1,721,056 research outputs found
Contribution of urbanization and climate variability on surface water depletion across USA watersheds
No full textSurface water resources are extremely vulnerable to climate variability and are seriously threatened by human activities. The depletion of surface water is expected to rapidly increase due to the combination of future climate change and world population growth projections. Under this scenario, the impacts of climate and human dynamics on surface water resources represent a global issue, requiring the definition of adequate management strategies that prevent water crisis and guarantee equitable access to freshwater resources. Remote sensing provides data that allow to monitor environmental change processes, such as changes in climatic conditions, land use, and spatial allocation of human settlements and activities. Although many products describing surface water dynamics and urban growth obtained from satellite imagery are available, an integrated analysis of such geospatial information has not been performed yet. Here, we explore the driving role of the variation in key climatic variables (e.g., precipitation, temperature, and soil moisture) and the extent of urban areas in the depletion of surface water across the watersheds in the United States by using data derived from remote sensing images and performing a correlation analysis. From our preliminary results, we observe that there is a positive correlation between surface water loss and the level of urbanization in each basin of our study area, meaning that surface water loss increases with the extent of urban area. On the contrary, we find that the correlation between surface water loss and precipitation has a counter-intuitive trend which needs to be further examined
Anthropogenic and climatic controls on surface water loss across USA
No full textSurface water resources are severely affected by human activities and climate variability, and their rapid depletion is one of the main challenges for sustainable development. This situation is expected to worsen because of climate change, world population growth and the associated conversion of rural lands into urban areas. Since about 70% of global population is projected to be living in cities by 2050, it is necessary to shed light on the influence of climate and human dynamics on water occurrence variation to better understand their driving role.
Remote sensing is a key tool for monitoring the process of environmental change because it provides the advantages of global spatial coverage, high temporal resolution, and fast updating. Satellite data enable to record changes in climatic conditions, land use, and spatial allocation of human settlement and activities, which are major factors in altering water dynamics. However, the potential of such data has not been fully exploited.
Here, the interrelation between spatial and temporal distribution of water depletion, changes in precipitation, and human dynamics across the USA watersheds is investigated using remote sensing data. In particular, the contribution of urbanization and precipitation variation to surface water decrease in the last 35 years (from 1984 to 2018) is evaluated at the basin scale. Preliminary results highlight the presence of a positive correlation between surface water loss and urban area growth. On the other hand, a counterintuitive increasing trend of surface water decrease with growing annual precipitation is found. A multiple linear regression among surface water loss, urbanization, and annual precipitation change is calculated, showing that most of the surface water loss can be attributed to the urbanization process. A spatial and temporal clustering analysis is then performed to better understand the influence of anthropogenic factors on surface water losses. Results clearly show a high level of urbanization close to surface water loss hotspots
Predicting Terrestrial Water Storage Anomalies at the Global Scale with a Machine-Learning Model
No full textLand Cover and Spatial Distribution of Surface Water Loss Hotspots in Italy
Full text linkIncreasing water withdrawals and changes in land cover/use are critically altering surface water bodies, often causing a noticeable reduction in their area. Such anthropogenic modification of surface waters needs to be thoroughly examined to recognize the dynamics through which humans affect the loss of surface water. By leveraging remotely-sensed data and employing a distance-decay model, we investigate the loss of surface water resources that occurred in Italy between 1984 and 2021 and explore its association with land cover change and potential human pressure. In particular, we first estimate the land cover conversion across locations experiencing surface water loss. Next, we identify and analytically model the influence of irrigated and built-up areas, which heavily rely on surface waters, on the spatial distribution of surface water losses across river basin districts and river basins in Italy. Our results reveal that surface water losses are mainly located in northern Italy, where they have been primarily replaced by cropland and vegetation. As expected, we find that surface water losses tend to be more concentrated in the proximity of both irrigated and built-up areas yet showing differences in their spatial occurrence and extent. These observed spatial patterns are well captured by our analytical model, which outlines the predominant role of irrigated areas, mainly across northern Italy and Sicily, and more dominant effects of built-up areas across the Apennines and in Sardinia. By highlighting land cover patterns following the loss of surface water and evaluating the relative distribution of surface water losses with respect to areas of human pressure, our analysis provides key information that could support water management and prevent future conditions of water scarcity due to unsustainable water exploitation
Contribution of Anthropogenic and Climatic drivers to the Surface Water Extent Change in the Contiguous United States
No full textSpatial influence of urban areas on surface water loss across the contiguous united states
No full textSurface water sustains freshwater ecosystems by preserving the integrity of their habitats and supplies water to many anthropogenic sectors. However, human activities impact surface water bodies and determine a progressive reduction of their extent. In particular, the process of urbanization due to urban population growth is expected to produce an increase of the exploitation of surface water in the surroundings of cities.
Here, we examine the driving role of urban areas in the spatial distribution of surface water loss across river basins of the contiguous United States (CONUS) using remote sensing data. We define surface water loss as any conversion from surface water to land that occurred between 1984 and 2018 and we compute the frequency of these losses as a function of distance from urban areas. We find that in all the rivers basins of the CONUS surface water loss is more intense around cities and declines as the distance from human settlements increases. Therefore, we define a distance-decay model that follows a truncated exponential probability distribution which is able to reproduce the observed decreasing trend, proving that urban areas cause an increasing stress on surface water resources in the proximity of human settlements. Moreover, we observe that the decrease in surface water loss is faster in river basins with larger urban agglomerations, indicating that the influence of urban areas on the spatial distribution of surface water loss increases as the extent of urban areas increases as well.
Finally, we investigate the role played by climate in the spatial interaction between urban areas and surface water losses and we notice that different pattern of exponential decay of surface water loss are found across the main climatic regions of the CONUS. Specifically, in areas with temperate and continental climate the presence of urban areas determines local and concentrated surface water losses, while losses are more distributed and reach greater distances in arid regions
Spatial distribution of surface water losses from urban areas across the contiguous united states
No full textHuman pressure on surface water is increasing globally, especially on river systems. Future scenarios of urban population growth anticipate an overexploitation of surface water resources in the proximity of cities, which in turn will produce environmental, social, and economic impacts whose effects are going to influence increasingly larger areas. Therefore, it is crucial to gain a better understanding of the dynamics of interaction between human settlements and surface water, to find a balance between urban planning and water management policies that ensure water conservation and ecosystem protection. In this study we assess the driving role of urban areas in the spatial distribution of surface water losses across the contiguous United States (CONUS). In particular, we analyze the frequency of occurrence of surface water loss as a function of distance from urban areas using remote sensing data and we define a distance decay model that reproduces the observed spatial behavior. We find that the frequency of surface water loss declines as the distance from urban areas increases and we successfully model this spatial trend with an exponential probability distribution function. Moreover, we observe distinct decay patterns of the frequency of occurrence of surface water loss associated to the main climatic conditions of the CONUS, as surface water losses are more concentrated around urban areas in regions with a temperate and continental climate, while they result to be more widespread over greater distances in regions with an arid climate
Influence of urban areas on surface water loss across USA watersheds
No full textHuman activities are one of the factors responsible for the rapid depletion of surface water resources. The projected growth of urban population, along with the associated process of urban sprawl, is expected to further increase anthropogenic surface water withdrawals. Although this scenario is threatening water security globally, highlighting the need for efficient and sustainable strategies of water and urbanization management, a spatially explicit analysis of the interaction between urban areas and surface water loss is still missing. In this analysis we use maps of urban areas and locations of surface water loss derived from remote sensing data across the watersheds in the United States to understand the spatial influence of human settlements on surface water depletion. By examining the distribution of the frequency of surface water loss locations as a function of distance from urban areas we find that in most of the basins as well as in the whole study area the depletion of surface water resources is higher close to human settlements. Therefore, we define a probabilistic distance-decay model to reproduce the observed decrease in surface water loss frequency and we observe that in 96% of the study area our model is effectively able to predict the observed decrease in surface water loss locations with distance from urban areas at the basin level (Pearson’s correlation coefficient r = 0.5). The same result is found for the whole study area as well (r = 0.997). Finally, we test the reliability of the distance-decay model through the comparison between the observed distance from urban areas at which on average surface water loss occurs and the theoretical value derived from the model evaluated for each basin and for the whole study area. The strong correlation (coefficient of determination R2 = 0.88) between the observed and theoretical distances proves that our probabilistic model applied across the U.S. represents a robust tool that can support the identification and the prediction of surface water depletion and can be possibly applied to other study areas
Regional prediction of basin-scale brown trout habitat suitability
Full text linkIn this study we propose a novel method for the estimation of ecological indices describing the habitat suitability of brown trout (Salmo trutta). Traditional hydrological tools are coupled with an innovative regional geostatistical technique, aiming at the prediction of the brown trout habitat suitability index where partial or totally ungauged conditions occur. Several methods for the assessment of ecological indices are already proposed in the scientific literature, but the possibility of exploiting a geostatistical prediction model, such as Topological Kriging, has never been investigated before. In order to develop a regional habitat suitability model we use the habitat suitability curve, obtained from measured data of brown trout adult individuals collected in several river basins across the USA. The Top-kriging prediction model is then employed to assess the spatial correlation between upstream and downstream habitat suitability indices. The study area is the Metauro River basin, located in the central part of Italy (Marche region), for which both water depth and streamflow data were collected. The present analysis focuses on discharge values corresponding to the 0.1-, 0.5-, 0.9-empirical quantiles derived from flow-duration curves available for seven gauging stations located within the study area, for which three different suitability indices (i.e. ψ10, ψ50 and ψ90) are evaluated. The results of this preliminary analysis are encouraging showing Nash-Sutcliffe efficiencies equal to 0.52, 0.65, and 0.69, respectively
Unraveling Long-Term Flood Risk Dynamics Across the Murray-Darling Basin Using a Large-Scale Hydraulic Model and Satellite Data
Full text linkRiver floods are one of the most devastating extreme hydrological events, with oftentimes
remarkably negative effects for human society and the environment. Economic losses
and social consequences, in terms of affected people and human fatalities, are increasing
worldwide due to climate change and urbanization processes. Long-term dynamics
of flood risk are intimately driven by the temporal evolution of hazard, exposure and
vulnerability. Although needed for effective flood risk management, a comprehensive
long-term analysis of all these components is not straightforward, mostly due to a
lack of hydrological data, exposure information, and large computational resources
required for 2-D flood model simulations at adequately high resolution over large spatial
scales. This study tries to overcome these limitations and attempts to investigate the
dynamics of different flood risk components in the Murray-Darling basin (MDB, Australia)
in the period 1973–2014. To this aim, the LISFLOOD-FP model, i.e., a large-scale 2-D
hydrodynamic model, and satellite-derived built-up data are employed. Results show
that the maximum extension of flooded areas decreases in time, without revealing any
significant geographical transfer of inundated areas across the study period. Despite
this, a remarkable increment of built-up areas characterizes MDB, with larger annual
increments across not-flooded locations compared to flooded areas. When combining
flood hazard and exposure, we find that the overall extension of areas exposed to high
flood risk more than doubled within the study period, thus highlighting the need for
improving flood risk awareness and flood mitigation strategies in the near future
- …
