Land Use Cover Types Research Articles

Assessing land-use/land-cover influence on surface water quality using a weighted inverse distance function in Bangweulu sub-catchment area, Zambia

Water quality is crucial for human health and aquatic ecosystems, and understanding the relationship between land use/land cover (LULC) and water quality is essential as urban and industrial growth expands. This study aimed to investigate the influence of LULC on specific water quality parameters, establish the Water Quality Index (WQI) for 34 sampling points, and assess the impact of LULC on the WQI. The study used parametric weighted distance function where the weighted inverse distance function (WIDF) was used in determining the contamination effective contribution area (Aec) for each LULC type of a particular location using Landsat 2020 classified image and 30 m DEM. The results showed a wide range of WQI values, with several significant correlations between LULC and water quality. Turbidity, total dissolved solids (TDS), iron (Fe2+), and electrical conductivity (EC) showed strong correlations with LULC (R2 > 0.7). Turbidity and Fe2+ were more correlated with built-up and forested areas (p-Value <0.05), respectively. Whereas, TDS and EC were more correlated with cropland (p-Value <0.05). The feacal coliform showed a weak correlation with LULC (R2 = 0.258), but had a significant correlation with built-up areas (p-Value <0.05). The WQI had a reasonable correlation with LULC (R2 = 0.649). Understanding these relationships could improve decision-making on land use planning and water quality management, predict river water quality, and shape sustainable LULC policies. This information could also help identify hotspots of potential water quality degradation and pinpoint areas for targeted interventions and restoration efforts.

Flow-weighted sourcing of freshwater runoff from Pacific-draining continental and coastal basins in south-western Patagonia (41-56° S): characterizing regional inputs to Chilean fjords

Global estimates of the supply of dissolved and suspended materials to the ocean, in order to be relevant at either political or ecological scales, belie a finer-scale analysis necessary for understanding specific terrestrial-marine interactions. This is especially true for continental runoff to the marine critical zone of inland fjords and channels, where mechanisms, drivers, and predictions need to be elaborated in the context of changing land use and shifting climate forcing. In fjords in south-western Patagonia, runoff from small coastal and large continental basins (~310 x103 km2), sourced from a diverse geography and wide climatic gradient (&amp;lt;150 – 6,000+ mm/year), correspond with a very low density of hydrological and water quality observations. Based on the recently developed regional runoff model (FLOW), we estimated the coastal freshwater discharges and characterized flow-weighted sourcing (land use-cover type, climate, glaciers/geology, and soil province) for Pacific drainages from 41° to 56° south latitude. An estimated 692 km3/year (mean across 1979-2018), or 2% of worldwide total, is more than 85% of previous estimates for the much larger Pacific South American input. Based on limited water quality observations and inference from runoff sourcing, we predict general patterns of export for four groups of continental resources important for marine productivity, including: significant regional variation in flow seasonality, a N-S gradient in declining input of silicic acid and increased glacial input of sediment and iron, and potential shift in dissolved organic matter input sources from rainforest (potentially labile) to peatlands (refractory). Finally, we emphasize the temporal and spatial consequences of near-reference condition river runoff for marine ecosystem productivity and function in the Patagonian fjords, with specific recommendations for water quality standards and sustained monitoring for coupled river and marine ecosystems.

Understanding tropical cyclone persistence over land: A case study of Cyclone Gulab

Abstract Tropical Cyclone (TC) Gulab originated in the Bay of Bengal during the post-monsoon season of 2021. Following an unusual westward trajectory, TC Gulab made landfall on the east coast of India, traversed central India, and reintensified over the Arabian Sea into TC Shaheen. This study employed an online Eulerian water vapor tracer (WVT) tool embedded within the Weather Research and Forecasting (WRF) model to investigate the role of land in terms of soil moisture and Land Use Land Cover (LULC) in persistance of TC Gulab over central India. We quantified the contributions of sub-regions and dominant LULC types within the Indian subcontinent to the precipitation associated with TC Gulab. Our findings indicate that evapotranspiration across the entire Indian subcontinent contributed approximately 30% to the post-landfall precipitation associated with TC Gulab. The highest contribution originated from the northwestern region, followed by the northeast. Croplands, the dominant LULC type, were the primary contributors, followed by forests. Despite changing the dominant land cover from cropland to forest, the low-pressure system persisted over land while altering the spatial patterns of precipitation. Sensitivity experiments demonstrated a linear decrease in precipitation originating from land with decreasing soil moisture (SM). Notably, there is a disproportionate decline in total precipitation with decreasing SM. Further analysis separating atmospheric vapor sources into land and ocean contributions using WVT revealed a compensatory mechanism. The contribution of oceanic vapor to atmospheric vapor over land increased when SM decreased due to increase in the latent heat over ocean. However, the total atmospheric vapor remained low, ultimately leading to a lower total precipitation. Although SM plays a role, our results highlight the importance of oceanic and atmospheric processes in determining TC persistence over land. This study offers valuable insights into the dynamics of land-atmosphere interactions during low-pressure systems of TCs.

The past and future dynamics of ecological resilience and its spatial response analysis to natural and anthropogenic factors in Southwest China with typical Karst

With the global land use/land cover (LULC) and climate change, the ecological resilience (ER) in typical Karst areas has become the focus of attention. Its future development trend and its spatial response to natural and anthropogenic factors are crucial for understanding the changes of ecologically fragile areas to human behavior. However, there is still a lack of relevant quantitative research. The study systematically analyzed the characteristics of LULC changes in Southwest China with typical Karst over the past 20 years. Drawing on the landscape ecology research paradigm, a potential-elasticity-stability ER assessment model was constructed. Revealing the characteristics and heterogeneity of the spatial distribution, annual evolution, and development trend of ER in the past and under different scenarios of shared socioeconomic pathways and representative concentration pathways (SSP-RCP) in the future. In addition, the spatial econometric model was utilized to reveal the spatial effect response mechanism of ER, and adaptive development strategies were proposed to promote the sustainable development of Southwest China. The study found that : (1) In the past 20 years, the LULC in Southwest China showed an accelerated change trend, the ER decreased declined in general, and there was significant spatial heterogeneity, showing the spatial distribution pattern of “west is larger than east, south is larger than north, and reduction in the west was slower than that in the east.” (2) Under the same SSP scenario, with the increase of RCP emission concentration, the area of the lowest-resilience increased significantly, and the area of the highest-resilience decreased. (3) The woodland was the largest contributor to ER per unit area in the Southwest China, and grassland was the main LULC type, which had a prominent impact on the ER of the study area. (4) The average precipitation and the normalized difference vegetation index (NDVI) were significant natural drivers of ER in the study area, and the economic growth, innovation, and optimization of industrial structure contributed to the ER of Southwest China. Overall, the integration of quantitative assessment and multi-scenario-based modeling not only provides new perspectives for understanding the pattern of change and response mechanisms, but also provides valuable references for other typical Karst regions around the world to achieve sustainable development.

The effect of land use and land cover on soil carbon storage in the Yellow River Delta, China: Implications for wetland restoration and adaptive management

Gaining a comprehensive understanding of the effect of land use/land cover (LULC) and soil depth on soil carbon storage, through the manipulation of external carbon input and turnover processes, is crucial for accurate predictions of regional soil carbon storage. Numerous research investigations have been conducted to examine the impact of LULC on the storage and cycling of carbon in the surface soils of coastal wetlands. Nevertheless, there remains a dearth of understanding concerning the implications of this phenomenon on subterranean soils, a crucial factor in discerning the capacity for carbon sequestration in coastal wetlands and implementing measures for their preservation. The study focused on the Yellow River Delta (YRD) in China, which serves as a representative model system. It aimed to assess the impact of LULC as well as soil depth on carbon storage. This was achieved by a combination of remote sensing interpretation and field samplings. The findings of the study indicate that there was an increase in soil organic carbon storage with both the area covered and the depth of the soil across the four different land use types, namely forest, grass, tidal flat, and cultivated land. Cultivated land was identified as the predominant LULC type, encompassing 41.73% of the entire YRD. Furthermore, it accounted for a substantial carbon storage of 76.08%. In comparison to soil layers at depths of 0–20 cm and 20–40 cm, 40–60 cm was discovered to have the maximum carbon storage, accounting for 42.29% of total carbon storage. Furthermore, one of the main factors influencing carbon storage is salinity, which shows a negative association with carbon storage. Moreover, the aforementioned findings underscore the significance of the conjoined physical and chemical properties induced by LULC in influencing the dynamics of soil carbon. This suggests that the inclusion of deep soil carbon in the estimation and restoration of soil carbon storage is necessary. This inclusion will support the realization of the United Nations' “Toward Zero Carbon” effort and facilitate the implementation of China's national carbon neutrality objectives.

Spatiotemporal dynamics of land use and land cover change around Volcanoes National Park and their implications for biodiversity conservation

ABSTRACT This study comprehensively analyses spatiotemporal land use/land cover (LULC) dynamics within a 10-km buffer zone surrounding Volcanoes National Park (VNP), Rwanda, from 2000 to 2019, integrating biophysical and socio-economic drivers. It aims to quantify LULC change extent, rate, and type around VNP and inside the park; identify socio-economic, demographic, and policy drivers of LULC change; and evaluate the impact of LULC changes on VNP’s biodiversity via habitat fragmentation, connectivity, and species diversity. Employing remote sensing, spatial modelling, and field data, we reveal profound transformations within the park’s periphery. Forests and woodlots have significantly declined, replaced by agriculture, grasslands, and built-up areas, particularly in the 5.1–10 km belt (92.29% forest loss). While reforestation efforts exist, they are outpaced by deforestation, creating a stark deforestation-to-reforestation ratio of 12:1 in the 5.1 10 km belt and 6:1 in the 0–5 km belt. This alarming trend threatens VNP’s biodiversity as resource dependent communities continue to extract firewood, construction materials, and beanpoles from the park. To mitigate these impacts, we propose integrated strategies encompassing strengthened law enforcement, sustainable land management practices, community-based conservation initiatives, and alternative livelihood development.

137Cs radiotracer in investigating influence of hillslope positions and land use on soil erosion and soil organic carbon stock—A case study in the Himalayan region

AbstractThe topography and land use/land cover (LULC) of the hillslope play a significant influence on soil erosion because of water, which is considered as a principal factor for the reduction of soil organic carbon content. Reliable information on the impact of erosion mechanism on soil organic carbon stock (SOCS) is essential for effectively accounting for the carbon flux that influences climate change. The main objectives of this study were to determine soil erosion based on the variation of 137Cs (Radiocesium) radionuclide activity at various hillslope positions and LULC in a hilly and mountainous region of the north‐western Himalayas. Additionally, the relationship between 137Cs concentration, soil erosion rate and SOCS were examined. Fallout radionuclide‐137Cs have emerged as a suitable method for assessing soil erosion in hilly and mountainous regions where rugged topography and extreme weather events restrain the conventional soil erosion assessment. The study revealed very high soil erosion rates of 32.89 and 30.70 t ha−1 year−1 in the lower hillslope positions with cultivated fields. The lowest soil erosion was obtained with a mean of 0.47 t ha−1 year−1 from the ridge with grassland, followed by the upper hillslope (5.50 t ha−1 year−1 under deodar forest and 14.07 t ha−1 year−1 under pine forest), and the middle hillslope (1.58 t ha−1 year−1 for deodar and 7.77 t ha−1 year−1 for pine forest). The soil erosion rates differ significantly between cultivated and forested regions, and there is also a significant difference between deodar and pine forests. Moreover, a significant difference was found between topographic positions concerning 137Cs, SOCS and soil redistribution rate. This difference was more pronounced at hillslope positions with different LULC. In both disturbed (cultivated) (r2 = .111) and undisturbed (forested and grassland) (r2 = .356) soils, positive and statistically significant (p &lt; .005) poor relationships were found between SOCS and 137Cs inventory. This indicates the presence of various factors influencing the soil organic carbon stock (SOCS) mechanism or the indirect contribution of soil erosion‐induced carbon loss. This suggests that forest cover can enhance SOCS in the soil, mitigating the adverse effects of soil erosion and climate change. Consequently, 137Cs could be effectively used to quantify the SOC stock in soil redistribution over the hillslope affected by soil erosion. Statistical analyses indicated that the 137Cs inventory, SOCS and erosion were significantly affected by various hillslope positions and LULC types.

Evaluating long-term impacts of land use/land cover changes on pollution loads at a catchment scale.

Evaluating how pollutant loads react to changes in land use/land cover (LULC) is a challenging task due to the intricate relationships among the many elements within a watershed. However, the difficulty in connecting LULC change and nonpoint source (NPS) pollution loads to streams may be lessened by combining hydrological modeling with geospatial tools and multivariate statistics. The objective of this study was to investigate the long-term effects of LULC change on NPS pollution loads in a highly human-dominated catchment, in central Ethiopia. In the study, hydrologic modeling was used to estimate the NPS parameters from multispectral Landsat images, and multivariate statistical techniques were then used to extract major LULC types that explain the variances of NPS loads between 1981 and 2020. The results demonstrated that there were human-induced LULC changes in the area, as the built-up and agricultural landscapes are rising (186.4% and 5.8%, respectively), and shrub and forest lands are decreasing (67.1% and 41%, respectively). As a result of these changes, the concentrations of nitrate (NO3), total P, total N, organic N, and organic P loads were increased by 69.41, 19.83, 18.45, 18.88, and 24.05%, respectively. Reductions in natural vegetation, as well as agriculture intensification, are the major contributors to the NPS pollutant losses to surface water sources. The result also revealed that pollution nutrients are strongly related to deforestation and agricultural land expansion. Proper adaptation strategies should be implemented to minimize the negative impact of LULC changes in the area.

Soil erosion assessment and identification of erosion hotspot areas in the upper Tekeze Basin, Northern Ethiopia

Soil erosion is a major environmental problem in Ethiopia, reducing topsoil and agricultural land productivity. Soil loss estimation is a critical component of sustainable land management practices because it provides important information about soil erosion hotspot areas and prioritizes areas that require immediate management interventions. This study integrates the Revised Universal Soil Loss Equation (RUSLE) with Google Earth Engine (GEE) to estimate soil erosion rates and map soil erosion in the Upper Tekeze Basin, Northern Ethiopia. SoilGrids250 m, CHIRPS-V2, SRTM-V3, MERIT Hydrograph, NDVI from sentinel collections and land use land cover (LULC) data were accessed and processed in the GEE Platform. LULC was classified using Random forest (RF) classification algorithm in the GEE platform. Landsat surface reflectance images from Landsat 8 Operational land imager (OLI) sensors (2021) was used for LULC classification. Besides, different auxiliary data were utilized to improve the classification accuracy. Using the RUSLE-GEE framework, we analyzed the soil loss rate in different agroecologies and LULC types in the upper Tekeze basin in Waghimra zone. The results showed that the average soil loss rate in the Upper Tekeze basin is 25.5 t ha−1 yr−1. About 63 % of the basin is experiencing soil erosion above the maximum tolerable rate, which should be targeted for land management interventions. Specifically, 55 % of the study area, which is covered by unprotected shrubland is experiencing mean annual soil loss of 34.75 t ha−1 yr−1 indicating the need for immediate soil conservation intervention. The study also revealed evidence that this high mean soil loss rate of the basin can be reduced to a tolerable rate by implementing integrative watershed management and exclosures. Furthermore, this study demonstrated that GEE could be a good source of datasets and a computing platform for RUSLE, in particular for data scarce semi-arid and arid environments. The results from this study are reliable for decision-making for rapid soil erosion assessment and intervention prioritization.

Land Use/Cover Dynamics and its Implication on the Sustainability of Urban Agriculture in Selected Urban Centers of Ethiopia

Abstract Analysis of urban Land Use/Land Cover (LULC) dynamics in light of urban agriculture (UA) helps to understand its implication for UA practice and in turn making the necessary interventions. Therefore, the main objective of this study was to examine the LULC dynamics in selected urban centers of Ethiopia (Addis Ababa, Bahir Dar, Adama, and Hawassa cities) for the last seventeen years (2006–2022). SPOT 5 satellite imagery for the year 2006 and 2016 and Sentinel image for the year 2022 were analyzed. In addition, data from key informant interviews, focus group discussions, and field observations were used to triangulate LULC analyses information and to identify the main causes of LULC dynamics in the studied urban centers. The findings reveled that there were rapid expansion of urban built-up areas at the expense of other urban LULC types mainly of peri urban horticultural lands for the last 17 years (2006‒2022) in Addis Ababa, Hawassa, Bahir Dar, and Adama cities of Ethiopia. This has adverse impact on the sustainability of UA. Rapid urban population growth mainly because of high rural urban migration, expansion of squatter settlement, and increment of investment were the main driving forces of LULC dynamics. Based on the findings of this study (changes in LULC and driving factors) the studied cities administrations or authorities need to develop sustainable development plans by considering UA.

Driving Mechanisms of Spatial Differentiation in Ecosystem Service Value in Opencast Coal Mines in Arid Areas: A Case Study in the Zhundong Economic and Technological Development Zone

The valuation of ecosystem services (ESs) is crucial for preserving ecosystems, assessing natural resources, and making decisions regarding compensation. In this study, we employed the InVEST model’s habitat quality (HQ) module to calculate the HQ and degradation levels in the study area using land use/land cover (LULC) data from 2000 to 2020. Our analysis utilized quantitative methods, including spatial correlation, hotspot analysis, and geo-probing, to determine the value of ESs and identify trends. Furthermore, we examined the spatial and temporal variation in the significance of ESs and their driving factors. The results show the following. (1) The primary LULC types in the Zhundong coalfield from 2000 to 2020 are grassland and barren areas. (2) The average value of the HQ index in the study area exhibited a generally decreasing trend. Between 2000 and 2010, HQ significantly declined, particularly in the region’s large barren industrial and mining zones. However, over time, the proportion of sites with minimal degradation improved steadily, resulting in better overall HQ in the study area by 2020. This pertains to the measures put in place by the local government to safeguard and rehabilitate the ecosystem. (3) The spatial distribution of the ecosystem service value (ESV) aligns with changes in HQ and LULC, with significant hotspots primarily observed in forest and grassland areas, nature reserves, and areas around water sources. (4) LULC, temperature, annual precipitation, and elevation are the main drivers of spatial variation in the ESV in the Zhundong area; the spatial variation in the ESV in the Zhundong coalfield is primarily influenced by the interaction between human factors and natural factors, in which LULC plays a dominant role. This study’s findings can guide the development of rational ecological planning, integrating resource conservation mining with effective zoning management.

Agricultural land use policies and landscape dynamics: Evidence from rainforest agroecological zone

Agricultural-land use policies play a crucial role in shaping agroecological landscapes globally. The evidence suggests that some of these policies tend to have undesired feedback/trade-offs, particularly about coastal resource use and conservation planning. The present study explores how agricultural policies influence land use/land cover (LULC) transition patterns in Ghana's Rain Forest Agroecological Zone (RFAZ). Landsat satellite images for 1991, 2008, and 2022 were acquired for the LULC mapping. Change detection and Intensity analysis were used to assess the pattern of land change. Also, documentary research processes were used to review and assess agricultural land use policies. The results showed that before rubber-related policy implementation, oil palm plantation was the dominant LULC type in the 1990 s. In the 1990 s and early 2000 s, there was a conscious government drive to leverage oil palm plantation development. This led to the growth in the size of oil palm plantations within the RFAZ landscape, considering the zone’s conducive natural environment. However, between 2008 and 2022, corresponding to the period of the increased promotion of rubber cultivation through the Outgrower project in the RFAZ, rubber plantations became the predominant land use, with an area of 11,763.81 ha in 2008 and 21,611.61 ha in 2022. The results from the LULC mapping and the intensity analysis showed that the Rubber Outgrowers Plantation Project (ROPP) and Norpalm Smallholder Scheme Project (NSSP) have degraded the natural cover through rubber and oil palm cultivation. The authors conclude that landscape dynamics, particularly in rainforest agroecological zones, represent a nexus challenge transforming policy adaptation's discursive context. The study recommends that agriculture and landscape policy/projects must have/take intermediary steps to address the feedback/trade-offs from well-intended initiatives. The study further suggests that management plans and strategies in the RFAZ should be consistent with the strict protection of forest reserves and water bodies.

Analysis of Land Use Land Cover and Land Surface Temperature in Karst Area: A Case Study Wonogiri Regency

&lt;p class="Abstract"&gt;Urban development and global climate change drive increased Land Surface Temperature (LST). Wonogiri Regency is an area that is within the development range of Surakarta City. Analysis of land surface temperature has become Important in Wonogiri Regency as a mitigation measure for urban heat islands. This study aims to measure Land Surface Temperature (LST) in Wonogiri Regency and determine the controlling factor in the form of Land Use Land Cover (LULC), Normalized Difference Vegetation Index (NDVI), seasons, and zones by landform. Using the Google Earth Engine platform, LST calculations, LULC classifications, and NDVI calculations can compute imagery. The dataset used is USGS Landsat 8. The analytical technique used in this study is comparative descriptive, which compares other controlling factors. The analysis results show the vital role of LULC, NDVI, seasonality, and landform on LST. LULC types of built-up land, low NDVI values, dry season, and southern zone (karst) tend to have higher LST than other factors.&lt;/p&gt;

Wintering raptor species distribution in a semiarid Mediterranean region: the relevance of lowlands and open habitats as stopover sites

As land-use cover types affect wintering birds’ strategies, studying their habitat suitability for species conservation is relevant. Predictive spatial models are considered excellent tools for conservation planning and improving our understanding of species distribution. Here we build models to predict the spatial distribution of raptor species that overwinter in SE Spain. We modelled the wintering raptor species distribution based on the presence-only data obtained between 2017 and 2019 and analysed their habitat preferences based on elevation and land-use cover variables. Our results show that altitude and distance to the coastline are the most important environmental factors to affect most species’ habitat suitability. Habitat type-related factors are other important predictors, and raptors subject of this study prefer lowlands and areas close to the coastline for overwintering by selecting open habitats, which include wetlands and irrigated and rainfed crops. This study highlights the importance of the habitat heterogeneity generated by wetlands and herbaceous crops within a low-altitude range as the optimal environment for wintering raptors. Such information should be considered for raptor conservation planning in human-altered landscapes.

Analysing Sustainable Urban Growth: Spatio-Temporal Dynamics of Urban Expansion in Gampola Urban Centre

Urbanization is a dynamic process which can be considered as one of the most significant indicators of development. It occurs both horizontally and vertically on the Earth’s surface according to a pattern which has positive and negative implications. Some countries measure their development by the level of urbanization because it directly affects for a country’s economy. During past decades, Gampola urban centre was experiencing a gradual urban growth and several implications. This study focuses on investigating urban expansion pattern of Gampola during 16 years by analysing three distinct years 2006, 2013, and 2022. Geographic Information System (GIS) and Remote Sensing (RS) techniques were employed to examine spatio-temporal transformations and urban expansion patterns of Gampola and its outskirts. Landsat images for three distinct years were classified using pixel-based supervised classification to determine Land Use Land Cover (LULC) of the study area which achieved an impressive overall accuracy of approximately 90%. Four major LULC types were identified those are prominent in the area namely, water, built-up, forest, paddy lands and bare lands. Temporal changes of vegetation cover for 16 years were analysed further using Normalized Difference Vegetation Index (NDVI). Consequent implications on Land Surface Temperature (LST) across the time period were analysed using thermal band of Landsat images. NDVI value has decreased from +0.7 to +0.5 during 2006-2013 and up to +0.4 during 2013-2022. LST analysis revealed a rise in temperature, increasing from 29.89° C up to 31.11° C during 2006- 2013 and surging to 33.14° C by 2022. Quantifying the urban expansion of Gampola was performed using buffer analysis. Analysis of urban areas grown within 1km distanced five buffer zones from urban core was performed to quantify urban expansion. Fourth buffer zone exhibited the highest urban growth, while first buffer zone displayed lowest urban growth during 2006 to 2022. In the interval between 2013 and 2022, the fifth buffer zone appeared as the zone with the highest urban growth. Further, Landscape Expansion Index (LEI) was employed to identify the urban expansion patterns, and Gampola urban area displayed an Edge Expansion growth type. We recommend the development of urbanized areas in a sustainable and efficient manner to mitigate adverse consequences and promote balanced growth.&#x0D; &#x0D; Keywords: GIS and RS, Urban expansion, LEI, LST, Sustainable development

Integrated flood risk assessment in Hunza-Nagar, Pakistan: unifying big climate data analytics and multi-criteria decision-making with GIS

Floods are a widespread natural disaster with substantial economic implications and far-reaching consequences. In Northern Pakistan, the Hunza-Nagar valley faces vulnerability to floods, posing significant challenges to its sustainable development. This study aimed to evaluate flood risk in the region by employing a GIS-based Multi-Criteria Decision Analysis (MCDA) approach and big climate data records. By using a comprehensive flood risk assessment model, a flood hazard map was developed by considering nine influential factors: rainfall, regional temperature variation, distance to the river, elevation, slope, Normalized difference vegetation index (NDVI), Topographic wetness index (TWI), land use/land cover (LULC), curvature, and soil type. The analytical hierarchy process (AHP) analysis assigned weights to each factor and integrated with geospatial data using a GIS to generate flood risk maps, classifying hazard levels into five categories. The study assigned higher importance to rainfall, distance to the river, elevation, and slope compared to NDVI, TWI, LULC, curvature, and soil type. The weighted overlay flood risk map obtained from the reclassified maps of nine influencing factors identified 6% of the total area as very high, 36% as high, 41% as moderate, 16% as low, and 1% as very low flood risk. The accuracy of the flood risk model was demonstrated through the Receiver Operating Characteristics-Area Under the Curve (ROC-AUC) analysis, yielding a commendable prediction accuracy of 0.773. This MCDA approach offers an efficient and direct means of flood risk modeling, utilizing fundamental GIS data. The model serves as a valuable tool for decision-makers, enhancing flood risk awareness and providing vital insights for disaster management authorities in the Hunza-Nagar Valley. As future developments unfold, this study remains an indispensable resource for disaster preparedness and management in the Hunza-Nagar Valley region.

Effects of land use/land cover change on hydrological responses of a watershed in the Central Rift Valley of Ethiopia

Abstract The purpose of this study is to evaluate the impacts of LULC changes on the hydrological components of a watershed using multivariate statistics, and hydrological modeling approaches. The study analyzed the LULC distributions, and changes corresponding to the years 2000, 2010, and 2020. The SWAT model was then applied to assess the hydrological impacts of these changes in the studied watershed. Finally, changes in LULC types were correlated with the water balance components using a Partial Least Squares Regression (PLSR) method. The result showed a continuous expansion of barren, built-up, and cropland areas, while forests, shrubs, and grassland decreased by about 67.12, 41, and 36.88%, respectively. The modeling result showed that surface runoff, water yield, and evapotranspiration decreased by 16.1, 2.9, and 9.3%, respectively. In contrast, base flow, soil water storage, and lateral flow of the watershed increased by up to 19.1%, 55.9%, and 150.4%, respectively, due to LULC changes. The PLSR model identified the cropland, forest, and shrub LULC types as the major factors affecting the water resource components. The study results provide useful information for policymakers and planners in the implementation of sustainable water resource planning and management in the context of environmental change.

Hydrogeological Implications of Slope and Land Use/Land Cover Distribution in Part of Southern, Nigeria

The study focuses on the hydrogeological implications of slope and Land Use/Land Cover (LULC) distributions in the Aniocha and Oshimili regions of Nigeria. Understanding the spatial variations in these parameters is critical for effective groundwater management and sustainable land use planning in these areas. The aim is to assess the spatial distribution of slopes and LULC types and their impact on groundwater recharge and surface runoff in the study area. The study employs spatial analysis techniques to categorize slope data into five classes and LULC data into seven types for the years 2017 and 2023. The analysis covers Aniocha North, Aniocha South, Ika North, Ika South, Oshimili North, and Oshimili South. The slope analysis reveals that the largest area (1022.73 km²) falls within the 0-1.52° slope category, indicating predominantly flat terrain with high infiltration potential. The LULC analysis shows that in 2017, trees covered the most extensive area (2143.21 km²), which decreased to 1573.76 km² by 2023, indicating significant deforestation. Built areas expanded from 281.76 km² to 391.99 km², reflecting increased urbanization. Flat terrains (0-3.51°) are conducive to groundwater recharge due to their high infiltration rates, whereas steeper slopes (3.51-26.00°) exhibit higher runoff potential, impacting groundwater recharge negatively. The reduction in tree cover and expansion of built areas have significant hydrogeological implications. Deforestation reduces groundwater recharge potential, while urbanization increases surface runoff, potentially leading to flooding and reduced groundwater levels. The study highlights the need for integrated land and water management strategies to balance development with environmental sustainability. Protecting and managing flat areas for groundwater recharge, implementing soil conservation in steeper regions, and promoting sustainable agricultural practices are essential. Urban planning should incorporate green infrastructure to mitigate the impacts of increased impervious surfaces. This study provides a comprehensive analysis of slope and LULC changes over time and their hydrogeological implications, offering valuable insights for sustainable land and water resource management in the Aniocha and Oshimili regions.

Riparian habitat quality as an indicator of land use/land cover effects on riverine water quality

Riparian land use/land cover (LULC) plays a crucial role in maintaining riverine water quality by altering the transport of pollutants and nutrients. Nevertheless, establishing a direct relationship between water quality and LULC is challenging due to the multi-indicator nature of both factors. Water quality encompasses a multitude of physical, chemical, and biological parameters, while LULC represents a diverse array of land use types. Riparian habitat quality (RHQ) serves as an indicator of LULC. Yet, it remains to be seen whether RHQ can act as a proxy of LULC for assessing the impact of LULC on riverine water quality. This study examines the interplay between RHQ, LULC and water quality, and develops a comprehensive indicator to predict water quality. We measured several water quality parameters, including pH (potential of hydrogen), TN (total nitrogen), TP (total phosphorus), Twater (water temperature), DO (dissolved oxygen), and EC (electrical conductivity) of the Yue and Jinshui Rivers draining to the Han River during 2016, 2017 and 2018. The water quality index (WQI) was further calculated. RHQ is assessed by the InVEST (Integrated Valuation of Ecosystem Services and Tradeoffs) model. Our study found noticeable seasonal differences in water quality, with a higher WQI observed in the dry season. The RHQ was strongly correlated with LULC compositions. RHQ positively correlated with WQI, and DO concentration and vegetation land were negatively correlated with Twater, TN, TP, EC, cropland, and construction land. These correlations were stronger in the rainy season. Human-dominated land, such as construction land and cropland, significantly contributed to water quality degradation, whereas vegetation promoted water quality. Regression models showed that the RHQ explained variations in WQI better than LULC types. Our study concludes that RHQ is a new and comprehensive indicator for predicting the dynamics of riverine water quality.

Potential of the satellite-based Dynamic Habitat Index (DHI) to capture changes in soil properties and drought conditions across Land Use/Land Cover types in a Central European landscape

This study evaluates the sensitivity of the Dynamic Habitat Index (DHI), utilizing multitemporal Normalized Difference Vegetation Index (NDVI) data, to changing environmental conditions across Land Use/Land Cover (LULC) types in a central European landscape (2017–2020). We observed distinct DHI characteristics for all LULC types, and the DHI responded to an extreme drought year in 2018 with no return to pre-drought conditions except for deciduous forests. The DHI also effectively captured spatio-temporal variability of pedo-climatic conditions. Thus, integrated with ancillary geodata, the DHI enhances traditional categorical LULC maps, offering applications in biodiversity and ecosystem research. Such integrated products could serve as valuable tools for decision makers to formulate sustainable land management strategies and contribute to Sustainable Develop Goal indicators related to land degradation, e.g. by identifying deviations from typical, context-specific DHI profiles as a response to disturbance and environmental stress.