Analysis of stochastic characteristics of the Benue River flow process

Stochastic characteristics of the Benue River streamflow process are examined under conditions of data austerity. The streamflow process is investigated for trend, non-stationarity and seasonality for a time period of 26 years. Results of trend analyses with Mann-Kendall test show that there is no trend in the annual mean discharges. Monthly flow series examined with seasonal Kendall test indicate the presence of positive change in the trend for some months, especially the months of August, January, and February. For the stationarity test, daily and monthly flow series appear to be stationary whereas at 1%, 5%, and 10% significant levels, the stationarity alternative hypothesis is rejected for the annual flow series. Though monthly flow appears to be stationary going by this test, because of high seasonality, it could be said to exhibit periodic stationarity based on the seasonality analysis. The following conclusions are drawn： （1） There is seasonality in both the mean and variance with unimodal distribution. （2） Days with high mean also have high variance. （3） Skewness coefficients for the months within the dry season period are greater than those of the wet season period, and seasonal autocorrelations for streamflow during dry season are generally larger than those of the wet season. Precisely, they are significantly different for most of the months. （4） The autocorrelation functions estimated ＂over time＂ are greater in the absolute value for data that have not been deseasonalised but were initially normalised by logarithmic transformation only, while autocorrelation functions for i = 1, 2 365 estimated ＂over realisations＂ have their coefficients significantly different from other coefficients.     

Cumulative impact of dam constructions on streamflow and sediment regime in lower reaches of the Jinsha River,China

The cumulative effect of cascade hydropower stations on river ecological environment has been widely concerned because of the significant streamflow hydrology change induced by dam constructions. The characteristics of the change in the lower reaches of the Jinsha River, China are analyzed based on long-term(1952–2015) hydrological and sedimentological data. The averaging coefficient, reservoir regulation coefficient(RRC), incoming sediment coefficient(ISC), and sediment transport modulus(STM), which reflect the variation of streamflow and sediment regimes, are defined and calculated. The results show that the construction and regulation of reservoirs reduces flow in flood season, increases flow in dry season, significantly altering the monthly discharge regimes. These alterations also led directly to changes in the timing of extreme flows at Pingshan Station. The monthly flow records at the basin outlet are reconstructed using stepwise regression, to reduce reservoir impacts. Comparisons of observed and reconstructed monthly flows demonstrate that the previous studies overestimated the cumulative effects of cascade reservoirs on flow processes. Furthermore, this study clearly illustrates that the reduction in sediment trapping and sediment transportation capacity together lead to the sharp reduction in annual sediment yield at the Pingshan Station. The earlier constructed reservoirs have more obvious effects on the ISC and STM than the more recent reservoirs and the effect of sediment trapping is related to reservoir location, on the main stream versus tributaries.     

Hydrological Processes in the Huaihe River Basin,China: Seasonal Variations,Causes and Implications

Understanding streamflow changes in terms of trends and periodicities and relevant causes is the first step into scientific management of water resources in a changing environment. In this study, monthly streamflow variations were analyzed using Modified Mann-Kendall(MM-K) trend test and Continuous Wavelet Transform(CWT) methods at 9 hydrological stations in the Huaihe River Basin. It was found that: 1) streamflow mainly occurs during May to September, accounting for 70.4% of the annual total streamflowamount with Cv values between 0.16–0.85 and extremum ratio values between 1.70–23.90; 2) decreased streamflow can be observed in the Huaihe River Basin and significant decreased streamflow can be detected during April and May, which should be the results of precipitation change and increased irrigation demand; 3) significant periods of 2–4 yr were detected during the 1960 s, the 1980 s and the 2000 s. Different periods were found at stations concentrated within certain regions implying periods of streamflow were caused by different influencing factors for specific regions; 4) Pacific Decadal Oscillation(PDO) has the most significant impacts on monthly streamflow mainly during June. Besides, Southern Oscillation Index(SOI), North Atlantic Oscillation(NAO) and the Ni?o3.4 Sea Surface Temperature(Ni?o3.4) have impacts on monthly streamflow with three months lags, and was less significant in time lag of six months. Identification of critical climatic factors having impacts on streamflow changes can help to predict monthly streamflow changes using climatic factors as explanatory variables. These findings were well corroborated by results concerning impacts of El Nino-Southern Oscillation(ENSO) regimes on precipitation events across the Huaihe River Basin. The results of this study can provide theoretical background for basin-scale management of water resources and agricultural irrigation.     

Daily and Monthly Suspended Sediment Load Predictions Using Wavelet Based Artificial Intelligence Approaches

In the current study, the efficiency of Wavelet-based Least Square Support Vector Machine(WLSSVM) model was examined for prediction of daily and monthly Suspended Sediment Load(SSL) of the Mississippi River. For this purpose, in the first step, SSL was predicted via ad hoc LSSVM and Artificial Neural Network(ANN) models; then,streamflow and SSL data were decomposed into subsignals via wavelet, and these decomposed sub-time series were imposed to LSSVM and ANN to simulate discharge-SSL relationship. Finally, the ability of WLSSVM was compared with other models in multistep-ahead SSL predictions. The results showed that in daily SSL prediction, LSSVM has better outcomes with Determination Coefficient(DC)=0.92 than ad hoc ANN with DC=0.88. However unlike daily SSL, in monthly modeling, ANN has a bit accurate upshot.WLSSVM and wavelet-based ANN(WANN) models showed same consequences in daily and different in monthly SSL predictions, and adding wavelet led to more accuracy of LSSVM and ANN. Furthermore,conjunction of wavelet to LSSVM and ANN evaluated via multi-step-ahead SSL predictions and, e.g.,DC LSSVM=0.4 was increased to the DC WLSSVM=0.71 in 7-day ahead SSL prediction. In addition, WLSSVM outperformed WANN by increment of time horizon prediction.     

Evaluating Suitability of Multiple Precipitation Products for the Lancang River Basin

Global reanalysis precipitation products could provide valuable meteorological information for flow forecasting in poorly gauged areas, helping to overcome a long-standing challenge in the field. But not all data sources are suitable for all regions or perform the same way in hydrological modeling, so it is essential to test the suitability of precipitation products before applying them. In this study, five widely used global high-resolution precipitation products—Asian Precipitation Highly Resolved Observational Data Integration Towards Evaluation of Water Resources(APHRODITE), National Centers for Environmental Prediction Climate Forecast System Reanalysis(NCEP-CFSR), Climate Hazards Group InfraRed Precipitation with Station Data(CHIRPS), China Gauge-based Daily Precipitation Analysis developed by China Meteorological Administration(CMA) and Agricultural Model Intercomparison and Improvement Project based on the NASA Modern-Era Retrospective Analysis for Research and Applications(AgMERRA)—were evaluated using statistical methods and a hydrological approach for their suitability for the Lancang River Basin. The results indicated that APHRODITE, CMA, AgMERRA and CHIRPS were more accurate precipitation indicators than NCEP-CFSR in terms of the multiyear average and seasonal spatial distribution pattern, all of the CHIRPS, Ag MERRA and APHRODITE perform better than CMA and NCEP-CFSR at the small, medium and high precipitation intensities ranges in subbasin11 and sunbabsin46. All five products performed better in subbasin46(a low-altitude region) than in subbasin11(a high-altitude region) on the daily and monthly scales. In addition to NCEP-CFSR, the other four products all presented encouraging potential for streamflow simulation at daily(Yunjinghong) and monthly(Yunjinghong, Jiuzhou and Gajiu) scale. Hydrological simulations forced with APHRODITE were the best of the five for the Yunjinghong station in capturing daily and monthly measured streamflow. Except for NCEP-CFSR, all products were very good for hydrological simulations for the Gajiu and Jiuzhou stations.     

Projection of future streamflow of the Hunza River Basin,Karakoram Range (Pakistan) using HBV hydrological model

Hydrologiska Byrans Vattenbalansavdeling(HBV) Light model was used to evaluate the performance of the model in response to climate change in the snowy and glaciated catchment area of Hunza River Basin. The study aimed to understand the temporal variation of streamflow of Hunza River and its contribution to Indus River System(IRS). HBV model performed fairly well both during calibration(R2=0.87, Reff=0.85, PBIAS=-0.36) and validation(R2=0.86, Reff=0.83, PBIAS=-13.58) periods on daily time scale in the Hunza River Basin. Model performed better on monthly time scale with slightly underestimated low flows period during bothcalibration(R2=0.94, Reff=0.88, PBIAS=0.47) and validation(R2=0.92, Reff=0.85, PBIAS=15.83) periods. Simulated streamflow analysis from 1995-2010 unveiled that the average percentage contribution of snow, rain and glacier melt to the streamflow of Hunza River is about 16.5%, 19.4% and 64% respectively. In addition, the HBV-Light model performance was also evaluated for prediction of future streamflow in the Hunza River using future projected data of three General Circulation Model(GCMs) i.e. BCC-CSM1.1, CanESM2, and MIROCESM under RCP2.6, 4.5 and 8.5 and predictions were made over three time periods, 2010-2039, 2040-2069 and 2070-2099, using 1980-2010 as the control period. Overall projected climate results reveal that temperature and precipitation are the most sensitiveparameters to the streamflow of Hunza River. MIROC-ESM predicted the highest increase in the future streamflow of the Hunza River due to increase in temperature and precipitation under RCP4.5 and 8.5 scenarios from 2010-2099 while predicted slight increase in the streamflow under RCP2.6 during the start and end of the 21 th century. However, BCCCSM1.1 predicted decrease in the streamflow under RCP8.5 due to decrease in temperature and precipitation from 2010-2099. However, Can ESM2 predicted 22%-88% increase in the streamflow under RCP4.5 from 2010-2099. The results of this study could be useful for decision making and effective future strategic plans for water management and their sustainability in the region.     

基于深度神经网络的GRACE等效水高及地表形变量预测

利用2002-04~2017-06 GRACE月时变重力场信息,反演得到三峡水库区域、长江流域和亚马逊流域的等效水高及地表垂直、水平形变时间序列。在LSTM(long short-term memory)网络基础上,通过堆叠LSTM结构以及在输出层中添加线性连接层来增加网络层数,构成深度LSTM神经网络对时间序列进行预测。引入注意力机制以提高模型对于序列长期特征的提取能力,并使用遗传算法筛选最佳网络层数和优化部分网络超参数。结果表明,在动态预测模式下,纳什系数NSE(Nash-Sutcliffe efficiency coefficient)最差为0.907 9,最好可达0.977 7,标准化的均方根误差R*(scaled root mean square error)最小为0.146 5,最大为0.297 5;在静态预测模式下,评价指标R*均低于0.062 2,NSE均大于0.99,表明模型性能优异。     

Snow cover variation and streamflow simulation in a snow-fed river basin of the Northwest Himalaya

Snowmelt is an important component of any snow-fed river system.The Jhelum River is one such transnational mountain river flowing through India and Pakistan.The basin is minimally glacierized and its discharge is largely governed by seasonal snow cover and snowmelt.Therefore,accurate estimation of seasonal snow cover dynamics and snowmeltinduced runoff is important for sustainable water resource management in the region.The present study looks into spatio-temporal variations of snow cover for past decade and stream flow simulation in the Jhelum River basin.Snow cover extent(SCE) was estimated using MODIS(Moderate Resolution Imaging Spectrometer) sensor imageries.Normalized Difference Snow Index(NDSI) algorithm was used to generate multi-temporal time series snow cover maps.The results indicate large variation in snow cover distribution pattern and decreasing trend in different sub-basins of the Jhelum River.The relationship between SCE-temperature,SCE-discharge and discharge-precipitation was analyzed for different seasons and shows strong correlation.For streamflow simulation of the entire Jhelum basin Snow melt Runoff Model(SRM) used.A good correlation was observed between simulated stream flow and in-situ discharge.The monthly discharge contribution from different sub-basins to the total discharge of the Jhelum River was estimated using a modified version of runoff model based on temperature-index approach developed for small watersheds.Stream power - an indicator of the erosive capability of streams was also calculated for different sub-basins.     

Hydrological impacts of climate change on streamflow of Dongliao River watershed in Jilin Province, China

The impacts of future climate change on streamflow of the Dongliao River Watershed located in Jilin Province,China have been evaluated quantitatively by using a general circulation model(HadCM3)coupled with the Soil and Water Assessment Tool(SWAT)hydrological model.The model was calibrated and validated against the historical monitored data from 2005 to 2009.The streamflow was estimated by downscaling HadCM3 outputs to the daily mean temperature and precipitation series,derived for three 30-year time slices,2020s,2050s and 2080s.Results suggest that daily mean temperature increases with a changing rate of 0.435℃per decade,and precipitation decreases with a changing rate of 0.761 mm per decade.Compared with other seasons,the precipitation in summer shows significant downward trend,while a significant upward trend in autumn.The annual streamflow demonstrates a general downward trend with a decreasing rate of 0.405 m3/s per decade.The streamflow shows significant downward and upward trends in summer and in autumn,respectively.The decreasing rate of streamflow in summer reaches 1.97 m 3 /s per decade,which contributes primarily to the decrease of streamflow.The results of this work would be of great benifit to the design of economic and social development planning in the study area.     

Identification of Suitable Hydrologic Response Unit Thresholds for Soil and Water Assessment Tool Streamflow Modelling

Use of a non-zero hydrologic response unit(HRU) threshold is an effective way of reducing unmanageable HRU numbers and simplifying computational cost in the Soil and Water Assessment Tool(SWAT) hydrologic modelling. However, being less representative of watershed heterogeneity and increasing the level of model output uncertainty are inevitable when minor HRU combinations are disproportionately eliminated. This study examined 20 scenarios by running the model with various HRU threshold settings to understand the mechanism of HRU threshold effects on watershed representation as well as streamflow predictions and identify the appropriate HRU thresholds. Findings show that HRU numbers decrease sharply with increasing HRU thresholds. Among different HRU threshold scenarios, the composition of land-use, soil, and slope all contribute to notable variations which are directly related to the model input parameters and consequently affect the streamflow predictions. Results indicate that saturated hydraulic conductivity, average slope of the HRU, and curve number are the three key factors affecting stream discharge when changing the HRU thresholds. It is also found that HRU thresholds have little effect on monthly model performance, while evaluation statistics for daily discharges are more sensitive than monthly results. For daily streamflow predictions, thresholds of 5%/5%/5%(land-use/soil/slope) are the optimum HRU threshold level for the watershed to allow full consideration of model accuracy and efficiency in the present work. Besides, the results provide strategies for selecting appropriate HRU thresholds based on the modelling goal.     

Impact of Meteorological Drought on Streamflow Drought in Jinghe River Basin of China

Under global climate change, drought has become one of the most serious natural hazards, affecting the ecological environ- ment and human life. Drought can be categorized as meteorological, agricultural, hydrological or socio-economic drought. Among the different categories of drought, hydrological drought, especially streamflow drought, has been given more attention by local govern- ments, researchers and the public in recent years. Identifying the occurrence of streamflow drought and issuing early warning can pro- vide timely information for effective water resources management. In this study, streamflow drought is detected by using the Standard- ized Runoff Index, whereas meteorological drought is detected by the Standardized Precipitation Index. Comparative analyses of fre- quency, magnitude, onset and duration are conducted to identify the impact of meteorological drought on streamflow drought. This study focuses on the Jinghe River Basin in Northwest China, mainly providing the following findings. 1） Eleven meteorological droughts and six streamflow droughts were indicated during 1970 and 1990 after pooling using Inter-event time and volume Criterion method. 2） Streamflow drought in the Jinghe River Basin lagged meteorological drought for about 127 days. 3） The frequency of streamflow drought in Jinghe River Basin was less than meteorological drought. However, the average duration of streamflow drought is longer. 4） The magnitude of streamflow drought is greater than meteorological drought. These results not only play an important theo- retical role in understanding relationships between different drought categories, but also have practical implications for streamflow drought mitigation and regional water resources management.     

Runoff responses to climate change in arid region of northwestern China during 1960–2010

Based on runoff, air temperature, and precipitation data from 1960 to 2010, the effects of climate change on water resources in the arid region of the northwestern China were investigated. The long-term trends of hydroclimatic variables were studied by using both Mann-Kendall test and distributed-free cumulative sum (CUSUM) chart test. Results indicate that the mean annual air temperature increases significantly from 1960 to 2010. The annual precipitation exhibits an increasing trend, especially in the south slope of the Tianshan Mountains and the North Uygur Autonomous Region of Xinjiang in the study period. Step changes occur in 1988 in the mean annual air temperature time series and in 1991 in the precipitation time series. The runoff in different basins shows different trends, i.e., significantly increasing in the Kaidu River, the Aksu River and the Shule River, and decreasing in the Shiyang River. Correlation analysis reveals that the runoff in the North Xinjiang (i.e., the Weigan River, the Heihe River, and the Shiyang River) has a strong positive relationship with rainfall, while that in the south slope of the Tianshan Mountains, the middle section of the north slope of the Tianshan Mountains and the Shule River has a strong positive relationship with air temperature. The trends of runoff have strong negative correlations with glacier coverage and the proportion of glacier water in runoff. From the late 1980s, the climate has become warm and wet in the arid region of the northwestern China. The change in runoff is interacted with air temperature, precipitation and glacier coverage. The results show that streamflow in the arid region of the northwestern China is sensitive to climate change, which can be used as a reference for regional water resource assessment and management.     

BDS卫星差分码偏差稳定性分析及其短期预报

利用MGEX(multi-GNSS experiment)发布的BDS卫星差分码偏差(differential code bias, DCB)产品，比较分析不同太阳活动水平下BDS卫星DCB产品的稳定性变化特性，并采用差分自回归移动平均(auto-regressive integrated moving average, ARIMA)时间序列预测模型，实现不同太阳活动水平下BDS卫星DCB的短期预报。结果表明，在太阳活动高年，BDS卫星DCB日解值稳定度、月稳定性均明显低于太阳活动低年，且不同卫星星座类型的BDS卫星DCB稳定性也存在差异；ARIMA时间序列预报结果与MGEX发布值符合程度较好，优于多项式拟合法预测结果。     

TRMM及GPM降水数据在高寒内陆河流域的准确性评估

降水数据的准确性和时空分辨率成为水文过程模拟的关键.卫星遥感降水资料的日益丰富为资料缺乏区的水文模拟带来了新的突破.本研究拟在资料缺乏、下垫面复杂,观测难、建模难的柴达木盆地高寒内陆河流域—巴音河中上游,基于近5年的TMPA 3B42、GPM IMERG V5及GPM IMERG V6逐日降水数据和气象站点观测数据建立...     

Hydrological Simulation Using TRMM and CHIRPS Precipitation Estimates in the Lower Lancang-Mekong River Basin

Satellite-based products with high spatial and temporal resolution provide useful precipitation information for data-sparse or ungauged large-scale watersheds. In the Lower Lancang-Mekong River Basin, rainfall stations are sparse and unevenly distributed, and the transboundary characteristic makes the collection of precipitation data more difficult, which has restricted hydrological processes simulation. In this study, daily precipitation data from four datasets(gauge observations, inverse distance weighted(IDW) data, Tropical Rainfall Measuring Mission(TRMM) estimates, and Climate Hazards Group InfraRed Precipitation with Stations(CHIRPS) estimates), were applied to drive the Soil and Water Assessment Tool(SWAT) model, and then their capability for hydrological simulation in the Lower Lancang-Mekong River Basin were examined. TRMM and CHIRPS data showed good performances on precipitation estimation in the Lower Lancang-Mekong River Basin, with the better performance for TRMM product. The Nash-Sutcliffe efficiency(NSE) values of gauge, IDW, TRMM, and CHIRPS simulations during the calibration period were 0.87, 0.86, 0.95, and 0.93 for monthly flow, respectively, and those for daily flow were 0.75, 0.77, 0.86, and 0.84, respectively. TRMM and CHIRPS data were superior to rain gauge and IDW data for driving the hydrological model, and TRMM data produced the best simulation performance. Satellite-based precipitation estimates could be suitable data sources when simulating hydrological processes for large data-poor or ungauged watersheds, especially in international river basins for which precipitation observations are difficult to collect. CHIRPS data provide long precipitation time series from 1981 to near present and thus could be used as an alternative precipitation input for hydrological simulation, especially for the period without TRMM data. For satellite-based precipitation products, the differences in the occurrence frequencies and amounts of precipitation with different intensities would affect simulation results of water balance components, which should be comprehensively considered in water resources estimation and planning.     

Evaluation of SWAT Model performance on glaciated and non-glaciated subbasins of Nam Co Lake,Southern Tibetan Plateau,China

This paper presents an assessment of the Soil and Water Assessment Tool(SWAT) on a glaciated(Qugaqie) and a non-glaciated(Niyaqu) subbasin of the Nam Co Lake. The Nam Co Lake is located in the southern Tibetan Plateau, two subbasins having catchment areas of 59 km~2 and 388 km~2, respectively. The scores of examined evaluation indices(i.e., R~2, NSE, and PBIAS) established that the performance of the SWAT model was better on the monthly scale compared to the daily scale. The respective monthly values of R~2, NSE, and PBIAS were 0.94, 0.97, and 0.50 for the calibration period while 0.92, 0.88, and -8.80 for the validation period. Glacier melt contribution in the study domain was simulated by using the SWAT model in conjunction with the Degree Day Melt(DDM) approach. The conjunction of DDM with the SWAT Model ensued improved results during both calibration(R~2=0.96, NSE=0.95, and PBIAS=-13.49) and validation (R~2=0.97, NSE=0.96, and PBIAS=-2.87) periods on the monthly time scale. Average contribution(in percentage) of water balance components to the total streamflow of Niyaqu and Qugaqie subbasins was evaluated. We found that the major portion(99.45%) of the streamflow in the Niyaqu subbasin was generated by snowmelt or rainfall surface runoff(SURF_Q), followed by groundwater(GW_Q, 0.47%), and lateral(LAT_Q, 0.06%) flows. Conversely, in the Qugaqie subbasin, major contributor to the streamflow(79.63%) was glacier melt(GLC_Q), followed by SURF_Q(20.14%), GW_Q(0.13%), and LAT_Q(0.089%). The contribution of GLC_Q was the highest(86.79%) in July and lowest(69.95%) in September. This study concludes that the performance of the SWAT model in glaciated catchment is weak without considering glacier component in modeling; however, it performs reasonably well in non-glaciated catchment. Furthermore, the temperature index approach with elevation bands is viable in those catchments where streamflows are driven by snowmelt. Therefore, it is recommended to use the SWAT Model in conjunction with DDM or energy base model to simulate the glacier melt contribution to the total streamflow. This study might be helpful in quantification and better management of water resources in data scarce glaciated regions.     

Impacts of global warming perturbation on water resources in arid zone: Case study of Kaidu River Basin in Northwest China

The main goal of this study was to assess the long-term impacts of global warming perturbation on water resources of the Kaidu River Basin in Northwest China. Temperature, precipitation and hydrology data during the past 29 years from 1979 to 2007 were collected and analyzed using parametric and non-parametric methods, the connection between temperature and precipitation by the combination of grey correlation analysis method and the hypothesis testing for trend of climate change. The results show a high inc...     

SWAT模型在土地利用/覆被变化剧烈地区的改进与应用

人口增长、气候变化、制度变迁、城市化等均会导致土地利用/覆被的变化,进而引起流域水文过程（截留、入渗、蒸散发和地下水补给等）和水循环过程的改变。当前,由于逐年土地利用/覆被数据获取困难、水文模型本身计算缺陷等问题,所有在流域尺度上开展的借助水文模型进行的土地利用/覆被变化影响下的水文模拟研究都存在一个共同缺点,就是采用的水文模型并不能逐年调用土地利用/覆被数据,即水文模型无法真实体现或模拟土地利用/覆被的时空变化。SWAT作为一个广泛应用的分布式水文模型,在其模拟期内,不能逐年调用土地利用/覆被数据,即在进行水文模拟时忽略了土地利用/覆被时间上的变化,这可能会影响其在土地利用/覆被变化剧烈地区（如黑河中游）的应用。黑河流域是典型的内陆河流域,也是中国西北地区第二大内陆河流域。黑河中游是黑河流域的径流耗散区。本文针对SWAT模型在考虑土地利用/覆被变化时的缺点,对其进行了改进并开发出能够逐年调用土地利用/覆被数据的LU-SWAT模型。在土地利用/覆被变化剧烈的黑河中游对SWAT和LU-SWAT模型的径流模拟效果进行比较,发现LU-SWAT模型更适用于黑河中游水循环模拟。     

Implications of climate change on streamflow of a snow-fed river system of the Northwest Himalaya

Air temperature and snow cover variability are sensitive indicators of climate change. This study was undertaken to forecast and quantify the potential streamflow response to climate change in the Jhelum River basin. The implications of air temperature trends (+0.11°C/decade) reported for the entire north-west Himalaya for past century and the regional warming (+0.7°C/decade) trends of three observatories analyzed between last two decades were used for future projection of snow cover depletion and stream flow. The streamflow was simulated and validated for the year 2007-2008 using snowmelt runoff model (SRM) based on in-situ temperature and precipitation with remotely sensed snow cover area. The simulation was repeated using higher values of temperature and modified snow cover depletion curves according to the assumed future climate. Early snow cover depletion was observed in the basin in response to warmer climate. The results show that with the increase in air temperature, streamflow pattern of Jhelum will be severely affected. Significant redistribution of streamflow was observed in both the scenarios. Higher discharge was observed during spring-summer months due to early snowmelt contribution with water deficit during monsoon months. Discharge increased by 5% 40% during the months of March to May in 2030 and 2050. The magnitude of impact of air temperature is higher in the scenario-2 based on regional warming. The inferences pertaining to change in future streamflow pattern can facilitate long term decisions and planning concerning hydro-power potential, waterresource management and flood hazard mapping in the region.     

Variations in sap flow of Zenia insignis under different rock bareness rate in North Guangdong,China

Understanding the impact of rock bareness on the transpiration in karst plants is essential to karst rocky desertification control and sustainable management of plantation in karst area.This study focused on the variations in sap flow of Zenia insignis caused by different rock bareness rate,and the impact of climate factors,soil water content(SWC)and leaf area index(LAI) on transpiration in karst plants,by continuously measuring sap flux densities (Fcd)of 12 sample trees using thermal dissipation probes and monitoring micrometeorology and SwC on a typical karst hill in north Guangdong of China during the year of 2016.Results show that:(1)the maximum hourly sap flux density occurred at11:00-14:00 and the peak daily sap flux density occurred in September.(2)Sap flow density of Zenia insignis increased with rock bareness rate at all hourly,daily and monthly scales,with the sequence of extremely severeseveremoderatemild rock bareness.(3)The transpiration of Zenia insi.gnis is controlled by different factors at different temporalscales.At hourly scale,transpiration was highly(n=144,R~20.72)correlated to Solar radiation(Rs),Air temperature(Ta),relative humidity(RH),and water vapor pressure deficit(VPD).At daily scale,transpiration was greatly(n=366,R20.31)affected by Solar radiation(Rs),Air temperature(Ta),and water vapor pressure deficit (VPD).While at monthly scale,transpiration was mainly(n=12,R~2=0.85)controlled by LAI.Our study proved that Zenia insi.gnis has a good physiecological adaption to fragile karst environment,and Zenia insignis plantation has long-term sustainability even in extremely rocky landscapes.The results may provide scientific basis for plantation management and ecological restoration in karst area.