Improvement of mid- to long-term runoff forecasting based on physical causes: application in Nenjiang basin,China

Abstract

An artificial neural network, mid- to long-term runoff forecasting model of the Nenjiang basin was established by deciding predictors using the physical analysis method, combined with long-term hydrological and meteorological information. The forecasting model was gradually improved while considering physical factors, such as the main flood season and non-flood season by stage, runoff sources and hydrological processes. The average relative errors in the simulation tests of the prediction model were 0.33 in the main flood season and 0.26 in the non-flood season, indicating that the prediction accuracy during the non-flood season was greater than that in the main flood season. Based on these standards, forecasting accuracy evaluation was conducted by comparing forecasting results with actual conditions: for 2001 to 2003 data, the pass rate of forecasting in the main flood season was 50%, while it was 93% in the non-flood season; for 2001–2010, the respective values were 45% and 72%. The accuracy of prediction was found to decrease as the length of record increases.

Editor D. Koutsoyiannis, Associate editor A. Viglione

Citation Li, H.-Y. Tian, L., Wu, Y., and Xie, M., 2013. Improvement of mid- to long-term runoff forecasting based on physical causes: application in Nenjiang basin, China. Hydrological Sciences Journal, 58 (7), 1414–1422.     

Long‐term runoff forecasting by combining hydrological models and meteorological records

Reservoir operation is generally based on the inflows of the upstream catchment of the reservoir. If the arriving inflows can be forecasted, that can benefit reservoir operation and management. This study attempts to construct a long‐term inflow‐forecasting model by combining a continuous rainfall–runoff model with the long‐term weather outlook from the Central Weather Bureau of Taiwan. The analytical results demonstrate that the continuous rainfall–runoff model has good inflow simulation performance by using 10‐day meteorological and inflow records over a 33‐year period for model calibration and verification. The long‐term inflow forecasting during the dry season was further conducted by combining the continuous rainfall–runoff model and the long‐term weather outlook, which was found to have good performance. Copyright © 2005 John Wiley & Sons, Ltd.     

Long‐term variations and temporal scaling of hydroclimatic time series with focus on the German part of the Elbe River Basin

Long‐term variations and temporal scaling of mean monthly time series of river flow, precipitation, temperature, relative humidity, air pressure, duration of bright sunshine, degree of cloud cover, short wave radiation, wind speed and potential evaporation within or in vicinity of the German part of the Elbe River Basin are analyzed. Statistically significant correlations between the 2–15 year scale‐averaged wavelet spectra of the hydroclimatic variables and the North Atlantic Oscillation‐ and Arctic Oscillation index are found which suggests that such long‐term patterns in hydroclimatic time series are externally forced. The Hurst parameter estimates (H) based on the Detrended Fluctuation Analysis (DFA) indicate persistence for discharge, precipitation, wind speed, air pressure and the degree of cloud cover, all having an annual cycle and a broad low‐frequency distribution. Also, DFA H parameter estimates are higher for discharge than for precipitation. The major long‐term quasi‐periodic variability modes of precipitation detected using Singular Spectrum Analysis coincide with those detected in the discharge time series. Upon subtraction of these low‐frequency quasi‐periodic modes, the DFA H parameter estimates suggest absence of the persistence for both precipitation and discharge. Copyright © 2013 John Wiley & Sons, Ltd.     

Changes in potential evapotranspiration and surface runoff in 1981–2010 and the driving factors in Upper Heihe River Basin in Northwest China

Changes in potential evapotranspiration and surface runoff can have profound implications for hydrological processes in arid and semiarid regions. In this study, we investigated the response of hydrological processes to climate change in Upper Heihe River Basin in Northwest China for the period from 1981 to 2010. We used agronomic, climatic and hydrological data to drive the Soil and Water Assessment Tool model for changes in potential evapotranspiration (ET₀) and surface runoff and the driving factors in the study area. The results showed that increasing autumn temperature increased snow melt, resulting in increased surface runoff, especially in September and October. The spatial distribution of annual runoff was different from that of seasonal runoff, with the highest runoff in Yeniugou River, followed by Babaohe River and then the tributaries in the northern of the basin. There was no evaporation paradox at annual and seasonal time scales, and annual ET₀ was driven mainly by wind speed. ET₀ was driven by relative humidity in spring, sunshine hour duration in autumn and both sunshine hour duration and relative humility in summer. Surface runoff was controlled by temperature in spring and winter and by precipitation in summer (flood season). Although surface runoff increased in autumn with increasing temperature, it depended on rainfall in September and on temperature in October and November. Copyright © 2016 John Wiley & Sons, Ltd.     

Multi‐method global sensitivity analysis (MMGSA) for modelling floodplain hydrological processes

When studying hydrological processes with a numerical model, global sensitivity analysis (GSA) is essential if one is to understand the impact of model parameters and model formulation on results. However, different definitions of sensitivity can lead to a difference in the ranking of importance of the different model factors. Here we combine a fuzzy performance function with different methods of calculating global sensitivity to perform a multi‐method global sensitivity analysis (MMGSA). We use an application of a finite element subsurface flow model (ESTEL‐2D) on a flood inundation event on a floodplain of the River Severn to illustrate this new methodology. We demonstrate the utility of the method for model understanding and show how the prediction of state variables, such as Darcian velocity vectors, can be affected by such a MMGSA. This paper is a first attempt to use GSA with a numerically intensive hydrological model. Copyright © 2007 John Wiley & Sons, Ltd.     

Regional extreme‐dry‐spell frequency analysis using the L‐moments method in the middle reaches of the Yellow River Basin,China

In this research, the regional extreme‐dry‐spell frequency in the middle reaches of the Yellow River Basin (YRB) is studied by the L‐moments method. The research area has been divided into three subregions (regions 1, 2 and 3), which have been identified as homogenous regions. The results of a goodness‐of‐fit test indicate that a generalized normal distribution is the optimal regional model for regions 1 and 2 whereas a generalized Pareto distribution is the optimal regional model for region 3. The return period analysis figures out that the maximum length‐of‐dry‐spell (MxDS) values increase from south to north in the southern part and increase from northeast to southwest in the northern part of the middle reaches of the YRB under different return periods. The increments of quantiles of dry spell under different return levels indicate that drought risk in region 1 is higher than that in regions 2 and 3. The analysis of the occurrence day of MxDS shows that MxDS mostly occurred during winter of 1998 and spring of 1999 in most stations during the considered period. By comparing summer MxDS events, it can be found that mean MxDS values have slightly increased in regions 1 and 2 during the last five decades. The maximum mean MxDS values appeared in the 2000s for regions 1 and 2 and in the 1990s for region 3. The atmospheric circulation shows that the positive anomaly centre in the west of North China, negative anomaly centre in the east of North China and the strong western Pacific subtropical high led to the decrease of precipitation in North China during the summer of 1997. Copyright © 2013 John Wiley & Sons, Ltd.     

Comparing the performance of empirical black‐box models for river flow forecasting in the Heihe River Basin,Northwestern China

For many practical reasons, the empirical black‐box models have become an increasingly popular modelling tool for river flow forecasting, especially in mountainous areas where very few meteorological observatories exist. In this article, precipitation data are used as the only input to estimate river flow. Using five empirical black‐box models—the simple linear model, the linear perturbation model, the linearly varying gain factor model, the constrained nonlinear system model and the nonlinear perturbation model–antecedent precipitation index—modelling results are compared with actual results in three catchments within the Heihe River Basin. The linearly varying gain factor model and the nonlinear perturbation model yielded excellent predictions. For better simulation accuracy, a commonly used multilayer feed‐forward neural network model (NNM) was applied to incorporate the outputs of the individual models. Comparing the performance of these models, it was found that the best results were obtained from the NNM model. The results also suggest that more reliable and precise predictions of river flow can be obtained by using the NNM model while also incorporating the combined outputs of different empirical black‐box models. Copyright © 2012 John Wiley & Sons, Ltd.     

极端降雨事件对南方红壤区径流和输沙的影响——基于赣江支流濂江上游流域的长序列分析(1984—2020年)

为探究极端降雨对南方红壤区流域水沙的影响,本文基于江西省鄱阳湖水系赣江上游濂江流域1984—2020年逐日降雨量、径流量和输沙量数据,使用95百分位法计算极端降雨,并采用最小事件间隔时间法分割降雨事件,综合应用Pettitt检验和线性回归方法对水沙突变、影响因子进行定量分析。结果表明:(1)发生极端降雨事件的时期是流域泥沙输出的关键时期,极端降雨对输沙量的贡献率达85.58%～87.79%,而对径流量的贡献为38.33%～43.42%。(2)在极端降雨情景下,年径流量从1984—1995年的209.21×10⁶ m³下降到1996—2020年的165.23×10⁶ m³,而年输沙量从1984—1995年的3.65×10⁴ t增加到1996—2020年的12.8×10⁴ t,相比于1984—1995年,1996—2020年的极端降雨所产生的径流量和输沙量占比有缩小趋势,分别表现为从43.42%到38.33%和从87.79%到85.58%。(3)极端降雨情景下...     

A statistical methodology for assessing the long‐term effects of antecedent drought conditions on stream runoff: applications to the Piedmont Province,southeastern United States

A method was developed to investigate the long‐term (months‐to‐years) effects (both magnitude and duration) of antecedent rainfall upon subsequent runoff coefficients (RCs) or runoff/rainfall ratios. The method was applied to a four‐state region (Georgia, South Carolina, North Carolina, and Virginia) within the southeastern Piedmont Province of the United States and incorporated a 59‐year data set of 19 United States Geological Survey stream gages and 57 National Climatic Data Center rain gages. The method was designed to facilitate statistical comparisons [Mann–Whitney rank sum tests] between various groups of normalized runoff coefficients (NRCs) representing 6–36 month periods which differed in terms of antecedent rainfall conditions. The results of this study show that under all subsequent rainfall conditions, with the exception of excess rainfall, a 1‐year period of antecedent drought lowered NRCs for at least 1 year following the drought. The principal finding of this study is that a year‐long drought period within the southeastern Piedmont Province lowers NRCs by ～25% during the following year when rainfall returns to normal. In most cases, RCs are significantly lower during the second year following a drought than they would be when anteceded by normal rainfall; however, the effects of drought wane during this period. This is a statistical and regional method that can be modified to other study areas; however, it cannot be used to predict storm‐event rainfall–runoff relationships for any specific basin. Copyright © 2010 John Wiley & Sons, Ltd.     

Long‐term change of seasonal snow cover and its effects on river runoff in the Tarim River basin,northwestern China

Spatio‐temporal variation of snow depth in the Tarim River basin has been studied by the empirical orthogonal function (EOF) based on the data collected by special sensor microwave/imager (SSM/I) and scanning multichannel microwave radiometer (SMMR) during the period from 1979 to 2005. The long‐term trend of snow depth and runoff was presented using the Mann‐Kendall non‐parametric test, and the effects of the variations of snow depth and climatic factors on runoff were analysed and discussed by means of the regression analysis. The results suggested that the snow depth variation on the entire basin was characterised by four patterns: all consistency, north–south contrast, north‐middle‐south contrast and complex. The first pattern accounting 39·13% of the total variance was dominant. The entire basin was mainly affected by one large‐scale weather system. However, the spatial and temporal differences also existed among the different regions in the basin. The significant snow depth changes occurred mainly in the Aksu River basin with the below‐normal snow depth anomalies in the 1980s and the above‐normal snow depth anomalies in the 1990s. The long‐term trend of snow depth was significant in the northwestern, western and southern parts of the basin, whereas the long‐term trend of runoff was significant in the northwestern and northeastern parts. The regression analysis revealed that the runoff of the rivers replenished by snow melt water and rainfall was related primarily to the summer precipitation, followed by the summer temperature or the maximum snow depth in the cold season. Our results suggest that snow is not the principal factor that contributes to the runoff increase in headstreams, although there was a slow increase in snow depth. It is the climatic factors that are responsible for the steady and continuous water increase in the headstreams. Copyright © 2009 John Wiley & Sons, Ltd.     

Investigation of the relationship between runoff and atmospheric oscillations,sea surface temperature,and local‐scale climate variables in the Yellow River headwaters region

The Yellow River headwaters region (YRHR) contributes nearly 40% of total flow in the Yellow River basin, which is suffering from a serious water shortage problem. Investigation of the relationship between runoff and climate variables is important for understanding the variation trend of runoff in the YRHR under global climate change. Global and local climate variables, including the West Pacific subtropical high; northern hemisphere polar vortex (NH); Tibetan Plateau Index B (TPI‐B); southern oscillation index; sea surface temperature; and precipitation, evaporation, and temperature, were fully considered to explore the relationship with runoff at Jimai, Maqu, and Tangnaihai stations from 1956 to 2014. The results reveal that runoff had a decreasing trend, which will likely be maintained in the future, and there was a significant change in runoff around 1995 at all stations. Correlation analysis indicated that runoff was dominated by precipitation, NH, temperature, and TPI‐B, and a substantial correlation was observed with sea surface temperature and evaporation, but there was little correlation with West Pacific subtropical high and southern oscillation index. Furthermore, impacts of climate change on runoff variations were distinctly different at different temporal scales. Three dominant runoff periodicities were identified by a singular spectrum analysis‐multitaper method and continuous wavelet transform, that is, 1.0‐, 6.9‐, and 24.8‐year runoff periodicities. In addition, runoff was positively correlated with temperature at a 1‐year periodicity, negatively correlated with TPI‐B at a 6.9‐year periodicity, and positively correlated with NH at a 24.8‐year periodicity, that is, temperature, TPI‐B, and NH‐controlled runoff at annual, interannual, and interdecadal scales. Further, all analyses of the stations in the YRHR showed excellent consistency. The results will provide valuable information for water resource management in the YRHR.     

Curve‐Number/Green–Ampt mixed procedure for streamflow predictions in ungauged basins: Parameter sensitivity analysis

A procedure combining the Soil Conservation Service‐Curve Number (SCS‐CN) method and the Green–Ampt (GA) infiltration equation was recently developed to overcome some of the drawbacks of the classic SCS‐CN approach when estimating the volume of surface runoff at a sub‐daily time resolution. The rationale of this mixed procedure, named Curve Number for Green–Ampt (CN4GA), is to use the GA infiltration model to distribute the total volume of the net hyetograph (rainfall excess) provided by the SCS‐CN method over time. The initial abstraction and the total volume of rainfall given by the SCS‐CN method are used to identify the ponding time and to quantify the hydraulic conductivity parameter of the GA equation. In this paper, a sensitivity analysis of the mixed CN4GA parameters is presented with the aim to identify conditions where the mixed procedure can be effectively used within the Prediction in Ungauged Basin perspective. The effects exerted by changes in selected input parameters on the outputs are evaluated using rectangular and triangular synthetic hyetographs as well as 100 maximum annual storms selected from synthetic rainfall time series. When applied to extreme precipitation events, which are characterized by predominant peaks of rainfall, the CN4GA appears to be rather insensitive to the input hydraulic parameters of the soil, which is an interesting feature of the CN4GA approach and makes it an ideal candidate for the rainfall excess estimation at sub‐daily temporal resolution at ungauged sites. Copyright © 2013 John Wiley & Sons, Ltd.     

Detecting the flow relationships between deep and shallow aquifers in an exploited groundwater system,using long‐term monitoring data and quantitative hydrogeology: the Acque Albule basin case (Rome,Italy)

Five years of hydrogeological monitoring and field activities performed in the complex hydrogeological system of the Acque Albule basin (AAB) were conducted to define the hydrogeological setting, the relationship between deep and shallow aquifers and a conceptual groundwater flow model of this exploited area using conventional quantitative techniques. The basin, which is located close to Rome (Italy) on the west side of the Apennine chain and just north of the Colli Albani volcano, subsided after development of a north–south fault system (about 115 000 y bp). The AAB experiences intense hydrothermal activity, which has produced a large travertine deposit (80‐m thick). The travertine deposit constitutes a fractured aquifer that is the final destination of more than 5 m³ s^‐1 of water and is strongly dewatered by quarry activities. The complex hydrogeology of this basin was investigated, revealing two main hydraulically connected aquifers, one thermalised and partly confined into the limestone bedrock and one unconfined in the travertine. The two aquifers are separated by a non‐continuous clayey aquiclude. The hydrogeological survey and geological characterisation contributed to the development of the groundwater flow conceptual model. Analysis and comparison of the monitored levels highlighted the pattern of flow between the deep and shallow parts of the flow system. Copyright © 2012 John Wiley & Sons, Ltd.     

Hydrological effects of water reservoirs on hydrological processes in the East River (China) basin: complexity evaluations based on the multi‐scale entropy analysis

Using the multi‐scale entropy analysis (MSE), we study the effects of water reservoirs on the river flow records based on long streamflow series covering January 1, 1954 and December 31, 2009 at four representative hydrological stations, i.e. the Longchuan, the Heyuan, the Lingxia and the Boluo stations. Hydrological effects of two major water reservoirs, the Xinfengjiang and the Fengshuba water reservoirs, are evaluated. The results indicate that: (1) before the construction of the water reservoirs, the complexity of the streamflow series comes to be decreasing from the upper to the lower East River and which should be attributed to the topographical properties and buffering effects of the river channel; (2) construction of water reservoirs greatly increases the complexity degree of the hydrological processes, and this influence is subjected to a damping process with the increase of distance between the water reservoirs and the hydrological stations; (3) power generation is the major function of the water reservoirs in the East River basin. The results of this study should be of theoretical and scientific merits in terms of conservation of the ecological environment and also water resources management under the influences of climate changes and intensifying human activities. Copyright © 2011 John Wiley & Sons, Ltd.