Hydrogeochemistry of Shale-Limestone-Mudstone Successions Aquifers—The Case of the Hantebet Sub Basin in Northern Ethiopia

The present paper provides evidence of the possible impact of shale-limestone-mudstone successions aquifers on groundwater chemistry by assessing the different hydrogeochemical processes. This was done by considering a sedimentary aquifer basin, namely the Hantebet sub basin (24.4 km2), Tekeze basin, northern Ethiopia. Groundwater is the main source of water supply in the sub basin extracted using hand dug wells, for domestic, irrigation and livestock uses. The sub basin is dominated by Paleozoic-Mesozoic sedimentary successions. Twenty groundwater samples were collected from hand dug wells using depth-integrated sampling techniques from both confined and unconfined aquifers. The major water bearing formations are gravely sand, weathered shale and weathered and fractured limestone, and intercalated weathered and fractured limestone and mudstone. The results indicate that groundwater is acidic to neutral, fresh, and hard to very hard. Ca2+, Na+, HCO-3 and SO2-4 are dominant ions compared to Mg2+, K+, and Cl- ions which show low to very low concentrations. Among eight hydrochemical facies identified, Ca-Na-HCO3 (40%), Ca-HCO3 (20%), Ca-Mg-Na-HCO3 (10%) and Ca-Na-HCO3-SO4 (10%) types dominate water chemistry. Dissolution of calcite and gypsum, and hydrolysis of feldspars, plagioclase, biotite and pyroxene are the major geochemical processes that control the chemistry of groundwater in the area. The intercalated shale beds are the source of sodium and chloride ions. Since, this study is based on groundwater from hand dug wells, the conclusions of this study should be further verified using groundwater from deep wells that are drilled in these successions.

Urban Stormwater and Sewerage Modelling: An Approach for Peak Runoff and Volume Assessment

In this study, an integrated approach for runoff estimation using the storm water management model (SWMM) was applied to undertake a stormwater and sewerage modelling in urban setting. The main objectives of the research and this manuscript include overload detection of sewer systems during extreme rainfall events with SWMM and to model and predict the relationship between precipitation parameters and overflooding of sewer collection system that includes emergency ponds to relieve flow from pump stations. The study takes into account monitored concurrent extreme rainfall event data and peak wet weather flows observed at outfall of collection system entering a wastewater treatment plant draining the urban centre. In the study SWMM was modified and adapted for the Tati and Ntshe confluence rivers draining the urban centre of Francistown in Northern Botswana. Landuse, soil, geological, drainage and sewerage network and imperviousness data sets were acquired and developed in GIS database. The runoff coefficient is found to range between 0.12 and 0.24 in the studied catchments. The calibrated model was able to predict the observed outputs with reasonable accuracy for calibration datasets of two peak flood events of 2016-Jan 12 and 2017-Feb 16 and verification flood events of 2016-Feb 05 and 2017-Feb 26. For six watersheds that drain the study area considered with a seventh entire collection system catchment area, we have evaluated the model performance using different criteria. We have found that correlation coefficients range from 0.539 to 0.813 and NSE ranges from 40.9% to 89.0%, and RSR ranges from 0.330 to 0.812 for the calibration datasets. Whereas, for the verification dataset, the correlation coefficients range from 0.539 to 0.813 and NSE values range from 40.9% to 89.0%, and RSR values range from 0.330 to 0.812. Using the criteria adopted, the SWMM-simulated runoff values are in acceptable agreement with the observed hydrographs.