Climate and land cover change impacts on stormwater runoff in large-scale coastal-urban environments

2021 ◽  
pp. 146017
Author(s):  
Erfanul Huq ◽  
Omar I. Abdul-Aziz
Keyword(s):  
Land Cover ◽  
Land Cover Change ◽  
Large Scale ◽  
Stormwater Runoff ◽  
Urban Environments

scholarly journals Four Decades of Land-Cover Change on the Kenai Peninsula, Alaska: Detecting Disturbance-Influenced Vegetation Shifts Using Landsat Legacy Data

Land ◽  
2020 ◽  
Vol 9 (10) ◽  
pp. 382
Author(s):  
Carson Baughman ◽  
Rachel Loehman ◽  
Dawn Magness ◽  
Lisa Saperstein ◽  
Rosemary Sherriff
Keyword(s):  
Land Cover ◽  
Land Cover Change ◽  
Large Scale ◽  
Forest Canopy ◽  
Tree Cover ◽  
Forest Loss ◽  
Environmental Response ◽  
Kenai Peninsula ◽  
Vegetation Shifts ◽  
Forest Land Cover

Across Alaska’s Kenai Peninsula, disturbance events have removed large areas of forest over the last half century. Simultaneously, succession and landscape evolution have facilitated forest regrowth and expansion. Detecting forest loss within known pulse disturbance events is often straightforward given that reduction in tree cover is a readily detectable and measurable land-cover change. Land-cover change is more difficult to quantify when disturbance events are unknown, remote, or environmental response is slow in relation to human observation. While disturbance events and related land-cover change are relatively instant, assessing patterns of post-disturbance succession requires long term monitoring. Here, we describe a method for classifying land cover and quantifying land-cover change over time, using Landsat legacy imagery for three historical eras on the western Kenai Peninsula: 1973–2002, 2002–2017, and 1973–2017. Scenes from numerous Landsat sensors, including summer and winter seasons, were acquired between 1973 and 2017 and used to classify vegetation cover using a random forest classifier. Land-cover type was summarized by era and combined to produce a dataset capturing spatially explicit land-cover change at a moderate 30-m resolution. Our results document large-scale forest loss across the study area that can be attributed to known disturbance events including beetle kill and wildfire. Despite numerous and extensive disturbances resulting in forest loss, we estimate that the study area has experienced net forest gain over the duration of our study period due to reforestation within large fire events that predate this study. Transition between forest and graminoid non-forest land cover including wetlands and herbaceous uplands is the most common land-cover change—representing recruitment of a graminoid dominated understory following forest loss and the return of forest canopy given sufficient time post-disturbance.

scholarly journals Analyses of Land Cover Change Trajectories Leading to Tropical Forest Loss: Illustrated for the West Kutai and Mahakam Ulu Districts, East Kalimantan, Indonesia

Land ◽  
2018 ◽  
Vol 7 (3) ◽  
pp. 108 ◽  
Author(s):  
Carina van der Laan ◽  
Arif Budiman ◽  
Judith Verstegen ◽  
Stefan Dekker ◽  
Wiwin Effendy ◽  
...  
Keyword(s):  
Land Cover ◽  
Land Cover Change ◽  
Large Scale ◽  
Expert Knowledge ◽  
Small Scale ◽  
Forest Loss ◽  
The West ◽  
East Kalimantan ◽  
Open Forest ◽  
Over Time

In Indonesia, land cover change for agriculture and mining is threatening tropical forests, biodiversity and ecosystem services. However, land cover change is highly dynamic and complex and varies over time and space. In this study, we combined Landsat-based land cover (change) mapping, pixel-to-pixel cross tabulations and expert knowledge to analyze land cover change and forest loss in the West Kutai and Mahakam Ulu districts in East Kalimantan from 1990–2009. We found that about one-third of the study area changed in 1990–2009 and that the different types of land cover changes in the study area increased and involved more diverse and characteristic trajectories in 2000–2009, compared to 1990–2000. Degradation to more open forest types was dominant, and forest was mostly lost due to trajectories that involved deforestation to grasslands and shrubs (~17%), and to a lesser extent due to trajectories from forest to mining and agriculture (11%). Trajectories from forest to small-scale mixed cropland and smallholder rubber occurred more frequently than trajectories to large-scale oil palm or pulpwood plantations; however, the latter increased over time. About 11% of total land cover change involved multiple-step trajectories and thus “intermediate” land cover types. The combined trajectory analysis in this paper thus contributes to a more comprehensive analysis of land cover change and the drivers of forest loss, which is essential to improve future land cover projections and to support spatial planning.

scholarly journals V2Karst V1.0: A parsimonious large-scale integrated vegetation-recharge model to simulate the impact of climate and land cover change in karst regions

2018 ◽  
Author(s):  
Fanny Sarrazin ◽  
Andreas Hartmann ◽  
Francesca Pianosi ◽  
Thorsten Wagener
Keyword(s):  
Land Cover ◽  
Groundwater Recharge ◽  
Land Cover Change ◽  
Large Scale ◽  
Synthetic Data ◽  
Temporal Distribution ◽  
Soil Parameters ◽  
Large Scale Assessment ◽  
Karst Areas ◽  
The Impact

Abstract. Karst aquifers are an important source of drinking water in many regions of the world. Karst areas are highly permeable and produce large amounts of groundwater recharge, while surface runoff is typically negligible. As a result, recharge in these systems may have a different sensitivity to climate and land cover changes compared to other less permeable systems. However, little effort has been directed toward assessing the impact of climate and land cover change in karst areas at large-scales. In this study, we address this gap by (1) introducing the first large-scale hydrological model including an explicit representation of both karst and land cover properties, and by (2) analysing the model's recharge production behaviour. To achieve these points, we first improve the evapotranspiration estimation of a previous large-scale karst recharge model (VarKarst). The new model (V2Karst V1.0) includes a parsimonious representation of relevant ET processes for climate and land cover change impact studies. We demonstrate the plausibility of V2Karst simulations at carbonate rock FLUXNET sites using soft rules and global sensitivity analysis. Then, we use virtual experiments with synthetic data to assess the sensitivity of simulated recharge to precipitation characteristics and land cover. Results reveal how both vegetation and soil parameters control the model behaviour, and they suggest that simulated recharge is sensitive to both precipitation (overall amount and temporal distribution) and land cover. Large-scale assessment of future karst groundwater recharge should therefore consider the combined impact of changes in land cover and precipitation properties, if it is to produce realistic projections of future change impacts.

Satellite-based assessment of large-scale land cover change in Asian arid regions in the period of 2001–2009

2013 ◽  
Vol 71 (9) ◽  
pp. 3935-3944 ◽  
Author(s):  
Jaeil Cho ◽  
Yang-Won Lee ◽  
Pat J.-F. Yeh ◽  
Kyung-Soo Han ◽  
Shinjiro Kanae
Keyword(s):  
Land Cover ◽  
Land Cover Change ◽  
Arid Regions ◽  
Large Scale ◽  
Large Scale Land

scholarly journals Detecting the impact of land cover change on observed rainfall

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e7523 ◽  
Author(s):  
Chun Xia Liang ◽  
Floris F. van Ogtrop ◽  
R. Willem Vervoort
Keyword(s):  
Land Cover ◽  
Land Cover Change ◽  
Large Scale ◽  
Southern Oscillation ◽  
Rainfall Variability ◽  
Tree Cover ◽  
Trend Test ◽  
South Central ◽  
The Impact ◽  
Step Trend

Analysis of observational data to pinpoint impact of land cover change on local rainfall is difficult due to multiple environmental factors that cannot be strictly controlled. In this study we use a statistical approach to identify the relationship between removal of tree cover and rainfall with data from best available sources for two large areas in Australia. Gridded rainfall data between 1979 and 2015 was used for the areas, while large scale (exogenous) effects were represented by mean rainfall across a much larger area and climatic indicators, such as Southern Oscillation Index and Indian Ocean Dipole. Both generalised additive modelling and step trend tests were used for the analysis. For a region in south central Queensland, the reported change in tree clearing between 2002–2005 did not result in strong statistically significant precipitation changes. On the other hand, results from a bushfire affected region on the border of New South Wales and Victoria suggest significant changes in the rainfall due to changes in tree cover. This indicates the method works better when an abrupt change in the data can be clearly identified. The results from the step trend test also mainly identified a positive relationship between the tree cover and the rainfall at p < 0.1 at the NSW/Victoria region. High rainfall variability and possible regrowth could have impacted the results in the Queensland region.

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