Observing Ecohydrological Processes: Challenges and Perspectives

Li, Xin; Vereecken, Harry; Ma, Can

doi:10.1007/978-3-662-48297-1_1

Cited by 3 publications

(2 citation statements)

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“…In particular, numerous long-term regional scale hydrological and ecohydrological monitoring networks have been built up with the aims to validate and understand the modeling and remote sensing products (Ma et al, 2008;Su et al, 2011;Yao et al, 2012;Yang et al, 2013;Wang et al, 2021a). Consequently, several datasets have been recently published covering the soil moisture/temperature, ecohydrological, and integrated monitoring dataset (Zhao et al, 2018;He et al, 2020;Li et al, 2020;Ma et al, 2020;Su et al, 2020a;Zhang et al, 2021). All the relevant work and datasets, linked with the remote sensing data and reanalysis products, inevitably help to facilitate our understanding of the coupled waterheat-carbon exchange processes that occur in this unique cold environment, termed the Third Pole Environment.…”

Section: Water-heat-carbon Exchange Processes In Cold Regionsmentioning

confidence: 99%

“…Earth system observation (ESO) and modelling (ESM) are two legs of the ESS. Many projects and initiatives were initiated and lots of Earth system observations for specific purposes were built up (see the reviews by Fu et al, 2010;Bojinski et al, 2014;Brantley et al, 2017;Baatz et al, 2018;Mirtl et al, 2018;Paganini et al, 2018;Su et al, 2018;Li & Vereecken, 2020). ESOs from point, field, catchment scale, with long term observation are of great importance to reveal the true nature of the specific systems.…”

Section: Introductionmentioning

confidence: 99%

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Coupled water-heat-carbon exchange processes in cold environments: observation and numerical modeling

Lian-yu¹

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I would like to take the 'Marathon' as the metaphor to describe my PhD journey. I'd say the experience 'on the road' is valuable and unforgettable to me. People might say that the starting point, which way you will select to go and where you start, is very important. Yes, I definitely agree. However, I want to leave most of my words to the running process here. Trial and error, making adjustments and modifications, pains and gains are all the necessary and beautiful (complex mood to say this word) scenery along the journey. You have to experience and learn how to enjoy and overcome them. Luckily, I am not lonely. Many people are to be appreciated here.First and foremost, I would like to express my sincere thanks to my promoter Prof. Dr. Bob Su, who initializes this running project and provides me with the message "there is a very interesting research topic I would like you to contribute something!". Your critical thinking, rich experience, continuous support and warming encouraging words, "Enjoy the journey! Cherish the person! Good health!", like the lighthouse, inspire me to keep on track and stand up from the failures and then move forward.

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Section: Water-heat-carbon Exchange Processes In Cold Regionsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Coupled water-heat-carbon exchange processes in cold environments: observation and numerical modeling

Lian-yu¹

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A New Forest Leaf Area Index Retrieval Algorithm Over Slope Surface

He,

Wen,

et al. 2024

IEEE Trans. Geosci. Remote Sensing

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Runoff observation in a tropical Brantas watershed as observed from long-term globally available TerraClimate data 2001–2020

Wiwoho

Astuti

2022

Geoenviron Disasters

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Runoff information and its dynamics are critical for supporting watershed management; however, spatio-temporal data about runoff is rare or unavailable in data-scarce regions. Information about the performance of remote sensing-based runoff and its potential application is limitedly known. In data-scarce regions, this condition impedes comprehensive watershed assessment especially in the midst of climate change impacts. This study examined the performance of globally available monthly runoff dataset provided by TerraClimate at ~ 4 km spatial resolution and employed them to assess the runoff dynamics in a humid tropic watershed. Monthly TerraClimate data shows a moderate performance with an r of 0.63, RMSE of 57–127 mm/month and NRMSE of 18–30% to the simulated runoff from a well-calibrated model. The upper region of Brantas watershed was found to be the hotspot of high runoff. About 25% of the study area belongs to high runoff (0–33rd percentile). Over the last two decades, runoff has been slightly increased across the study area. Green vegetation fraction (GVF), precipitation, and topography are critical for regulating runoff dynamics. While topography and precipitation impact on runoff are straightforward, the GVF’s role is complex and site-specific. High runoff was found mostly to be associated with high precipitation and steep slope. GVF appears to be less effective in representing ground cover against runoff generation due to high variability of actual ground cover types. Using time-series and change vector analysis (CVA) of runoff and GVF, the dynamics of watershed condition was examined. Long-term CVA analysis also found that the condition in Brantas watershed was fluctuated with slight increase in impaired condition. The study exemplified the potential use of the remote sensing-based runoff data in a tropical data-scarce region. Despite limitation of the runoff data due to its moderate performance, the globally available monthly runoff data from TerraClimate can be used to support regional water resource assessment in data-scare regions. Future improvement that includes downscaling and use of machine learning can be considered to improve the remotely sensed runoff data to deliver the bigger benefits of such data.

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Observing Ecohydrological Processes: Challenges and Perspectives

Cited by 3 publications

References 75 publications

Coupled water-heat-carbon exchange processes in cold environments: observation and numerical modeling

Coupled water-heat-carbon exchange processes in cold environments: observation and numerical modeling

A New Forest Leaf Area Index Retrieval Algorithm Over Slope Surface

Runoff observation in a tropical Brantas watershed as observed from long-term globally available TerraClimate data 2001–2020

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