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

Chilagane, Nyemo A.; Kashaigili, Japhet J.; Mutayoba, Edmund

doi:10.4236/gep.2020.82006

Cited by 8 publications

(9 citation statements)

References 15 publications

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“…The combined classification included both supervised classification and unsupervised classification methods, which are broadly used in land cover classification. The maximum likelihood algorithm (MLC) is the most commonly used method in supervised classification with remotely sensed image data [3], which computes the posterior possibility of a pixel fitting into the corresponding class based on the Bayes theorem [34]. The Universal Transverse Mercator (UTM) map coordinate system, Zone 48 North, and Datum Arc 1984 (WGS_1984_UTM_ZONE_48N) were used in these images.…”

Section: Image Processing and Data Analysismentioning

confidence: 99%

Using RS Data-Based CA–Markov Model for Dynamic Simulation of Historical and Future LUCC in Vientiane, Laos

et al. 2020

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: Land use/cover change (LUCC) is one of the causes of global climate and environmental change. Understanding rapid LUCC in urbanized areas is vital for natural resources management for sustainable development. This study primarily considered Vientiane, the capital of Laos, which experienced rapid LUCC due to both natural and anthropogenic factors. The study used geographical information system (GIS) combined with ERDAS and TerrSet technologies to objectively process the ground surveyed and remotely obtained data in order to investigate the historical LUCC as well as predict future LUCC in the study area during the periods of 1995–2018 and 2030–2050, respectively. A comprehensive list of assessment factors comprised of both natural and anthropogenic factors was used for analysis using the cellular automata–Markov (CA–Markov) model. The results show a historical loss of intact forest of 24.36% and of bare land of 1.01%. There were also tremendous increases in degraded forest (11.36%), agricultural land (8.91%), built-up areas (4.49%) and water bodies (1.16%). Finally, the LUCC prediction results indicate the conversion of land use from one type to another, particularly from natural to anthropogenic use, in the near future. These changes demonstrate that the losses associated with ecosystem services will destructively impact human wellbeing in the city and other areas of the country. The study results provide the basic scientific knowledge for LUCC planners, urban designers and natural resources managers. They serve as a decision-making support tool for the establishment of sustainable land resource utilization policies in Vientiane and other cities of similar conditions.

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Section: Image Processing and Data Analysismentioning

confidence: 99%

Using RS Data-Based CA–Markov Model for Dynamic Simulation of Historical and Future LUCC in Vientiane, Laos

et al. 2020

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“…Spatial data includes 30 m resolution digital elevation model (DEM) downloaded from NASA (https://reverb.echo.nasa.gov). The digital Open Journal of Modern Hydrology LULC map (Figure 2) of the study area for 1990, 2015 and 2040 obtained from LULC change analysis reported by [22], mapped based on Landsat TM for 1990 and Landsat OLI for 2015 (http://earthexplorer.usgs.gov). Land use/land cover for the year 2040 was projected based on CA-Markov chain analysis.…”

Section: Swat Model Inputsmentioning

confidence: 99%

“…Results (Appendix 1 and Appendix 2) indicate that land use and land cover change between 1990 and 2015 and the projected land use/cover for the year 2040 as reported by [22]. The report detailed the decrease in forest, riverine for-…”

Section: Land Use Land Cover Change Analysismentioning

confidence: 99%

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

Chilagane¹,

Kashaigili²,

Mutayoba³

et al. 2021

OJMH

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Little Ruaha River catchment (6370 Km 2 ) 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 How to cite this paper: Chilagane, N.A.,

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“…Other researchers [14,15] carried out hydrological studies in the Mbarali River and Wami river subbasins, respectively, highlighting the impacts of climate change and landcover dynamics on river flows. The consequences of land cover dynamics on catchment hydrology have equally been conducted in the Little Ruaha River catchment [16]. Some studies, albeit scanty, that aimed at assessing the impact of land cover changes on groundwater recharge in Tanzania have been carried out in the northern part of Tanzania recently [17,18].…”

Section: Background Informationmentioning

confidence: 99%

Natural Groundwater Recharge Response to Climate Variability and Land Cover Change Perturbations in Basins with Contrasting Climate and Geology in Tanzania

Mussa

Mjemah

Machunda

2021

Earth

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The response of aquifers with contrasting climate and geology to climate and land cover change perturbations through natural groundwater recharge remains inadequately understood. In Tanzania and elsewhere in the world, studies have been conducted to assess the impact of climate change and variability, and land use/cover changes on stream flow using different models, but similar studies on groundwater dynamics are inadequate. This study, therefore, examined the influence of land use/cover and climate dynamics on natural groundwater recharge in basins with contrasting climate and geology in Tanzania, applying the modified soil moisture balance method, coupled with the curve number (CN). The method hinges on the balance between the incoming water from precipitation and the outflow of water by evapotranspiration. The different parameters in the soil moisture balance method were computed using the Thornthwaite Water Balance software. The potential evapotranspiration (PET) was calculated using the daily maximum and minimum temperatures, utilizing two-temperature-based PET methods, Penman–Monteith (PM) and Hargreaves–Samani (HS). The rainfall data were obtained from the gauging stations under the Tanzania Meteorological Agency and some additional data were acquired from climate observatories management by water basins. The results show that there has been a quasi-stable CN in the Singida semi-arid, fractured crystalline basement aquifer (74.2 in 1997, 73.64 in 2005, and 73.87 in 2018). In the Kimbiji, humid, Neogene sedimentary aquifer, the CN has been steadily increasing (66.69 in 1997, 69.08 in 2008, and 71.42 in 2016), indicating the rapid land cover changes in the Kimbiji aquifer as compared to the Singida aquifer. For the Kimbiji humid aquifer, the PET calculated using the Penman–Monteith (PM) method for the 1996/1997, 2007/2008, and 2015/2016 hydrological years were 1156.5, 1079.5, and 1143.9 mm/year, respectively, while for the Hargreaves–Samani (HS) method, the PET was found to be 1046.1, 1138.3, and 1204.4 mm/year for the 1996/1997, 2007/2008, and 2015/2016 hydrological years, respectively. For the Singida semi-arid aquifer, the PM PET method resulted in 2083.3, 2053.6, and 1875.4 mm/year for the 1996/1997, 2004/2005, and 2017/2018 hydrological years, respectively. The HS method produced relatively lower PET values for the semi-arid area (1839.4, 1814.7, and 1710.2 mm/year) for the 1996/1997, 2004/2005, and 2017/2018 hydrological years, respectively. It was equally revealed that the recharge and aridity indices correspond with the PET calculated using two temperature-dependent methods. The decline of certain land covers (forests) and increase in others (built-up areas) have contributed to the increase in surface runoff in each study area, possibly resulting in the decreasing trend of groundwater recharge. An overestimation of the PET using the HS method in the Kimbiji humid aquifer was observed, which was relatively smaller than the overestimation of the PET using the PM method in the Singida semi-arid aquifer. Despite the difference in climate and geology, the response of the two aquifers to rainfall is similar. The combined influence of climate and land cover changes on natural groundwater recharge was observed to be prominent in the Kimbiji aquifer, while only climate variability appreciably influences natural groundwater recharge in the Singida semi-arid aquifer. El Nino and the Southern Oscillation as part of the climate variability phenomenon dwarfed the time lags between rainfall and recharge in the two basins, regardless of their difference in climate and geology.

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

Cited by 8 publications

References 15 publications

Using RS Data-Based CA–Markov Model for Dynamic Simulation of Historical and Future LUCC in Vientiane, Laos

Using RS Data-Based CA–Markov Model for Dynamic Simulation of Historical and Future LUCC in Vientiane, Laos

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

Natural Groundwater Recharge Response to Climate Variability and Land Cover Change Perturbations in Basins with Contrasting Climate and Geology in Tanzania

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