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Monitoring Ecohydrology with Remote Sensing

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A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Biogeosciences Remote Sensing".

Deadline for manuscript submissions: 30 November 2024 | Viewed by 10912

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Special Issue Editors

Dr. Pamela L. Nagler

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Guest Editor

U.S. Geological Survey, Southwest Biological Science Center, 520 N. Park Ave., Tucson, AZ 85719, USA
Interests: spatial ecohydrology; remote sensing of dryland ecosystems; UAS; riparian vegetation; phenology; evapotranspiration; environmental assessments using multi-scale optical imagery; environmental flows

Dr. Tanya Doody

E-Mail Website
Guest Editor

CSIRO, Land and Water, Waite Campus, Adelaide, SA 5064, Australia
Interests: invasive species ecology; ecosystem function; surface processes; ecological physiology; natural resource management; freshwater ecology; earth sciences not elsewhere classified

Dr. Sicong Gao

E-Mail Website
Guest Editor

CSIRO, Land and Water, Waite Campus, Adelaide, SA 5064, Australia
Interests: radiative transfer model; sun-induced chlorophyll fluorescence (SIF); environmental flows; drought and heat stress; evapotranspiration; lidar

Special Issue Information

Dear Colleagues,

Ecohydrological research is a critical frontier which informs and improves monitoring and management of terrestrial and freshwater ecosystems. In general, this research field consists of four aspects which are essential to understand (1) the impact of ecosystem changes on hydrological processes; (2) the effects of changes in hydrological processes on ecosystems; (3) water–ecological–social interactions and watershed water management; and (4) ecohydrological processes that are important to land–atmosphere interactions and feedback. The focus in recent, past decades, where bioclimatic and ecohydrologic pressures have been dramatic, has been on anthropogenic impacts on the environment which results in altered ecological functions, as determined by advances in ecohydrological research. However, challenges in in-situ data collection and monitoring across multiple temporal and spatial scales continues to hinder a broader understanding of ecosystem functions and condition. With technological and data analytical advances, remote sensing data collection and interpretation have significantly evolved, where sensors can directly or indirectly obtain hydrologic and ecologic variables and parameters that cannot be observed by conventional means and can provide long-term, dynamic, and continuous multiple-scale data from drones to satellite imagery. Thus, advancing the use of remote sensing to monitor ecohydrological variables such as evapotranspiration, phenological change, or soil moisture can help inform policy decisions and inform national and international environmental management. This Special Issue aims to investigate the functional relationships between hydrology and ecology at multiple spatial and temporal scales using remote-sensing data to advance the ecohydrological monitoring of terrestrial ecosystems.

Manuscripts are encouraged which are related to the following topics:

Ecosystem energy, water, and nutrient fluxes;
Water–ecological interactions and watershed hydrological management;
Vegetation–atmosphere interactions;
Inundation, vegetation communities, landcover mapping, and change detection.

Additional topics will also be considered.

Dr. Pamela L. Nagler
Dr. Tanya Doody
Dr. Sicong Gao
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

hydrology and ecohydrology
water cycle/use/stress
soil moisture
evapotranspiration
ecological processes and functions

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Published Papers (8 papers)

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Research

16 pages, 7033 KiB

Open AccessArticle

Establishment of Remote Sensing Inversion Model and Its Application in Pollution Source Identification: A Case Study of East Lake in Wuhan

by Shiyue He, Yanjun Zhang, Lan Luo and Yuanxin Song

Remote Sens. 2024, 16(18), 3402; https://doi.org/10.3390/rs16183402 - 13 Sep 2024

Cited by 1 | Viewed by 590

Abstract

In remote watersheds or large water bodies, monitoring water quality parameters is often impractical due to high costs and time-consuming processes. To address this issue, a cost-effective methodology based on remote sensing was developed to predict water quality parameters over a large and operationally challenging area, especially focusing on East Lake. Sentinel-2 satellite image data were used as a proxy, and a multiple linear regression model was developed to quantify water quality parameters, namely chlorophyll-a, total nitrogen, total phosphorus, ammonia nitrogen and chemical oxygen demand. This model was then applied to East Lake to obtain the temporal and spatial distribution of these water quality parameters. By identifying the locations with the highest concentrations along the boundaries of East Lake, potential pollution sources could be inferred. The results demonstrate that the developed multiple linear regression model provided a satisfactory relationship between the measured and simulated water quality parameters. The coefficients of determination R² of the multiple linear regression models for chlorophyll-a, total nitrogen, total phosphorus, ammonia nitrogen and chemical oxygen demand were 0.943, 0.781, 0.470, 0.624 and 0.777, respectively. The potential pollution source locations closely matched the officially published information on East Lake pollutant discharges. Therefore, using remote sensing imagery to establish a multiple linear regression model is a feasible approach for understanding the exceedance and distribution of various water quality parameters in East Lake. Full article

(This article belongs to the Special Issue Monitoring Ecohydrology with Remote Sensing)

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20 pages, 2364 KiB

Open AccessArticle

On Connecting Hydrosocial Parameters to Vegetation Greenness Differences in an Evolving Groundwater-Dependent Ecosystem

by Matthew R. Lurtz, Ryan R. Morrison and Pamela L. Nagler

Remote Sens. 2024, 16(14), 2536; https://doi.org/10.3390/rs16142536 - 10 Jul 2024

Viewed by 956

Abstract

Understanding groundwater-dependent ecosystems (i.e., areas with a relatively shallow water table that plays a major role in supporting vegetation health) is key to sustaining water resources in the western United States. Groundwater-dependent ecosystems (GDEs) in Colorado have non-pristine temporal and spatial patterns, compared to agro-ecosystems, which make it difficult to quantify how these ecosystems are impacted by changes in water availability. The goal of this study is to examine how key hydrosocial parameters perturb GDE water use in time and in space. The temporal approach tests for the additive impacts of precipitation, surface water discharge, surface water mass balance as a surrogate for surface–groundwater exchange, and groundwater depth on the monthly Landsat normalized difference vegetation index (NDVI). The spatial approach tests for the additive impacts of river confluences, canal augmentation, development, perennial tributary confluences, and farmland modification on temporally integrated NDVI. Model results show a temporal trend (monthly, 1984–2019) is identifiable along segments of the Arkansas River at resolutions finer than 10 km. The temporal impacts of river discharge correlate with riparian water use sooner in time compared to precipitation, but this result is spatially variable and dependent on the covariates tested. Spatially, areal segments of the Arkansas River that have confluences with perennial streams have increased cumulative vegetation density. Quantifying temporal and spatial dependencies between the sources and effects of GDEs could aid in preventing the loss of a vulnerable ecosystem to increased water demand, changing climate, and evolving irrigation methodologies. Full article

(This article belongs to the Special Issue Monitoring Ecohydrology with Remote Sensing)

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24 pages, 21182 KiB

Open AccessArticle

Effects of Climate Change and Human Activities on Runoff in the Upper Reach of Jialing River, China

by Weizhao Shi, Yi He and Yiting Shao

Remote Sens. 2024, 16(13), 2481; https://doi.org/10.3390/rs16132481 - 6 Jul 2024

Cited by 1 | Viewed by 801

Abstract

In recent years, the runoff of numerous rivers has experienced substantial changes owing to the dual influences of climate change and human activities. This study focuses on the Lixian hydrological station’s controlled basin, located in the upper reaches of the Jialing River in China. The objective is to assess and quantify the impacts of human activities and climate change on runoff variations. This study analyzed runoff variations from 1960 to 2016 and employed the Soil and Water Assessment Tool (SWAT) model, the long short-term memory (LSTM) model, and eight Budyko framework formulations to assess factors influencing runoff. Additionally, it used the patch-generating land use simulation (PLUS) and SWAT models to simulate future runoff scenarios under various conditions. The results indicate the following. (1) The study area has witnessed a significant decline in runoff (p < 0.01), while potential evapotranspiration shows a significant upward trend (p < 0.01). Precipitation displays a nonsignificant decreasing trend (p > 0.1). An abrupt change point in runoff occurred in 1994, dividing the study period into baseline and change periods. (2) The Budyko results reveal that human activities contributed 50% to 60% to runoff changes. According to the SWAT and LSTM models, the contribution rates of human activities are 63.21% and 52.22%, respectively. Human activities are thus identified as the predominant factor in the decline in runoff. (3) Human activities primarily influence runoff through land cover changes. Conservation measures led to a notable increase in forested areas from 1990 to 2010, representing the most significant change among land types. (4) Future land use scenarios suggest that the highest simulated runoff occurs under a comprehensive development scenario, while the lowest is observed under an ecological conservation scenario. Among the 32 future climate scenarios, runoff increases significantly with a 10% increase in precipitation and decreases substantially with a 15% reduction in precipitation. These findings underscore the significant impact of human activities and climate change on runoff variations in the upper reaches of the Jialing River, highlighting the importance of incorporating both factors in water resource management and planning. Full article

(This article belongs to the Special Issue Monitoring Ecohydrology with Remote Sensing)

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19 pages, 2617 KiB

Open AccessArticle

Investigating the Impact of Xylella Fastidiosa on Olive Trees by the Analysis of MODIS Terra Satellite Evapotranspiration Time Series by Using the Fisher Information Measure and the Shannon Entropy: A Case Study in Southern Italy

by Luciano Telesca, Nicodemo Abate, Michele Lovallo and Rosa Lasaponara

Remote Sens. 2024, 16(7), 1242; https://doi.org/10.3390/rs16071242 - 31 Mar 2024

Cited by 1 | Viewed by 1440

Abstract

Xylella Fastidiosa has been recently detected for the first time in southern Italy, representing a very dangerous phytobacterium capable of inducing severe diseases in many plants. In particular, the disease induced in olive trees is called olive quick decline syndrome (OQDS), which provokes the rapid desiccation and, ultimately, death of the infected plants. In this paper, we analyse about two thousands pixels of MODIS satellite evapotranspiration time series, covering infected and uninfected olive groves in southern Italy. Our aim is the identification of Xylella Fastidiosa-linked patterns in the statistical features of evapotranspiration data. The adopted methodology is the well-known Fisher–Shannon analysis that allows one to characterize the time dynamics of complex time series by means of two informational quantities, the Fisher information measure (FIM) and the Shannon entropy power (SEP). On average, the evapotranspiration of Xylella Fastidiosa-infected sites is characterized by a larger SEP and lower FIM compared to uninfected sites. The analysis of the receiver operating characteristic curve suggests that SEP and FIM can be considered binary classifiers with good discrimination performance that, moreover, improves if the yearly cycle, very likely linked with the meteo-climatic variability of the investigated areas, is removed from the data. Furthermore, it indicated that FIM exhibits superior effectiveness compared to SEP in discerning healthy and infected pixels. Full article

(This article belongs to the Special Issue Monitoring Ecohydrology with Remote Sensing)

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19 pages, 5012 KiB

Open AccessArticle

Drought Dynamics in the Nile River Basin: Meteorological, Agricultural, and Groundwater Drought Propagation

by Zemede M. Nigatu, Wei You and Assefa M. Melesse

Remote Sens. 2024, 16(5), 919; https://doi.org/10.3390/rs16050919 - 6 Mar 2024

Cited by 6 | Viewed by 2219

Abstract

The Nile River Basin (NRB) has experienced a notable rise in drought episodes in recent decades. The propagation of meteorological, agricultural, and groundwater drought dynamics in the NRB was investigated in this study. The following drought indices examined the correlation and propagation among meteorological, agricultural, and groundwater droughts. These are the standardized precipitation evapotranspiration index (SPEI), soil moisture index, Gravity Recovery and Climate Experiment, and GRACE Follow-On (GRACE/GRACE-FO)-derived groundwater drought index (GGDI). These droughts were comprehensively evaluated in the NRB from 2003 to 2022. The cross-wavelet transform approach highlighted the links between droughts. The following are the key findings: (1) In the NRB, the cross-wavelet energy spectrum of wavelet coherence can indicate the internal connection between meteorological versus (vs.) agricultural and agricultural versus (vs.) groundwater drought. The time scale with the most significant correlation coefficient is the drought propagation time. (2) The El Niño–Southern Oscillation (ENSO) correlated with agricultural and groundwater drought much more than the Indian Ocean Dipole (IOD), demonstrating that ENSO has an important impact on drought advancement. (3) The R² values were 0.68 for GGDI vs. standardized soil moisture index (SSI), 0.71 for Blue Nile Region (BNR) GGDI vs. SSI, and 0.55 for SSI vs. Standardized Precipitation Evapotranspiration Index (SPEI). Similarly, in the Lake Victoria Region (LVR), GGDI vs. SSI was 0.51 and SSI vs. SPEI was 0.55, but in the Bahr-el-Ghazal Region (BER), GGDI vs. SSI was 0.61 and SSI vs. SPEI was 0.27 during the whole research period with varied lag durations ranging from 1 to 6 months. Thus, the propagation of drought (i.e., meteorological, agricultural, and groundwater drought) dynamics has the potential to reshape our understanding of drought evolution, which could lead to early drought forecasting across the NRB and similar climatic regions. Full article

(This article belongs to the Special Issue Monitoring Ecohydrology with Remote Sensing)

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26 pages, 11080 KiB

Open AccessArticle

Prediction of Open Woodland Transpiration Incorporating Sun-Induced Chlorophyll Fluorescence and Vegetation Structure

by Sicong Gao, William Woodgate, Xuanlong Ma and Tanya M. Doody

Remote Sens. 2024, 16(1), 143; https://doi.org/10.3390/rs16010143 - 28 Dec 2023

Cited by 1 | Viewed by 1290

Abstract

Transpiration (T) represents plant water use, while sun-induced chlorophyll fluorescence (SIF) emitted during photosynthesis, relates well to gross primary production. SIF can be influenced by vegetation structure, while uncertainties remain on how this might impact the relationship between SIF and T, especially for open and sparse woodlands. In this study, a method was developed to map T in riverine floodplain open woodland environments using satellite data coupled with a radiative transfer model (RTM). Specifically, we used FluorFLiES, a three-dimensional SIF RTM, to simulate the full spectrum of SIF for three open woodland sites with varying fractional vegetation cover. Five specific SIF bands were selected to quantify their correlation with field measured T derived from sap flow sensors. The coefficient of determination of the simulated far-red SIF and field measured T at a monthly scale was 0.93. However, when comparing red SIF from leaf scale to canopy scale to predict T, performance declined by 24%. In addition, varying soil reflectance and understory leaf area index had little effect on the correlation between SIF and T. The method developed can be applied regionally to predict tree water use using remotely sensed SIF datasets in areas of low data availability or accessibility. Full article

(This article belongs to the Special Issue Monitoring Ecohydrology with Remote Sensing)

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19 pages, 9326 KiB

Open AccessArticle

Integrating Earth Observation with Stream Health and Agricultural Activity

by David Chatzidavid, Eleni Kokinou, Stratos Kokolakis and Matina Karagiannidou

Remote Sens. 2023, 15(23), 5485; https://doi.org/10.3390/rs15235485 - 24 Nov 2023

Cited by 1 | Viewed by 1138

Abstract

The overall health of streams, including their surrounding urban or agricultural areas, is inextricably linked to general ecological balance and public health (physical and mental well-being). This study aims to contribute to the monitoring of rural or suburban areas adjacent to streams. Specifically, low-cost and rapid ground and Earth observation techniques were used to (a) obtain a rapid assessment of stream soil and water patterns, (b) create a database of selected parameters for the study area that can be used for future comparisons, and (c) identify soil variability in agricultural fields adjacent to streams and determine soil zones that will enable the rational use of inputs (water, fertilisers, and pesticides). Robust techniques from related fields of topography, geology, geophysics, and remote sensing were combined using GIS for two selected areas (I and II) in Heraklion, central Crete (Greece) in the eastern Mediterranean. Our results indicate that area I (east of Heraklion) is under pressure only in its coastal part, most probably due to urbanisation (land change). The agricultural fields of area II (west of Heraklion) show normal values for the distribution of electrical conductivity and magnetic susceptibility and present spatial variability indicating intra-parcel zones. Intra-parcel variability of the conductivity and magnetic susceptibility should be considered in future cropping and environmental management. Full article

(This article belongs to the Special Issue Monitoring Ecohydrology with Remote Sensing)

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21 pages, 5274 KiB

Open AccessArticle

Vegetation Dynamics and Its Trends Associated with Extreme Climate Events in the Yellow River Basin, China

by Yanping Cao, Zunyi Xie, Xinhe Huang, Mengyang Cui, Wenbao Wang and Qingqing Li

Remote Sens. 2023, 15(19), 4683; https://doi.org/10.3390/rs15194683 - 25 Sep 2023

Cited by 1 | Viewed by 1477

Abstract

As a vital ecological barrier in China, Yellow River Basin (YRB) is strategically significant for China’s national development and modernization. However, YRB has fragile ecosystems, and is sensitive to climatic change. Extreme climate events (e.g., heavy precipitation, heatwaves, and extreme hot and cold) occur frequently in this basin, but the implications (positive and negative effects) of these events on vegetation dynamics remains insufficiently understood. Combing with net primary productivity (NPP), the normalized difference vegetation index (NDVI) and extreme climate indexes, we explored the spatio–temporal characteristics of plants’ growth and extreme climate, together with the reaction of plants’ growth to extreme climate in the Yellow River Basin. This study demonstrated that annual NPP and NDVI of cropland, forest, and grassland in the study region all revealed a climbing tendency. The multi-year monthly averaged NPP and NDVI were characterized by a typical unimodal distribution, with the maximum values of NPP (66.18 gC·m⁻²) and NDVI (0.54) occurring in July and August, respectively. Spatially, multi–year averaged of vegetation indicators decreased from southeast to northwest. During the study period, carbon flux (NPP) and vegetation index (NDVI) both exhibited improvement in most of the YRB. The extreme precipitation indexes and extreme high temperature indexes indicated an increasing tendency; however, the extreme low temperature indexes reduced over time. NPP and NDVI were negatively associated with extreme low temperature indexes and positively correlated with extreme high temperature indexes, and extreme precipitation indicators other than consecutive dry days. Time lag cross–correlation analysis displayed that the influences of extreme temperature indexes on vegetation indexes (NPP and NDVI) were delayed by approximately six months, while the effects of extreme precipitation indexes were immediate. The study outcomes contribute to our comprehension of plants’ growth, and also their reaction to extreme climates, and offer essential support for evidence–based ecological management practices in the Yellow River Basin. Full article

(This article belongs to the Special Issue Monitoring Ecohydrology with Remote Sensing)

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