Study on snowmelt runoff simulation in the Kaidu River basin

Alpine snowmelt is an important generation mode for runoff in the source region of the Tarim River basin, which covers four subbasins characterized by large area, sparse gauge stations, mixed runoff supplied by snowmelt and rainfall, and remarkably spatially heterogeneous precipitation. Taking the Kaidu River basin as a research area, this study analyzes the influence of these characteristics on the variables and parameters of the Snow Runoff Model and discusses the corresponding determination strategy to improve the accuracy of snowmelt simulation and forecast. The results show that: (i) The temperature controls the overall tendency of simulated runoff and is dominant to simulation accuracy, as the measured daily mean temperature cannot represent the average level of the same elevation in the basin and that directly inputting it to model leads to inaccurate simulations. Based on the analysis of remote sensing snow maps and simulation results, it is reasonable to approximate the mean temperature with 0.5 time daily maximum temperature. (ii) For the conflict between the limited gauge sta-tion and remarkably spatial heterogeneity of rainfall, it is not realistic to compute rainfall for each elevation zone. After the measured rainfall is multiplied by a proper coefficient and adjusted with runoff coefficient for rainfall, the measured rainfall data can satisfy the model demands. (iii) Adjusting time lag according to the variation of snowmelt and rainfall position can improve the simulation precision of the flood peak process. (iv) Along with temperature, the rainfall increases but cannot be completely monitored by limited gauge stations, which results in precision deterioration.     

Application and evaluation of a snowmelt runoff model in the Tamor River basin,Eastern Himalaya using a Markov Chain Monte Carlo (MCMC) data assimilation approach

Previous studies have drawn attention to substantial hydrological changes taking place in mountainous watersheds where hydrology is dominated by cryospheric processes. Modelling is an important tool for understanding these changes but is particularly challenging in mountainous terrain owing to scarcity of ground observations and uncertainty of model parameters across space and time. This study utilizes a Markov Chain Monte Carlo data assimilation approach to examine and evaluate the performance of a conceptual, degree‐day snowmelt runoff model applied in the Tamor River basin in the eastern Nepalese Himalaya. The snowmelt runoff model is calibrated using daily streamflow from 2002 to 2006 with fairly high accuracy (average Nash–Sutcliffe metric ~0.84, annual volume bias < 3%). The Markov Chain Monte Carlo approach constrains the parameters to which the model is most sensitive (e.g. lapse rate and recession coefficient) and maximizes model fit and performance. Model simulated streamflow using an interpolated precipitation data set decreases the fractional contribution from rainfall compared with simulations using observed station precipitation. The average snowmelt contribution to total runoff in the Tamor River basin for the 2002–2006 period is estimated to be 29.7 ± 2.9% (which includes 4.2 ± 0.9% from snowfall that promptly melts), whereas 70.3 ± 2.6% is attributed to contributions from rainfall. On average, the elevation zone in the 4000–5500 m range contributes the most to basin runoff, averaging 56.9 ± 3.6% of all snowmelt input and 28.9 ± 1.1% of all rainfall input to runoff. Model simulated streamflow using an interpolated precipitation data set decreases the fractional contribution from rainfall versus snowmelt compared with simulations using observed station precipitation. Model experiments indicate that the hydrograph itself does not constrain estimates of snowmelt versus rainfall contributions to total outflow but that this derives from the degree‐day melting model. Lastly, we demonstrate that the data assimilation approach is useful for quantifying and reducing uncertainty related to model parameters and thus provides uncertainty bounds on snowmelt and rainfall contributions in such mountainous watersheds. Copyright © 2013 John Wiley & Sons, Ltd.     

Incorporating accumulated temperature and algorithm of snow cover calculation into the snowmelt runoff model

An accurate simulation of snowmelt runoff is of much importance in arid alpine regions. Data availability is usually an obstacle to use energy‐based snowmelt models for the snowmelt runoff simulation, and temperature‐based snowmelt models are more appealing in these regions. The snow runoff model is very popular nowadays, especially in the data sparse regions, because only temperature, precipitation and snow cover data are required for inputs to the model. However, this model uses average temperature as index, which cannot reflect the snowmelt simulation in the high altitude band. In this study, the snow runoff model is modified on the basis of accumulated active temperature. Snow cover calculation algorithm is added and is no longer needed as input but output. This makes the model able to simulate long‐time runoff and long‐time snow cover variation in every band. An examination of the improved model in the Manas River basin showed that the model is effective. It can reproduce the behaviour of the hydrology and can reflect the actual snow cover fluctuation. Copyright © 2012 John Wiley & Sons, Ltd.     

Snow cover and runoff modelling in a high mountain catchment with scarce data: effects of temperature and precipitation parameters

Snowmelt is an important source of runoff in high mountain catchments. Snowmelt modelling for alpine regions remains challenging with scarce gauges. This study simulates the snowmelt in the Karuxung River catchment in the south Tibetan Plateau using an altitude zone based temperature‐index model, calibrates the snow cover area and runoff simulation during 2003–2005 and validates the model performance via snow cover area and runoff simulation in 2006. In the snowmelt and runoff modelling, temperature and precipitation are the two most important inputs. Relevant parameters, such as critical snow fall temperature, temperature lapse rate and precipitation gradient, determine the form and amount of precipitation and distribution of temperature and precipitation in hydrological modelling of the sparsely gauged catchment. Sensitivity analyses show that accurate estimation of these parameters would greatly help in improving the snowmelt simulation accuracy, better describing the snow‐hydrological behaviours and dealing with the data scarcity at higher elevations. Specifically, correlation between the critical snow fall temperature and relative humidity and seasonal patterns of both the temperature lapse rate and the precipitation gradient should be considered in the modelling studies when precipitation form is not logged and meteorological observations are only available at low elevation. More accurate simulation of runoff involving snowmelt, glacier melt and rainfall runoff will improve our understanding of hydrological processes and help assess runoff impacts from a changing climate in high mountain catchments. Copyright © 2013 John Wiley & Sons, Ltd.     

雷达测雨误差及其对淮河流域径流模拟的影响

将雷达测雨数据与分布式水文模型相耦合进行径流过程模拟,分析雷达测雨误差及其径流过程模拟效果,研究雷达测雨误差对径流过程模拟的影响效应.在对淮河流域气象中心业务化的5种淮河流域雷达测雨数据进行误差分析的基础上,采用雷达测雨数据驱动HEC-HMS水文模型,模拟分析淮河息县水文站以上流域2007年7月1-10日强降雨集中期的径流过程.结果表明:利用雷达测雨数据的径流模拟结果与实测资料的模拟结果基本吻合,各种雷达测雨数据误差经过HEC-HMS水文模型传递后,误差明显减小.联合校准法对应的模拟效果最好,过程流量相对误差NBs'和洪峰流量相对误差Z'分别为-20.2%和-13.3%.     

Application of snowmelt runoff model for water resource management

Snow‐covered areas (SCAs) are the fundamental source of water for the hydrological cycle for some region. Accurate measurements of river discharge from snowmelt can help manage much needed water required for hydropower generation and irrigation purposes. This study aims to apply the snowmelt runoff model (SRM) in the Upper Indus basin by the Astore River in northern Pakistan for the years 2000 to 2006. The Shuttle Radar Topographic Mission (SRTM) data are used to generate the Digital Elevation Model (DEM) of the region. Various variables (snow cover depletion curves (SCDCs), temperature and precipitation) and parameters (degree‐day factor, recession coefficient, runoff coefficients, time lag, critical temperature and temperature lapse rate) are used as input in the SRM. However, snow cover data are direct and an important input to the SRM. Satellite data from the Moderate Resolution Imaging Spectroradiometer (MODIS) are used to estimate the SCA. Normalized difference snow index (NDSI) algorithm is applied for snow cover mapping and to differentiate snow from other land features. Nash–Sutcliffe coefficient of determination (R²) and volume difference (D_V) are used for quality assessment of the SRM. The results of the current research show that for the study years (2000–2006), the average value of R² is 0·87 and average volume difference D_V is 1·18%. The correlation coefficient between measured and computed runoff is 0·95. The results of the study further show that a high level of accuracy can be achieved during the snowmelt season. The simulation results endorse that the SRM in conjunction with MODIS snow cover product is very useful for water resource management in the Astore River and can be used for runoff forecasts in the Indus River basin in northern Pakistan. Copyright © 2011 John Wiley & Sons, Ltd.     

TEMPORAL AND SPATIAL CHARACTERISTICS OF RAINFALL IN THE NAM RIVER DAM BASIN OF KOREA

An investigation into rainfall variability in time and space in the Nam River dam basin of Korea is made with the use of the coefficient of variation and the correlation coefficient. The Nam River dam basin is a small mountainous watershed where wind direction and orography are the dominant influences on the pattern and distribution of rainfall. Rainfall distribution was found to vary with elevation, position, wind direction and distance from a reference station. The results of this study can be used in the design of rain gauge network, hydrological forecasting and for other applications in the Nam River dam basin.     

Modelling runoff using optical satellite remote sensing data in a high mountainous alpine catchment of Italy

Development of hydrological models for seasonal and real-time runoff forecast in rivers of high alpine catchments is useful for management of water resources. The conceptual models for this purpose are based on a temperature index and/or energy budget and can be either lumped or distributed over the catchment area. Remote sensing satellite data are most useful to acquire near real-time geophysical parameters in order to input to the distributed forecasting models. In the present study, integration of optical satellite remote sensing-derived information was made with ground meteorological and hydrological data, and predetermined catchment morphological parameters, to study the feasibility of application of a distributed temperature index snowmelt runoff model to one of the high mountainous catchments in the Italian Alps, known as Cordevole River Basin. Five sets of Landsat Multispectral Scanning System (MSS) and Thematic Mapper (TM) computer-compatible tapes (CCTs) were processed using digital image processing techniques in order to evaluate the snow cover variation quantitatively. Digital elevation model, slope and aspect parameters were developed and used during satellite data processing. The satellite scenes were classified as snow, snow under transition and snow free areas. A second-order polynomial fit has been attempted to approximate the snow depletion and to estimate daily snow cover areal extent for three elevation zones of the catchment separately. Model performance evaluation based on correlation coefficient, Nash–Sutcliffe coefficient and percentage volume deviation indicated very good simulation between measured and computed discharges for the entire snowmelt period. The use of average temperature values computed from the maximum and minimum temperatures into the model was studied and a suitable algorithm was proposed. © 1997 John Wiley & Sons, Ltd.     

Research on runoff forecast approaches to the Aksu River basin

The Aksu River (the international river between China and Kirghiz) has become the main water source for the Tarim River. It significantly influences the Tarim River’s formation, development and evolution. Along with the western region development strategy and the Tarim River basin comprehensive development and implementation, the research is now focused on the Aksu River basin hydrologic characteristic and hydrologic forecast. Moreover, the Aksu River is representative of rivers supplied with glacier and snow melt in middle-high altitude arid district. As a result, the research on predicting the river flow of the Aksu River basin has theoretical and practical significance. In this paper, considering the limited hydrometeorological data for the Aksu River basin, we have constructed four hydrologic forecast approaches using the daily scale to simulate and forecast daily runoff of two big branches of the Aksu River basin. The four approaches are the upper air temperature and the daily runoff correlation method, AR(p) runoff forecast model, temperature and precipitation revised AR(p) model and the NAM rainfall-runoff model. After comparatively analyzing the simulation results of the four approaches, we discovered that the temperature and precipitation revised AR(p) model, which needs less hydrological and meteorological data and is more predictive, is suitable for the short-term runoff forecast of the Aksu River basin. This research not only offers a foundation for the Aksu River and Tarim Rivers’ hydrologic forecast, flood prevention, control and the entire basin water collocation, but also provides the hydrologic forecast reference approach for other arid ungauged basins.     

Estimating source regions for snowmelt runoff in a Rocky Mountain basin: tests of a data‐based conceptual modeling approach

In many mountain basins, river discharge measurements are located far away from runoff source areas. This study tests whether a basic snowmelt runoff conceptual model can be used to estimate relative contributions of different elevation zones to basin‐scale discharge in the Cache la Poudre, a snowmelt‐dominated Rocky Mountain river. Model tests evaluate scenarios that vary model configuration, input variables, and parameter values to determine how these factors affect discharge simulation and the distribution of runoff generation with elevation. Results show that the model simulates basin discharge well (NSCE and R >0.90) when input precipitation and temperature are distributed with different lapse rates, with a rain‐snow threshold parameter between 0 and 3.3 °C, and with a melt rate parameter between 2 and 4 mm °C^?1 d^?1 because these variables and parameters can have compensating interactions with each other and with the runoff coefficient parameter. Only the hydrograph recession parameter can be uniquely defined with this model structure. These non‐unique model scenarios with different configurations, input variables, and parameter values all indicate that the majority of basin discharge comes from elevations above 2900 m, or less than 25% of the basin total area, with a steep increase in runoff generation above 2600 m. However, the simulations produce unrealistically low runoff ratios for elevations above 3000 m, highlighting the need for additional measurements of snow and discharge at under‐sampled elevations to evaluate the accuracy of simulated snow and runoff patterns. Copyright © 2013 John Wiley & Sons, Ltd.     

Research on runoff forecast approaches to the Aksu River basin

The Aksu River (the international river between China and Kirghiz) has become the main water source for the Tarim River. It significantly influences the Tarim River's formation, development and evolution. Along with the western region development strategy and the Tarim River basin comprehensive devel-opment and implementation, the research is now focused on the Aksu River basin hydrologic charac-teristic and hydrologic forecast. Moreover, the Aksu River is representative of rivers supplied with gla-cier and snow melt in middle-high altitude arid district. As a result, the research on predicting the river flow of the Aksu River basin has theoretical and practical significance. In this paper, considering the limited hydrometeorological data for the Aksu River basin, we have constructed four hydrologic forecast approaches using the daily scale to simulate and forecast daily runoff of two big branches of the Aksu River basin. The four approaches are the upper air temperature and the daily runoff correlation method, AR(p) runoff forecast model, temperature and precipitation revised AR(p) model and the NAM rainfall-runoff model. After comparatively analyzing the simulation results of the four approaches, we discovered that the temperature and precipitation revised AR(p) model, which needs less hydrological and meteorological data and is more predictive, is suitable for the short-term runoff forecast of the Aksu River basin. This research not only offers a foundation for the Aksu River and Tarim Rivers' hydrologic forecast, flood prevention, control and the entire basin water collocation, but also provides the hydrologic forecast reference approach for other arid ungauged basins.     

A distributed monthly hydrological model for integrating spatial variations of basin topography and rainfall

Hydrological models at a monthly time‐scale are important tools for hydrological analysis, such as in impact assessment of climate change and regional water resources planning. Traditionally, monthly models adopt a conceptual, lumped‐parameter approach and cannot account for spatial variations of basin characteristics and climatic inputs. A large requirement for data often severely limits the utility of physically based, distributed‐parameter models. Based on the variable‐source‐area concept, we considered basin topography and rainfall to be two major factors whose spatial variations play a dominant role in runoff generation and developed a monthly model that is able to account for their influences in the spatial and temporal dynamics of water balance. As a hybrid of the Xinanjiang model and TOPMODEL, the new model is constructed by innovatively making use of the highly acclaimed simulation techniques in the two existing models. A major contribution of this model development study is to adopt the technique of implicit representation of soil moisture characteristics in the Xinanjiang model and use the TOPMODEL concept to integrate terrain variations into runoff simulation. Specifically, the TOPMODEL topographic index ln(a/tanβ) is converted into an index of relative difficulty in runoff generation (IRDG) and then the cumulative frequency distribution of IRDG is used to substitute the parabolic curve, which represents the spatial variation of soil storage capacity in the Xinanjiang model. Digital elevation model data play a key role in the modelling procedures on a geographical information system platform, including basin segmentation, estimation of rainfall for each sub‐basin and computation of terrain characteristics. Other monthly data for model calibration and validation are rainfall, pan evaporation and runoff. The new model has only three parameters to be estimated, i.e. watershed‐average field capacity WM, pan coefficient η and runoff generation coefficient α. Sensitivity analysis demonstrates that runoff is least sensitive to WM and, therefore, it can be determined by a prior estimation based on the climate and soil properties of the study basin. The other two parameters can be determined using optimization methods. Model testing was carried out in a number of nested sub‐basins of two watersheds (Yuanjiang River and Dongjiang River) in the humid region in central and southern China. Simulation results show that the model is capable of describing spatial and temporal variations of water balance components, including soil moisture content, evapotranspiration and runoff, over the watershed. With a minimal requirement for input data and parameterization, this terrain‐based distributed model is a valuable contribution to the ever‐advancing technology of hydrological modelling. Copyright © 2006 John Wiley & Sons, Ltd.     

Cross-spectral analysis of rainfall and runoff for Raritan and Mullica river basins in New Jersey

Cross-correlation and cross-spectral analysis were employed in the analysis of rainfall and runoff in two river basins: the Raritan and Mullica River basins in New Jersey. Cross-covariance and coherence were studied in the correlograms for the following correlation cases: (a) rainfall-runoff for each one basin separately; (b) rainfall-rainfall analysis for two main meteorological stations in each one of the basins; (c) runoff-runoff for two main gaging stations in each one of the basins. From the estimates of the coherence at various frequencies the cross-spectral analysis shows a highly nonlinear relationship between rainfall and runoff in Raritan and Mullica River basins. A poor coherence observed at the annual cycles for each basin makes it difficult to predict the annual oscillations of runoff from those of rain-fall by a linear regression model. The high coherence between rainfall (or runoff) at the first station and rainfall (or runoff) at the second station within the same basin at almost all frequencies establishes an accurate prediction on a linear basis.     

Modelling the rainfall–runoff process of the Mara River basin using the Soil and Water Assessment Tool

The delicate balance between human utilization and sustaining its pristine biodiversity in the Mara River basin (MRB) is being threatened because of the expansion of agriculture, deforestation, human settlement, erosion and sedimentation and extreme flow events. This study assessed the applicability of the Soil and Water Assessment Tool (SWAT) model for long‐term rainfall–runoff simulation in MRB. The possibilities of combining/extending gage rainfall data with satellite rainfall estimates were investigated. Monthly satellite rainfall estimates not only overestimated but also lacked the variability of observed rainfall to substitute gage rainfall in model simulation. Uncertainties related to the quality and availability of input data were addressed. Sensitivity and uncertainty analysis was reported for alternative model components and hydrologic parameters used in SWAT. Mean sensitivity indices of SWAT parameters in MRB varied with and without observed discharge data. The manual assessment of individual parameters indicated heterogeneous response among sub‐basins of MRB. SWAT was calibrated and validated with 10 years of discharge data at Bomet (Nyangores River), Mulot (Amala River) and Mara Mines (Mara River) stations. Model performance varied from satisfactory at Mara Mines to fair at Bomet and weak at Mulot. The (Nash–Sutcliff efficiency, coefficient of determination) results of calibration and validation at Mara Mines were (0.68, 0.69) and (0.43, 0.44), respectively. Two years of moving time window and flow frequency analysis showed that SWAT performance in MRB heavily relied on quality and abundance of discharge data. Given the 5.5% area contribution of Amala sub‐basin as well as uncertainty and scarcity of input data, SWAT has the potential to simulate the rainfall runoff process in the MRB. Copyright © 2012 John Wiley & Sons, Ltd.     

太湖北岸湖滨带观测场水生植物群落特征及其影响因素分析

研究了鄱阳湖流域在1955-2002年间的径流系数的变化,重点分析了它与水循环的两个基本要素:降水量和蒸发量的关系,同时对其原因进行了初步的探讨.经分析,在鄱阳湖流域中,径流系数较大的是饶河流域和信江流域,较小的是抚河流域;在年内变化上,4-6月为五河流域径流系数比较大的月份,这与鄱阳湖流域降水集中期相对应.在空间上,4-6月仍然以饶河流域和信江流域相对较大,而抚河流域较小,特别是8月份的径流系数远小于其他四河;年代际变化上,1990s径流系数增加较为显著.尽管鄱阳湖流域的径流系数除了受气候因子的影响外,还受到水土流失和地形等因素的影响,但是降水量的增加,特别是暴雨频率的增加仍然是其主要影响因素,蒸发量的减小对径流系数的增加也有一定程度的影响.径流系数与气温并无明显的线性相关关系.     

Estimation of rainfall from infrared‐microwave satellite data for basin‐scale hydrologic modelling

The infrared‐microwave rainfall algorithm (IMRA) was developed for retrieving spatial rainfall from infrared (IR) brightness temperatures (TBs) of satellite sensors to provide supplementary information to the rainfall field, and to decrease the traditional dependency on limited rain gauge data that are point measurements. In IMRA, a SLOPE technique (ST) was developed for discriminating rain/no‐rain pixels through IR image cloud‐top temperature gradient, and 243K as the IR threshold temperature for minimum detectable rainfall rate. IMRA also allows for the adjustment of rainfall derived from IR‐TB using microwave (MW) TBs. In this study, IMRA rainfall estimates were assessed on hourly and daily basis for different spatial scales (4, 12, 20, and 100 km) using NCEP stage IV gauge‐adjusted radar rainfall data, and daily rain gauge data. IMRA was assessed in terms of the accuracy of the rainfall estimates and the basin streamflow simulated by the hydrologic model, Sacramento soil moisture accounting (SAC‐SMA), driven by the rainfall data. The results show that the ST option of IMRA gave accurate satellite rainfall estimates for both light and heavy rainfall systems while the Hessian technique only gave accurate estimates for the convective systems. At daily time step, there was no improvement in IR‐satellite rainfall estimates adjusted with MW TBs. The basin‐scale streamflow simulated by SAC‐SMA driven by satellite rainfall data was marginally better than when SAC‐SMA was driven by rain gauge data, and was similar to the case using radar data, reflecting the potential applications of satellite rainfall in basin‐scale hydrologic modelling. Copyright © 2010 John Wiley & Sons, Ltd.     

Effects of the catchment runoff coefficient on the performance of TOPMODEL in rainfall–runoff modelling

Effects of the catchment runoff coefficient on the performance of TOPMODEL in simulating catchment rainfall–runoff relationships are investigated in this paper, with an aim to improve TOPMODEL's simulation efficiency in catchments with a low runoff coefficient. Application of TOPMODEL in the semi‐arid Yihe catchment, with an area of 2623 km² in the Yellow River basin of China, produced a Nash–Sutcliffe model efficiency of about 80%. To investigate how the catchment runoff coefficient affects the performance of TOPMODEL, the whole observed discharge series of the Yihe catchment is multiplied with a larger‐than‐unity scale factor to obtain an amplified discharge series. Then TOPMODEL is used to simulate the amplified discharge series given the original rainfall and evaporation data. For a set of different scale factors, TOPMODEL efficiency is plotted against the corresponding catchment runoff coefficient and it is found that the efficiency of TOPMODEL increases with the increasing catchment runoff coefficient before reaching a peak (e.g. about 90%); after the peak, however, the efficiency of TOPMODEL decreases with the increasing catchment runoff coefficient. Based on this finding, an approach called the discharge amplification method is proposed to enhance the simulation efficiency of TOPMODEL in rainfall–runoff modelling in catchments with a low runoff coefficient. Copyright © 2004 John Wiley & Sons, Ltd.     

Snow and glacier melt in the Satluj River at Bhakra Dam in the western Himalayan region

Abstract

Streamflow in the Himalayan rivers is generated from rainfall, snow and ice. The distribution of runoff produced from these sources is such that the streamflow may be observed in these rivers throughout the year, i.e. they are perennial in nature. Snow and glacier melt runoff contributes substantially to the annual flows of these rivers and its estimation is required for the planning, development and management of the water resources of this region. The average contribution of snow and glacier melt runoff in the annual flows of the Satluj River at Bhakra Dam has been determined. Keeping in view the availability of data for the study basin, a water balance approach was used and a water budget period of 10 years (October 1986-September 1996) was considered for the analysis. The rainfall input to the study basin over the water budget period was computed from isohyets using rainfall data of 10 stations located at different elevations in the basin. The total volume of flow for the same period was computed using observed flow data of the Satluj River at Bhakra Dam. A relationship between temperature and evaporation was developed and used to estimate the evapotranspiration losses. The snow-covered area, and its depletion with time, was determined using satellite data. It was found that the average contribution of snow and glacier runoff in the annual flow of the Satluj River at Bhakra Dam is about 59%, the remaining 41% being from rain.     

Comparative application of two mathematical models to predict sedimentation in Yermasoyia Reservoir,Cyprus

The Yermasoyia Reservoir is located northeast of the town of Limassol, Cyprus. The storage capacity of the reservoir is 13·6 × 10⁶ m³. The basin area of the Yermasoyia River, which feeds the reservoir, totals 122·5 km². This study aims to estimate the mean annual deposition amount in the reservoir, which originates from the corresponding basin. For the estimate of the mean annual sediment inflow into the reservoir, two mathematical models are used alternatively. Each model consists of three submodels: a rainfall‐runoff submodel, a soil erosion submodel and a sediment transport submodel for streams. In the first model, the potential evapotranspiration is estimated for the rainfall‐runoff submodel, and the soil erosion submodel of Schmidt and the sediment transport submodel of Yang are used. In the second model, the actual evapotranspiration is estimated for the rainfall‐runoff submodel, and the soil erosion submodel of Poesen and the sediment transport submodel of Van Rijn are used. The deposition amount in the reservoir is estimated by means of the diagram of Brune, which delivers the trap efficiency of the reservoir. Daily rainfall data from three rainfall stations, and daily values of air temperature, relative air humidity and sunlight hours from a meteorological station for four years (1986–89) were available. The computed annual runoff volumes and mean annual soil erosion rate are compared with the respective measurement data. Copyright © 2006 John Wiley & Sons, Ltd.     

The Runoff Declining Process and Water Quality in Songhuajiang River Catchment,China under Global Climatic Change

The runoff in Songhuajiang River catchment has experienced a decreasing trend during the second half of the 20th century. Serially complete daily rainfall data of 42 rainfall stations from 1959 to 2002 and daily runoff data of five meteorological stations from 1953 to 2005 were obtained. The Mann–Kendall trend test and the sequential version of Mann–Kendall test were employed in this study to test the monthly and annual trends for both rainfall and runoff, to determine the start point of abrupt runoff declining, and to identify the main driving factors of runoff decline. The results showed an insignificant increasing trend in rainfall but a significant decreasing trend in runoff in the catchment. For the five meteorological stations, abrupt runoff decline occurred during 1957–1963 and the middle 1990s. Through Mann–Kendall comparisons for the area‐rainfall and runoff for the two decreasing periods, human activity, rather than climatic change, is identified as the main driving factor of runoff decline. Analysis of land use/cover shows that farmland is most related with runoff decline among all the land use/cover change in Nenjiang catchment. From 1986 to 1995, the area of farmland increased rapidly from 6.99 to 7.61 million hm². Hydraulic engineering has a significant influence on the runoff decline in the second Songhuajiang catchment. Many large‐scale reservoirs and hydropower stations have been built in the upstream of the Second Songhuajiang and lead to the runoff decline. Nenjiang and the Second Songhuajiang are the two sources of mainstream of Songhuajiang. Decreased runoff in these two sub‐catchments then results in runoff decrease in mainstream of Songhuajiang catchment. It is, therefore, concluded that high percent agricultural land and hydraulic engineering are the most probable driving factors of runoff decline in Songhuajiang River catchment, China.