Characterising groundwater and surface-water interconnections using hydrogeology,hydrochemistry and stable isotopes in the Ouémé Delta,southern Benin

The Mio-Pliocene aquifer of the coastal sedimentary basin of Benin is the most exploited aquifer for water supply to the urbanised region in the southern part of the country. The population explosion is putting increasing pressure on quantitative and qualitative aspects of the groundwater resources. Preventing groundwater contamination caused by surface waters requires a thorough understanding of surface-water/groundwater interactions, especially the interactions between the Mio-Pliocene aquifer and surface waters. This study aimed to investigate the interactions between groundwater and surface waters along the major rivers (Sô River and Ouémé Stream) and brooks in the Ouémé Delta. Field campaigns identified 75 springs located in the valleys which feed the rivers, and thus maintain their base flow. The piezometric results indicated, through flow direction assessment, that the Mio-Pliocene aquifer feeds Ouémé Stream and Sô River. Chemical analyses of groundwater and surface waters show similar chemical facies, and changes in the chemical composition in groundwater are also observed in the surface waters. Moreover, the isotopic signatures of surface waters are similar to those of the groundwater and springs, which led to the identification of potential groundwater discharge areas. As a result of groundwater discharge into surface waters, the fraction of groundwater in the surface water is more than 66% in the brooks, regardless of the season. In the Ouémé Stream and Sô River, the fraction of groundwater is 0–21% between June and September, while from October to March it is 47–100%.

     

Analysis of meteorological drought variability in Niger and its connection with climate indices

Based on a three-month-scale standardized precipitation index (SPI-3) computed from the available rainfall data of 13 stations of Niger, meteorological drought trends, periodicities and the relationships with 10 oceanic–atmospheric variables were analysed using the Mann-Kendall test, continuous wavelet transform and cross-wavelet analysis, respectively. The results revealed a significant (p < 5%) increase in drought at five of the 13 stations. A common dominant drought periodicity of 2 years was found at all of the stations, whereas significant periodicities varied from 2 to 32 years at six stations. Among the considered climate indices, South Atlantic sea-surface temperature, Southern Oscillation Index, sea-level pressure, geopotential height and relative humidity from the Atlantic basin oscillated in anti-phase relative to the SPI-3 at an inter-annual to decadal time scale from 1960 to 1990. In this period, relative humidity from the Mediterranean basin and zonal wind oscillated in phase with the drought index.     

Ocean air masses from the East Asian monsoon dominate the land-surface atmospheric water cycles in the coastal areas of Liaodong Bay,Northeast China

Long-term atmospheric water vapour hydrogen (δ²H), oxygen (δ¹⁸O) and deuterium excess (d-excess) can provide unique insights into the land-atmosphere coupling processes. The in-situ measurements of atmospheric water vapour δ²H, δ¹⁸O and d-excess were conducted above a reed wetland of Liaodong Bay (2019–2020). We found significant inter-annual variations in atmospheric water vapour isotopes between the two growing (May–September) seasons. The δ²H, δ¹⁸O and d-excess of atmospheric water vapour exhibited different seasonal and diurnal cycles concerning the vertical measurement heights, especially in 2019. The isotopic differences of atmospheric water vapour among vertical measurement heights were more evident in the daytime. Rainfall events directly impacted the diurnal patterns of water vapour isotopes, and the influences depended on rainfall intensities. However, only weak correlations existed between water vapour isotopes and local meteorological factors (R² = 0.01–0.16, p < 0.001), such as water vapour concentration (w), Relative Humidity (RH) and surface air temperature (T_a). Based on the back-air trajectory analyses, the spatial–temporal dynamics of atmospheric water vapour isotopes are highly synchronized with monsoon activities. Different water vapour sources influence the water vapour isotope in this region and the higher d-excess value is related to the intense convection brought by the monsoon. High-resolution measurements of atmospheric water vapour isotopes will improve our understanding of the hydrological cycles in coastal areas.     

Aquifer porosity in the Pan-African semi-arid context

Water scarcity is one of the major concerns that people are facing worldwide. Although the liquid is absolutely abundant through the globe, its availability poses too much problems specifically to each region. Those problems can result in one or a combination of three basic situations: declining water (drought), overabundance of surface water (floods) or degradation of the quality of water (pollution). All these situations are reflected in the scarcity of good quality water. Arid regions are particularly concerned. In such areas where groundwater contained in aquifers is usually perceived as providence, any project of groundwater exploration and exploitation must be preceded by prior careful and meticulous investigation, in order to avoid early and premature drying. This investigation is likely to predict the future behaviour of aquifers and to improve the groundwater resources management. Beside fundamental properties as hydraulic conductivity, the present paper that addresses the water sector in the semi-arid region of northern Cameroon emphasizes the importance of porosity on aquifer productivity and consequently on the groundwater resources management. The porosity of the local aquifer has then been determined using the Waxman and Smits model which establishes a reliable relationship between the apparent and corrected formation factors, F _a and F _c , taking the clay effects into consideration. This approach can be applied in other similar semi-arid regions through the world.     

Analysis of geological structure and anthropological factors affecting arsenic distribution in the Lahore aquifer,Pakistan

This study investigated the potential factors affecting arsenic concentration in the groundwater system of Lahore, Pakistan. The effects of several factors such as population density (PD), pumping rate (PR), impermeable land use (LU), surface elevation (SE), and water-table elevation (WL) on arsenic concentration were studied in 101 union councils of Lahore. Forty single and multi-factor models were established using geographic information system (GIS) techniques to develop an arsenic contamination map and to investigate the most effective combinations among factors. Additionally, statistical tests were used to evaluate arsenic concentration between classes of the same single factor. The arsenic concentration in the Lahore aquifer varied from 0.001 to 0.143 mg L^?1. The highest arsenic concentrations were detected in the Walled City and the town of Shahdara. Among the 40 raster models, groundwater arsenic concentration showed the best matching frequency with single-factor models for PD (50.70 %) and SE (47 %). Thus, PD and SE were used to develop an arsenic distribution raster map, and they were also used to study the effect of aquifer depth on arsenic concentration. PD was found to have hidden latent variables such as PR and LU. The shallow aquifer depth was negatively correlated with arsenic concentration (r?=??0.23) and positively with PR (r?=?0.15). Therefore, when there was high PR in wells with smaller aquifer depth, the arsenic concentration was high. The existing water treatment and alternative water resources are good options, which should be developed to deal with Lahore wells contaminated with arsenic at high concentrations.     

Wavelet–copula‐based mutual information for rainfall forecasting applications

Under a climate change, the physical factors that influence the rainfall regime are diverse and difficult to predict. The selection of skilful inputs for rainfall forecasting models is, therefore, more challenging. This paper combines wavelet transform and Frank copula function in a mutual information‐based input variable selection (IVS) for non‐linear rainfall forecasting models. The marginal probability density functions (PDFs) of a set of potential rainfall predictors and the rainfall series (predictand) were computed using a wavelet density estimator. The Frank copula function was applied to compute the joint PDF of the predictors and the predictand from their marginal PDFs. The relationship between the rainfall series and the potential predictors was assessed based on the mutual information computed from their marginal and joint PDFs. Finally, the minimum redundancy maximum relevance was used as an IVS stopping criterion to determine the number of skilful input variables. The proposed approach was applied to four stations of the Nigerien Sahel with rainfall series spanning the period 1950–2016 by considering 24 climate indices as potential predictors. Adaptive neuro‐fuzzy inference system, artificial neural networks, and random forest‐based forecast models were used to assess the skill of the proposed IVS method. The three forecasting models yielded satisfactory results, exhibiting a coefficient of determination between 0.52 and 0.69 and a mean absolute percentage error varying from 13.6% to 21%. The adaptive neuro‐fuzzy inference system performed better than the other models at all the stations. A comparison made with KDE‐based mutual information showed the advantage of the proposed wavelet–copula approach.     

Understanding the occurrences of fault and landslide in the region of West-Cameroon using remote sensing and GIS techniques

Natural Hazards - Remote sensing was used to visualize the West region with the purpose of investigating recent natural hazards observed in this area. Various approaches used based on...