Assessment of Climate Change’s Impacts on River Flows in the Songwe Sub-Basin

River flow in the Songwe sub-basin is predicted to alter due to climate change, which would have an impact on aquatic habitats, infrastructure, and people’s way of life. Therefore, the influence of climate change should be taken into account when making decisions about the sustainable management of water resources in the sub-basin. This study looked into how river discharge would react to climate change in the future. By contrasting hydrological characteristics simulated under historical climate (1981-2010) with projected climate (2011-2040, 2041-2070, and 2071-2100) under two emission scenarios, the effects of climate change on river flow were evaluated (RCP 4.5 and RCP 8.5). The ensemble average of four CORDEX regional climate models was built to address the issue of uncertainty introduced by the climate models. The SWAT model was force-calibrated using the results from the generated ensemble average for the RCP 4.5 and RCP 8.5 emission scenarios in order to mimic the river flow during past (1981-2010) and future (2011-2100) events. The increase in river flows for the Songwe sub-basin is predicted to be largest during the rainy season by both the RCP 4.5 and RCP 8.5 scenarios. Under RCP 8.5, the abrupt decrease in river flow is anticipated to reach its maximum in March 2037, when the discharge will be 44.84 m3/sec, and in March 2027, when the discharge will be 48 m3/sec. The extreme surge in river flow will peak, according to the RCA4, in February 2023, in April 2083 under RCP 4.5, and, according to the CCLM4 and RCA4, in November 2027 and November 2046, respectively. The expected decrease and increase in river flow throughout both the dry and wet seasons may have an impact on the management of the sub-water basin’s resources, biodiversity, and hydraulic structures. The right adaptations and mitigation strategies should be adopted in order to lessen the negative consequences of climate change on precipitation, temperature, and river flow in the sub-basin.

Impact of Land Use and Land Cover Changes on Surface Runoff and Sediment Yield in the Little Ruaha River Catchment

Little Ruaha River catchment (6370 Km2) in the Southern Agricultural Growth Corridor of Tanzania (SAGCOT), is one of the country’s most significant waterways due to its ecological composition and economic value. Regardless of its ecological and economical value, the regional hydrologic condition has been tremendously affected due to land uses alteration, influenced by different socio-economic factors. This study aimed to understand the associated impacts of the present Land Use Land Cover (LULC) change on the surface runoff and sediment yield in the Little Ruaha River Catchment. Hydrological modelling using Soil and Water Assessment Tool (SWAT Model) was done to quantify the impact of land use and land cover dynamics on catchment water balance and sediment loads. The calibration and validation of the SWAT model were performed using sequential uncertainty fitting (SUFI-2). The results showed that, for the given LULC change, the average annual surface runoff increased by 2.78 mm while average annual total sediment loading increased by 3.56 t/ha, the average annual base flow decreased by 2.68 mm, ground water shallow aquifer recharge decreased from 2.97 mm and a slight decrease in average annual ground water deep aquifer recharge by 0.14 mm. The model predicts that in the future, there will be a further increase in both surface runoff and sediment load. Such changes, increased runoff generation and sediment yield with decreased base flow have implications on the sustenance flow regimes particularly the observed reduced dry season river flow of the Little Ruaha River, which in turn cause adverse impacts to the biotic component of the ecosystem, reduced water storage and energy production at Mtera Hydroelectrical dam also increasing the chances of flooding at some times of the year. The study recommends land use planning at the village level, and conservation agricultural practices to ameliorate the current situation. Developing multidisciplinary approaches for integrated catchment management is the key to the sustainability of Little Ruaha River catchment.

Modeling Surface Water Availability for Irrigation Development in Mbarali River Sub-Catchment Mbeya, Tanzania

Although Tanzania has a large land suitable for irrigation development, only 4.2% of the arable land which is potential for irrigation has been developed. Mbarali District is characterized by commercial and small-scale irrigation activities for paddy production. Currently, surface water availability for irrigation in Mbarali District is dwindling due to high water demands. Inadequate studies that estimate water availability for irrigation is one of the underlying factors to the lack of irrigation development in many parts of Tanzania including in Mbarali District. This study, therefore, aimed to model surface water availability for irrigation development in Mbarali River sub-catchment Mbeya, Tanzania. The Soil and Water Analysis Tool (SWAT) model and field observations were used to accomplish the study. The model estimates that Mbarali River sub-catchment receives about 631 mm of total mean precipitation annually. About 53% of received precipitation is lost through evapotranspiration, 12% recharged to deep aquifer and the remaining 35% discharged to the stream flow through surface runoff, lateral flow and return flow from unconfined aquifer. Discharge to the steam flow contributes to the total annual means of river discharge ranging from 0 - 10 cubic meters per second at upper catchment to 120 - 140 cubic meters per second at lower catchment. The study recommends that the lower reach of the Mbarali River sub-catchment is potential for irrigation than the upper reach as it has potential river flow that can support irrigation activities. The study also notes the urgent need for water reallocation plan to meet competing water needs in the lower reach of Mbarali River sub-catchment. Moreover, the study addresses the potentiality of irrigation in upper catchment under sustainable water management practices including excavation of small ponds to capture and store surface runoff for dry season use or to supplement irrigation as the rainfall declines.

Evaluation for the Performance of the CORDEX Regional Climate Models in Simulating Rainfall Characteristics over Mbarali River Catchment in the Rufiji Basin, Tanzania

This study aims to evaluate the performance of the individual Regional Climate Models (RCMs) used in Coordinated Regional Climate Downscaling Experiment (CORDEX) and the ensemble average of the four RCMs to feign the characteristics of the rainfall pattern for the Mbarali River catchment in Rufiji Basin for the period of 1979 to 2005. Statistical analysis for model performance such as Root mean square error, Mean error, Pearson correlation coefficient, Mean, Median, standard deviation and trend analysis are used. In addition to the statistical measure of model performance, the models are tested on their ability to capture the observed annual cycles and interannual variability of rainfall. Results indicated that the RCMs from the CORDEX indicated a better performance to reproduce the rainfall characteristics over Mbarali River catchment in Rufiji Basin. They reproduced fairly the Era Interim annual cycle and inter-annual variability of rainfall. The ensemble average performed better than individual models in representing rainfall over Mbarali River catchment in Rufiji Basin. These suggest that rainfall simulation from the ensemble average will be used for the assessment of the hydrological impact studies over Mbarali River catchment in Rufiji Basin.

Homogeneity of Monthly Mean Air Temperature of the United Republic of Tanzania with HOMER

The long-term climate datasets are widely used in a variety of climate analyses. These datasets, however, have been adversely impacted by inhomogeneities caused by, for example relocations of meteorological station, change of land use cover surrounding the weather stations, substitution of meteorological station, changes of shelters, changes of instrumentation due to its failure or damage, and change of observation hours. If these inhomogeneities are not detected and adjusted properly, the results of climate analyses using these data can be erroneous. In this paper for the first time, monthly mean air temperatures of the United Republic of Tanzania are homogenized by using HOMER software package. This software is one of the most recent homogenization software and exhibited the best results in the comparative analysis performed within the COST Action ES0601 (HOME). Monthly mean minimum (TN) and maximum (TX) air temperatures from 1974 to 2012 were used in the analysis. These datasets were obtained from Tanzania Meteorological Agency (TMA). The analysis reveals a larger number of artificial break points in TX (12 breaks) than TN (5 breaks) time series. The homogenization process was assessed by comparing results obtained with Correlation analysis and Principal Component analysis (PCA) of homogenized and non-homogenized datasets. Mann-Kendal non-parametric test was used to estimate the existence, magnitude and statistical significance of potential trends in the homogenized and non-homogenized time series. Correlation analysis reveals stronger correlation in homogenized TX than TN in relation to non-homogenized time series. Results from PCA suggest that the explained variances of the principal components are higher in homogenized TX than TN in relation to non-homogenized time series. Mann-Kendal non-parametric test reveals that the number of statistical significant trend increases higher with homogenized TX (96%) than TN (67%) in relation to non-homogenized datasets.

Historical and Future Spatial and Temporal Changes in Land Use and Land Cover in the Little Ruaha River Catchment, Tanzania

Increased anthropogenic activities in the Little Ruaha River Catchment have modulated the catchment condition, nevertheless, the future changes as a result of increased anthropogenic activities are unknown. Understanding the future changes is vitally important for the design of appropriate strategies towards sustainable management of the catchment resources. This study applied Remote Sensing and GIS techniques (Jensen & Lulla, 1987) to assess the historical long-term changes in land use and land cover using Landsat satellite images of 1990, 2005 and 2015, and modelled the future change in land use and land cover up to 2040 using the stochastic CA-Markov chain (Almeida et al., 2005). The historical land use and land cover change detection results indicate that between 1990 and 2005 the area under forest changed from 39,872 ha to 22,957 ha, woodland changed from 109,692 ha to 72,809 ha, wetland decreased from 19,157 ha to 11,785 ha, the cultivated land increased from 106,782 ha to 109,047 ha, likewise, the built-up area increased from 9408 ha to 11,674 ha. Results between 2005 and 2015 show the substantial changes where the forest decline from 22,957 ha to 15,950 ha, woodland decreased from 72,809 ha to 58,554 ha and the wetland changed from 11,785 ha to 5622 ha. Cultivated land and built up area increased from 109,047 ha and 11,674 ha to 143,468 ha and 13,765 ha respectively. Generally, the study has revealed the substantial decline in forest, woodland and wetland by 23,922 ha, 51,138 ha and 13,535 ha respectively, and an increase of cultivated land and built up area by 36,668 ha and 4357 ha respectively in 15 years, between 1990 and 2015. The predicted future land use and cover for the next 15 years (2040) showed an overall increase in cultivated land, built up area, grassland and bushland to 24.82%, 2.24%, 25.18% and 20.41% respectively, and a decrease in forest, woodland and wetland in the order of 1.87%, 7.87% and 0.03% respectively. The study concludes that, there have been significant changes in land use and cover in the catchment which likely to impend the sustainability of the catchment productivity, hence recommends the holistic system thinking and analysis approach in management and utilization of catchment resources.

Assessing the Impacts of Land Use and Land Cover Changes on Hydrology of the Mbarali River Sub-Catchment. The Case of Upper Great Ruaha Sub-Basin, Tanzania

Intensification of agricultural land use and population growth from 1990-2017 has caused changes in land cover and land use of the Mbarali River sub-catchment which is located in the Upper Great Ruaha Sub basin, Tanzania. This has affected the magnitude of the surface runoff, total water yield and the groundwater flow. This study assesses the impacts of the land cover and land use changes on the stream flows and hydrological water balance components (surface runoff, water yield, percolation and actual evapotranspiration). The land use and land cover (LULC) maps for three window period snapshots, 1990, 2006 and 2017 were created from Landsat TM and OLI_TIRS with the help of QGIS version 2.6. Supervised classification was used to generate LULC maps using the Maximum Likelihood Algorithm and Kappa statistics for assessment of accuracy. SWAT was set up and run to simulate stream flows and hydrological water balance components. The assessment of the impacts of land use and land cover changes on stream flows and hydrological water balance component was performed by comparing hydrological parameters simulated by SWAT using land use scenarios of 2006 and 2017 against the baseline land use scenario of 1990. Accuracy of LULC classification was good with Kappa statistics ranging between 0.9 and 0.99. There was a drastic increase in areal coverage of cultivated land, for periods 1990-2006 (5.84%) and 2006-2017 (12.05%) compared to other LULC. During 2006 and 2017 surface runoff increased by 4% and 9% respectively;however, water yield increased by only 0.5% compared to 1990 baseline period. This was attributed to increased proportion of cultivated land in the sub-catchment which has a high curve number (59.60) that indicates a higher runoff response and low infiltration rate.

Moist Potential Vorticity Vector for Diagnosis of Heavy Rainfall Events in Tanzania

In this paper, we modify the convective vorticity vector (CVV) defined as a cross product of absolute vorticity and gradient of equivalent potential temperature to moist potential vorticity vector (MPVV) defined as a cross product of absolute vorticity () and the gradient of the moist-air entropy potential temperature (). The patterns of (MPVV) are compared with the patterns of heavy rainfall events that occurred over different regions in Tanzania on 20th to 22nd December, 2011 and on 5th to 8th May, 2015. Moreover, the article aimed at assessing the relative contributions of the magnitude, horizontal and vertical components of (MPVV) detecting on the observed patterns of rainfall events. Dynamic and thermodynamic variables: wind speed, temperature, atmospheric pressure and relative humidity from numerical output generated by the Weather Research and Forecasting (WRF) model running at Tanzania Meteorological Agency (TMA) were used to compute MPVV. It is found that MPVV provide accurate tracking of locations received heavy rainfall, suggesting its potential use as a dynamic tracer for heavy rainfall events in Tanzania. Finally it is found that the first and second components of MPVV contribute almost equally in tracing locations received heavy rainfall events. The magnitude of MPVV described the locations received heavy rainfall events better than the components.