Past and Future Land Use/Land Cover Changes in the Ethiopian Fincha Sub-Basin

Abstract

The increasing human pressure on African regions is recognizable when looking at Land Use Land Cover (LULC) change maps, generally derived from satellite imagery. Using the Ethiopian Fincha watershed as a case study, the present work focuses on (i) identifying historical LULC change in the period 1989–2019; (ii) estimating LULC in the next thirty years, combining Geographical Information Systems (GIS) with Land Change Modelling (LCM). Landsat5/8 images were combined with field evidence to map LULC in three reference years (1989, 2004, 2019), while the Multi-Layer Markov Chain (MPL-MC) model of LCM was applied to forecast LULC in 2030, 2040, and 2050. The watershed was classified into six classes: waterbody, grass/swamp, built-up, agriculture; forest; and shrub. The results have shown that, in the past 30 years, the Fincha watershed experienced a reduction in forest and shrubs of about −40% and −13%, respectively, mainly due to ever-increasing agricultural activities, and such a trend is also expected in the future. In fact, for the period 2019–2050, LCM simulated a significant decrease in both forest and shrubs (around −70% and −20%, respectively), in favor of more areas covered by grass (19%) and built-up (20%). It is worth noting that a decrease in natural forests can drive an increase in soil erosion, fostering siltation in the water reservoirs located in the sub-basin. The study pointed out the urgency of taking actions in the sub-basin to counteract such changes, which can eventually lead to a less sustainable environment.

Advances in characterizing and monitoring land cover/use and associated ecosystem changes using remote sensing data

“…Land use is a key SWAT model input that influences surface runoff, evapotranspiration, erosion, nutrients and pesticide load in a watershed. The LULC data used in the present research were previously described by Regasa and Nones (2022), who, using satellite imagery and Geographic Information Systems, investigated LULC changes in past (1989,2004,2019) and future (2030,2040,2050) years. In their study, ground truth data, key informant interviews and focal group discussions were also considered to reduce uncertainties associated with deriving LULC from remote sensing.…”

Remote sensing assessment of anthropogenic and climate variation effects on river channel morphology and vegetation: Impact of dry periods on a European piedmont river

“…The first satellite (Landsat 1) was launched in 1972, and, since then, a series of additional satellites have been launched, with the most recent Landsat 9 operating since 2021. These satellites carry multispectral sensors able to provide surface reflectance measurements used for a wide range of scientific and land management applications (Cavallo et al, 2022; Wulder et al, 2004), including morphological evolution of river channels (Halder & Mowla Chowdhury, 2023; Nones, 2021) changes in land cover land use (Potapov et al, 2022; Regasa & Nones, 2022), vegetation coverage (Andreatta et al, 2022; Xie et al, 2019) and surface water extent (Li et al, 2022; Pekel et al, 2016). The recent advancements in using satellite imagery required also the development of an up‐to‐date database able to handle an increasing quantity of information.…”

Impact of land use land cover change using remote sensing with integration of socio-economic data on Rural Livelihoods in the Nashe watershed, Ethiopia

“…Most of the time more biodiversity has been observed in wetland and forestland than in other land use types [ 9 ]. Recently, a study focused on sub-Saharan Africa, showing a decrease in land covered by the natural environment, mostly due to anthropogenic activities such as population growth, economic development, urbanization, and globalization [ 10 ].…”

“…These reports have revealed heterogeneity in changes in the type, pattern, direction, and magnitude of LULC across the country and highlighted the difficulty of extrapolating the known trends to unstudied areas. Therefore, region-specific information on such changes in the LULC is essential for land-use planning aimed at wise resource management and maximizing the productivity of both agricultural and non-agricultural land at regional and national scales [ 10 ].…”

“…[ 5 ] on the title of impacts of hydropower dam construction on the adjacent rural households' food insecurity in Northwestern Ethiopia, and also as studied by Ref. [ 10 ] on title of Past and Future LULCC in the Ethiopian Fincha Sub-Basin. However, no one scholar addressed the impact of LULCC using GIS with Integration of Socio-Economic on Rural Livelihoods, and as well as on the environment particularly in the Nashe Watershed western, Ethiopia.…”