Search Results (12)

With the acceleration of urbanization and the increased frequency of extreme rainfall events, flooding has emerged as one of the most serious natural disaster problems, particularly affecting riparian cities. This study conducted a flooding risk assessment and an analysis of the driving factors behind flood disasters in the Songhua River Basin utilizing an improved Soil Conservation Service Curve Number (SCS-CN) model. First, the model was improved by slope adjustments and effective precipitation coefficient correction, with its performance evaluated using the Nash–Sutcliffe efficiency coefficient (NSE) and the Root Mean Square Error (RMSE). Second, flood risk mapping was performed based on the improved model, and the distribution characteristics of the flooding risk were analyzed. Additionally, the Geographical Detector (GD), a spatial statistical method for detecting factor interactions, was employed to explore the influence of natural, economic, and social factors on flooding risk using factor detection and interaction detection methods. The results demonstrated that the improvements to the SCS-CN model encompassed two key aspects: (1) the optimization of the CN value through slope correction, resulting in an optimized CN value of 50.13, and (2) the introduction of a new parameter, the effective precipitation coefficient, calculated based on rainfall intensity and the static infiltration rate, with a value of 0.67. Compared to the original model (NSE = 0.71, rRMSE = 19.96), the improved model exhibited a higher prediction accuracy (NSE = 0.82, rRMSE = 15.88). The flood risk was categorized into five levels based on submersion depth: waterlogged areas, low-risk areas, medium-risk areas, high-risk areas, and extreme-risk areas. In terms of land use, the proportions of high-risk and extreme-risk areas were ranked as follows: water > wetland > cropland > grassland > shrub > forests, with man-made surfaces exacerbating flood risks. Yilan (39.41%) and Fangzheng (31.12%) faced higher flood risks, whereas the A-cheng district (6.4%) and Shuangcheng city (9.4%) had lower flood risks. Factor detection results from the GD revealed that river networks (0.404) were the most significant driver of flooding, followed by the Digital Elevation Model (DEM) (0.35) and the Normalized Difference Vegetation Index (NDVI) (0.327). The explanatory power of natural factors was found to be greater than that of economic and social factors. Interaction detection indicated that interactions between factors had a more significant impact on flooding than individual factors alone, with the highest explanatory power for flood risk observed in the interaction between annual precipitation and DEM (q = 0.762). These findings provide critical insights for understanding the spatial drivers of flood disasters and offer valuable references for disaster prevention and mitigation strategies. Full article

The study aimed to investigate the spatiotemporal variation of annual precipitation and extreme precipitation within the Songhua River Basin (SRB). It utilized precipitation data collected from 60 meteorological stations within the SRB during the period 1968–2019. Employing Empirical Orthogonal Function (EOF) analysis, it decomposed spatiotemporal characteristics of annual precipitation in the SRB. Through Pearson correlation analysis, application of the cross-wavelet transform, and wavelet coherence analysis, the current study explored the correlation between geographical factors, local air temperature, circulation factors, and annual and extreme precipitation. The results indicated an increasing trend for annual precipitation and for most indices of extreme precipitation within the SRB, apart from the consecutive dry days (CDD). Spatially, a general pattern of “more in the east and less in the west” was observed. Annual precipitation types in the basin were resolved into two modes with the first mode showing a general tendency of more (or less) precipitation over the entire basin, while the second mode exhibited less (or more) precipitation in the western areas and more (or less) in the eastern areas. Longitude, latitude, and altitude significantly impacted annual precipitation and extreme precipitation. Local air temperature notably affected the consecutive wet days (CWD). The West Pacific Subtropical High (WPSH) exerts a strong influence on the annual precipitation and extreme precipitation within the basin. Full article

The aim of this study is to evaluate the performance of the Global Climate Model (GCM) of the Coupled Model Intercomparison Project Phase 6 (CMIP6) in historical simulations of temperature and precipitation. The goal is to select the best performing GCMs for future projection of temperature and precipitation in the Second Songhua River Basin under multiple shared socioeconomic pathways (SSPs). Interannual variability skill (IVS) and Taylor diagrams are used to evaluate the spatiotemporal performance of GCMs against temperature and precipitation data published by the China Meteorological Science Commons during 1956–2016. In addition, five relatively independent models are selected to simulate the temperature and precipitation for 2021–2050 using Hierarchical Clustering. The selected models are CMCC-ESM2, EC-Earth3-Veg-LR, IPSL-CM6A-LR, MIROC-ES2L, and MPI-ESM1-2-HR. The projected results find that SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios show an increasing trend of future annual mean temperature and precipitation. However, for annual precipitation, there is a mixed state of increase and decrease among different models on the seasonal scale. In general, future temperature and precipitation changes still show a trend of growth and uneven distribution in the Second Songhua River Basin, which may be further accelerated by human activities. Full article

Understanding the role of climate change and catchment characteristics in hydrological activity is important for the efficient use of water resources. In this study, a Budyko framework suitable for non-steady conditions was used to assess the impacts of climate change and catchment characteristics on the long-term changes in annual and seasonal runoff in the Second Songhua River (SSR) basin during the last 30 years. Based on the analysis of the hydro-meteorological series of the SSR, the runoff in the SSR basin showed a non-significant increasing trend. The hydro-meteorological elements changed abruptly in 2009, and the study period was divided into a baseline period (1989–2009) and a disturbed period (2010–2018). Runoff increased during the disturbed period compared to the baseline period, with a significant increase in spring runoff in the upstream area and summer runoff in the downstream area. The attribution analysis results indicated that the annual runoff was mainly affected by climatic factors, and 66.8–99.6% of yearly runoff changes were caused by climate change. Catchment characteristics had little effect on yearly runoff but significantly affected seasonal runoff. The catchment characteristics affecting runoff were mainly increased water withdrawal, changes in snowfall, degradation of permafrost, and changes in reservoir operation. This study provides a basis for further understanding the intra-annual runoff variability for SSR and other similar rivers. Full article

The Second Songhua River Basin is located at the northern edge of the East Asian monsoon region in China. The river basin has a large interannual rainfall-runoff variation often associated with frequent droughts and floods. Therefore, the mid-long-term runoff prediction is of great significance. According to a review of the national and international literature, there are few studies on sunspots in the prediction of medium- and long-term runoff. In this study, sunspots are selected as the influencing factors of runoff based on the mechanism of astronomical factors; sensitivity analysis was used to identify the time delay of sunspots’ influence on runoff and determine the prediction factor (relative number of sunspots in January and March). The BP (backpropagation) network is used to identify the correlation between prediction factors and prediction items (monthly average inflow rate of the Fengman Reservoir and the Baishan Reservoir in the flood season), and then the prediction model is constructed. According to the test results of historical data and the actual forecast results, the forecast is working well, and the accuracy of qualitative forecasting is high. Full article

Densely distributed Global Navigation Satellite System (GNSS) stations can invert the terrestrial water storage anomaly (TWSA) with high precision. However, the uneven distribution of GNSS stations greatly limits the application of TWSA inversion. The purpose of this study was to compensate for the spatial coverage of GNSS stations by simulating the vertical deformation in unobserved grids. First, a new deep learning weight loading inversion model (DWLIM) was constructed by combining the long short-term memory (LSTM) algorithm, inverse distance weight, and the crustal load model. DWLIM is beneficial for improving the inversion accuracy of TWSA based on the GNSS vertical displacement. Second, the DWLIM-based and traditional GNSS-derived TWSA methods were utilized to derive TWSA over mainland China. Furthermore, the TWSA results were compared with the TWSA solutions of the Gravity Recovery and Climate Experiment (GRACE) and Global Land Data Assimilation System (GLDAS) model. The results indicate that the maximum Pearson’s correlation coefficient (PCC), Nash–Sutcliffe efficiency (NSE) coefficient, and root mean square error (RMSE) equal 0.81, 0.61, and 2.18 cm, respectively. The accuracy of DWLIM was higher than that of the traditional GNSS inversion method according to PCC, NSE, and RMSE, which were increased by 67.11, 128.15, and 22.75%. The inversion strategy of DWLIM can effectively improve the accuracy of TWSA inversion in regions with unevenly distributed GNSS stations. Third, this study investigated the variation characteristics of TWSA based on DWLIM in 10 river basins over mainland China. The analysis shows that the TWSA amplitudes of Songhua and Liaohe River basins are significantly higher than those of the other basins. Moreover, TWSA sequences in each river basin contain annual seasonal signals, and the wave peaks of TWSA estimates emerge between June and July. Overall, DWLIM provides a useful measure to derive TWSA in regions where GNSS stations are uneven or sparse. Full article

Climate change and human activities are two important factors affecting surface runoff. In water resource management and planning, it is generally important to separate the contribution of these factors when assessing runoff changes. The Changbai Mountain area is rich in water resources and is an important hydropower energy base for Northeast China. This study used Sen’s slope estimator to explore trends in runoff precipitation and evapotranspiration from 1960 to 2016, and the results showed a downward trend in runoff and an upward trend in precipitation and evaporation in most areas. The mutation point of the annual time series for the observed runoff was estimated, and the time series was divided into the base period (1960–1975) and impact period (1976–2016). Based on the Budyko framework, we performed attribution analysis of the runoff changes, and analyzed the difference between the mountainous region and the whole basin. We determined that the impacts of climate change and human activities, on average, accounted for decreases in the runoff by 60.15% and 39.85%, respectively, for the Second Songhua River Basin; 73.74% and 26.26%, respectively, for the Tumen River Basin; 84.76% and 15.24%, respectively, for the Yalu River Basin; human activities were the main causes of runoff changes in the Changbai Mountain area; climate change was the main cause of runoff changes in mountainous regions. The results of this study show that the reasons for the change in runoff in mountainous regions and the whole basin in the same area are different, which has some illuminating significance for water resources management of different elevation areas. Full article

In the past several decades, climate change and human activities have influenced hydrological processes, and potentially caused more frequent and extensive flood and drought risks. Therefore, identification and quantification of the driving factors of runoff variation have become a hot research area. This paper used the trend analysis method to show that runoff had a significant downward trend during the past 60 years in the Second Songhua River Basin (SSRB) of Northeast China. The upper, middle, and lower streams of five hydrological stations were selected to analyze the breakpoint of the annual runoff in the past 60 years, and the breakpoints were used to divide the entire study period into two sub-periods (1956–1974 and 1975–2015). Using the water–energy coupling balance method based on Choudhury–Yang equation, the climatic and catchment landscape elasticity coefficient of the annual runoff change was estimated, and attribution analysis of the runoff change was carried out for the Fengman Reservoir and Fuyu stations in SSRB. The change in potential evapotranspiration has a weak effect on the runoff, and change in precipitation and catchment landscape were the leading factors affecting runoff. Impacts of climate change and land cover change were accountable for the runoff decrease by 80% and 11% (Fengman), 17% and 206% (Fuyu) on average, respectively; runoff was more sensitive to climate change in Fengman, and was more sensitive to catchment landscape change in Fuyu. In Fengman, the population was small, owing to the comparatively inhospitable natural conditions, and so human activities were low. However, in Fuyu, human activities were more intensive, and so had more impact on runoff for the Lower Second Songhua River compared to the Upper Second Songhua River. Full article

Drought is a natural extreme climate event which occurs in most parts of the world. Northeastern China is one of the major agricultural production areas in China and also a typical vulnerable climate zone. To understand the spatio-temporal characteristics of drought over northeastern China, we first assessed the trends of precipitation and temperature. Drought events were then characterized by Standardized Precipitation Evapotranspiration Index over various temporal scales. The Trend Free Prewhitening Mann–Kendall test and distinct empirical orthogonal function, were used to investigate the trends and spatio-temporal patterns of droughts. The results indicate precipitation increasing trends are mostly detected in Heilongjiang and Jinling provinces, however, the majority of the trends are insignificant. Temperature increasing trends are detected over the entire northeastern China and most of them are significant. Decreasing drought trends are observed in Heilongjiang province and some bordering area in Jilin province, whereas increasing trends are noticed in Liaoning province and some bordering area in Jilin province. Two main sub-regions of drought variability—the Liaohe River Plain and the Second Songhua River basin (LS region), and the Songnen Plain and the Lesser Hinggan Mountains (SL region) are identified, and the detected droughts for the two sub-regions correspond well with recorded drought loss. The results will be beneficial for regional water resource management and planning, agriculture production, and ecosystem protection in northeastern China. Full article

Rainstorm weather systems and storm flood characteristics were studied to explore the relationship between the rainstorm weather system, the type of rainstorm, the cause of the flood and the time of occurrence, and some basic characteristics law of storm floods are summarized in the Second Songhua River Basin (Northeastern China). Then, the periodicity of catastrophic years was identified using the commensurability method and is shown to have an average of 11 years. Compared with simple flood forecasting, forecasting of flood-causing precipitation has a longer forecast period, which can gain the requisite time to discharge a reservoir and regain storage capacity, lower the limitation level, and manage the occurrence of flooding. Full article

The Second Songhua River is the biggest river system in Jilin Province, China. In recent years, the rapid economic development in this area has increased the prominence of water resources and water-related environmental problems; these include surface water pollution and the overexploitation of groundwater resources. Bank infiltration on the floodplains of the Second Songhua River is an important process of groundwater-surface water exchange under exploitation conditions. Understanding this process can help in the development of water resource management plans and strategies for the region. In this research, a multi-criteria evaluation index system was developed with which to evaluate the suitability of bank filtration along the Second Songhua River. The system was comprised of main suitability indexes for water quantity, water quality, the interaction intensity between surface water and groundwater, and the exploitation condition of groundwater resources. The index system was integrated into GIS (Geographic Information System) to complete the evaluation of the various indicators. According to the weighted sum of each index, the suitability of river bank filtration (RBF) in the study area was divided into five grades. Although the evaluation index system and evaluation method are applicable only to the Second Songhua River basin, the underlying principle and techniques it embodies can be applied elsewhere. For future generalization of the evaluation index system, the specific evaluation index and its scoring criteria should be modified appropriately based on local conditions. Full article

Climate variation and human activities are commonly recognized as two major factors affecting basin hydrology. However, quantifying their individual effect on runoff is challenging. In this study, long-term (1960–2009) river discharge and weather data in the Songhua River Basin (SRB, 556,800 km²), Northeast China, were gathered to separate the impacts of climate variation and human activities on runoff in five sub basins of the SRB. Mann-Kendall test, moving t-test and precipitation-runoff double cumulative curve were utilized to identify trends and change points of the hydrometeorlogical variables. Based on the change point, the 50-year study period was divided into two time series: 1960–1974 where minimal human activities took place and 1975–2009 where extensive land use change occurred and river engineering projects were undertaken. Subsequently, individual contributions of climate and human factors were assessed through a hydrologic sensitivity analysis. Our study found a significant decline in runoff of the SRB over the past 50 years. Contribution of climate variation and human activities to the change varied temporally and spatially. For the 1975–2009 period, human activities made a greater contribution (62%–82%) to the total runoff decline of the SRB. However, climate variation played a bigger role in runoff reduction in two sub river basins (63%–65%) between 1975 and 1989, as well as in runoff increase in other two sub river basins (85%–86%) between 1990 and 1999. Spatially, the effect of human activities on runoff decline was relatively stronger in the lower basin areas in the 1960s and 1970s while showing an increasing role in the upper basin areas in the past two decades. Full article