Water quantity and quality simulation by improved SWAT in highly regulated Huai River Basin of China

High regulation of dams or sluices disturbs flow regimes and pollutant transformation process significantly in most basins over the world. The water quality and quantity simulation in highly regulated river basins is always a very complicated task. The Huai River Basin is a typical area in China with the highest density of water projects and serious pollution problems simultaneously. In this paper, a procedure based on Soil and Water Assessment Tool (SWAT) was proposed to carry out the water quantity and quality simulation of Huai River Basin by incorporating the operation rules of dams or sluices into the reservoir regulation module. The water quality module in SWAT is extended to suit the actual situation of river basin in China. The results show that: for runoff simulation, 28 of all the 38 stations (73.7%) have the acceptable performance, with the average correlation coefficient and efficiency coefficient of 0.83 and 0.66, respectively in the calibration period. In the validation period, 17 of all the 34 stations (50%) have the acceptable performance, with the average correlation coefficient and efficiency coefficient of 0.77 and 0.54, respectively. The model performs the worst for reservoirs, little better for sluices and the best for unregulated stations. Comparing to the low flow and high flow simulation of original SWAT model, the low flow simulation of reservoirs and the high flow simulation of sluices are much better because of their different main purposes. For water quality simulation, the standard reaching rates of NH₃–N and COD_Mn are 55.9% (19/34) and 67.6% (23/34) respectively for all the stations, and the average relation coefficients are 0.46 and 0.48 respectively. Comparing with the results of original SWAT model, the improved model better reproduces the long-term water quantity and quality processes in the Huai River Basin of China. This study provides a new approach and reference to understand the variation of water quantity and quality in highly regulated river basin, and is expected as technical support for the environment restoration and integrated management in the basins, especially in China.     

赣江流域多种数据同化方案的径流模拟比较

为了探讨水文模型在不同水文数据同化方案下的径流模拟差异,本文采用集合卡尔曼滤波算法,以遥感蒸散发产品、实测径流为观测数据,构建了基于新安江模型的数据同化框架。基于此框架设计了4种不同同化方案(DA-ET、DAET(K)、DA-ET-Q、DA-ET-Q(K))以及1种对照方案OL,以赣江流域开展实例研究,评估了水文数据同化中遥感蒸散发产品的时间分辨率、模型蒸散发相关参数时变与否以及多源数据同化对径流模拟的影响。结果表明:在DA-ET方案下,同化两种不同时间分辨率的蒸散发产品均能提高模型整体的径流模拟精度,且时间分辨率更高的产品的同化效果更好;在DA-ET方案的基础上,考虑加入实测径流进行同化能够提升模型径流模拟精度,且DA-ET(K)与DA-ET-Q(K)方案所得径流相对误差的减幅均超过了20%,说明在蒸散发同化过程中同时考虑蒸散发参数动态变化的结果更优;相较于OL方案,4种同化方案均能不同程度地提高模型对径流高水部分的模拟能力,但DA-ET-Q(K)方案表现最差,而其余方案差异并不显著。本研究有助于进一步了解不同数据同化方案在径流模拟中的差异,从而为水资源高效利用与科学管理提供科学依据...     

Simulating streamflow in the Upper Halda Basin of southeastern Bangladesh using SWAT model

ABSTRACT

Most catchments in tropical regions are ungauged and data deficient, complicating the simulation of water quantity and quality. Yet, developing and testing hydrological models in data-poor regions is vital to support water management. Here, we used the Soil and Water Assessment Tool (SWAT) to predict stream runoff in Halda Basin in Bangladesh. While the calibrated model’s performance was satisfactory (R² = 0.80, NSE = 0.71), the model was unable to track the extreme low flow peaks due to the temporal and spatial variability of rainfall which may not be fully captured by using data from one rainfall gauging station. Groundwater delay time, baseflow alpha factor and curve number were the most sensitive parameters influencing model performance. This study improves understanding of the key processes of a catchment in a data-poor, monsoon driven, small river basin and could serve as a baseline for scenario modelling for future water management and policy framework.     

Improvement of SWAT2000 modelling to assess the impact of dams and sluices on streamflow in the Huai River basin of China

Hydrological simulation and assessment in a dam–sluice regulated river basin are a complex and challenging issue. In this article, an improved SWAT2000 modelling system was developed that incorporated the Shuffled complex evolution (SCE‐UA) optimization algorithm and the multi‐site and multi‐objective calibration strategy. The implication of multi‐objective is different for different types of outlets, i.e. streamflow for an ordinary outlet, inflow for a sluice, and water storage for a reservoir. Model parameters were redefined to improve model simulations. The surface runoff lag time (SURLAG) was extended as a spatially distributed parameter, and a correction coefficient was introduced to modify the saturated hydraulic conductivity. The modelling system was then applied to the Huai River basin of China under various climatic conditions, including a very dry year (1999), a dry year (1981), an average year (1971), and wet year (1991). In all, 26 dams and 35 sluices were considered, among which about 20 dams/sluices were used for model calibration. The impact assessment primarily focused on the very dry year (1999). The results indicated that the released water from large reservoirs was blocked in the river channels by sluices located downstream. In the very dry year, the dam–sluice operations could result in an increase of the runoff volume during the non‐flood season and a decrease in runoff during the flood season, but the changing magnitude during the non‐flood season was much greater. An important conclusion of this case study is that the sluices in the Sha‐Yin branch located in the north region and the dams in the southern mountainous region above the Wangjiaba Hydrological Station have played the most significant role in regulating the streamflow of the entire river basin. The methods addressed in this article can simulate hydrological regime in the river basins regulated by dams and sluices under different climatic conditions at the whole‐watershed scale. Copyright © 2010 John Wiley & Sons, Ltd.     

Occurrence,shape and movement of daily rainfall in the Huai Basin,China

The upper reaches of the Huai River in Central China are located in the East Asian monsoon region. Strong seasonality, as well as large interannual variability of rainfall, causes floods and an uneven supply of water. In order to conserve the water and mitigate the floods, dams and flood protection structures are constructed. Their design requires information about the rainfall. Daily observations from 1957 to 1986 from 78 rain gauges were used to study shape, orientation, movement and geographical and seasonal occurrence of storms in the 79 000 km² study area. The rainfall characteristics were described using graphical plots, cross‐ and autocorrelation. Storms larger than 50 mm/day were found to occur from February to November, whereas storms exceeding 350 mm/day were confined to the main rainfall season from late June to mid‐August. The southern part of the study area experienced a break in the rainfall season in late July, corresponding to the seasonal northward shift of the rain belt. A weekly periodicity of 7–8 days for rainfall was found during June–July, but not during August–September. During the whole period June–September, the spatial pattern of daily rainfall revealed an elongated shape, more pronounced during June–July than August–September. The rainfall area was orientated approximately from WSW to ENE during the whole period, and showed an anticlockwise rotation of about 16° per day during June–July. The cross‐correlation analysis revealed that the rainfall area moved about 100 km/day eastward. These results and an investigation of meteorological maps indicate that the spatial correlation pattern of daily rainfall is produced by cold fronts on the Mei‐Yu front. Suggestions are made as to how to use the results for the construction of design rainfalls in the study area. Copyright © 1999 John Wiley & Sons, Ltd.     

Use of daily precipitation uncertainties in streamflow simulation and forecast

Among other sources of uncertainties in hydrologic modeling, input uncertainty due to a sparse station network was tested. The authors tested impact of uncertainty in daily precipitation on streamflow forecasts. In order to test the impact, a distributed hydrologic model (PRMS, Precipitation Runoff Modeling System) was used in two hydrologically different basins (Animas basin at Durango, Colorado and Alapaha basin at Statenville, Georgia) to generate ensemble streamflows. The uncertainty in model inputs was characterized using ensembles of daily precipitation, which were designed to preserve spatial and temporal correlations in the precipitation observations. Generated ensemble flows in the two test basins clearly showed fundamental differences in the impact of input uncertainty. The flow ensemble showed wider range in Alapaha basin than the Animas basin. The wider range of streamflow ensembles in Alapaha basin was caused by both greater spatial variance in precipitation and shorter time lags between rainfall and runoff in this rainfall dominated basin. This ensemble streamflow generation framework was also applied to demonstrate example forecasts that could improve traditional ESP (Ensemble Streamflow Prediction) method.     

Combining the SWAT model with sequential uncertainty fitting algorithm for streamflow prediction and uncertainty analysis for the Lake Dianchi Basin,China

Streams play an important role in linking the land with lakes. Nutrients released from agricultural or urban sources flow via streams to lakes, causing water quality deterioration and eutrophication. Therefore, accurate simulation of streamflow is helpful for water quality improvement in lake basins. Lake Dianchi has been listed in the ‘Three Important Lakes Restoration Act’ in China, and the degradation of its water quality has been of great concern since the 1980s. To assist environmental decision making, it is important to assess and predict hydrological processes at the basin scale. This study evaluated the performance of the soil and water assessment tool (SWAT) and the feasibility of using this model as a decision support tool for predicting streamflow in the Lake Dianchi Basin. The model was calibrated and validated using monthly observed streamflow values at three flow stations within the Lake Dianchi Basin through application of the sequential uncertainty fitting algorithm (SUFI‐2). The results of the autocalibration method for calibrating and the prediction uncertainty from different sources were also examined. Together, the p‐factor (the percentage of measured data bracketed by 95% prediction of uncertainty, or 95PPU) and the r‐factor (the average thickness of the 95PPU band divided by the standard deviation of the measured data) indicated the strength of the calibration and uncertainty analysis. The results showed that the SUFI‐2 algorithm performed better than the autocalibration method. Comparison of the SUFI‐2 algorithm and autocalibration results showed that some snowmelt factors were sensitive to model output upstream at the Panlongjiang flow station. The 95PPU captured more than 70% of the observed streamflow at the three flow stations. The corresponding p‐factors and r‐factors suggested that some flow stations had relatively large uncertainty, especially in the prediction of some peak flows. Although uncertainty existed, statistical criteria including R² and Nash–Sutcliffe efficiency were reasonably determined. The model produced a useful result and can be used for further applications. Copyright © 2012 John Wiley & Sons, Ltd.     

Impact of climate change on streamflow in the arid Shiyang River Basin of northwest China

Climate change may significantly affect the hydrological cycle and water resource management, especially in arid and semi‐arid regions. In this paper, output from the Providing Regional Climates for Impacts Studies (PRECIS) regional climate model were used in conjunction with the Soil and Water Assessment Tool (SWAT) to analyse the effects of climate change on streamflow of the Xiying and Zamu rivers in the Shiyang River basin, an important arid region in northwest China. After SWAT model calibration and validation, streamflow in the Shiyang River Basin was simulated using the PRECIS climate model data for greenhouse gas emission scenarios A2 (high emission rate) and B2 (low emission rate) developed by Intergovernmental Panel on Climate Change. Monthly streamflow and hydrological extremes were compared for present‐day years (1961–1990), the 2020s (2011–2040), 2050s (2041–2070) and 2080s (2071–2100). The results show that mean monthly streamflow in Shiyang River Basin generally increased in the 2020s, 2050s and 2080s between 0.7–6.1% at the Zamu gauging station and 0.1–4.8% at the Xiying gauging station. The monthly minimum streamflow increased persistently, but the maximum monthly streamflows increased in the 2020s and slightly decreased in the 2050s and 2080s. This study provides valuable information for guiding future water resource management in the Shiyang River Basin and other arid and semi‐arid regions in China. Copyright © 2011 John Wiley & Sons, Ltd.     

Sensitivity of streamflow simulation in the Delaware River Basin to forecasted land‐cover change for 2030 and 2060

In order to simulate the potential effect of forecasted land‐cover change on streamflow and water availability, there has to be confidence that the hydrologic model used is sensitive to small changes in land cover (<10%) and that this land‐cover change exceeds the inherent uncertainty in forecasted conditions. To investigate this, a 26‐year streamflow record was simulated for 33 basins (54–928 km²) in the Delaware River Basin using three dates of land cover: the 2011 National Land‐Cover Dataset (Homer, Fry, & Barnes, 2012 ), 2030 land‐cover conditions representing median values from 101 equally‐likely forecasts, and 2060 land‐cover conditions corresponding to the same iterations used to represent 2030. Streamflow was simulated using a process‐based hydrologic model that includes both pervious and impervious methods as parameterized by three land‐cover‐based hydrologic response units (HRUs)—forested, agricultural, and developed land. Small, but significant differences in streamflow magnitude, variability, and seasonality were seen among the three time periods—2011, 2030, and 2060. Temporal differences were discernible from the range of conditions simulated with 101 equally likely forecasts for 2030. Development was co‐located with the most frequent landscape components, as characterized by topographic wetness index, resulting in a change in hydrology for each HRU, highlighting that knowing the location of disturbance is key to understanding potential streamflow changes. These results show that streamflow simulation using regional calibration that incorporates land‐cover‐based HRUs can be sensitive to relatively small changes in land‐cover and that temporal trends resulting from land‐cover change can be isolated in order to evaluate other changes that might affect water resources.     

Changes in daily temperature and precipitation extremes in the Yellow River Basin, China

Spatiotemporal changes in climatic extremes in the Yellow River Basin from 1959 to 2008 were investigated on the basis of a suite of 27 climatic indices derived from daily temperature and precipitation data from 75 meteorological stations with the help of the Mann–Kendall test, linear regression method and GIS technique. Furthermore, the changes in the probability distribution of the extreme indices were examined. The results indicate: (1) The whole basin is dominated by significant increase in the frequency of warm days and warm nights, and dominated by significant decrease in the frequency of cold days and cold nights. Although trends in absolute temperature indices show less spatial coherence compared with that in the percentile-based temperature indices, overall increasing trends can be found in Max Tmax (TXx), Min Tmax (TXn), Max Tmin (TNx) and Min Tmin (TNn). (2) Although the spatial patterns and the number of stations with significant changes for threshold and duration temperature indices are also not identical, general positive trends in warm indices (i.e., summer days (SU25), tropical nights (TR20), warm spell duration indicator and growing season length) and negative trends in cold indices (i.e., frost days, ice days and cold spell duration indicator) can be found in the basin. Annual nighttime temperature has increased at a faster rate than that in daytime temperature, leading to obvious decrease in diurnal temperature range. (3) The changes in precipitation indices are much weaker and less spatially coherent compared with these of temperature indices. For all precipitation indices, only few stations are characterized by significantly change in extreme precipitation, and their spatial patterns are always characterized by irregular and insignificant positive and negative changes. However, generally, changes in precipitation extremes present drying trends, although most of the changes are insignificant. (4) Results at seasonal scale show that warming trends occur for all seasons, particularly in winter. Different from that in other three seasons, general positive trends in max 1-day precipitation (Rx1DAY) and max 5-day precipitation (Rx5DAY) are found in winter. Analysis of changes in probability distributions of indices for 1959–1983 and 1984–2008 indicate a remarkable shift toward warmer condition and a less pronounced tendency toward drier condition during the past decades. The results can provide beneficial reference to water resource and eco-environment management strategies in the Yellow River Basin for associated policymakers and stakeholders.     

Estimating daily streamflow in the Congo Basin using satellite-derived data and a semi-distributed hydrological model

ABSTRACT

The application of remotely-sensed data for hydrological modeling of the Congo Basin is presented. Satellite-derived data, including TRMM precipitation, are used as inputs to drive the USGS Geospatial Streamflow Model (GeoSFM) to estimate daily river discharge over the basin from 1998 to 2012. Physically-based parameterization was augmented with a spatially-distributed calibration that enables GeoSFM to simulate hydrological processes such as the slowing effect of the Cuvette Centrale. The resulting simulated long-term mean of daily flows and the observed flow at the Kinshasa gauge were comparable (40 631 and 40 638 m³/s respectively), in the 7-year validation period (2004–2010), with no significant bias and a Nash-Sutcliffe model efficiency coefficient of 0.70. Modeled daily flows and aggregated monthly river outflows (compared to historical averages) for additional sites confirm the model reliability in capturing flow timing and seasonality across the basin, but sometimes fails to accurately predict flow magnitude. The results of this model can be useful in research and decision-making contexts and validate the application of satellite-based hydrological models driven for large, data-scarce river systems such as the Congo.     

Spatial distribution and temporal trends in daily and monthly precipitation concentration indices in the upper reaches of the Huai River, China

Understanding precipitation variations on various timescales and their correlations is important for assessment of flood risk and utilization of water resources. In this study, the spatial and temporal patterns of precipitation concentration in the upper reaches of the Huai River, China, were investigated using two indices: the precipitation concentration index (PCI) and the concentration index (CI) for measuring seasonality and daily heterogeneity using monthly and daily precipitation series, respectively. In particular, the trends of PCI and CI were tested by the Mann–Kendall method, and relationship among PCI, CI and percentage of precipitation contributed by the rainiest days was analyzed by the linear correlation analysis. The results show a significant seasonality of the rainfall distribution and very in homogeneous temporal distribution of the daily rainfall in the south part of the study area, especially in the three reservoirs. Positive trends in the PCI and CI were found at most stations, although none of the PCI trends were statistically significant. Daily heterogeneity of the rainfall in a year is highly correlated with the heavy rainfall amount of the 15 % rainiest days, and seasonality in rainfall distribution over a year can be partly explained by the daily rainfall heterogeneity.     

Comparison of local and global approximators in multivariate chaotic forecasting of daily streamflow

ABSTRACT

Although it is conceptually assumed that global models are relatively ineffective in modelling the highly unstable structure of chaotic hydrologic dynamics, there is not a detailed study of comparing the performances of local and global models in a hydrological context, especially with new emerging machine learning models. In this study, the performance of a local model (k-nearest neighbour, k-nn) and, as global models, several recent machine learning models – artificial neural network (ANN), least square-support vector regression (LS-SVR), random forest (RF), M5 model tree (M5), multivariate adaptive regression splines (MARS) – was analysed in multivariate chaotic forecasting of streamflow. The models were developed for Australia’s largest river, the River Murray. The results indicate that the k-nn model was more successful than the global models in capturing the streamflow dynamics. Furthermore, coupled with the multivariate phase-space, it was shown that the global models can be successfully used for obtaining reliable uncertainty estimates for streamflow.     

基于SWAT模型的淮河上游流域设计洪水修订

变化环境下洪水序列的一致性遭到破坏,引发基于统计原理计算的设计洪水可靠性下降,亟需开展非一致性条件下的设计洪水修订研究.以淮河上游流域为研究区域,运用Pettitt检验法和滑动t检验法综合检测年最大洪峰流量序列突变点,在此基础上,采用SWAT分布式水文模型对变异前的洪峰与洪量序列进行还现,利用径流深的模拟结果修订设计洪...     

Comparison of daily streamflow forecasts using extreme learning machines and the random forest method

ABSTRACT

Daily streamflow forecasting is a challenging and essential task for water resource management. The main goal of this study was to compare the accuracy of five data-driven models: extreme learning machine (basic ELM), extreme learning machine with kernels (ELM-kernel), random forest (RF), back-propagation neural network (BPNN) and support vector machine (SVR). The results show that the ELM-kernel model provided a superior alternative to the other models, and the basic ELM model had the poorest performance. To further evaluate the predictive capacities of the five models, the estimations of low flow and high flow in the testing dataset were compared. The RF model was slightly superior to the other models in predicting the peak flows, and the ELM-kernel model showed the highest prediction precision of low flows. There was no single model that showed obvious advantages over the other models in this study. Therefore, further exploration is required for the hydrological forecasting problems.     

基于修正SWAT模型的岩溶地区非点源污染模拟初探——以横港河流域为例

岩溶流域含水系统的主要特征之一是连通地表的落水洞等垂直管道将近水平的地下暗河联系起来,降水及其形成的地表径流可以通过这些管道迅速地灌入地下河系,从而改变了水及其所携带的非点源污染物质在垂直与水平方向的传输速度与数量,使岩溶流域内地表-地下之间的物质交换与传输过程变得比较复杂;应用广泛的SWAT模型在模拟岩溶地区的水文、水质时会存在一些不足与局限.为此,本文针对岩溶水系统特征,引入落水洞、伏流、暗河的水文过程以及主要营养盐的输移过程,修正SWAT模型原有的水文循环过程及相关算法,改变其只适用于松散均匀介质流域非点源污染模拟的单一特征,并研究建立适合于岩溶流域的非点源污染模型和相应的模拟方法.选取横港河流域岩溶地区作为非点源污染的对象,应用修正后的模型通过控制性的模拟方法和敏感性性分析,定量评估落水洞、伏流、暗河等岩溶特征对氮、磷等主要非点源污染物质输移的影响及其带来的时空效应,并进一步探讨落水洞、伏流、暗河等对地表-地下水文与营养盐的交互作用及转换机理.结果表明,岩溶特征对流域的氮、磷负荷有增加作用,其中总磷的增加明显大于总氮的增加,总磷和总氮的增量分别为0.86%和2.12%;植被岩溶指数的增加会导致流域可溶性磷、有机磷的产出量增加,有机氮、地表产流中硝酸氮和沉积磷的产出量则居其次,落水洞改变了降雨的产流方式,增加了落水洞所在流域的有机磷和有机氮的产出,其增量变化在0~0.7和0~0.3 kg/hm²之间.     

Changes of flow regimes and precipitation in Huai River Basin in the last half century

Huai River Basin, as the sixth largest river basin in China, has a high‐regulated river system and has been facing severe water problems. In this article, the changing patterns of runoff and precipitation at 10 hydrological stations from 1956 to 2000 on the highly regulated river (Shaying River) and less‐regulated river (Huai River) in the basin are evaluated at the monthly, seasonal and annual scales using the Mann–Kendall test and simple linear regression model. The results showed that: (1) No statistically significant trends of precipitation in the upper and middle Huai River Basins were detected at the annual scale, but the trend of annual runoff at Baiguishan, Zhoukou and Fuyang stations in Shaying River decreased significantly, whereas the others were not. Moreover, the decreasing trends of runoff for most months were significant in Shaying River, although the trend of monthly precipitation decreased significantly only in April in the whole research area and the number of months in the dry season having significantly decreasing trends in runoff was more than that in the wet season. (2) The rainfall–runoff relationship was significant in both highly regulated river and less‐regulated river. In regulated river, the reservoirs have larger regulation capacity than the floodgates and thus have the smaller correlation coefficient and t‐value. In Huai River, the correlation coefficients decreased from upper stream to downstream. (3) The regulation of dams and floodgates for flood control and water supply was the principal reason for the decreasing runoff in Huai River Basin, although the decreasing precipitation in April in this basin was statistically significant. The findings are useful for recognizing hydrology variation and will provide scientific foundation to integrated water resources management in Huai River Basin. Copyright © 2010 John Wiley & Sons, Ltd.