Xinanjiang Model Research Articles

Long-term water budget estimation with the modified distributed model – LISFLOOD-WB over the Lushi basin, China

In a modification of the distributed hydrological model, LISFLOOD-WB, a two-source canopy scheme is used to predict both the canopy transpiration and soil evaporation. A revised soil storage capacity curve from the Xinanjiang model is applied to take into account the sub-grid heterogeneity. The modified model is used to estimate the long-term (1980–1997) water budget of the Lushi basin (4423 km2), China. All the input data fields are integrated in a four-dimensional GIS data structure with a raster grid spacing of 1-km. The basin channel network is determined from digital elevation data, and the spatial pattern of canopy leaf area index (LAI) is retrieved from NOAA/AVHRR NDVI images. Generally, the model efficiency for discharge prediction is acceptable, but the discharges are overestimated in the driest years and underestimated in the wettest years. The results indicated that the influence of inter-annual variation of spatial patterns of LAI detected by NOAA/AVHRR NDVI on the estimates of annual evapotranspiration is negligible. Annually averaged ratios of overland flow, infiltration and canopy interception to precipitation are 24±7%, 56±10% and 20±2%, respectively. The inter-annual variations of precipitation and predicted evapotranspiration are relatively high with standard deviations of 5.1 mm day−1 and 2.4 mm day−1, respectively, whereas the inter-annual variation of the net radiation is much less. Monthly temporal patterns of soil moisture follow precipitation strongly. Spatially precipitation and LAI are both significantly correlated with evapotranspiration, although precipitation has a slightly more dominant control. The linear relationship between water yield and LAI is weak on a grid by grid basis.

Development of a distributed hydrological model and its application to soil erosion simulation in a forested catchment during storm period

AbstractA spatially distributed Xinanjiang model (DXAJ) has been developed to simulate the hourly hydrological process of a storm event caused by Typhoon No. 11 during the period of the 22–23 August 2001 in the Kamafusa Lake catchment, Miyagi Prefecture, Japan. The catchment is divided into 50 × 50 m2 grid cells, and the runoff generation component of the Xinanjiang rainfall‐runoff model is applied to each grid cell. An optimal routing order approach is used to implement the distributed routing, i.e. the runoff generated in each grid cell is routed together with upstream inflow from upstream grid cells to downstream grid cells according to the optimal routing order, which is derived from a simulated stream network. One process‐based soil erosion model is coupled onto this distributed hydrological model to simulate suspended solids generation in each grid cell and generated suspended solids are routed together with runoff from upstream grid cells to downstream grid cells. The simulation results are in good agreement with the observed hydrograph and pollutograph. The soil erosion simulation was improved through the consideration of rainfall intensity in the soil erosion model. Copyright © 2003 John Wiley & Sons, Ltd.

Combining a fuzzy optimal model with a genetic algorithm to solve multi-objective rainfall–runoff model calibration

An automatic calibration methodology for the Xinanjiang model that has been successfully and widely applied in China is presented. The automatic calibration of the model consists of two parts: water balance parameter and runoff routing parameter calibration. The former is based on a simple genetic algorithm (GA). The latter is based on a new method which combines a fuzzy optimal model (FOM) with a GA for solving the multiple objective runoff routing parameters calibration problem. Except for the specific fitness where the membership degree of alternative obtained by FOM with limited alternatives and multi-objectives is employed, the GA with multiple objectives in this paper is otherwise the same as the simple GA. The parameter calibration includes optimization of multiple objectives: (1) peak discharge, (2) peak time and (3) total runoff volume. Thirty-four historical floods from 12 years in the Shuangpai Reservoir are applied to calibrate the model parameters whilst 11 floods in recent 2 years are utilized to verify these parameters. Results of this study and application show that the hybrid methodology of GAs and the FOM is not only capable of exploiting more the important characteristics of floods but also efficient and robust.

DEVELOPMENT OF A SIMULATION MODEL OF WATER UTILIZATION BASED ON A DISTRIBUTED HYDROLOGICAL MODEL

The objective of this study is to develop a simulation model of water utilization such as reservoir regulation, water intake and irrigation. This model is based on a distributed hydrological model developed by the authors. In this model, the entire river basin is divided into many grid blocks, the type of water utilization of all grid blocks can be defined. In this study, these data are stored in a database in which all grid blocks are arranged in the order same with the optimal routing order. In the simulation, the runoff generation is computed by using XinAnJiang model. The sum of runoff from a grid block and upstream river channels subjects to the water use, and then be routed to adjacent downstream grid block by using the kinematic wave method. In this study, this simulation model is applied to the Brantas River basin in Indonesia. The result shows the applicability of this simulation model.

Application of SCE-UA Method for Calibrating the Xinanjiang Watershed Model

以前在使用新安江模型时人们遇到的最大困难可归因于缺乏有效的参数全局优化的数学方法.事实上对于一个缺乏经验的人来说,模型参数的人工试错计算的过程是一个相当不容易的过程,并且耗时颇多.为此,近些年来研究者们正在探索把概念性水文模型中的专家经验与自动优化计算相结合的方法或者数学优化中的全局优化方法,如SEC UA方法.本文首先简述新安江模型,而后采用3个大小和气候条件各不相同的流域对SCE UA算法就在新安江模型计算的参数优化进行了研究.研究结果表明,SCE UA算法用来进行新安江模型的参数优化所取得的效果是好的.从率定和检验的结果来看,SCE UA算法可以使得率定的新安江模型的参数达到全局最优并且从概念上也合理.;The difficulties involved in manually calibrating the Xinanjiang watershed model have in the past been partly attributable to the lack of robust optimization tools. In fact manual calibration process can be a rather frustrating and time-consuming exercise for an inexperienced person. Therefore,in recent years researchers are exploring ways to incorporate expert knowledge of conceptual watershed models into the automatic calibration procedures. This paper presents a brief introduction to the Xinanjiang model and a researdiw Tork on application of SCE-UA method for calibrating Xinanjiang watershed model using hydrological data of three catchments of different size and dimatic mnditioiis. Results show that the overall performance of SCE-UA method for calibrating the Xinanjiang model is very good. On the basis of the results derived from the calibration and verification stages it seems that SCE-UA is capable of finding a global optimum and (onceptually realistic parameter set for the Xinanjiang model.

A modified spatial soil moisture storage capacity distribution curve for the Xinanjiang model

The Xinanjiang model provides a statistically integral structure to describe the runoff generation on partial areas over a catchment. In the original version of the model, a single parabolic curve is used to describe the soil moisture variation. In reality however, the spatial and temporal distribution of soil moisture is quite complex because many different states, which change with seasons of the year, co-exist in the catchment. In this study, a more general double parabolic curve is proposed to describe the complex soil moisture variation. It consists of lower and upper branches, with the lower branch for the wet condition, the upper branch for the dry condition, and a smooth transition. Two parameters, c and b represent the relative weight between the lower and the upper branches and their gradients. The single parabolic curve of the original Xinanjiang model can be thought of as a special case of the proposed double parabolic curve. Both the single and double parabolic curves perform similarly when used with storm events isolated from daily data in the wet seasons, but the double parabolic curve improves the predictions significantly when used with data from the dry seasons. When used with hourly event data there is no significant difference between the two curves because of the dominance of the wet soil moisture condition. Even in this case, the double parabolic curve differentiates the parameter values more clearly for different soil moisture states. There is also a slight improvement on the predictions for storms in the dry seasons.

Effects of model complexity and structure, data quality, and objective functions on hydrologic modeling

Three medium sized, dry catchments located in Africa and USA were modeled with four or five conceptual rainfall-runoff (CRR) models of different complexity. The models were the Pitman model of South Africa (16 parameters), the Sacramento model of USA (21 parameters), the NAM model of Europe (15 parameters), the Xinanjiang model of China (15 parameters), and the SMAR model of Ireland (nine parameters). Between these models, the Xinanjiang model has been consistently doing better mainly because it is the only model that considers the non-uniform distribution of runoff producing areas to simulate the runoff. On the whole, it seems that standard, good quality hydrologic data can still support modeling of dry catchments with traditional CRR models. The model performance depends more on the model structure, the objective function used in automatic calibration, and data quality, than on model complexity or calibration data length. For relatively dry catchments such as the great Usuthu catchment, wet years should be preferred over dry years for the calibration data.

A COMPARATIVE STUDY OF A SWEDISH AND A CHINESE HYDROLOGICAL MODEL1

ABSTRACT: There are a large number of conceptual hydrological models available today. It is not easy to immediately identify the similarities and differences between the different models. The Swedish HBV model and the Chinese Xinanjiang model are two examples of conceptual, semi‐distributed, rainfall‐runoff models. The Xinanjiang model was designed for use in humid and semi‐humid regions, with no routine for the snowmelt runoff, whereas the snow routine is an important part of the HBV model in many applications. The model structures of the two models may be described in four routines, compared in this paper. The integral structures of them are similar, but there are some differences, especially in the runoff production routine. The physical significance and physical definitions of some model parameters were analyzed. Both models were tested in two basins. Both models gave similar results, and both models performed well in the application. The similarity of the results obtained by different model structures leads to the following two conclusions. First, more effort should probably be spent on the improvement of input data quality and coverage than on the development of more detailed model structures only. Second, inference about basin behavior and characteristics from the values of calibrated model parameters must be made with great caution.

Estimation of River Discharge using Xinanjiang Model

This paper presents the performance of Xinanjiang rainfall-runoff model for a basin (524.9 Km2), of Yodo River catchment in Japan. The model has been modified to use the evapotranspiration values computed using the Energy Balance Method instead of the conventional pan evaporation method. This has been achieved by using the hourly precipitation and discharge observations in addition to the hourly evapotranspiration values. To compute the hourly evapotranspiration the Energy Balance method has been used which originally provides the daily values, therefore time distribution procedure for short wave radiation has been incorporated and AMeDAS data was used for the computations. The performance of Xinanjiang model was checked using hourly and daily data.

The Xinanjiang model applied in China

The Xinanjiang model is a rainfall-runoff, distributed, basin model for use in humid and semi-humid regions. The evapotranspiration component is represented by a model of three soil layers. Runoff production occurs on repletion of storage to capacity values which are assumed to be distributed throughout the basin. Prior to 1980, runoff was separated into surface and groundwater components using Horton's concept of infiltration. Subsequently, the concept of hillslope hydrology was introduced with an additional component, interflow, being identified. Runoff concentration to the outflow of each sub-basin is represented by a unit hydrograph or by a lag and route technique. The damping or routing effects of the channel system connecting the sub-basins are represented by Muskingum routing. There are fifteen parameters in all, of which the model is particularly sensitive to six. Optimization of the parameters is achieved with different objective functions according to the nature of each parameter. The model has been widely used in China since 1980, mainly for flood forecasting, though more recently it is also being used for other purposes.