Runoff Forecast for the Flood Season Based on Physical Factors and Their Effect Process and Its Application in the Second Songhua River Basin, China

The Second Songhua River Basin is located at the northern edge of the East Asian monsoonregion in China. The river basin has a large interannual rainfall-runoff variation often associated withfrequent 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 inthe prediction of medium- and long-term runoff. In this study, sunspots are selected as the influencingfactors of runoff based on the mechanism of astronomical factors; sensitivity analysis was used toidentify the time delay of sunspots’ influence on runoff and determine the prediction factor (relativenumber of sunspots in January and March). The BP (backpropagation) network is used to identifythe correlation between prediction factors and prediction items (monthly average inflow rate of theFengman Reservoir and the Baishan Reservoir in the flood season), and then the prediction model isconstructed. According to the test results of historical data and the actual forecast results, the forecastis working well, and the accuracy of qualitative forecasting is high

Spatio-temporal assessment of meteorological drought under the influence of varying record length: the case of Upper Blue Nile Basin, Ethiopia

This study investigates the spatial and temporal variation of meteorological droughts in the Upper Blue Nile (UBN) basin in Ethiopia using long historical records (1953–2009) for 14 meteorological stations, and relatively short records (1975–2009) for 23 other stations. The influence of using varying record length on drought category was studied by comparing the Standard Precipitation Index (SPI) results from the 14 stations with long record length, by taking out incrementally 1-year records from 1953 to 1975. These analyses show that the record length from 1953 to 1975 has limited effect on changing the drought category and hence the record length from 1975 to 2009 could be used for drought analysis in the UBN basin. Spatio-temporal analyses of the SPI values show that throughout the UBN basin seasonal or annual meteorological drought episodes occurred in the years 1978/79, 1984/85, 1994/95 and 2003/04. Persistency from seasonal to annual drought, and from one year to the next, has been found. The drought years identified by this SPI analysis for the UBN basin are known for their devastating impact in other parts of Ethiopia

An improved rainfall-threshold approach for robust prediction and warning of flood and flash flood hazards

This paper presents an improved method of using threshold of peak rainfall intensity for robust flood/flash flood evaluation and warnings in the state of São Paulo, Brazil. The improvements involve the use of two tolerance levels and the delineating of an intermediate threshold by incorporating an exponential curve that relates rainfall intensity and Antecedent Precipitation Index (API). The application of the tolerance levels presents an average increase of 14% in the Probability of Detection (POD) of flood and flash flood occurrences above the upper threshold. Moreover, a considerable exclusion (63%) of non-occurrences of floods and flash floods in between the two thresholds significantly reduce the number of false alarms. The intermediate threshold using the exponential curves also exhibits improvements for almost all time steps of both hydrological hazards, with the best results found for floods correlating 8-h peak intensity and 8 days API, with POD and Positive Predictive Value (PPV) values equal to 81% and 82%, respectively. This study provides strong indications that the new proposed rainfall threshold-based approach can help reduce the uncertainties in predicting the occurrences of floods and flash floods

SRS-GDA: A spatial random sampling toolbox for grid-based hydro-climatic data analysis in environmental change studies

We present in this paper the development of a new, open-source MATLAB toolbox SRS-GDA that aims to providerandom spatial sampling of grid-based hydro-climatic datasets for environmental change studies. This toolboxaddresses the needs of quantifying how hydro-climatic responses, which are often driven by grid-based forcingdatasets such as climate model projections, vary with location and scale. The toolbox can be used to carry outrandom spatial sampling of grid-based quantities with various constraints: shape, size, location, dominantorientation and resolution. A case study of a large dataset, the GEAR rainfall dataset is supplied to demonstratethe typical uses case of this toolbox. The provision of the toolbox for downloading together with the sample datais also presented

Impacts of urbanization on precipitation patterns in the greater Beijing–Tianjin–Hebei metropolitan region in northern China

We present a statistical method to quantify the contribution of urbanization to precipitation changes during 1958-2017 across the greater Beijing-Tianjin-Hebei (BTH) metropolitan region in northern China. We find distinct trends in precipitation in the past six decades: decreasing in annual and summer while increasing in other seasons. The spatial patterns of precipitation show discernible terrain-induced characteristics with high values in the buffer zones of plain and mountain areas and low values in the northwestern mountainous regions. Our results indicate that although urbanization has limited impacts on the trends and spatial patterns of precipitation, it has a positive contribution to the changes in precipitation for about 80% of the comparisions conducted, especially in autumn (100%), with the negative contribution being dominant in summer (66.67%). In addition, these results are sensitive to the classifications of urban and rural stations, suggesting that how to classify urban/rural areas is a crucial step to estimate the potential contribution of urbanization to precipitation changes. These findings also support that urbanization can diversify and enhance the variations in precipitation, with urban areas becoming a secondary center along with more increasing or less decreasing trends in precipitation

Assessing Climate Change Impact on Water Resources in Water Demand Scenarios Using SWAT-MODFLOW-WEAP

In this article, we present the use of the coupled land surface model and groundwater flow model SWAT-MODFLOW with the decision support tool WEAP (Water Evaluation and Planning software) to predict future surface-water abstraction scenarios in a complex river basin under conditions of climate change. The modelling framework is applied to the Dee River catchment in Wales, United Kingdom. Regarding hydrology, the coupled model improves overall water balance and low-streamflow conditions compared with a stand-alone SWAT model. The calibrated SWAT-MODFLOW is employed with high-resolution climate model data from the UKCP18 project with the future scenario of RCP85 from 2020 to 2040. Then, water supply results from SWAT-MODFLOW are fed into WEAP as input for the river reach in the downstream region of the river basin. This system is utilized to create various future scenarios of the surface-water abstraction of public water supply in the downstream region—maximum licensed withdraw, 50% authorized abstractions, monthly time series with 1% increases in water use, and maximum water withdraw per year based on historical records repeated every year with 1% increases in water use—to estimate the unmet demands and streamflow requirement. This modelling approach can be used in other river basins to manage scenarios of supply and demand

An Area-Orientated Analysis of the Temporal Variation of Extreme Daily Rainfall in Great Britain and Australia

This paper presents an analysis of the temporary variation of the area-orientated annual maximum daily rainfall (AMDR) with respect to the three spatial properties: location, size and shape of the region-of-interest (ROI) in Great Britain and Australia using two century-long datasets. The Maximum Likelihood and Bayesian Markov-Chain-Monte-Carlo methods are employed to quantify the time-varying frequency of AMDR, where a large proportion of the ROIs shows a non-decreasing level of most frequent AMDR. While the most frequent AMDR values generally decrease with larger-sized ROIs, their temporal variation that can be attributed to the climate change impact does not show the same dependency on the size. Climate change impact on ROI-orientated extreme rainfall is seen higher for rounded shapes although the ROI shape is not as significant as the other two spatial properties. Comparison of the AMDR at different return levels shows an underestimation by conventionally used stationary models in regions where a nonstationary (i.e., time-varying) model is preferred. The findings suggest an overhaul of the current storm design procedure in view of the impact of not only climate change but also spatial variation in natural processes

Spatial variation of catchment-oriented extreme rainfall in England and Wales

This paper presents the spatial variation of the annual maximum daily rainfall (AMDR) in more than 900 catchments of England and Wales over the last century with respect to different spatial features including geographic location, elevation, size, orientation and shape of catchments. A SPER toolbox is employed to extract the spatial features of catchments where the AMDR is modelled by a well-tested Generalized Extreme Value (GEV) distribution. The results show that the GEV parameters μ and σ exhibit similar patterns and are usually larger with higher elevations. Increasing catchment size can decrease parameters due to areal averaging, however, in the middle-sized transition regions of the rainfall variation, e.g., east Wales, the trend reverses. For areas at high elevation, parameters are greater in the west-northwest-oriented catchments while parameters in west-northwest or east-northeast-oriented catchments at lower elevation are similar or smaller than those with a north-south orientation. An elongated shape catchment usually has smaller parameters than a rounded shape one. These findings reveal the heterogeneity of extreme rainfall distribution in space with respect to different spatial characteristics of catchments even under the same climate, which lays a basis for further catchment-based analysis concerning the relationship between hydrological response and geomorphic properties

A Flood Risk Framework Capturing the Seasonality of and Dependence Between Rainfall and Sea Levels—An Application to Ho Chi Minh City, Vietnam

State-of-the-art flood hazard maps in coastal cities are often obtained from simulating coastal or pluvial events separately. This method does not account for the seasonality of flood drivers and their mutual dependence. In this article, we include the impact of these two factors in a computationally efficient probabilistic framework for flood risk calculation, using Ho Chi Minh City (HCMC) as a case study. HCMC can be flooded sub-annually by high tide, rainfall and storm surge events or a combination thereof during the monsoon or tropical cyclones. Using long gauge observations, we stochastically model 10,000 years of rainfall and sea level events based on their monthly distributions, dependence structure and co-occurrence rate. The impact from each stochastic event is then obtained from a damage function built from selected rainfall and sea level combinations, leading to an expected annual damage (EAD) of $1.02B (95th annual damage percentile of$2.15B). We find no dependence for most months and large differences in expected damage across months ($36M-166M) driven by the seasonality of rainfall and sea levels. Excluding monthly variability leads to a serious underestimation of the EAD by 72% to 83%. This is because high-probability flood events, which can happen multiple times during the year and are properly captured by our framework, contribute the most to the EAD. This application illustrates the potential of our framework and advocates for the inclusion of flood drivers’ dynamics in coastal risk assessments