Assessing the spatio-temporal variations of surface water quality is important for water environment management. In this study, surface water samples are collected from 2008 to 2015 at 17 stations in ...the Ying River basin in China. The two pollutants i.e. chemical oxygen demand (COD) and ammonia nitrogen (NH
3
-N) are analyzed to characterize the river water quality. Cluster analysis and the seasonal Kendall test are used to detect the seasonal and inter-annual variations in the dataset, while the Moran’s index is utilized to understand the spatial autocorrelation of the variables. The influence of natural factors such as hydrological regime, water temperature and etc., and anthropogenic activities with respect to land use and pollutant load are considered as driving factors to understand the water quality evolution. The results of cluster analysis present three groups according to the similarity in seasonal pattern of water quality. The trend analysis indicates an improvement in water quality during the dry seasons at most of the stations. Further, the spatial autocorrelation of water quality shows great difference between the dry and wet seasons due to sluices and dams regulation and local nonpoint source pollution. The seasonal variation in water quality is found associated with the climatic factors (hydrological and biochemical processes) and flow regulation. The analysis of land use indicates a good explanation for spatial distribution and seasonality of COD at the sub-catchment scale. Our results suggest that an integrated water quality measures including city sewage treatment, agricultural diffuse pollution control as well as joint scientific operations of river projects is needed for an effective water quality management in the Ying River basin.
Streamflow information is of great significance for flood control, water resources utilization and management, ecological services, etc. Continuous streamflow prediction in ungauged basins remains a ...challenge, mainly due to data paucity and environmental changes. This study focuses on the modification of a nonlinear hydrological system approach known as the time variant gain model and the development of a regressive method based on the modified approach. This method directly correlates rainfall to runoff through physically based mathematical transformations without requiring additional information of evaporation or soil moisture. Also, it contains parsimonious parameters that can be derived from watershed properties. Both characteristics make this method suitable for practical uses in ungauged basins. The Huai River Basin of China was selected as the study area to test the regressive method. The results show that the proposed methodology provides an effective way to predict streamflow of ungauged basins with reasonable accuracy by incorporating regional watershed information (soil, land use, topography, etc.). This study provides a useful predictive tool for future water resources utilization and management for data-sparse areas or watersheds with environmental changes.
This study investigates the changes of rainfall patterns along with the underlying reasons in the Nansi Lake Basin (NLB), China during 1960–2009. Results show that the annual rainfall increases from ...the northwest to the southeast of the NLB. From the temporal variation perspective, annual rainfall decreases slightly in the majority of stations. Furthermore, in spite of no pronounced trends are detected in all stations, the annual rainfall series fluctuate intensely, and present step changes around the year of 1974 and 2002. This change pattern of rainfall is verified by the approximately wet–dry–wet phase pattern, which is exhibited in the standardized departures of annual rainfall series, during the three sub-periods divided by the pre-obtained two change years. In particular, the parametric t test demonstrate that the step change in 2002 is significant. The variations in the rainy season (RS, June–September) rainfall contributed mostly to the changes in the annual rainfall, and a high similarity of change patterns between the RS and annual rainfall is also observed. The long term mean RS and annual rainfall decreases largely from the sub-period of 1960–1974 to 1974–2002, and increased largely from the sub-period of 1974–2002 to 2002–2009 in the NLB. Besides, various elements, such as the summer East Asian summer monsoon and summer Pacific decadal oscillation, may together lead to the step changes in summer rainfall over our study area.
This paper investigates hydrological responses to climate change in the Luan River basin in North China. The average outputs of IPCC AR4 multi-models under different scenarios (SRES-A2, A1B and B1) ...are used to drive the SWAT model after calibration to simulate hydrological processes during 2011–2099. Results show increasing trends for precipitation, temperature and runoff under all scenarios, while compared to the baseline, the annual runoff decreases except for a slight increase during the 2080s under the A2 and A1B scenarios; meanwhile, the runoff in spring, autumn and winter decreases except for a slight increase during the 2080s under A2.
The unit hydrograph (UH) is a hydrological tool that represents the unit response of a watershed to a unit input of rainfall. UH models based on lumped reservoir and channel conceptual cascade assume ...that rainfall is evenly distributed, thus limiting the use of UHs to relatively small watersheds of less than around 500 km2 in area. In this paper, a new hydrograph prediction method, named the generalized concentration curve (GCC), was derived that can be applied to large heterogeneous watersheds. The GCC method divides the watershed into subareas by isochrones. In each subarea, an independent linear reservoir-channel cascade model that considers both attenuation and translation is established. Comparative application of the GCC and the traditional Nash instantaneous unit hydrograph to 18 storm events from three medium-sized watersheds (727, 1,800 and 5,253 km2 in area) revealed superior performance of the GCC, with the average Nash–Sutcliffe efficiency coefficient higher by 7.66%, and the average peak discharge error lower by 4.14%. This study advances the theory of UH and expands the scope of application of UH to larger watersheds.
PDF
