Browsing by Author "Yadav, Brijesh"

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Analysis of land use and land-cover pattern to monitor dynamics of Ngorongoro world heritage site (Tanzania) using hybrid cellular automata-Markov model
(Elsevier, 2022) Mwabumba, Mohamed; Yadav, Brijesh; Rwiza, Mwemezi; Larbi, Isaac; Twisa, Sekela
Assessment of land-use and land-cover (LULC) change of any region is one of the prominent features used in environmental resource management and its overall sustainable development. This study analyzed the LULC changes of Ngorongoro Conservation Area (NCA) and its surroundings using Remote Sensing and Geographical Information System integrated with Cellular Automata-Markov model. The LULC maps for the years 1995, 2005, and 2016 were classified using unsupervised and supervised classification procedure, and projected for 2025 and 2035 under business-as-usual scenario using the CA–Markov model. The results indicated maximum gains and losses in cultivated land and woodland in the study duration, respectively. The projected LULC for the period 2025 to 2035 showed a reduction in bushland, forest, water, and woodland, but an intensification in cultivated land, grassland, bare land, and the built-up area. The natural forests with high environmental values were found to be continuously declining under the current land management trend, causing the loss in the NCA’s ecological values. For sustainable management, the authorities must reach conciliation between the existing LULC patterns change and ecosystem services monitoring. A rational land use plan must be made to control the increase of cultivated land and built-up area counting a rational land use plan and ecosystem services protection guidelines. Decision makers should involve stakeholder to support improved land use management practices for balanced and sustainable ecosystem services strategies.
Assessment of Groundwater Quality under Changing Climate in Ngorongoro Conservation Area, Tanzania
(American Society of Civil Engineers, 2022-07) Mwabumba, Mohamed; Jahangeer, Jahangeer; Beegum, Sahila; Yadav, Brijesh; Rwiza, Mwemezi
Understanding the hydrochemical composition of water resources in the Ngorongoro Conservation Area (NCA, Dodoma, Tanzania) related to climate variability is essential for sustainable development. Thus, the current study used the HYDRUS-1D model to assess the groundwater quality change due to the leaching of hydrochemicals from surface water under the climate variability of the NCA. This study observed that the area’s surface water had varying hydrochemical contaminants, whereas the groundwater is currently most suitable for drinking and domestic purposes. However, it is predicted that two anions (Cl−1 and PO4−3) and two cations (Na+ and K+) are expected to exceed the permissible limits from 2036 to 2050, considering the anticipated climatic conditions. Changes in groundwater quality for cations and anions are significantly correlated to evapotranspiration and temperature, with Pearson’s coefficient of determinations r between 0.35 and 0.66. The findings of this study are necessary to benchmark better water resources management planning.
Rainfall and temperature changes under different climate scenarios at the watersheds surrounding the Ngorongoro Conservation Area in Tanzania
(Elsevier, 2022-04) Mwabumba, Mohamed; Yadav, Brijesh; Rwiza, Mwemezi; Larbi, Isaac; Dotse, Sam-Quarcoo; Manoba, Andrew; Sarpong, Solomon; Kwawuvi, Daniel
Considering the high vulnerability of Northern Tanzania to climate change, an in-depth assessment at the local scale is required urgently to formulate sustainable adaptations measures. Therefore, this study analyzed the fu- ture (2021-2050) changes in rainfall and temperature under the representative concentration pathways (RCP4.5 and RCP8.5) for the watersheds surrounding the Ngorongoro Conservation Area (NCA) at a spatio-temporal scale relative to the observed historical (1982-2011) period. The climate change analysis was performed at monthly and annual scale using outputs from a multi-model ensemble of Regional Climate Models (RCMs) and statistically downscaled Global Climate Models (GCMs). The performance of the RCMs were evaluated, and the downscaling of the GCMs were performed using Statistical Downscaling System Model (SDSM) and LARS-WG, with all the models indicating a higher accuracy at monthly scale when evaluated using statistical indicators such as corre- lation (r), Nash-Sutcliff Efficiency (NSE) and percentage bias (PBIAS). The results show an increase in the mean annual rainfall and temperature in both RCPs. The percentage change in rainfall indicated an increase relative to historical data for all seasons under both RCPs, except for the June, July, August and September (JJAS) season, which showed a decrease in rainfall. Spatially, rainfall would increase over the entire basin under both RCPs with higher increase under RCP4.5. Similar spatial increase results are also projected for temperature under both RCPs. The results of this study provide vital information for the planning and management of the studied watershed under changing climatic conditions.