Dynamics of Rainfall Pattern and Groundwater Adnan Et Al
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Dynamics Of Rainfall Pattern And Groundwater Adnan et al., DYNAMICS OF RAINFALL PATTERN AND GROUNDWATER QUANTITY IN KANO BASEMENT COMPLEX: EVIDENCE FROM GROUND AND SATELLITE DATA Adnan Abdulhamid1, Murtala Muhammad Badamasi1 and Murtala Uba Mohammed1 1Department of Geography, Bayero University, Kano ABSTRACT In recent year’s incidence of surface water changes has been identified from satellite studies. Studies also attest that groundwater quantity is also changing.It is a usual symmetry that increases in rainfall would yield a corresponding increase in groundwater storage. Since 1990s rainfall in Kano began to increase in quantity, but its corresponding effective storage of groundwater quantity has been on the decrease. The study explore the missing link between the increasing rainfall and decreasing groundwater quantity in the Kano Basement complex using evidence from field data and satellite data sources. 30 years gridded rainfall data was obtained from global precipitation climatology center (GPCC) website, and rainfall trends and patterns were examined using percent changes in rainfall and groundwater. The result shows that rainfall trend has been on the increase especially around the Metropolitan Kano from the late 1990s to date, with corresponding decrease in groundwater quantity. It is concluded that anthropogenic activities especially ground water abstraction were identified as one of major causes. It is therefore recommended that adequate monitoring and planning of groundwater abstraction is needed to ensure sustainable water management. Key words: Rainfall, Kano Basement complex, Gridded Rainfall data, Satellite data, Digital Elevation Model (DEM, Groundwater INTRODUCTION Groundwater storage is an essential area which can be studied in both time and space. component of terrestrial water storage which During dry season ground water plays a crucial role influences base flow of river discharge of sustaining the river discharges. In dry season (Somorowska, 2004). And in Nigeria as well as in condition with prolonged period of absence of other parts of the tropics, rainfall is the major factor rainfall, groundwater tends to increase since the controlling aquifer recharges. Groundwater on dynamic water resources according to the local basement complex is more often seen as physical parameters of surface-subsurface system discontinuous since wells hydraulic connections are (WRECA, 1985). The piezometric water level was rare. In Kano state, it is observed from the previous always at equilibrium. studies that despite low aquifer thickness and low Recently, communities began to see discharge, weathered mantle are found in most parts depletion in the dynamic groundwater resources. of the state with little intrusions (Abdulhamid, 2010). The rate of depletion can be inferred from The general groundwater fluctuations indicated the observations of groundwater levels conducted at hydraulic connectivity for all identified points across point scale (Abdulhamid, 2010). In view of that, this Kano state and beyond through the porous medium paper examines the relationship between rainfall (Abdulhamid, 2010). The porosity of the weathered quantity and aquifer storage in the area with a view rocks (gravel, sandstone, clayey sand and sand) of to add to the understanding of extreme hydrological the area allow groundwater movement across the events. MATERIALS AND METHODS Study Area Kano State which correspond to the areal Longitude 70 4’E and 90 3’E. It is bounded to the coverage of basement complex covers the area North West by Katsina State, to the South by Kaduna extending between Latitudes 100 3’N and 120 4’N and 188 st Proceedings of the 1 International conference on Drylands Dynamics Of Rainfall Pattern And Groundwater Adnan et al., State and to the North East by Jigawa State, while to the South East by Bauchi State (Figure 1). north to 1200mm in the Southern tips. On the Kano experiences four distinct seasons, Rani (warm average, the wettest month is August has the and dry), Damina (wet and warm), Kaka (cool and highest number of rainstorms and sediment dry)and Bazara (hot and dry)closely associated with generation while the mean annual temperature in the movement of the Inter Tropical Discontinuity area ranges from 26oC to 32oC, with the high diurnal (ITD) zone. The mean annual Rainfall is about temperature ranges of 13.1oC and relative humidity of 884mm varying greatly from as low as 600mm in the 17% - 90% (Kowal and Knabe, 1972; Olofin 1987). Slopes on the surface are heading to the Chad basin formation or the main river beds (Szentes, 1974; Bennett, et al., 1978). While observation from the stratigraphy of some selected areas of basement shows the lithological characteristics of the study area. Using lithology log data presented by WRECA, 1974 and WARDROP, 1990 which revealed the stratigraphy of many places of the region, the morphology at each point is clearly visible. The layers of Basement complex have been examined through log wells and indicated that groundwater fluctuate between 4 to 27 meters in the area (Figure 2). Samples have also shown different formations of basement. Figure 1: Kano State 189 st Proceedings of the 1 International conference on Drylands Dynamics Of Rainfall Pattern And Groundwater Adnan et al., Figure 2: Stratigraphy of some parts of Basement Complex in the Kano Region Methods Three different data sets were used for the study: data gridded rainfall data and DEM were gridded satellite rainfall data from 1980- 2009; digital downloaded from the website of global precipitation elevation model (DEM); and groundwater yield data climatology center and global land cover facility for year 2000 (232 points) and 1990 (31 points). The respectively. While the groundwater data for years 190 st Proceedings of the 1 International conference on Drylands Dynamics Of Rainfall Pattern And Groundwater Adnan et al., were extracted from the works of Adnan (2010) and method of using regression, spatial interpolation and KNARDA (1990). This study presents an integrated per cent change (Figure 3). Figure 3: Work flow for the study. Latitude and longitude images were extracted from 5 year data for rainfall (1995-2000) and 2005-2010 DEM and in combination with gridded rainfall data were used respectively. For the purpose of analysis it using regression analysis spatial estimate of rainfall is important to make the following clarifications. values were generated for the entire period of study. Annual rainfall can vary abruptly from one year to Inverse distance weighted (IDW) Interpolation the other. So in other to provide a relatively stable technique was used to estimate the spatial annual rainfall average of five year data was use. On groundwater yield for year 2000. Because the 2010 the other hand groundwater changes slowly so groundwater data is limited (just about 31 points) To taking yearly data can suffice. estimate the average rainfall for years 1990 and 2010, In the last stage percentage change was them them regressed to estimate the relationship. Other estimated for both groundwater and rainfall for the extraneous variables were then used for explaining year 2000and 2010. The two change images were the change pattern and relationship observed. RESULTS AND DISCUSSIONS Rainfall Distribution The spatial distribution of rainfall across the 850mm. When this pattern is compared to recent basement complex shows a northwest and short term averages of 2000 and 2010 one observed southeast trend with a northward decrease from an increase in the amount of rainfall received. This over 1100mm to 550mm (Figure 5a). The long term increase in the amount of rainfall also include average rainfall shows that nearly three quarter of increase spatial coverage northwards (Figure 5b, and the surface area receives an average rainfall of 5c). This can be further demonstrated in Figure 6 191 st Proceedings of the 1 International conference on Drylands Dynamics Of Rainfall Pattern And Groundwater Adnan et al., where the profile for the average annual rainfall for for 1996-2000 signifying upward trend. 2005-2009 seems wetted than the annual average A temporal profile of 4 locations along the north-south gradient from 1980 to 2009 shows the drought years for 1984, 1987, 1990, 2000 and 2004 (Figure 7). All the 4 locations show similar pattern of a positive trend in rainfall amount. 192 st Proceedings of the 1 International conference on Drylands Dynamics Of Rainfall Pattern And Groundwater Adnan et al., Figure 5: Annual Average rainfall (mm) in Kano State. a) Average annual rainfall (1980-2009). b) Average annual rainfall for the year 2000 (1996-2000); and c) Average annual rainfall for year 2009 (2005-2009). a b Figure 6: Spatial profile of rainfall distribution along north-south gradient Figure 7: Temporal annual rainfall for 4 locations in Kano. 1) Doguwa Local Government 2) Bunkere Local Government 3) Kano Municipal Local Government 4) Makoda Local Government. Variation in rainfall The coefficient of variability across the study area ranged between 10 to 15 per cent with the latitude 120 N and above showing more variability (Figure 8a). The strength of this variability and consistency of rainfall over the 193 st Proceedings of the 1 International conference on Drylands Dynamics Of Rainfall Pattern And Groundwater Adnan et al., period of 1980 -2009 was examined using coefficient of determination (Figure 8b). The result showed that vast majority of the central part of the study area are consistent in terms of positive rainfall trend. a b Figure 8: a) Coefficient of variation rainfall image, b) Coefficient of determination rainfall image Interpolated Groundwater Yield result. Most of the points studied were concentrated Figure 9 shows the spatial distribution of in the central parts of the study site. However, the groundwater for the two period under study (years distribution showed that groundwater has 2000 and 2010). The number of points as well as the decreased over the years. spatial spread of the points have influenced the a b Figure 9: Spatial distribution of groundwater yield (m3/s). a) year 2000 b) years 2010.