Detecting Changes in Hydro-Climatic Variables during the Last Four Decades (1975-2014) on Downstream Kaduna River Catchment, Nigeria

This study aimed to detect trends in the long-term hydro-climatic series using non-parametric methods. The annual and seasonal linear trends of rainfall, temperature, runoff, water level and evaporation were analysed for stations in downstream Kaduna River Basin during 1975-2014. The non-parametric Mann-Kendall and Sen’s estimator of slope procedures were adopted to identify if there exists an increasing or decreasing trend with their statistical significance at 95% level of confidence. The datasets were checked to account for auto-correlation prior to determining trends using Mann-Kendall test. The existence of abrupt changes was detected by means of Cumulative Sum Charts and Bootstrapping analysis. The results of study indicated increasing trends for seasonal and annual temperature and runoff series. Water level and evaporation revealed statistically decreasing trends both on annual and seasonal periods. However, for the period 1975 to 2014 no significant distinctive trend was observed for rainfall at the investigated stations. Change-points in time series were identified in all the investigated hydro-climatic records for the sub-basin. Generally, the detection of the trend for hydro-climatic variables by Mann-Kendall test conforms to Sen’s test results. It is concluded that the basin is sensitive to climate variability and water stress impacts which will affect food security. So, it would be necessary to make adjustments in the adaptive water-use strategies being adopted at present in the catchment.

Analysis of Hydro-Climatical Variability in the Mo Basin in Togo

Climate changes are affecting water resources around the world and the Mo Basin (MB) in Togo is no exception to this observation. This study aims at analyzing the influence of hydro-climatical data in the Mo Basin. To achieve this, Pettit’s stationarity break tests, Hubert’s segmentation, Nicholson’s [1] reduced centered index, Lamb [2] and flow coefficients have been applied. In addition, temperature, precipitation, evapotranspiration, relative humidity and discharge data from 1961 to 2018 have been used for this purpose. While rainfall is decreasing despite an increase of 22.8% at the Fazao station and 2.8% at Sotouboua station, the flow coefficients evolve synchronously with the precipitation data and show a strong link between both parameters. The climatic balance sheet is positive six months in the year (May to October), throughout the period of observation (1961-2018). Only 1962 and 1963 recorded an annual rainfall greater than the annual evapotranspiration. The other years undergo a climatic drought, increasingly pronounced, which strongly impacts the hydrology of rivers. This has a strong impact on water resources and food security and resources of the Fazao-Malfakassa reserve in the region.

Climate Change and Dynamics of the ITCZ on the Hydro-Climatic Regime of the Northern Ecosystems of the Gulf of Guinea: A Case of the Grand-Lahou Lagoon System

Atmospheric dynamics and climatology in West Africa are strongly dominated by the latitudinal migration of the ITCZ which imposes directly or indirectly determinism on coastal ecosystems. Thus, the Grand-Lahou lagoon system and its watershed are influenced by the ITCZ, whose seasonal study made it possible to understand its mode of action first on climatic factors, then hydroclimatic, and finally hydrological in the context of global changes. The study of these factors showed a differentiated impact of its migration on the hydrological regime defining a new configuration of the lagoon system and beyond;the coastal ecosystems of the northern coast of the Gulf of Guinea irrigated by numerous fluvial inputs. Salinity, a hydrological parameter of critical ecosystem importance, combined with transparency and depth, has enabled the spatio-temporal description of hydrology. To do this, a series of monthly measurements (in-situ) for spatial coverage of 25 stations was tested. Long before that, the climatic and hydroclimatic parameters were obtained respectively at SODEXAM, the meteorological site earth.nullschool.net and ONADE. This study brought together the dynamics of the ITCZ and the hydrological system of the lagoon.

Combining BPANN and wavelet analysis to simulate hydro-climatic processes a case study of the Kaidu River, North-west China

Using the hydrological and meteorological data in the Kaidu River Basin during 1957-2008, we simulated the hydro-climatic process by back-propagation artificial neural network （BPANN） based on wavelet analysis （WA）, and then compared the simulated results with those from a multiple linear regression （MLR）. The results show that the variation of runoff responded to regional climate change. The annual runoff （AR） was mainly affected by annual average temperature （AAT） and annual precipitation （AP）, which revealed different varia- tion patterns at five time scales. At the time scale of 32-years, AR presented a monotonically increasing trend with the similar trend of AAT and AP. But at the 2-year, 4- year, 8-year, and 16-year time-scale, AR presented non-linear variation with fluctuations of AAT and AP. Both MLR and BPANN successfully simulated the hydro- climatic process based on WA at each time scale, but the simulated effect from BPANN is better than that from MLR.

Weather Events Associated with Strong Earthquakes and Seismic Swarms in Italy

This study discusses the possible relationship between potentially destructive seismic events,earthquake swarms,and intense weather events occurring in the same epicentral zone at time intervals ranging from one day to a few weeks.The objective of the present study is,therefore,to analyze the interaction between the lithosphere,atmosphere,and ionosphere in order to propose,prospectively,a new hydro-climatic model to be applied not only in Italy,where this research was carried out.The study concerns some of the most intense Italian earthquakes starting from 1920,with the destructive event in Lunigiana,in North Western Apennines,until the recent earthquake swarm that hit the Emilia-Romagna region followed,as in the cases analyzed in this research,by strong atmospheric disturbances.The recurrence associating seismic events with atmospheric precipitation allows us to propose some hypotheses about the triggering mechanism.In tectonically stressed areas,during pre-seismic and seismic phases,the release of gases from the ground and electrical charges near active faults is known.It is hypothesized that water condensation nuclei are carried by radon gas on atmospheric gases,also originating from cosmic rays in the upper atmosphere,generated by air ionization.

Flooding and its relationship with land cover change, population growth, and road density

Bangladesh experiences frequent hydro-climatic disasters such as flooding.These disasters are believed to be associated with land use changes and climate variability.However,identifying the factors that lead to flooding is challenging.This study mapped flood susceptibility in the northeast region of Bangladesh using Bayesian regularization back propagation(BRBP)neural network,classification and regression trees(CART),a statistical model(STM)using the evidence belief function(EBF),and their ensemble models(EMs)for three time periods(2000,2014,and 2017).The accuracy of machine learning algorithms(MLAs),STM,and EMs were assessed by considering the area under the curve—receiver operating characteristic(AUC-ROC).Evaluation of the accuracy levels of the aforementioned algorithms revealed that EM4(BRBP-CART-EBF)outperformed(AUC>90%)standalone and other ensemble models for the three time periods analyzed.Furthermore,this study investigated the relationships among land cover change(LCC),population growth(PG),road density(RD),and relative change of flooding(RCF)areas for the period between 2000 and 2017.The results showed that areas with very high susceptibility to flooding increased by 19.72%between 2000 and 2017,while the PG rate increased by 51.68%over the same period.The Pearson correlation coefficient for RCF and RD was calculated to be 0.496.These findings highlight the significant association between floods and causative factors.The study findings could be valuable to policymakers and resource managers as they can lead to improvements in flood management and reduction in flood damage and risks.

A New Statistical Approach to Assess Climate Variability in the White Bandama Watershed,Northern Cote d’Ivoire

The population of northern C&#244te d’Ivoire, especially in the white Bandama watershed, lives for majority in rural areas and depends on farming, which is mainly linked to climate variability. This study evaluates the trends within watershed’s hydro-climatic variables and their level of significance over the period 1950-2000. The methodological approach consists in applying successively standardized indexes to detect trends and breaks in hydro-climatic long-term data. The Mann-Kendall statistical test lets us know the trends significance and the Kendall-Theil Robust Line test reveals their magnitude. The Student’s t test underlines break years. Results show that although rainfall has decreased, this decline is not statistically significant. However, temperature and potential evapotranspiration have strongly rised and discharge was submitted to high decline. These changes in hydrometeorological variables appeared from 1970 to 1980. This study is different from others conducted on climate variability in the northern C&#244te d’Ivoire by the methodological statistical framework implemented and the understanding of significance level of climate trends. Until now, authors used the standardized index to detect trends in hydro-climatic parameters. For this work, we added the Mann-Kendall statistical test to assess the significance level of these trends at α = 5% and 10%. Then, the Kendall-Theil statistical test was used to highlight the trends magnitude and the student’s t test to know the break years.

Application of Parametric-Based Framework for Regionalisation of Flow Duration Curves

It is common knowledge that the end user of stream flow data may necessarily not have any prior knowledge of the quality control measures applied in their generation, therefore, conclusions drawn most often times may not be effective as desired. Thus, this study is an attempt at providing an independent quality construct to boost the confidence in the use of stream flow data by developing regional flow duration curves for selected ungauged stations of the upper Niger River Basin, Nigeria. Toward this end, stream flow data for seven gauging stations cover some sub basins in the Basin were obtained;precisely, monthly stream flow data covering a range of eleven to fifty-three years period. The flow duration curves from the gauging stations were fitted with three probability distribution models;i.e., logarithmic, power and exponential regression models. For the regionalisation, parameterisation was carried out in terms of the drainage area alone to allow for simplicity of models. Results obtained showed that the exponential regression model, in terms of Coefficient of Determination (R2) had the best fit. Though the regionalised model was simple, measurable agreement was obtained during the calibration and validation phases. However, considering the length of data used and probable variability in the stream flow regime, it is not possible to objectively generalise on the quality of the results. Against this backdrop, it suffices to take into cognisance the need to use an ensemble of catchment characteristics in the development of the flow duration curves and the overall regional models;this is important considering the implications of anthropogenic activities and hydro-climatic variations.