Hydrological response of semi-arid river catchment to rainfall and temperature fluctuations

Determining the response of basin water resources to rainfall and temperature fluctuations is a crucial source of information for basins water resources planning and management. The study used a descriptive, Mann-Kendall trend test (M-K) and Multiple Linear Regression (MLR). The mean, standard deviations and variations were spatially interpolated using the geostatistical technique. The trend results showed an increase in both rainfall and temperature series. However, the only statistically significant trends were in June and September for rainfall series and in February, May, and April for the temperature series. Rainfall exhibited high temporal variability whereas temperature showed high spatial variability. The intra-annual variability was higher than the inter-annual variability, suggesting that the local climate is largely controlled by natural force. The result of the multiple linear regression (R2=0.431), indicates that the hydrology and water resources of the basin are impacted largely by factors not considered in this study such as land use changes, infiltration, and rate of evaporation among others. However, among the factor considered, rainfall (Beta = 0.505; P = 001) has the highest impacts on the river discharge behavior and should be given preference while addressing water resources predicaments in the catchment

Long-term water quality assessment in a tropical monsoon

Multivariate statistical techniques such as principal component analysis (PCA) and cluster analysis (CA) were applied to water quality parameters in order to interpret complex matrices for better assessment of water quality and environmental status of a watershed. A study was conducted to assess water quality and to establish relationship among water quality parameters in Kelantan River basin. Water quality data was obtained from Department of Environment, (DOE) Malaysia from 2005-2014. Multivariate statistical techniques such as principal component analysis (PCA) and cluster analysis (CA) were applied to 15 water quality parameters in order to interpret complex matrices for better assessment of water quality and environmental status of the watershed. From the results, five PCs were extracted which are collectively accountable for controlling approximately 70% of the watershed’s water quality. Results of cluster analysis indicated that three water quality parameters that included total suspended solids, total solids and turbidity control the water quality of the study area. These parameters were allocated into three clusters based on their similarity. The finding of this study will contribute to existing knowledge of the problems associated with water quality in the basin. This information can be put to use by land use managers and policy makers for future planning and development of the watershed

Detection and prediction of land use change impact on the streamflow regime in Sahelian river basin, Northwestern Nigeria

Detecting and predicting the impact of land use/land cover (LULC) changes on streamflow are crucial sources of information for the effective management and protection of land and water resources in Sahelian ecosystems such as the Hadejia river basin. In this study, LULC change detection was performed using ENVI, while the LULC modeling was conducted using the cellular automata (CA)–Markov in the IDRISI environment. However, the streamflow trend and variation were assessed using the Mann–Kendall (MK) trend test and the inverse distance weightage (IDW). Before the LULC modeling and projection (2030), the LULC was classified for 1990, 2000, and 2010 using supervised classification. Model output revealed a strong relationship between LULC and streamflow trend, thus, the decade 1990–2000 was the decade with high forest clearance and streamflow output, and consequently severe floods. However, the decade 2000–2010 witnessed land use expansion mainly via construction (3.4%). Meanwhile, the scenario will slightly change in the future as agriculture is projected to expand by about 9.3% from 2010 to 2030 due to the increased human population. Thus, food insecurity aggravated by climate change should be anticipated, and measures to avert/reduce their effects must be initiated

Modelling impacts of climate variability and land use change on water balance in the Hadejia River Basin, Northern Nigeria

Hadejia River Basin (HRB) is located in the semi-arid region of northern Nigeria. The total area of the basin is about 24,896 km2 with about 60% of the population engaged in agricultural activities. Other socioeconomic activities are fishing, grazing, and recreation. Almost all the operational activities are climate dependent and sensitive, therefore any change/variation in climate or factors that may aggravate its impacts such as land use change in the basin might have consequential impacts on the water balance and socioeconomic lives of the people of the area estimated at about 15 million inhabitants. This river basin has attracted several studies, however, none of these studies investigated the impact of climate variability and land use change on the water balance of the basin using any hydrological model such as SWAT. Modelling the impacts of future climate and land use change on water balance in the Hadejia River Basin (HRB) was achieved through the following objectives; (i) examining the trends of precipitation and temperature under the recent climate change (ii) determining the presence of trends and variations in the river discharge (iii) predicting the pattern of land use changes based on the past few decades, and (iv) evaluating current and project the impacts of climate variability and land use change on the water balance of HRB. The methods and techniques used to achieve the stated objectives include multivariate statistical analysis such as ANOVA, cluster analysis, multiple linear regression, Mann-Kendall (MK) and Modified Mann-Kendall (MMK) both of which were used for trend and variations analysis. Others were remote sensing, GIS, CA– Markov model for land use change classification, simulation, and prediction. Furthermore, the future impact of climate and land use/cover changes were evaluated using an integrated approach, combining the climate (GCMs), hydrological (SWAT) and the land use prediction (CA–Markov) models. The results showed increased warming with noticeable moisture improvement that is relatively uniform over the entire landscape (1980-2015). Land use analysis indicates a drastic transformation of forest to non-forest land uses, with the construction land uses being the most expanding land use type with percentage changes of 0.50%, 1.95%, 5.31% in 1990, 2000 and 2016 and 7.8% for the projected period (2032). The calibration and validation of the SWAT result was both acceptable with Nash-Sutcliffe (NS) = 0.72 and 0.63, indicating good performance and robustness of the model. For the future simulations (2020-2040) executed in two different scenarios (1st and 2nd). The results show a decline in average annual precipitation (23.4%), runoff (2.1%), baseflow (3.7%), streamflow (20.4%) and potential evapotranspiration (PET) (0.82%) in the first scenario. While, in the second scenario surface runoff rise by 12.6% but yet water yield declined by 27.2%, suggesting the influence of land use change on surface runoff. On the whole, the basin shows a high sensitivity to climate variations than to the changing land use. Despite this reality, attention should be given to climate and land use issues/problems in the basin, before it gets out of hand. Immediate action should be taken right away on the later the fact that it is logically within human control/ability, unlike climate

Evidence of climate variability from rainfall and temperature fluctuations in semi-arid region of the tropics

The pattern of rainfall and temperature behaviour in the Hadejia River Basin (HRB) has been assessed. The behaviour of rainfall and temperature have been used as proxies in detecting the presence of climate variability. Historical rainfall and temperature monthly data spanning thirty-six years (1980–2015) obtained from the Nigerian Meteorological Agency (NIMET) was used in this study. ANOVA and Mann-Kendall trend test was used for the data analysis. The ANOVA results showed significant variation in rainfall, maximum and minimum temperature between the stations. The Mann-Kendall trend test result shows an increasing trend in both rainfall and temperature in annual statistics, though statistically insignificant. However, the monthly trends result showed mixed results of both significant and insignificant as well as increasing and decreasing trends. The mean, standard deviation and the coefficient of variation were spatially interpolated using inverse distance weightage technique for easy comprehension. Even though the annual increasing trends result was statistically insignificant except for two out of the ten stations, it is still crucial for planning water-related activities and programs considering the sensitivity and fragility of the region to minor climatic variations