distinct wave train type anomalous circulation develops over Eurasia,propagating southeastward from mid–high latitudes to South China,resulting in an anomalous cyclonic circulation around the Sea of Japan and North China,and an intensified western North Pacific subtropical high(WNPSH).The anomalous sinking motion related to the strengthened WNPSH inhibits water vapor convergence and results in reduced extreme precipitation over SC.In contrast,the anomalous southwesterly winds on the western flank of the WNPSH transport warm and moist air northward and converge with the anomalous northerly flow over the YRB,contributing to intense moisture convergence,which increases precipitation potential and the likelihood of extreme rainfall.Our findings provide valuable insights for improving the understanding and prediction of July extreme precipitation in Southeast China.
基金Project supported by the Ministry of Science and Technology of China (Grant No.96-912-01-02) and the Chinese Academy of Sciences (Grant No. KZ-952-S1-216).
文摘Some analytical results of the measured runoff during 1950s to 1980s at outlet hydrological stations of 33 main rivers and climatic data collected from 84 meteorological stations in Xinjiang Autonomous Region are presented.Comparison of hydrological and climatic parameters before and after 1980 shows that the spring runoff for most rivers after 1980s increased obviously at a rate of about 10％, though the spring air temperature did not rise very much. Especially,an increment by 20％ for alpine runoff is observed during May when intensive snow melting occurred in the alpine region. To the contrary, the runoff in June decreased about 5％. When the summer or annual runoff is taken into account,direct relationship can be found between the change in runoff and the ratio of glacier-coverage, except the runoff in August when the glacier melting is strong, indicating that climatic warming has an obvious effect on the contribution of glacier melting to the runoff increase.
基金supported by“Western Light Project”(Grant No.2002407)the Chinese Academy of Sciences and The National High Technology Research and Development Program of China(863 Program-2002AA133062).
文摘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.
文摘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
