Hydrological Response of the Wami–Ruvu Basin to Land-Use and Land-Cover Changes and Its Impacts for the Future

The evaluation of the hydrological responses of river basins to land-use and land-cover (LULC) changes is crucial for sustaining water resources. We assessed the impact of LULC changes (1990–2018) on three hydrological components (water yield (WYLD), evapotranspiration (ET), and sediment yield (SYLD)) of the Wami–Ruvu Basin (WRB) in Tanzania, using the Soil and Water Assessment Tool (SWAT). The 1990 LULC imagery was used for SWAT simulation, and imagery from 2000, 2010, and 2018 was used for comparison with modelled hydrological parameters. The model was calibrated (1993–2008) and validated (2009–2018) in the SWAT-CUP after allowing three years (1990–1992) for the warm-up period. The results showed a decrease in WYLD (3.11 mm) and an increase in ET (29.71 mm) and SYLD (from 0.12 t/h to 1.5 t/h). The impact of LULC changes on WYLD, ET, and SYLD showed that the increase in agriculture and built-up areas and bushland, and the contraction of forest led to the hydrological instability of the WRB. These results were further assessed with climatic factors, which revealed a decrease in precipitation and an increase in temperature by 1°C. This situation seems to look more adverse in the future, based on the LULC of the year 2036 as predicted by the CA–Markov model. Our study calls for urgent intervention by re-planning LULC and re-assessing hydrological changes timely.

Geospatial Evaluation of Land Use and Land Cover Changes in Ashulia Industrial Hub in Dhaka, Bangladesh

Spatial and temporal evaluation of the land use and land cover (LULC) changes, its dynamism and overall consequences are considered the fundamental variables in global climate change. These immense changes influence ecosystem, life, and livelihoods. Over the last few decades, industrial expansion in Bangladesh has a major effect on LULC across the suburban areas of the capital city Dhaka, especially the surrounding areas of Ashulia industrial hub. While providing new approaches to improve the frontiers of antecedent revolutions, particularly those of LULC changes monitoring and mapping, this study tried to evaluate further land development and planning in the study area between 2014 and 2020. Remote sensing imageries and relevant multiple secondary information were consecutively used as datasets. The interactive supervised classification tool using a maximum likelihood process was applied in LULC changes evaluations, detections, and as well providing fruitful explanations. Therefore, evaluated LULC maps’ overall accuracies were between 84% and96%, and kappa coefficient between 0.83 and 0.92. The results revealed that the urbanization and built-up area were the prime LULC type (77.36% in 2020) in the study area and were exceedingly increasing land cover type over water bodies, bare land and vegetation. Overall, in between 2014 and 2020, the LULC types as of water bodies, barelands, and vegetation have decreased by 212 hectares, 435 hectares, and 470 hectares, respectively. Moreover, overall downward trends of LULC changes were identified in all the land use types except built-up area. Hence, imbalanced land conversions and lack of proper planning together were creating the region highly vulnerable to several disasters as well as imbalanced ecosystem. Th study findings can help the decision makers and planners apart from future research.

Analysis of Land Use and Land Cover Changes in Urban Areas Using Remote Sensing: Case of Blantyre City

Blantyre City has experienced a wide range of changes in land use and land cover (LULC). This study used Remote Sensing (RS) to detect and quantify LULC changes that occurred in the city throughout a twenty-year study period, using Landsat 7 Enhanced Thematic Mapper (ETM+) images from 1999 and 2010 and Landsat 8 Operational Land Imager (OLI) images from 2019. A supervised classification method using an Artificial Neural Network (ANN) was used to classify and map LULC types. The kappa coefficient and the overall accuracy were used to ascertain the classification accuracy. Using the classified images, a postclassification comparison approach was used to detect LULC changes between 1999 and 2019. The study revealed that built-up land and agricultural land increased in their respective areas by 28.54 km2 (194.81%) and 35.80 km2 (27.16%) with corresponding annual change rates of 1.43 km·year−1 and 1.79 km·year−1. The area of bare land, forest land, herbaceous land, and waterbody, respectively, decreased by 0.05%, 90.52%, 71.67%, and 6.90%. The LULC changes in the study area were attributed to urbanization, population growth, social-economic growth, and climate change. The findings of this study provide information on the changes in LULC and driving factors, which Blantyre City authorities can utilize to develop sustainable development plans.

Integrated Approach to Quantify the Impact of Land Use and Land Cover Changes on Water Quality of Surma River, Sylhet, Bangladesh

This study aims to assess the impacts of land use and land cover (LULC) changes on the water quality of the Surma river in Bangladesh. For this, seasonal water quality changes were assessed in comparison to the LULC changes recorded from 2010 to 2019. Obtained results from this study indicated that pH, electrical conductivity (EC), and total dissolved solids (TDS) concentrations were higher during the dry season, while dissolved oxygen (DO), 5-day biological oxygen demand (BOD5), temperature, total suspended solids (TSS), and total solids (TS) concentrations also changed with the season. The analysis of LULC changes within 1000-m buffer zones around the sampling stations revealed that agricultural and vegetation classes decreased; while built-up, waterbody and barren lands increased. Correlation analyses showed that BOD5, temperature, EC, TDS, and TSS had a significant relationship (5% level) with LULC types. The regression result indicated that BOD5 was sensitive to changing waterbody (predictors, R2 = 0.645), temperature was sensitive to changing waterbodies and agricultural land (R2 = 0.889); and EC was sensitive to built-up, vegetation, and barren land (R2 = 0.833). Waterbody, built-up, and agricultural LULC were predictors for TDS (R2 = 0.993); and waterbody, built-up, and barren LULC were predictors for TSS (R2 = 0.922). Built-up areas and waterbodies appeared to have the strongest effect on different water quality parameters. Scientific finding from this study will be vital for decision makers in developing more robust land use management plan at the local level.

Habitat Integrity in Protected Areas Threatened by LULC Changes and Fragmentation: A Case Study in Tehran Province, Iran

The integration and connection of habitats in protected areas (PAs) are essential for the survival of plant and animal species and attaining sustainable development. Investigating the integrity of PAs can be useful in developing connections among patches and decreasing the fragmentation of a habitat. The current study has analyzed spatial and temporal changes to habitat to quantify fragmentation and structural destruction in PAs in Tehran Province, Iran. To achieve this purpose, the trends in land use/land cover (LULC) changes and the quantitative metrics of the landscape ecology approach have been examined. The results revealed that in Lar National Park, low-density pasture has the top increasing trend with 4.2% from 1989 to 2019; in Jajrud PA, built-up has the top increasing trend with 1.5% during the studied years; and among the land uses in TangehVashi Natural Monument, bare land has the top increasing trend with 0.6% from 1989 to 2019. According to the findings, habitat fragmentation and patch numbers have expanded in the studied areas due to the development of economic and physical activities. The results also indicate that the current trend of habitat fragmentation in PAs will have the highest negative impacts, especially in decreasing habitat integrity, changing the structure of patterns and spatial elements, and increasing the edge effect of patches.

Analysing land use/land cover changes and its dynamics using remote sensing and GIS in Gubalafito district, Northeastern Ethiopia

Mapping and quantifying the status of Land use/Land cover (LULC) changes and drivers of change are important for identifying vulnerable areas for change and designing sustainable ecosystem services. This study analyzed the status of LULC changes and key drivers of change for the last 30 years through a combination of remote sensing and GIS with the surveying of the local community understanding of LULC patterns and drivers in the Gubalafto district, Northeastern Ethiopia. Five major LULC types (cultivated and settlement, forest cover, grazing land, bush land and bare land) from Landsat images of 1986, 2000, and 2016 were mapped. The results demonstrated that cultivated and settlement constituted the most extensive type of LULC in the study area and increased by 9% extent. It also revealed that a substantial expansion of bush land and bare land areas during the past 30 years. On the other hand, LULC classes that has high environmental importance such as grazing land and forest cover have reduced drastically through time with expanding cultivated and settlement during the same period. The grazing land in 1986 was about 11.1% of the total study area, and it had decreased to 5.7% in 2016. In contrast, cultivated and settlement increased from 45.6% in 1986 to 49.5% in 2016. Bush land increased from 14.8 to 21% in the same period, while forest cover declined from 8.9 to 2% in the same period. The root causes for LULC changes in this particular area include population growth, land tenure insecurity, and common property rights, persistent poverty, climate change, and lack of public awareness. Therefore, the causes for LULC changes have to be controlled, and sustainable resources use is essential; else, these scarce natural resource bases will soon be lost and will no longer be able to play their contribution in sustainable ecosystem services. Article Highlights Forest cover and grazing lands declined rapidly. Fluctuating trends in cultivated and settlement, bush land and bare land. Population pressure and associated demand are the main causes behind LULC changes in the study area.

Effects of Long-Term Land Use and Land Cover Changes on Ecosystem Service Values: An Example from the Central Rift Valley, Ethiopia

Changes in land use and land cover (LULC) are the leading contributors to the decline and loss of ecosystem services in the world. The present study covered the Central Rift Valley lakes basin in Ethiopia, focusing on the valley floor and the East and West escarpments, to analyze changes in LULC and to estimate associated losses in ecosystem service values (ESVs). Covering both upstream and downstream areas in the basin, the study addressed major gaps in existing studies by connecting the sources and sinks of material (e.g., sediment and water) in source-to-lake systems. Additionally, the study facilitated the identification of critical areas for conserving natural resources and reversing the decline of associated ESVs in the Central Rift Valley. A post-classification comparison approach was used to detect LULC changes between 1973 and 2020 using four Landsat images from 1973, 1990, 2005 and 2020. The value transfer valuation method was used to estimate the changes in ESVs due to LULC changes. Among the seven major identified LULC classes, farmlands, settlements, and bare lands showed positive changes, while forestlands, grasslands, shrublands and waterbodies showed negative changes over the last 47 years. The expansion of farmlands, for example, has occurred at the expense of grasslands, forestlands and shrublands. The changes in LULC over a period of 47 years resulted in a total loss of US $62,110.4 × 106 in ESVs. The contributors to the overall loss of ESVs in decreasing order are provisioning services (US $33,795.1 × 106), cultural services (US $28,981.5 × 106) and regulating services (US $652.9 × 106). The results imply that addressing the degradation of land and water resources is crucial to reversing the loss of ecosystem services and achieving the national Sustainable Development Goals (SDGs) related to food and water security (SDGs 2 and 6) and life on land (SDG 15).

IMPACT OF LAND USE AND LAND COVER CHANGES ON RUNOFF PREDICTION IN OGBESE RIVER WATERSHED

Land use and land cover (LULC) changes in Ogbese watershed due to urbanization implies increased areas of low infiltration. This results to higher flow rates downstream the watershed. This study estimates the changes in peak flow rates at the watershed’s outlet for present and future LULC. Rainfall-runoff simulation was achieved with Hydrologic Engineering Centre-Hydrologic Modeling System (HEC-HMS) version 4.2 while future LULC was projected with Markov Chain model. Rainfall inputs to the hydrologic model were obtained from intensity-duration-frequency curves for Ondo state. Landsat 7, Enhanced Thematic mapper plus (ETM+) image and Landsat 8 operational land imager (OLI) with path 190 and row 2 were used to generate LULC images for the years 2002, 2015 and 2019. Six LULC classes were extracted as follows: built up area, bare surface, vegetation, wetland, rock outcrop and waterbody. Future LULC in year 2025 and 2029 were projected with Markov Chain model. The model prediction was verified with Nash Sutcliffe Efficiency index (NSE). NSE value of 0.79 was calculated indicating LULC changes in the watershed was Markovian. Results show that built up area cover in 2019 is projected to increase by 26.1% in 2024 and 39.9% in 2029 and wetland is projected to decreased by 1.2% in 2024 and 2.3% by 2029. Runoff peaks for these LULC projections indicate increase by 0.24% in 2024 and 1.19% in 2029 at the watershed’s outlets for 100-year return period rainfall.

Geo-spatial Analysis of Land Use Land Cover (LULC) Changes in Oluwa Forest Reserve and its Environs

Mankind’s existence and modification of the landscape have had a profound effect on the natural environment. Anthropogenic activities such as agriculture, mining, deforestation and construction have influenced the shifting patterns of land use. This has resulted in a significant effect on local weather and climate. The use of remote sensing data in recent times has been of immense help in monitoring the changing pattern of vegetation. Therefore this study utilized remote sensing and geographic information system (GIS) methods to identify factors responsible for land use land cover (LULC) changes in Oluwa Forest Reserve between 1984 and 2017. The result showed that Primary forest was reduced by about 5% between 1984 and 2000 and by about 12% between 2000 and 2017 and the non-forest got increased by about 4% and 2% from 1984 to 2000 and from 2000 to 2017 respectively. Future forecast shows that primary forest will decrease by about 3% while the non-forest will increase by 5% by 2034. The results also revealed that the changes in forest cover between 2000 and 2017 were actively influenced by the closeness of settlements to the forest. It is therefore recommended that the findings of this study should be adopted by relevant authorities as a useful forest management tool.