Comparative Analysis of Climatic Change Trend and Change-Point Analysis for Long-Term Daily Rainfall Annual Maximum Time Series Data in Four Gauging Stations in Niger Delta

The aim of this study is to establish the prevailing conditions of changing climatic trends and change point dates in four selected meteorological stations of Uyo, Benin, Port Harcourt, and Warri in the Niger Delta region of Nigeria. Using daily or 24-hourly annual maximum series (AMS) data with the Indian Meteorological Department (IMD) and the modified Chowdury Indian Meteorological Department (MCIMD) models were adopted to downscale the time series data. Mann-Kendall (MK) trend and Sen’s Slope Estimator (SSE) test showed a statistically significant trend for Uyo and Benin, while Port Harcourt and Warri showed mild trends. The Sen’s Slope magnitude and variation rate were 21.6, 10.8, 6.00 and 4.4 mm/decade, respectively. The trend change-point analysis showed the initial rainfall change-point dates as 2002, 2005, 1988, and 2000 for Uyo, Benin, Port Harcourt, and Warri, respectively. These prove positive changing climatic conditions for rainfall in the study area. Erosion and flood control facilities analysis and design in the Niger Delta will require the application of Non-stationary IDF modelling.

Identifying Extreme Rainfall Events Using Functional Outliers Detection Methods

Outlier detection techniques play a vital role in exploring unusual data of extreme events that have a critical effect considerably in the modeling and forecasting of functional data. The functional methods have an effective way of identifying outliers graphically, which might not be visible through the original data plot in classical analysis. This study’s main objective is to detect the extreme rainfall events using functional outliers detection methods depending on the depth and density functions. In order to identify the unusual events of rainfall variation over long time intervals, this work conducts based on the average monthly rainfall of the Taiz region from 1998 to 2019. Data were extracted from the Tropical Rainfall Measuring Mission and the analysis has been processed by R software. The approaches applied in this study involve rainbow plots, functional highest density region box-plot as well as functional bag-plot. According to the current results, the functional density box-plot method has proven effective in detecting outlier compared to the functional depth bag-plot method. In conclusion, the results of the current study showed that the rainfall over the Taiz region during the last two decades was influenced by the extreme events of years 1999, 2004, 2005, and 2009.

基于DEM的洪涝灾害监测模型与应用(英文)

In order to assess the flood damage rapidly and accurately,this paper proposed a practical method of flood disaster monitoring based on meso-scale automatic weather stations rainfall data and 1:5 million high-precision DEM (digital elevation model) data.It can predict roughly areas by the automatic weather station rainfall analysis and processing when the floods happen.Using partitions 'horizontal' approximation methods,the model of DEM flooding disaster's monitoring has been constructed based on 1:5 million high-precision DEM.And the technical methods applied to the analysis of experimental area.The result of flood disaster's monitoring is carried on comparison and the analysis through the verification by CBERS-02B.It finds that the area of floods is very consistent by the model of DEM and CBERS-02B flooding disaster's monitoring.So the method of flood disaster's motoring based on DEM can be real-time,dynamic,and can monitor the flood zone accurately and effectively.It also can provide the decision making department with present and assisting scheme of policy making.

Water storage changes and balances in Africa observed by GRACE and hydrologic models

Continental water storage plays a major role in Earth＇s climate system. However, temporal and spatial variations of continental water are poorly known, particularly in Africa. Gravity Recovery and Climate Experiment （GRACE） satellite mission provides an opportunity to estimate terrestrial water storage （TWS） variations at both continental and river-basin scales. In this paper, seasonal and secular variations of TWS within Africa for the period from January 2003 to July 2013 are assessed using monthly GRACE coefficients from three processing centers （Centre for Space Research, the German Research Centre for Geo- sciences, and NASA＇s Jet Propulsion Laboratory）. Monthly grids from Global Land Data Assimilation System （GLDAS）-I and from the Tropical Rainfall Measuring Mission （TRMM）- 3B43 models are also used in order to understand the reasons of increasing or decreasing water storage. Results from GRACE processing centers show similar TWS estimates at seasonal timescales with some differences concerning inter-annual trend variations. The largest annual signals of GRACE TWS are observed in Zambezi and Okavango River basins and in Volta River Basin. An increasing trend of 11.60 mm/a is found in Zambezi River Basin and of 9 mm/a in Volta River Basin. A phase shift is found between rainfall and GRACE TWS （GRACE TWS is preceded by rainfall} by 2-3 months in parts of south central Africa. Comparing GLDAS rainfall with TRMM model, it is found that GLDAS has a dry bias from TRMM model.