APHRODITE降水数据驱动的融雪径流模拟

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

Use of SWAT to determine the effects of climate and land use changes on streamflow and sediment concentration in the Purna River basin,India

A semi-distributed, physically based, basin-scale Soil and Water Assessment Tool (SWAT) model was developed to determine the key factors that influence streamflow and sediment concentration in Purna river basin in India and to determine the potential impacts of future climate and land use changes on these factors. A SWAT domain with a Geographical Information System (GIS) was utilized for simulating and determining monthly streamflow and sediment concentration for the period 1980–2005 with a calibration period of 1980–1994 and validation period of 1995 to 2005. Additionally, a sequential uncertainty fitting (SUFI-2) method within SWAT-CUP was used for calibration and validation purpose. The overall performance of the SWAT model was assessed using the coefficient of determination (R²) and Nash–Sutcliffe efficiency parameter (E_NS) for both calibration and validation. For the calibration period, the R² and E_NS values were determined to be 0.91 and 0.91, respectively. For the validation period, the R² and E_NS were determined to be 0.83 and 0.82, respectively. The model performed equally well with observed sediment data in the basin, with the R² and E_NS determined to be 0.80 and 0.75 for the calibration period and 0.75 and 0.65 for the validation, respectively. The projected precipitation and temperature show an increasing trend compared to the baseline condition. The study indicates that SWAT is capable of simulating long-term hydrological processes in the Purna river basin.     

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.     

Parameter estimation of SWAT and quantification of consequent confidence bands of model simulations

Soil and Water Assessment Tool (SWAT) is a river basin scale model widely used to study the impact of land management practices in large, complex watersheds. Even though model output uncertainties are generally recognized to affect watershed management decisions, those uncertainties are largely ignored in model applications. The uncertainties of SWAT simulations are quantified using various methods, but simultaneous attempt to calibrate a model so as to reduce the uncertainty are seldom done. This study aims to use an uncertainty reduction procedure that helps calibrate the SWAT model. The shuffled complex evolutionary metropolis algorithm for uncertainty analysis is employed for this purpose, and is demonstrated using the data from the St. Joseph River basin, USA. The values of the performance indices, the r² and the Nash–Sutcliffe efficiency (NSE) for the simulations during calibration period was found to be 0.81 (same for r² and NSE) and 0.79 for validation period indicating a good simulation by the model. The results also indicate that the algorithm helps reduce the uncertainty (percentage of coverage?=?62% and average width?=?19.2 m³/s), and also identifies the plausible range of parameters that simulate the processes with less uncertainty. The confidence bands of simulations are obtained that can be employed in making uncertainty-based decisions on watershed management practices.     

SWAT模型在海拉尔河流域径流模拟中的应用研究

以海拉尔河上游流域作为研究区域,基于Arc GIS构建SWAT分布式水文模型对流域水文过程进行模拟,通过对流域的基础数据整合,模型采用1999~2003年实测径流数据进行参数率定,将2004~2010年实测径流数据作为模型的验证期,对模型在海拉尔河上游的适用性进行研究。通过对月和年径流模拟值和实测值的比较,率定期和验证期的Nash系数Ens和相关系数R2分别在0.861~0.873和0.877~0.899之间。基于这两个评价标准可知:SWAT模型在海拉尔河上游流域有良好的适用性,可以为该流域的水资源管理提供依据。     

Spatiotemporal characteristics of earthquake disaster losses in China from 1993 to 2016

The present study analyzes the runoff response during extreme rain events over the basin of Subarnarekha River in India using soil and water assessment tool (SWAT). The SWAT model is configured for the Subarnarekha River basin with 32 sub-basins. Three gauging stations in the basin (viz., Adityapur, Jamshedpur and Ghatshila) were selected to assess the model performance. Daily stream flow data are taken from Central Water Commission, India—Water Resources Information System. Calibration and validation of the model were performed using the soil and water assessment tool-calibration uncertainty programs (SWAT-CUPs) with sequential uncertainty fitting (SUFI-2) algorithm. The model was run for the period from 1982 to 2011 with a calibration period from 1982 to 1997 and a validation period from 1998 to 2011. The sensitivity of basin parameters has been analyzed in order to improve the runoff simulation efficiency of the model. The study concluded that the model performed well in Ghatshila gauging station with a Nash–Sutcliffe efficiency (NSE) of 0.68 during calibration and 0.62 during validation at daily scale. The model, thus calibrated and validated, was then applied to evaluate the extreme monsoon rain events in recent years. Five extreme events were identified in Jamshedpur and Ghatshila sub-basins of Subarnarekha River basin. The simulation results were found to be good for the extreme events with the NSE of 0.89 at Jamshedpur and 0.96 at Ghatshila gauging stations. The findings of this study can be useful in runoff simulation and flood forecasting for extreme rainfall events in Subarnarekha River basin.     

Satellite-based rainfall estimation and discharge measurement of Middle Indus River,Pakistan

The impacts of floods and droughts are intensified by climate change, lack of preparedness, and coordination. The average rainfall in study area is ranging from 200 to 400 mm per year. Rain gauge generally provides very accurate measurement of point rain rates and the amounts of rainfall but due to scarcity of the gauge locations provides very general information of the area on regional scale. Recognizing these practical limitations, it is essential to use remote sensing techniques for measuring the quantity of rainfall in the Middle Indus. In this research, Tropical Rainfall Measuring Mission (TRMM) estimation can be used as a proxy for the magnitude of rainfall estimates from classical methods (rain gauge), quantity, and its spatial distribution for Middle Indus river basin. In order to use TRMM satellite data for discharge measurement, its accuracy is determined by statistically comparing it with in situ gauged data on daily and monthly bases. The daily R ² value (0.42) is significantly lower than monthly R ² value (0.82), probably due to the time of summation of TRMM 3-hourly precipitation data into daily estimates. Daily TRMM data from 2003 to 2012 was used as input forcing in Soil and Water Assessment Tool (SWAT) hydrological model along with other input parameters. The calibration and validation results of SWAT model give R ² = 0.72 and 0.73 and Nash-Sutcliffe coefficient of efficiency = 0.69 and 0.65, respectively. Daily and monthly comparison graphs are generated on the basis of model discharge output and observed data.     

提孜那甫河流域融雪径流模拟及不确定性分析

为了开展寒旱山区典型流域融雪径流过程的研究,提高融雪径流模型（SRM）在山区融雪地区的水文过程模拟精度,本文选取新疆提孜那甫河流域作为典型研究区,在SRM径流计算基础上,加入合适的基流数据并进行不确定性分析。考虑4种常见的基流分割方法（数字滤波法、加里宁法、BFI法（滑动最小值法）和HYSEP（hydrograph separation program）法）,基于贝叶斯理论,采用马尔科夫链蒙特卡洛（MCMC）模拟进行参数不确定性分析,对使用不同基流数据SRM的融雪径流模拟表现进行综合评价。分析结果表明,基于加里宁基流分割方法的模型（SRM_K）能够最佳地模拟研究区融雪径流过程（纳什系数NSE在识别期和验证期分别为0.866和0.721,大于其他对比模型）。MCMC模拟能够较好地识别SRM参数,获得可靠的参数后验概率分布。当实测降水资料缺乏或其代表性较差时,TRMM（tropical rainfall measuring mission）卫星数据能够描述研究区的降水过程特征。     

滦河流域土地利用/覆被变化的水文响应

以滦河流域为研究区,利用1985和2000年土地利用数据,结合SWAT分布式水文模型定量评价了流域土地利用/覆被变化的水文效应,并分析了流域地表径流变化与主要景观类型的响应关系。结果表明:SWAT（Soil and Water Assessment Tool）模型可以较好地模拟滦河流域的月流量过程,在研究区具有较好的适用性;1985—2000年流域林地向草地和耕地的转变导致流域年均地表径流和总径流量分别增加了12.6%和5.1%;并使得流域年均地表径流变化空间差异显著,整体呈增加趋势,且主要受到林地变化的影响,而在三道河子以上集水区地表径流的变化则主要受到耕地景观的影响。合理规划土地利用格局,对于流域水资源可持续利用具有重要意义。     

SWAT manual calibration and parameters sensitivity analysis in a semi-arid watershed in North-western Morocco

Being a laborious approach, manual calibration of hydrologic model in a semi-arid context requires in-depth knowledge of the watershed and as much as possible field input data to obtain reliable simulations. In this study, manual calibration and relative sensitivity analysis approaches of the SWAT model (Soil and Water Assessment Tool) were applied for water balance in a 1993 km² watershed (on the R’dom river) located in North-western Morocco. The watershed is located in a semi-arid area dominated by agro-forestry activities. The objectives of this study were (i) to perform a local sensitivity analysis of the SWAT model taking into consideration the watershed characteristics and (ii) to implement a detailed methodology of manual calibration and validation of the model in a semi-arid context. Sensitivity analysis has been carried out on 12 different SWAT input parameters, and has revealed that 4 input parameters only were the most influential ones on flow components of the R’dom watershed. Model manual calibration was conducted along 2006 and 2007 by comparing measured and predicted monthly and daily discharges and taking Nash-Sutcliffe coefficient (NSE), determination coefficient (R ²), and percent bias (PBIAS) as goodness-of-fit indicators. Validation has been performed by the same approach through 2008 and 2009 period. All final NSE values were above 0.5, R ² values exceeded 0.7, and PBIAS lower than 25% demonstrating satisfactory model performances over the study watershed conditions. The SWAT model set-up with measured input data, manually calibrated and validated, reflects well the real hydrologic processes occurring in the R’dom watershed and can be used to assess current and future conditions and to evaluate alternative management practices.     

Runoff Change in Taizihe River Basin Under Future Climate Change Based on HBV Model

Taking the Taizihe River Basin located in Liaoning Province as a study area, we applied HBV hydrological model to simulate the hydrological process of this river basin with the support of observed daily precipitation, mean temperature, hydrological data in Xiaolinzi hydrologic station, and global digital elevation model data from SRTM3, land utilization types, etc. According to the simulation results of daily runoff, the possible impact of future climate change on runoff was analyzed through forcing HBV model by RegCM4.4 dynamic downscaled climatic data. The results show that HBV model performed generally well for daily simulation of the Taizihe River Basin with Nash Sutcliffe coefficient and deterministic coefficient being all over 0.60 in the calibration period and validation period, and the response of flooding to precipitation were simulated better. This indicates the HBV model can be successfully applied to the Taizihe River Basin. Mean temperature will increase obviously with persistent rising trend by RegCM4.4 model in 2021-2070 under RCP4.5 scenario. Annual precipitation and runoff depth are expected to reduce a bit. Compared with the baseline period (1986-2005), annual runoff depth will increase by 9.79%. At the same time, the runoff depth will increase significantly in summer and autumn. The variation of runoff quantile indicates that both peak extreme runoff and dry extreme runoff will increase to different degrees than that in the baseline period. In the future, the Taizihe River Basin will be likely to experience extreme flooding.     

东北半干旱地区流域分布式水文模拟——以洮儿河流域为例

以东北半干旱地区典型流域-洮儿河流域为研究对象,应用SWAT模型对流域水文过程进行了模拟研究;选择流域上游子流域和中下游子流域分别进行参数敏感性分析,识别出影响模拟结果的敏感参数,研究发现部分参数敏感性存在空间变异性,分析主要原因在于气候和下垫面的空间异质性导致了流域上下游产流模式存在差异。采用1988-1997年水文气象数据进行模型率定和验证,结果表明：干流水文站月流量过程率定期Nash-Sutcliffe 效率系数平均值为0.78,验证期为0.72,相关系数都达到0.86以上,水量误差大多在20%以内,对日过程的模拟也有较高的精度;枯水年模拟结果较差,主要是因为流域降水站数量不够,难以反映降水的时空分布。对于水文、气象等资料相对缺乏的东北半干旱地区,SWAT模型的模拟结果总体令人满意,可以应用于与流域径流相关的各种模拟分析,研究成果对进一步加强洮儿河流域水资源综合管理提供了依据和手段。     

气候变化对玛纳斯河的径流量影响预测模拟分析

山区积雪和冰川融水径流是内陆干旱区的重要水资源, 研究全球变暖情景下温度对融雪径流的影响具有重要意义. 以典型的内陆河玛纳斯流域上游为例, 利用基于度-日因子算法的SRM(Snowmelt Runoff Model)融雪径流模型, 根据当前变化趋势和年内分配模拟出20种假定来模拟未来气候情景(气温上升1 ℃、 2 ℃、 3 ℃、 4 ℃和降水变化率为0、 ±10%、 ±20%的随机组合情况)下的河道径流量, 从而计算出径流量的变化率, 分析了温度和降水变化对径流量的影响. 结果表明: 对于以雪冰融水为主要补给的玛纳斯河, 随着温度和降水的增加, 径流量也会增加, 并会使融雪径流提前. 假定降水量不发生大的变化, 温度增高1 ℃, 径流量增大13%~16%; 在气温一定时, 降雨量增加10%, 径流量增加2%左右, 说明气温和降水都对干旱区内陆河山区径流形成具有重要影响. 该研究对制定气候变化情景下的水资源适应对策具有重要指导意义.     

Future climate change impact evaluation on hydrologic processes in the Bharalu and Basistha basins using SWAT model

Urbanisation and climate change can have adverse effects on the streamflow and water balance components in river basins. This study focuses on the understanding of different hydrologic responses to climate change between urban and rural basins. The comprehensive semi-distributed hydrologic model, SWAT (Soil and Water Assessment Tool), is used to evaluate how the streamflow and water balance components vary under future climate change on Bharalu (urban basin) and Basistha (rural basin) River basins near the Brahmaputra River in India based on precipitation, temperature and geospatial data. Based on data collected in 1990–2012, it is found that 98.78% of the water yield generated for the urban Bharalu River basin is by surface runoff, comparing to 75% of that for the rural Basistha basin. Comparison of various hydrologic processes (e.g. precipitation, discharge, water yield, surface runoff, actual evapotranspiration and potential evapotranspiration) based on predicted climate change scenarios is evaluated. The urban Bharalu basin shows a decrease in streamflow, water yield, surface runoff, actual evapotranspiration in contrast to the rural Basistha basin, for the 2050s and 2090s decades. The average annual discharge will increase a maximum 1.43 and 2.20 m³/s from the base period for representative concentration pathways (RCPs) such as 2.6 and 8.5 pathways in Basistha River and it will decrease a maximum 0.67 and 0.46 m³/s for Bharalu River, respectively. This paper also discusses the influence of sensitive parameters on hydrologic processes, future issues and challenges in the rural and urban basins.     

基于分布式水文模型的雅鲁藏布江径流水源组成解析

为开展河川径流的水源解析,构建过程描述和本构参数两方面均有较强物理性的分布式水文模型。以雅鲁藏布江为对象,利用水文分区曲线对降雨、融雪和融冰等不同水源主导的流量过程进行划分,以划分的流量过程线子集对相应水文过程参数进行分步率定,提高了水文模型参数的物理性,以此构建了雅鲁藏布江流域分布式水文模型及参数集,内部多个水文站点和流域雪水当量的验证表明模型具有良好的性能。基于模型解析了2001-2015年间雅鲁藏布江的径流水源组成,降雨、融雪、融冰水源对总径流量贡献的比例分别为66%、20%和14%。本文方法对高山寒区径流的水源解析有普遍意义,结果对理解气候变化下雅鲁藏布江径流变化趋势有参考价值。     

Effects of historical and projected land use/cover change on runoff and sediment yield in the Netravati river basin,Western Ghats,India

In this study, the effects of changes in historical and projected land use land cover (LULC) on monthly streamflow and sediment yield for the Netravati river basin in the Western Ghats of India are explored using land use maps from six time periods (1972, 1979, 1991, 2000, 2012, and 2030) and the soil and water assessment tool (SWAT). The LULC for 2030 is projected using the land change modeller with the assumption of normal growth. The sensitivity analysis, model calibration, and validation indicated that the SWAT model could reasonably simulate streamflow and sediment yield in the river basin. The results showed that the spatial extent of the LULC classes of urban (1.80–9.96%), agriculture (31.38–55.75%), and water bodies (1.48–2.66%) increased, whereas that of forest (53.04–27.03%), grassland (11.17–4.41%), and bare land (1.09–0.16%) decreased from 1972 to 2030. The streamflow increased steadily (7.88%) with changes in LULC, whereas the average annual sediment yield decreased (0.028%) between 1972 and 1991 and increased later (0.029%) until 2012. However, it may increase by 0.43% from 2012 to 2030. The results indicate that LULC changes in urbanization and agricultural intensification have contributed to the increase in runoff, amounting to 428.65 and 58.67 mm, respectively, and sediment yield, amounting to 348 and 43 ton/km², respectively, in the catchment area from 1972 to 2030. The proposed methodology can be applied to other river basins for which temporal digital LULC maps are available for better water resource management plans.     

基于分布式水文模型的雅鲁藏布江径流水源组成解析

为开展河川径流的水源解析，构建过程描述和本构参数两方面均有较强物理性的分布式水文模型。以雅鲁藏布江为对象，利用水文分区曲线对降雨、融雪和融冰等不同水源主导的流量过程进行划分，以划分的流量过程线子集对相应水文过程参数进行分步率定，提高了水文模型参数的物理性，以此构建了雅鲁藏布江流域分布式水文模型及参数集，内部多个水文站点和流域雪水当量的验证表明模型具有良好的性能。基于模型解析了2001—2015年间雅鲁藏布江的径流水源组成，降雨、融雪、融冰水源对总径流量贡献的比例分别为66%、20%和14%。本文方法对高山寒区径流的水源解析有普遍意义，结果对理解气候变化下雅鲁藏布江径流变化趋势有参考价值。     

Analysis of snowmelt model for flood forecast for water in arid zone: case of Tarim River in Northwest China

Field studies were carried out in Tarim River Basin, Northwest China for analysis of snowmelt model for flood forecast for a river in arid zone. Snow is a major source for water availability in arid zone of Northwest China where 50% of snow cover withdrew by sublimation during dry and cold climatic condition. The analysis of weekly forecast of daily discharges was helped by the temperature index model, ARIMA model for temperature and flow, D-IUH runoff model and D-IUH model estimation where the temperature forecast was used as driving variable; the numerical simulations were carried out using SUSA^® software for testing the sensitivity of the D-IUH to the input values of the parameter and an analysis of the forecast results against the set of input parameters resulted in a determination coefficient R ² = 0.5. The standard deviation was 3.28 and the mean for the Tarim River was 5.37 (mm d^?1) implying that the forecasted data is in strong agreement with the observed data. The combination of methods is better useful for calculation in order to avoid errors of appreciation.     

使用积雪遥感面积数据改善山区春季融雪径流模拟精度

随着寒区水文模拟研究的深入,春季融雪径流模拟误差大这一问题越来越明显.针对此问题,以八宝河流域为研究区,利用积雪衰减曲线将MODIS积雪面积比例产品转化为雪水当量,并用其更新分布式水文模型GBHM(Geomorphology-Based Hydrological Model)中模拟的雪水当量,达到提高春季融雪径流模拟精度的目的.利用GBHM模型对八宝河流域2005-2007年进行了模型预热,参数率定,同时选择2008年进行模型检验.结果表明:GBHM模型在八宝河流域有较好的径流模拟精度,年均纳什效率系数(NSE)达到0.64.但模型对春季融雪过程的模拟效果较差,通过引入积雪遥感数据,这一问题得到很大改善.加入积雪遥感数据后,2008年3-6月径流模拟精度NSE和相对偏差Bias分别由-1.0、-0.45改进为0.58、0.06,单点雪水当量模拟精度获得提高,流域水量平衡也更加合理.     

考虑径流成分的雅鲁藏布江月径流模拟

通过构建雅鲁藏布江流域分布式水文模型SWAT,并以1989~1998年为率定期,1999~2005年为验证期对3个水文站(奴各沙、羊村、奴下)的月径流进行了模拟。从模型参数组里选取径流成分模拟不同的2组参数,以Nash-Sutcliffe效率系数(NS)、相关系数(R~2)及相对误差(PBIAS)为评价指标,来分析模型的模拟结果好坏。结果表明:率定期内,在径流成分1下奴各沙、羊村站和奴下站的R~2值高达0.9以上,NS系数分别为0.9、0.92和0.72,PBIAS的值为7.1%、18.5%及34.2%,但径流成分与实际情况出入较大。而径流成分2下,模拟得到的评价指标虽然不是很高,但径流成分比较合理。验证期总体结论一致。因此,建议在模型率定验证中要充分考虑径流成分的作用,从而提高模型模拟的精度。