Christopher E. Ndehedehe

On the potentials of multiple climate variables in assessing the spatio-temporal characteristics of hydrological droughts over the Volta Basin

Multiple drought episodes over the Volta basin in recent reports may lead to food insecurity and loss of revenue. However, drought studies over the Volta basin are rather generalised and largely undocumented due to sparse ground observations and unsuitable framework to determine their space-time occurrence. In this study, we examined the utility of standardised indicators (standardised precipitation index (SPI), standardised runoff index (SRI), standardised soil moisture index (SSI), and multivariate standardised drought index (MSDI)) and Gravity Recovery and Climate Experiment (GRACE) derived terrestrial water storage to assess hydrological drought characteristics over the basin. In order to determine the space-time patterns of hydrological drought in the basin, Independent Component Analysis (ICA), a higher order statistical technique was employed. The results show that SPI and SRI exhibit inconsistent behaviour in observed wet years presupposing a non-linear relationship that reflects the slow response of river discharge to precipitation especially after a previous extreme dry period. While the SPI and SSI show a linear relationship with a correlation of 0.63, the correlation between the MSDIs derived from combining precipitation/river discharge and precipitation/soil moisture indicates a significant value of 0.70 and shows an improved skill in hydrological drought monitoring over the Volta basin during the study period. The ICA-derived spatio-temporal hydrological drought patterns show Burkina Faso and the Lake Volta areas as predominantly drought zones. Further, the statistically significant negative correlations of pacific decadal oscillations (0.39 and 0.25) with temporal evolutions of drought in Burkina Faso and Ghana suggest the possible influence of low frequency large scale oscillations in the observed wet and dry regimes over the basin. Finally, our approach in drought assessment over the Volta basin contributes to a broad framework for hydrological drought monitoring that will complement existing methods while looking forward to a longer record of GRACE observations.

Climate teleconnections influence on West Africa's terrestrial water storage

There is some evidence of rapid changes in the global atmosphere and hydrological cycle caused by the influence of climate variability. In West Africa, such changes impacts directly on water resources leading to incessant extreme hydro-meteorological conditions. This study examines the association of three global climate teleconnections (El-Nino Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), and Atlantic Multi-decadal Oscillation (AMO)) with changes in terrestrial water storage (TWS) derived from both Modern-Era Retrospective Analysis for Research and Applications (MERRA, 1980–2015) and Gravity Recovery and Climate Experiment (GRACE,2002-2014). In the Sahel region, positive phase of AMO coincided with above-normal rainfall (wet conditions) and the negative phase with drought conditions, and confirms the observed statistically significant association (𝑟=0.62) between AMO and the temporal evolutions of standardised precipitation index. This relationship corroborates the observed presence of AMO-driven TWS in much of the Sahel region (though considerably weak in some areas). While ENSO appears to be more associated with GRACE-derived TWS over the Volta basin (𝑟=–0.40), this study also shows a strong presence of AMO and ENSO induced TWS derived from MERRA reanalysis data in the coastal West African countries and most of the regions below latitude 10°N. The observed presence of ENSO and AMO driven TWS are noticeable in tropical areas with relatively high annual/bimodal rainfall and strong inter-annual variations in surface water. The AMO has a wider footprint and sphere of influence on the region s TWS and suggests the important role of North Atlantic Ocean. IOD related TWS also exists in West Africa and its influence on the region s hydrology maybe secondary and somewhat complementary. Nonetheless, presumptive evidence from the study indicates that ENSO and AMO are the two major climatic indices more likely to impact on West Africa s TWS.

Tide modelling using support vector machine regression

Abstract This research explores the novel use of support vector machine regression (SVMR) as an alternative model to the conventional least squares (LS) model for predicting tide levels. This work is based on seven harmonic constituents: M2, S2, N2, K2, K1, O1 and P1. The SVMR is modelled with four kernel functions: linear, polynomial, Gaussian radial basis function and neural. The computed r-square and root mean square error for the linear, polynomial, Gaussian radial basis function and neural SVMR kernels as well the LS indicate a strong correlation between the observed and predicted tides. But for the linear kernel the results of all the kernels are slightly better than the LS. The statistical tests of the difference between the observed tide and the LS and SVMR predicted tides and between the LS and SVMR predicted tides are insignificant at the 95% confidence level.

Modelling the impacts of global multi-scale climatic drivers on hydro-climatic extremes (1901–2014) over the Congo basin

The knowledge of interactions between oceanic and atmospheric processes and associated influence on drought episodes is a key step toward designing robust measure that could support government and institutional measures for drought preparedness to promote region-specific drought risk-management policy solutions. This has become necessary for the Congo basin where the preponderance of evidence from few case studies shows long-term drying and hydro-climatic extremes attributed to perturbations of the nearby oceans. In this study, statistical relationships are developed between observed standardised precipitation index (SPI) and global sea surface temperature using principal component analysis as a regularization tool prior to the implementation of a canonical scheme. The connectivity between SPI patterns and global ocean-atmosphere phenomena was thereafter examined using the output from this scheme in a predictive framework based on non-linear autoregressive standard neural network. The Congo basin is shown to have been characterized by persistent and severe multi-year droughts during the earlier (1901-1930) and latter (1991-2014) decades of the last century. The impacts of these droughts were extensive affecting more than 50% of the basin between 1901 and 1930 and about 40% during the 1994-2006 period. Analysis of the latest decades (1994-2014) shows that relative to the two climatological periods between 1931 and 1990, the Congo basin has somewhat become drier. This likely contributed to the observed change in the hydrological regimes of the Congo river (after 1994) as indicated by the relationship between SPI and runoff index (r = 0.69 and 0.64 for 1931-1990 and 1961-1990 periods, respectively as opposed to r = 0.38 for 1991-2010 period). Pacific ENSO influences large departures in precipitation (r = 0.89) but prediction skill metrics demonstrate that multi-scale ocean-atmosphere phenomena (R2 = 84%, 78%, and 77% for QBO, AMO, and ENSO, respectively) significantly impact on hydro-climatic extremes, especially droughts over the Congo basin.