Samuel Nii Odai

The Black Volta River basin faces several challenges, which impede the sustainability of its water resources and biodiversity. Climate change coupled with land use/land cover (LULC) change patterns account for most of the observed hydrological changes in the basin. The aim of this study was to assess the impact of changes in the climate and LULC on water resources in the basin, and its effect on the livelihoods of downstream users, particularly regarding water allocations. The water evaluation and planning (WEAP) model was applied to the assessment of runoff and streamflow and the percentage future water demand under climate change scenarios (RCP 2.6 and RCP 8.5), as well as the effects of current and future changes on water supply systems. LULC data from 1990 to 2019 were processed to detect the changes in LULC patterns in the basin. The results showed that from 1990 and 2019, the land use classes of settlements/bare ground, open savannah woodland, croplands, and waterbodies increased by 339.5%, 77.4%, 24.4%, and 607%, respectively. Close savannah woodlands, wetlands, and grasslands all decreased by 97%, 99.8%, and 21.2%, respectively. Overall, there was a significant difference in LULC changes. Hence, measures needed to be put in place to curb the changes, as the observed changes posed a serious challenge to the basin’s water resources. The results from the WEAP simulations also indicated that in the future, changes in discharge would be visible in September with ranges between 0.72 × 10⁶ m³ and 1.9 × 10⁶ m³ for RCP 2.6, and 0.65 × 10⁶ m³ and 2.5 × 10⁶ m³ for RCP 8.5, per month. Although the median values illustrate an increase in water availability from river discharge compared with the reference scenario, the uncertainties in future changes largely exceeded the predicted increases. Annual variability of the mean annual flows is projected to decrease over the period in the Black Volta Basin. Therefore, the outcomes of this study will be useful for different stakeholders within the basin in water resources planning and the formulation of appropriate policies for improving land use planning.

Reconstructing missing streamflow data can be challenging when additional data are not available, and missing data imputation of real-world datasets to investigate how to ascertain the accuracy of imputation algorithms for these datasets are lacking. This study investigated the necessary complexity of missing data reconstruction schemes to obtain the relevant results for a real-world single station streamflow observation to facilitate its further use. This investigation was implemented by applying different missing data mechanisms spanning from univariate algorithms to multiple imputation methods accustomed to multivariate data taking time as an explicit variable. The performance accuracy of these schemes was assessed using the total error measurement (TEM) and a recommended localized error measurement (LEM) in this study. The results show that univariate missing value algorithms, which are specially developed to handle univariate time series, provide satisfactory results, but the ones which provide the best results are usually time and computationally intensive. Also, multiple imputation algorithms which consider the surrounding observed values and/or which can understand the characteristics of the data provide similar results to the univariate missing data algorithms and, in some cases, perform better without the added time and computational downsides when time is taken as an explicit variable. Furthermore, the LEM would be especially useful when the missing data are in specific portions of the dataset or where very large gaps of ‘missingness’ occur. Finally, proper handling of missing values of real-world hydroclimatic datasets depends on imputing and extensive study of the particular dataset to be imputed.

Water resources are a major concern for any socio-economic development. As the quality of many surface fresh water sources increasingly deteriorate, more pressure is being imparted into groundwater aquifers. Since groundwater and the aquifers that host it are inherently vulnerable to anthropogenic impacts, there is a need for sustainable pumping strategies. However, groundwater resource management is challenging due to the heterogeneous nature of aquifer systems. Aquifer hydrogeology is highly uncertain, and thus it is imperative that this uncertainty is accounted for when managing groundwater resource pumping. This, therefore, underscores the need for an efficient optimization tool which can sustainably manage the resource under uncertainty conditions. In this paper, we apply a procedure which is new within the context of groundwater resource management—the Retrospective Optimization Approximation (ROA) method. This method is capable of designing sustainable groundwater pumping strategies for aquifers which are characterized by uncertainty arising due to scarcity of input data. ROA framework solves and evaluates a sequence of optimization sub-problems in an increasing number of realizations. We used k-means clustering sampling technique for the realizations selection. The methodology is demonstrated through application to an hypothetical example. The optimization problem was solved and analyzed using “Active Set” algorithm implemented under MATLAB environment. The results indicate that the ROA sampling based method is a promising approach for optimizing groundwater pumping rates under conditions of hydrogeological uncertainty.

Satellite-based rainfall estimation products provide a vital alternative source of rainfall data in areas where conventional precipitation measurement is not readily available. In order to facilitate the use of these products there is the need to evaluate their accuracies. This study evaluated the accuracy of three satellite rainfall products; TMPA 3B42RT, TMPA 3B42 and CMORPH in the Pra basin (23,330 km²) of Ghana. The evaluation was through the point-to-pixel method by comparing 0.25°x 0.25° satellite grids to gauged rainfall based on gauge locations and analyzed statistically using correlation coefficient (r), bias and percent bias (pBias) as the performance verification methods. Seven (7) gauge stations with no missing data for the period of 2003-2008 was used in the evaluation. The analysis was based on daily, monthly, annual and seasonal timescales. Our results showed a good correlation between the TMPA products and the gauged data on all timescales considered. The CMORPH on the other hand showed huge overestimation at all gauge locations. The TMPA 3B42 was seen to be the best amongst the three products. The overall rainfall in the basin was well depicted by the TMPA 3B42 and 3B42RT. Although there wasn’t a perfect match between the 3B42RT and 3B42 products and the gauged rainfall, these products can be used to supplement gauged rainfall measurements in the basin and in estimation of rainfall in ungauged basins with similar characteristics.

Soil loss is not limited to change from forest or woodland to other land uses/covers. It may occur when there is agricultural land-use/cover modification or conversion. Soil loss may influence loss of carbon from the soil, hence implication on greenhouse gas emission. Changing land use could be considered actually or potentially successful in adapting to climate change, or may be considered maladaptation if it creates environmental degradation. In semi-arid northern Ghana, changing agricultural practices have been identified amongst other climate variability and climate change adaptation measures. Similarly, some of the policies aimed at improving farm household resilience toward climate change impact might necessitate land use change. The heterogeneity of farm household (agents) cannot be ignored when addressing land use/cover change issues, especially when livelihood is dependent on land. This paper therefore presents an approach for simulating soil loss from an agro-ecosystem using multi-agent simulation (MAS). We adapted a universal soil loss equation as a soil loss sub-model in the Vea-LUDAS model (a MAS model). Furthermore, for a 20-year simulation period, we presented the impact of agricultural land-use adaptation strategy (maize cultivation credit i.e., maize credit scenario) on soil loss and compared it with the baseline scenario i.e., business-as-usual. Adoption of maize as influenced by maize cultivation credit significantly influenced agricultural land-use change in the study area. Although there was no significant difference in the soil loss under the tested scenarios, the incorporation of human decision-making in a temporal manner allowed us to view patterns that cannot be seen in single step modeling. The study shows that opening up cropland on soil with a high erosion risk has implications for soil loss. Hence, effective measures should be put in place to prevent the opening up of lands that have high erosion risk.

Despite its contribution to global disease burden, diarrhoeal disease is still a relatively neglected area for research funding, especially in low-income country settings. The SNOWS consortium (Scientists Networked for Outcomes from Water and Sanitation) is funded by the Wellcome Trust under an initiative to build the necessary research skills in Africa. This paper focuses on the research training needs of the consortium as identified during the first three years of the project. We reviewed the reports of two needs assessments. The first was a detailed needs assessment led by one northern partner, with follow-up visits which included reciprocal representation from the African universities. The second assessment, led by another northern partner, focused primarily on training needs. The reports from both needs assessments were read and stated needs were extracted and summarised. Key common issues identified in both assessments were supervisory skills, applications for external research funding, research management, and writing for publication in the peer-reviewed scientific literature. The bureaucratisation of university processes and inconsistencies through administration processes also caused problems. The lack of specialist laboratory equipment presented difficulties, particularly of inaccessibility through a lack of skilled staff for operation and maintenance, and of a budget provision for repairs and running costs. The lack of taught PhD modules and of research training methods also caused problems. Institutionally, there were often no mechanisms for identifying funding opportunities. On the other hand, grantees were often unable to understand or comply with the funders’ financial and reporting requirements and were not supported by their institution. Skills in staff recruitment, retention, and performance were poor, as were performance in proposal and paper writing. The requirements for ethical clearance were often not known and governance issues not understood, particularly those required by funders. SNOWS believes that working with African universities to develop networks that support African-led research driven by the local context is an effective approach to develop and retain research skills needed to change policy and practice in water, sanitation, and hygiene in Africa.

In this paper, the ability of the Burgers equation model (BEM) to describe the monoclinal-rising-wave phenomenon is presented. The BEM is transformed by standardizing the initial and final normal flow depths; and by introducing a moving coordinate system into the equation. The resulting equation is tested numerically and analytically by introducing an abrupt flow increase between initial and final steady flow causing a positive translatory wave at the upstream end of the channel. The wave attained a stable form after a long time has elapsed, and it finally approached a monoclinal-rising-wave. In the case of a negative translatory wave the wave never attained a stable form, but changed continually with the passage of time. Comparison made between the numerical solutions presented graphically and the analytical deductions confirm the ability of the BEM to describe the monoclinal-wave phenomenon in conveyance channels

A Burgers equation model (BEM) for simulating translatory waves in conveyance channels is extracted from the Saint-Venant equations for small perturbations in initial uniform flow. The present study improves upon the previous model and presents analytical solutions for the simulation of translatory waves occurring in conveyance channels. The BEM is reduced to the linear diffusion equation using the Cole–Hopf transformation and then solved by means of the Green’s function assuming an infinite domain. The simulation studies performed show that the BEM results are comparable to those of the Saint-Venant equations for small perturbations in the initial uniform flow conditions and for Froude numbers within the subcritical region. The BEM could be useful for flood routing and for simulating release of water from a reservoir into a conveyance channel when the flow perturbation is small.

To simulate slow transients in wide rectangular open channels of finite length, the St. Venant equations are approximated by a single Burgers' equation for flow depth. Flow velocity is expressed as a function of flow depth and its gradient to satisfy the continuity of flow. The Burgers' equation model has three constants uniquely determined with the Froude number of initial uniform flow to satisfy approximately the conservation of momentum for small perturbations of flow depth about an initial constant. For a given set of fixed boundary depths, depth profile and channel storage of final steady nonuniform flow are readily obtained in analytical form. This is a useful feature of the Burgers' equation model. Comparison of the Burgers' equation model with the St. Venant equations is made based on numerical results.