City-wide, high-resolution mapping of evapotranspiration to guide climate-resilient planning

Vulova, Stenka; Rocha, Alby Duarte; Meier, Fred; Nouri, Hamideh; Schulz, Christian; Soulsby, Chris; Tetzlaff, Doerthe; Kleinschmit, Birgit

doi:10.1016/j.rse.2023.113487

Cited by 12 publications

(4 citation statements)

References 124 publications

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“…NDVI is normally seen as an effective index reflecting large-scale vegetation coverage and growth status, and is among the most extensively applied vegetation indices ( Schultz et al., 2016 ; Lu et al., 2019 ; Vulova et al., 2023 ). In this research, Surface Reflectance (SR) images of Landsat were used to calculate NDVI in accordance with GEE cloud platform, and Maximum Value Composites (MVC) were applied to composite the NDVI data spanning from 1985 and 2020 ( Lanorte et al., 2014 ; Liu et al., 2022 ).…”

Section: Methodsmentioning

confidence: 99%

An advanced TSMK-FVC approach combined with Landsat 5/8 imagery for assessing the long-term effects of terrain and climate on vegetation growth

Xu,

Shen,

et al. 2024

Front. Plant Sci.

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IntroductionAs an exceptional geographical entity, the vegetation of the Qinghai-Tibetan Plateau (QTP) exhibits high sensitivity to climate change. The Baima Snow Mountain National Nature Reserve (BNNR) is located in the south-eastern sector of the QTP, serving as a transition area from sub-tropical evergreen broadleaf forest to high-mountain vegetation. However, there has been limited exploration into predicting the temporal and spatial variability of vegetation cover using anti-interference methods to address outliers in long-term historical data. Additionally, the correlation between these variables and environmental factors in natural forests with complex terrain has rarely been analyzed.MethodsThis study has developed an advanced approach based on TS (Theil-Sen slope estimator) MK (Mann-Kendall test)-FVC (fractional vegetation cover) to accurately evaluate and predict the time and spatial shifts in FVC within the BNNR, utilizing the GEE (Google Earth Engine). The satellite data utilized in this paper consisted of Landsat images spanning from 1986 to2020. By integrating TS and MK methodologies to monitor and assess the FVC trend, the Hurst index was employed to forecast FVC. Furthermore, the association between FVC and topographic factors was evaluated, the partial correlation between FVC and climatic influences was analyzed at the pixel level (30×30m).Results and discussionHere are the results of this research: (1) Overall, the FVC of the BNNR exhibits a growth trend, with the mean FVC value increasing from 59.40% in 1986 to 68.67% in 2020. (2) The results based on the TS-MK algorithm showed that the percentage of the area of the study area with an increasing and decreasing trend was 59.03% (significant increase of 28.04%) and 22.13% (significant decrease of 6.42%), respectively. The coupling of the Hurst exponent with the Theil-Sen slope estimator suggests that the majority of regions within the BNNR are projected to sustain an upward trend in FVC in the future. (3) Overlaying the outcomes of TS-MK with the terrain factors revealed that the FVC changes were notably influenced by elevation. The partial correlation analysis between climate factors and vegetation changes indicated that temperature exerts a significant influence on vegetation cover, demonstrating a high spatial correlation.

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Section: Methodsmentioning

confidence: 99%

An advanced TSMK-FVC approach combined with Landsat 5/8 imagery for assessing the long-term effects of terrain and climate on vegetation growth

Xu,

Shen,

et al. 2024

Front. Plant Sci.

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“…These provide a fuller, more nuanced approach to understanding hydrological function, by integrating diverse complementary field data on the water cycle beyond simply rainfall and runoff (Hutchins et al, 2017 ). These include hydroclimatic fluxes (Vulova et al, 2023 ), isotopic and water quality characteristics (Kuhlemann et al, 2020 ), soil moisture and groundwater processes (Duethmann et al, 2022 ; Schaffitel et al, 2020 ), and vegetation parameters (Bernard et al, 2022 ; Crampe et al, 2021 ); data which are either empirically derived or remotely sensed at various spatial and temporal scales. Such data can then drive exploratory, multi-calibrated modeling to develop hypotheses of hydrological functions (e.g., Birkel et al, 2014 ; Kuppel et al, 2018 ).…”

Section: Introductionmentioning

confidence: 99%

Integrated monitoring and modeling to disentangle the complex spatio-temporal dynamics of urbanized streams under drought stress

López Moreira Mazacotte,

Tetzlaff,

Marx

et al. 2024

Environ Monit Assess

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We have a poor understanding of how urban drainage and other engineered components interact with more natural hydrological processes in green and blue spaces to generate stream flow. This limits the scientific evidence base for predicting and mitigating the effects of future development of the built environment and climate change on urban water resources and their ecosystem services. Here, we synthesize > 20 years of environmental monitoring data to better understand the hydrological function of the 109-km2 Wuhle catchment, an important tributary of the river Spree in Berlin, Germany. More than half (56%) of the catchment is urbanized, leading to substantial flow path alterations. Young water from storm runoff and rapid subsurface flow provided around 20% of stream flow. However, most of it was generated by older groundwater (several years old), mainly recharged through the rural headwaters and non-urban green spaces. Recent drought years since 2018 showed that this base flow component has reduced in response to decreased recharge, causing deterioration in water quality and sections of the stream network to dry out. Attempts to integrate the understanding of engineered and natural processes in a traditional rainfall-runoff model were only partly successful due to uncertainties over the catchment area, effects of sustainable urban drainage, adjacent groundwater pumping, and limited conceptualization of groundwater storage dynamics. The study highlights the need for more extensive and coordinated monitoring and data collection in complex urban catchments and the use of these data in more advanced models of urban hydrology to enhance management.

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“…Vulova et al very recently followed this approach to map hourly uxes of H 2 O in 10 × 10 m grid-cells across Berlin using as reference ux data from two EC ux towers. 40 Mobile measurements have been used to investigate the spatial variability of GHG in terms of concentrations at high spatial resolution within the urban landscape, [41][42][43] but not in terms of emissions. Similarly, mobile platforms have been instrumented for evaluating the spatial variability of temperature, humidity and other microclimatic variables at street level, but not for measuring uxes of heat or moisture.…”

Section: Introductionmentioning

confidence: 99%

“…Vulova et al very recently followed this approach to map hourly fluxes of H 2 O in 10 × 10 m grid-cells across Berlin using as reference flux data from two EC flux towers. 40…”

Section: Introductionmentioning

confidence: 99%

High-resolution maps of carbon dioxide and moisture fluxes over an urban neighborhood

Velasco

Segovia

Roth

2023

Environ. Sci.: Atmos.

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City-wide, high-resolution mapping of evapotranspiration to guide climate-resilient planning

Cited by 12 publications

References 124 publications

An advanced TSMK-FVC approach combined with Landsat 5/8 imagery for assessing the long-term effects of terrain and climate on vegetation growth

An advanced TSMK-FVC approach combined with Landsat 5/8 imagery for assessing the long-term effects of terrain and climate on vegetation growth

Integrated monitoring and modeling to disentangle the complex spatio-temporal dynamics of urbanized streams under drought stress

High-resolution maps of carbon dioxide and moisture fluxes over an urban neighborhood

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