Geology topics

Pamela L. Nagler

Publications and source records attributed to Pamela L. Nagler.

At least 19 recordsLinked to original sources

USGS2026

Groundwater dependency and hydroclimatic influences on riparian and upland vegetation productivity, Upper San Pedro, Arizona, United States

In arid and semi-arid regions, groundwater sustains vegetation through subsurface water access, yet the responses of groundwater-dependent ecosystems (GDEs) to changing hydroclimate and groundwater availability are relatively understudied. This study investigates seasonal and spatial patterns in vegetation greenness using Landsat Enhanced Vegetation Index (EVI) values across riparian and upland zones in the semi-arid Upper San Pedro (USP) watershed, southern Arizona, which experiences a bimodal precipitation regime. We paired 25 years (2000–2024) of EVI and depth to groundwater (DTG) data from 89 wells and climate metrics (precipitation and vapour pressure deficit) to quantify the sensitivity of vegetation to subsurface moisture as well as atmospheric moisture supply and demand. Vegetation at wells near the USP riparian area showed strong associations between EVI and DTG anomalies during the monsoon season, indicating sustained groundwater use even during this wet period when summer precipitation is abundant. In contrast, upland vegetation that lacked access to groundwater showed minimal sensitivity in EVI to DTG and was generally less responsive to vapour pressure deficit. Interestingly, the riparian GDEs were not decoupled from precipitation and climate variability. These results underscore the importance of groundwater for maintaining riparian productivity and highlight the utility of remote sensing in identifying vegetation-climate-groundwater linkages across heterogeneous dryland landscapes.

Arizona↗

USGS2026

James Buttle Review: A synthesis of riparian plant water use over two decades in North American drylands

Assessing riparian ecosystem water use, particularly transpiration from vegetation and evaporation from soils (‘plant water use’, hereafter), is key to developing sound water management approaches. In western North America, a multidecadal drought is reducing water availability and increasing the use of detailed water budgets. Questions related to both removal of vegetation for water salvage and budgeting water to maintain valuable riparian areas have led to a wealth of studies on riparian plant water use across dryland river systems in North America. Towards evaluating broad patterns in riparian plant water use, we synthesise results from over two decades of research, with the goal of informing water management policies and planning. This study asks: (1) Do some riparian plant communities exhibit lower plant water use than others? (2) Do riparian plant communities have higher water use under hotter climates? (3) Can statistical models based on existing data, plant communities and climate data be used to predict water use for unmeasured locations? Using hierarchical Bayesian models to synthesise data on annual and daily-scale plant water use, we show that marshes, cottonwood-willow stands and tamarisk not impacted by biocontrol use larger amounts of water at the annual scale than other vegetation communities. All plant communities have higher annual water use in hotter climates, which is likely related to a longer growing season and higher evaporative demand. Statistical models based on existing water-use data, plant communities and climate provide bounds on plant water use that can be applied to unmeasured locations and used to evaluate the effects of plant community change on water use. This synthesis produces the most complete summary of riparian plant water use in North American drylands to date and provides water use predictions across different climate and community scenarios that can be used for current and future conditions.

Arizona, California, Colorado, Idaho, Nevada, New ↗

USGS2026

Bird guilds exhibit varied responses to floodplain forest restoration in the Colorado River delta, Mexico

Grouping species into guilds can be useful to inform management decisions locally and at broader scales because guilds lack species-specificity. We investigated the response of five breeding bird guilds to riparian habitat restoration in the arid Colorado River delta, based on two decades of bird detections (2002–2021) at 230 bird count stations across 7 routes in actively revegetated (“restored”) sites, and 20 routes in non-actively revegetated (“control”) sites. We used guilds based on habitat associations. We also described changes in vegetation and explored their influence on bird species detections and guild dynamics. Riparian forest bird specialists responded positively to active revegetation, but this positive response was delayed and weaker in a river reach where restoration began later and featured less typical riparian vegetation. Birds associated with wetland habitat showed a positive response to restoration in the wettest reach, which had a baseline of high abundance of wetland birds in control sites and relatively abundant macrophyte cover. Conversely, the abundance of desert scrub bird specialists was highest in the driest and least vegetated restored reach. Generalists only exhibited decreased detections in the wettest restored reach. All this occurred while declines of riparian forest, wetland, desert scrub, and generalist bird species observed over a decade prior to restoration had stabilized in control sites. Detections of birds associated with agricultural fields increased in the study area, irrespective of restoration efforts. Our study demonstrates that the choice of bird guilds as ecological indicators can significantly influence the interpretation of restoration outcomes.

Arizona↗

USGS2025

Advancing broadscale spatial evapotranspiration modelling by incorporating sun-induced chlorophyll fluorescence measurements

Evapotranspiration (ET) describes the sum of water transfer from the ground surface through soil evaporation and water loss from leaf stomata into the atmosphere − critical factors linking the global water and carbon cycles. Myriad ET models based on remote sensing data provide spatially continuous estimates of ET; however, leaf photosynthetic information is critical to ensure accurate ET estimates, which are difficult to measure from space. Remotely sensed sun-induced chlorophyll fluorescence (SIF) provides a proxy of stomatal conductance activity with high performance in predicting plant transpiration, which can account for a large proportion of terrestrial and riverine ET. This study aims to improve estimates of tree water use in semi-arid to arid environments. In this study, a fixed stomatal conductance model and three SIF-driven canopy conductance (g sc ) models were applied to model potential ET (PET). The models estimated PET using the Penman-Monteith equation with: (1) a constant leaf stomatal conductance; (2) a transpiration-driven g sc model; (3) a g sc model based on electron-transfer rate and vapor pressure deficit, and a (4) Ball-Berry stomatal conductance model. A machine learning model was then applied to scale PET to actual ET (AET) using remote sensing and climate data. Accordingly, four AET models were cross-validated with in-situ measured AET at 52 sites, including 21 eddy covariance flux tower sites, and 31 sap-flow measurement sites (semi-arid and plantation area), for various plant functional types in Australia. This study demonstrated that SIF effectively captured seasonal variations of g sc , finding that AET models with SIF-driven g sc models correlated well with in-situ measured AET (R 2 = 0.64). Modelled AET with dynamic variations of g sc generated lower prediction error (0.85 mm day −1 ), while the AET model with fixed stomatal conductance tended to overestimate AET in floodplains and underestimate it in evergreen broadleaf forests, indicating using fixed stomatal conductance results in unstable performance when modelling AET. This study demonstrated that SIF-driven AET models improved broadscale estimation of ET. Our findings provide vital broadscale hydrological data to assist catchment and regional water management, particularly over unmonitored areas at risk of future climate-driven reductions in rainfall.

Journal of Hydrology↗

USGS2024

Remote sensing of actual evapotranspiration from croplands

Agriculture accounted for the majority of human water use and for more than 90% of global freshwater consumption during the twentieth century (Hoekstra and Mekonnen, 2012; Shiklomanov, 2000). Streamflow depletion due to enhanced evapotranspiration (ET) from irrigated crops impacts freshwater ecosystems globally (Foley et al., 2005). Water scarcity limits crop production in many arid and semiarid regions, and water is likely to be a key resource limiting food production and food security in the twenty-first century (Foley et al., 2011; Vorosmarty et al., 2000). Despite this, estimates of the location and temporal dynamics of ET from croplands are often uncertain at a variety of spatial and temporal scales. Better information on ET can be useful in several applications at a range of spatial scales, including water resources, agronomy, and meteorology (e.g., Rivas and Caselles, 2004). At the scale of irrigation projects, maps of ET can assist with irrigation scheduling and demand assessment. Measurements of ET are required for monitoring plant water requirements, plant growth, and productivity, as well as for irrigation management and deciding when to carry out cultivation procedures (e.g., Consolli et al., 2006; Glenn et al., 2007; Yang et al., 2010).

Book chapter↗

USGS2024

On connecting hydro-social parameters to vegetation greenness differences in an evolving groundwater-dependent ecosystem

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.

Colorado↗

USGS2024

Effect of water delivery and irrigation for riparian restoration in the Colorado River Delta, Mexico

Along Mexico's arid Colorado River Delta, the riparian corridor lacks water due to a reduction in frequent flows, climate change, human infrastructure, and altered riparian landcover from disturbances to invasive species, fire, and high soil and water salinities, which have led to declines in riparian plant health in recent decades. Restoration efforts focusing on small plots have successfully revitalized habitat, which is the motivation for this research. Accurate estimations of water use by riparian vegetation are crucial in arid environments, where measuring actual evapotranspiration (ETa) poses a significant challenge in these narrow corridors. This study utilizes field-validated remote sensing techniques to quantify ETa at restoration sites. Our methods are twofold; we use the Landsat-8 two-band Enhanced Vegetation Index (EVI2) to monitor changes in vegetation greenness—a proxy of plant health—and we integrate EVI2 with potential evapotranspiration (ET) to calculate ETa. Our findings reveal a notable increase in vegetation greenness within the restoration sites over 9 years, with an average increase of 41.3%. Conversely, greenness in adjacent, unrestored control areas declined by 27.3%. The study also indicates a 22.1% increase in ETa in the restored areas, compared to a 30.8% reduction in the unrestored regions. Restored sites in reach 4 experienced ETa increases ranging from 9.2 to 12.2%, whereas their unrestored counterparts show a decline of 21.4%. Valuable estimates are provided of riparian greenness and water use that may assist natural resource managers who are tasked with allocating water and managing habitats within similar riparian corridors.

Colorado River Delta↗

USGS2024

An ensemble mean method for remote sensing of actual evapotranspiration to estimate water budget response across a restoration landscape

Estimates of actual evapotranspiration (ETa) are valuable for effective monitoring and management of water resources. In areas that lack ground-based monitoring networks, remote sensing allows for accurate and consistent estimates of ETa across a broad scale—though each algorithm has limitations (i.e., ground-based validation, temporal consistency, spatial resolution). We developed an ensemble mean ETa (EMET) product to incorporate advancements and reduce uncertainty among algorithms (e.g., energy-balance, optical-only), which we use to estimate vegetative water use in response to restoration practices being implemented on the ground using management interventions (i.e., fencing pastures, erosion control structures) on a private ranch in Baja California Sur, Mexico. This paper describes the development of a monthly EMET product, the assessment of changes using EMET over time and across multiple land use/land cover types, and the evaluation of differences in vegetation and water distribution between watersheds treated by restoration and their controls. We found that in the absence of a ground-based monitoring network, the EMET product is more robust than using a single ETa data product and can augment the efficacy of ETa-based studies. We then found increased ETa within the restored watershed when compared to the control sites, which we attribute to increased plant water availability.

Baja California Sur↗

USGS2024

Greenness and actual evapotranspiration in the unrestored riparian corridor of the Colorado River Delta in response to in-channel water deliveries in 2021 and 2022

Natural resource managers may utilize remotely sensed data to monitor vegetation within their decision-making frameworks for improving habitats. Under binational agreements between the United States and Mexico, seven reaches were targeted for riparian habitat enhancement. Monitoring was carried out using Landsat 8 16-day intervals of the two-band enhanced vegetation index 2 (EVI2) for greenness and actual evapotranspiration (ETa). In-channel water was delivered in 2021 and 2022 at four places in Reach 4. Three reaches (Reaches 4, 5 and 7) showed no discernable difference in EVI2 from reaches that did not receive in-channel water (Reaches 1, 2, 3 and 6). EVI2 in 2021 was higher than 2020 in all reaches except Reach 3, and EVI2 in 2022 was lower than 2021 in all reaches except Reach 7. ET(EVI2) was higher in 2020 than in 2021 and 2022 in all seven reaches; it was highest in Reach 4 (containing restoration sites) in all years. Excluding restoration sites, compared with 2020, unrestored reaches showed that EVI2 minimally increased in 2021 and 2022, while ET(EVI2) minimally decreased despite added water in 2021–2022. Difference maps comparing 2020 (no-flow year) to 2021 and 2022 (in-channel flows) reveal areas in Reaches 5 and 7 where the in-channel flows increased greenness and ET(EVI2).

Colorado River and Delta↗

USGS2024

Avian communities respond to plant and landscape composition in actively revegetated floodplains of the Colorado River delta in Mexico

We examined the influence of local habitat factors such as plant community composition and species cover, and landscape habitat factors (e.g., land cover types) on the composition of the avian community in an arid-region large river delta (Colorado River). This 106 river km-long study area has experienced restoration through environmental water deliveries and active management of vegetation for ca. 10 years after decades of degradation. Variation partitioning and spatial models (Moran Eigenvector Maps) showed that plant communities and land cover combined explained 29.3% of the variability of 115 bird species, with a high overlap of 13.1% as vegetation and landscape factors were partially confounded and spatially correlated. Redundancy analyses showed that a higher cover of native riparian trees and shrubs and a larger amount of land covered by forests, typical characteristics of revegetated sites, favored bird species with affinity for riparian forests. Marshland and open water landscape features and high cover of macrophytes (which were common in the wettest river reach among the five included in the study), irrespective of active revegetation, were associated with a higher prevalence of wetland birds. Dominance by the non-native shrub Tamarix spp. and, especially, barren areas were detrimental to most bird species. The proportion of agricultural lands around the study sites was related to high abundance of generalists and some non-native species. Overall, our study showed that both local (vegetation) and landscape (land use) factors are important considerations for restoration of riparian bird communities.

Ecological Engineering↗

USGS2024

Strategic restoration planning for land birds in the Colorado River Delta, Mexico

Ecological restoration is an essential strategy for mitigating the current biodiversity crisis, yet restoration actions are costly. We used systematic conservation planning principles to design an approach that prioritizes restoration sites for birds and tested it in a riparian forest restoration program in the Colorado River Delta. Restoration goals were to maximize the abundance and diversity of 15 priority birds with a variety of habitat preferences. We built abundance models for priority birds based on the current landscape, and predicted bird distributions and relative abundances under a scenario of complete riparian forest restoration throughout our study area. Then, we used Zonation conservation planning software to rank this restored landscape based on core areas for all priority birds. The locations with the highest ranks represented the highest priorities for restoration and were located throughout the river reach. We optimized how much of the available landscape to restore by simulating restoration of the top 10–90% of ranked sites in 10% intervals. We found that total diversity was maximized when 40% of the landscape was restored, and mean relative abundance was maximized when 80% of the landscape was restored. The results suggest that complete restoration is not optimal for this community of priority birds and restoration of approximately 60% of the landscape would provide a balance between maximum relative abundance and diversity. Subsequent planning efforts will combine our results with an assessment of restoration costs to provide further decision support for the restoration-siting process. Our approach can be applied to any landscape-scale restoration program to improve the return on investment of limited economic resources for restoration.

Colorado River Delta↗

USGS2024

U.S.-Mexico Borderland & vegetation community map

People on both sides of the United States-Mexico border need a high-resolution, binational vegetation community map that spans the entire United States-Mexico borderlands. Traditionally, mapping efforts in this region were impeded by complex logistics related to the international border, differing national needs and plans, and resource allocations and priorities. To address this need, scientists from the U.S. Geological Survey (USGS) Southwest Biological Science Center partnered with the Sonoran Joint Venture, the U.S. Fish and Wildlife Service (FWS) Migratory Bird Program, data engineers from the Department of Biosystems Engineering at the University of Arizona, and collaborators from the Wildlands Network, the Borderlands Program to produce the first prototype land cover map within the overlapping Mojave Desert, Sonoran Desert, and the North American Bird Conservation Initiative’s Bird Conservation Region 33 (BCR33) using Landsat satellite data . BCR33 is an area of high biodiversity, providing habitat for bird species of concern and other wildlife. The land cover map supports FWS recovery plan efforts related to conservation planning activities for many species, including Yellow-billed Cuckoo ( Coccyzus americanus ), Cactus Ferruginous Pygmy-Owl ( Glaucidium brasilianum cactorum ), Southwestern Willow Flycatcher ( Empidonax traillii extimus ), Yuma Ridgway’s Rail ( Rallus obsoletus yumanensis ), Bendire’s thrasher ( Toxostoma bendirei ), LeConte’s thrasher ( Toxostoma lecontei ), Masked Bobwhite ( Colinus virginianus ridgwayi ), jaguar ( Panthera onca ), and endangered plants such as Bartram’s stonecrop ( Graptopetalum bartramii ) and the Pima pineapple cactus ( Coryphantha robustispina ssp. robustispina ). In 2024, a Phase-II map for the full BCR33 region was completed, increasing the understanding of the binational nature of natural communities. The published map and associated paper can be found here .

Borderland↗

USGS2024

Colorado Delta riparian plant health improvement

The riparian corridor along Mexico’s arid Colorado River Delta is being affected by reduction in river flow and increases in heat, drought, human infrastructure, and disturbances. These disturbances can change riparian land cover by limiting water availability for riparian plant species, increasing fire intensity and frequency, and increasing soil and water salinities. In response to these forms of degradation, restoration efforts have begun to restore riparian habitats and native plant health, but vegetation greenness and corresponding plant water use continue to decline in unrestored reaches. Researchers from the U.S. Geological Survey (USGS) Southwest Biological Science Center are monitoring riparian plant health along the Colorado River Delta to support better ecohydrological decision-making. The researchers are helping a binational team to protect, restore, and maintain native vegetation within the 150-km long riparian corridor. Researchers are using Landsat 8 Operational Land Imager (OLI) data spanning 2014–2022 to measure greenness, a proxy for plant health, and actual evapotranspiration (ETa). Using an empirical model for ETa, evapotranspiration is estimated over each 16-day Landsat 8 OLI overpass period by considering the 8 days before and after the overpass date. In their paper, researchers noted an increase in vegetation greenness within the restoration sites over nine years, with an average increase of 41.3%, which may be partially due to targeted water deliveries at the restoration sites. Conversely, greenness in adjacent, unrestored control areas declined by 27.3%. The study showed a 22.1% increase in ETa in restored areas, compared to a 30.8% reduction in unrestored regions. Restored sites in one restored area experienced ETa increases up to 12.2%, whereas their unrestored counterparts showed a decline of 21.4%. These estimates of riparian greenness and water use may assist natural resource managers who are tasked with allocating water and managing habitats within similar riparian corridors.

Conference Paper↗

USGS2023

Crop water use dynamics over arid and semi-arid croplands in the lower Colorado River Basin

Numerous studies have evaluated the application of Remote Sensing (RS) techniques for mapping actual evapotranspiration (ETa) using Vegetation-Index-based (VI-based) and surface energy balance methods (SEB). SEB models computationally require a large effort for application. VI-based methods are fast and easy to apply and could therefore potentially be applied at high resolution; however, the accuracy of VI-based methods in comparison to SEB-based models remains unclear. We tested the ETa computed with the modified 2-band Enhanced Vegetation Index (METEVI2) implemented in the Google Earth Engine – for mapping croplands’ water use dynamics in the Lower Colorado River Basin. We compared METEVI2 with the well-established RS-based products of OpenET (Ensemble, eeMETRIC, SSEBop, SIMS, PT_JPL, DisALEXI and geeSEBAL). METEVI2 was then evaluated with measured ETa from four wheat fields (2017–2018). Results indicated that the monthly ETa variations for METEVI2 and OpenET models were comparable, though of varying magnitudes. On average, METEVI2 had the lowest difference rate from the average observed ETa with 17 mm underestimation, while SIMS had the highest difference rate (82 mm). Findings show that METEVI2 is a cost-effective ETa mapping tool in drylands to track crop water use. Future studies should test METEVI2’s applicability to croplands in more humid regions.

Lower Colorado River basin↗

USGS2023

Supplying ecosystem services on US rangelands

Rangelands comprise 40% of the conterminous United States and they supply essential ecosystem services to society. A scenario assessment was conducted to determine how accelerating biophysical and societal drivers may modify their future availability. Four scenarios emerged: two may maintain rural communities by sustaining the prevailing ecosystem service of beef cattle production, and two may transform rural communities through expansion of renewable energy technologies and infusion of external capital from amenity land sales. Collaborative organizations representing diverse societal sectors may most effectively identify and manage trade-offs among ecosystem service availability, and equitably prioritize food and energy security, environmental quality and cultural identity.

Nature Sustainability↗

USGS2023

Random forest classification of multitemporal Landsat 8 spectral data and phenology metrics for land cover mapping in the Sonoran and Mojave Deserts

Geospatial data and tools evolve as new technologies are developed and landscape change occurs over time. As a result, these data may become outdated and inadequate for supporting critical habitat-related work across the international boundary in the Sonoran and Mojave Deserts Bird Conservation Region (BCR 33) due to the area’s complex vegetation communities and the discontinuity in data availability across the United States (US) and Mexico (MX) border. This research aimed to produce the first 30 m continuous land cover map of BCR 33 by prototyping new methods for desert vegetation classification using the Random Forest (RF) machine learning (ML) method. The developed RF classification model utilized multitemporal Landsat 8 Operational Land Imager spectral and vegetation index data from the period of 2013–2020, and phenology metrics tailored to capture the unique growing seasons of desert vegetation. Our RF model achieved an overall classification F-score of 0.80 and an overall accuracy of 91.68%. Our results portrayed the vegetation cover at a much finer resolution than existing land cover maps from the US and MX portions of the study area, allowing for the separation and identification of smaller habitat pockets, including riparian communities, which are critically important for desert wildlife and are often misclassified or nonexistent in current maps. This early prototyping effort serves as a proof of concept for the ML and data fusion methods that will be used to generate the final high-resolution land cover map of the entire BCR 33 region.

Remote Sensing↗

USGS2023

Mapping vegetation index-derived actual evapotranspiration across croplands using the Google Earth Engine platform

Precise knowledge of crop water consumption is essential to better manage agricultural water use, particularly in regions where most countries struggle with increasing water and food insecurity. Approaches such as cloud computing and remote sensing (RS) have facilitated access, process, and visualization of big geospatial data to map and monitor crop water requirements. To find the most reliable Vegetation Index (VI)-based evapotranspiration (ETa) for croplands in drylands, we modeled and mapped ETa using empirical RS methods across the Zayandehrud river basin in Iran for two decades (2000–2019) on the Google Earth Engine platform using the Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index 2 (EVI2). Developed ET-VI products in this study comprise three NDVI-based ETa (ET-NDVI*, ET-NDVI* scaled , and ET-NDVI Kc ) and an EVI2-based ETa (ET-EVI2). We (a) applied, for the first time, the ET-NDVI* method to croplands as a crop-independent index and then compared its performance with the ET-EVI2 and crop ET, and (b) assessed the ease and feasibility of the transferability of these methods to other regions. Comparing four ET-VI products showed that annual ET-EVI2 and ET-NDVI* scaled estimations were close. ET-NDVI Kc consistently overestimated ETa. Our findings indicate that ET-EVI2 and ET-NDVI Kc were easy to parametrize and adopt to other regions, while ET-NDVI* and ET-NDVI* scaled are site-dependent and sensitive to image acquisition time. ET-EVI2 performed robustly in arid and semi-arid regions making it a better tool. Future research should further develop and confirm these findings by characterizing the accuracy of VI-based ETa over croplands in drylands by comparing them with available ETa products and examining their performance using crop-specific comparisons.

Remote Sensing↗

USGS2023

A river basin spatial model to quantitively advance understanding of riverine tree response dynamics to water availability and hydrological management

Ecological condition continues to decline in arid and semi-arid river basins globally due to hydrological over-abstraction combined with changing climatic conditions. Whilst provision of water for the environment has been a primary approach to alleviate ecological decline, how to accurately monitor changes in riverine trees at fine spatial and temporal scales, remains a substantial challenge. This is further complicated by constantly changing water availability across expansive river basins with varying climatic zones. Within, we combine rare, fine-scale, high frequency temporal in-situ field collected data with machine learning and remote sensing, to provide a robust model that enables broadscale monitoring of physiological tree water stress response to environmental changes via actual evapotranspiration (ET). Physiological variation of Eucalyptus camaldulensis (River Red Gum) and E. largiflorens (Black Box) trees across 10 study locations in the southern Murray-Darling Basin, Australia, was captured instantaneously using sap flow sensors, substantially reducing tree response lags encountered by monitoring visual canopy changes. Actual ET measurement of both species was used to bias correct a national spatial ET product where a Random Forest model was trained using continuous timeseries of in-situ data of up to four years. Precise monthly AMLETT ( A ustralia-wide M achine L earning ET for T rees) ET outputs in 30 m pixel resolution from 2012 to 2021, were derived by incorporating additional remote sensing layers such as soil moisture, land surface temperature, radiation and EVI and NDVI in the Random Forest model. Landsat and Sentinal-2 correlation results between in-situ ET and AMLETT ET returned R 2 of 0.94 (RMSE 6.63 mm period −1 ) and 0.92 (RMSE 6.89 mm period −1 ), respectively. In comparison, correlation between in-situ ET and a national ET product returned R 2 of 0.44 (RMSE 34.08 mm period −1 ) highlighting the need for bias correction to generate accurate absolute ET values. The AMLETT method presented here, enhances environmental management in river basins worldwide. Such robust broadscale monitoring can inform water accounting and importantly, assist decisions on where to prioritize water for the environment to restore and protect key ecological assets and preserve floodplain and riparian ecological function.

The Journal of Environmental Management↗