Dongryeol Ryu

University of Melbourne | MSD · Department of Infrastructure Engineering

Water temperature is a critical factor for aquatic ecosystems, influencing both chemical and biological processes, such as fish growth and mortality; consequently, river and lake ecosystems are sensitive to climate change (CC). Currently proposed CC scenarios indicate that air temperature for the Mediterranean Jucar River will increase higher in su...

While the impacts of climate change on global food security have been studied extensively, the capability of emerging tools that couple land surface processes and crop growth in reproducing inter‐annual yield variability at regional scale remains to be tested rigorously. In this study, we analyzed the effects of weather variations between years (19...

Benchmarking is an effective management tool to improve irrigation performance through comparison with other irrigation management units; however, its application is often limited by the data available to support the analysis. This study developed a benchmarking system that reduces reliance on local data by using satellite-based estimates and quant...

Farm-level seasonal irrigation water usage is often highly variable across time and space in an irrigation district. Identifying the driving factors of this variation can help researchers and managers understand the underlying efficiency of water usage, identify the sources of water waste and develop best irrigation practices to facilitate the deve...

Terrestrial Water Storage (TWS) changes have been estimated at basin to continental scales from gravity variations using data from the Gravity Recovery and Climate Experiment (GRACE) satellites since 2002. The relatively low spatial resolution (∼300 km) of GRACE observations has been a main limitation in such studies. Various data processing strate...

Accurately monitoring Canopy Nitrogen Concentration (CNC) is a prerequisite for precision nitrogen (N) fertiliser management at the farm scale with carbon and N budgeting across the landscape and ecosystems. While many spectral indices have been proposed for CNC monitoring, their applicability and accuracy are often adversely affected by confoundin...

Long-range weather forecasts provide predictions of atmospheric, ocean and land surface conditions that can potentially be used in land surface and hydrological models to predict the water and energy status of the land surface or in crop growth models to predict yield for water resources or agricultural planning. However, the coarse spatial and tem...

For over a century, numerous proposals for increasing available water in central Australia have been raised, inspired in part by the natural occurrence of the ephemeral lake, Kati Thanda‐Lake Eyre. It has also been proposed that additional rainfall generated by the lake would spread beyond the lake itself, potentially opening up large tracts of unc...

In-season crop type mapping can assist in early yield estimation, however, such data are not widely available. Currently available crop type maps mostly rely on either optical imagery or synthetic aperture radar (SAR), but there is a growing number of research that demonstrates the potential of synergistic optical and SAR data fusion. This research...

Agricultural field boundary information is an essential input for precision agriculture. This paper proposes a Multi-scale Multi-task Boundary Detection Deep Learning (DL) Network (MMBDNet) based on spatial attention mechanisms to delineate agricultural fields using high-resolution optical satellite imagery. The designed DL architecture simultaneou...

Irrigation accounts for ~70% of global freshwater withdrawals and ~90% of consumptive water use, driving myriad Earth system impacts. In this Review, we summarize how irrigation currently impacts key components of the Earth system. Estimates suggest that more than 3.6 million km2 of currently irrigated land, with hot spots in the intensively cultiv...

Climate model estimates show significant groundwater depletion during the 20th century, consistent with global mean sea level (GMSL) budget analysis. However, prior to the Argo float era, in the early 2000’s, there is little information about steric sea level contributions to GMSL, making the role of groundwater depletion in this period less certai...

Deriving evapotranspiration is crucial for determining the water requirements of crops and for efficiently allocating water resources for irrigation. Various experiments and methods have proven that earth observation (EO) is a useful tool for estimating evapotranspiration and supporting irrigation and water resource management at different scales....

As the fundamental regulator of energy exchange in the vegetation–soil–atmosphere circulation system, soil moisture is a key parameter for drought monitoring and is indispensable to the land surface hydrological processes. In order to overcome the constraints of the Perpendicular Drought Index, PDI (performs poorly over the fields with dense vegeta...

Within-season crop classification using multispectral imagery is an effective way to generate timely crop maps that can support water and crop management; however, developing such models is challenging due to limited satellite imagery and ground truth data available during the season. This study investigated ways to optimize the use of multi-year s...

To accurately project future water availability under a drying climate, it is important to understand how precipitation is partitioned into other terrestrial water balance components, such as fluxes (evaporation, transpiration, runoff) and changes in storage (soil moisture, groundwater). Many studies have reported unexpected large runoff reductions...

A multispectral camera records image data in various wavelengths across the electromagnetic spectrum to acquire additional information that a conventional camera fails to capture. With the advent of high-resolution image sensors and color filter technologies, multispectral imagers in the visible wavelengths have become popular with increasing comme...

In this work, we demonstrate a low-cost multispectral thermal sensor system composed of plasmonic imaging filters integrated with an uncooled monochrome thermal sensor and associated deep imaging methods.

Long-range weather forecasts provide predictions of atmospheric, ocean and land surface conditions that can potentially be used in land surface and hydrological models to predict the water and energy status of the land surface or in crop growth models to predict yield for water resources or agricultural planning. However, the coarse spatial and tem...

Real-time crop canopy nitrogen concentration (CNC) and aboveground biomass (AGB) sensing capability can enable precision agriculture with significant economic and ecological benefits. Canopy spectral response in visible near-infrared (VNIR, 400-979 nm) has been widely used to estimate CNC and AGB of canopies but is often confounded by the soil back...

Accurate specification of spatiotemporal errors of remotely sensed soil moisture (SM) data is essential for a correct assessment of their utility and optimally integrating multiple SM products or assimilating them into hydrological models. Although Triple Collocation Analysis (TCA) has been widely used to provide SM errors, the impact of rescaling...

Flood warnings provide information about the timing and magnitude of impending floods, which can help mitigate the adverse impacts of flooding. Flood forecasts are highly influenced by uncertainty associated with rainfall forecasts as well as initial catchment wetness. Event-based models are simple and parsimonious and are widely favored by practit...

Flood warnings provide information about the timing and magnitude of impending floods, which can help mitigate the adverse impacts of flooding. Flood forecasts are highly influenced by uncertainty associated with rainfall forecasts as well as initial catchment wetness. Event-based models are simple and parsimonious and are widely favored by practit...

The Millennium Drought lasted more than a decade and is notable for causing persistent shifts in the relationship between rainfall and runoff in many southeastern Australian catchments. Research to date has successfully characterised where and when shifts occurred and explored relationships with potential drivers, but a convincing physical explanat...

Irrigation cools near surface air temperature by increasing evapotranspiration from wetter soil. However, elevated evapotranspiration can also increase atmospheric albedo and enhance the local greenhouse effect via increased atmospheric water vapor. Their net effects on daily air temperature remains controversial. Here we show that in several consi...

The rising price and reduced availability of irrigation water in many places around the world urge optimized irrigation practices to save water while increasing crop productivity. Benchmarking is a useful tool to compare the efficacy of different irrigation practices, to identify more efficient water use and to enhance the adoption of proven techno...

A multispectral camera records image data in various wavelengths across the electromagnetic spectrum to acquire additional information that a conventional camera fails to capture. With the advent of high-resolution image sensors and colour filter technologies, multispectral imagers in the visible wavelengths have become popular with increasing comm...

X-band KOMPSAT-5 provides a good perspective for soil moisture retrieval at high-spatial resolution over arid and semi-arid areas. In this paper, an intercomparison of KOMPSAT-5 and C-band Sentinel-1 radar data in soil moisture retrieval was conducted over agricultural fields in Wimmera, Victoria, Australia. Optical images from Sentinel-2 were also...

Irrigation water is an expensive and limited resource and optimal scheduling can boost water efficiency. Scheduling decisions often need to be made several days prior to an irrigation event, so a key aspect of irrigation scheduling is the accurate prediction of crop water use and soil water status ahead of time. This prediction relies on several ke...

The out-of-phase rainfall and temperature and deep root system make the sequential connection between past rainfall events, soil water storage, and forest growth response complicated and temporally extended in asynchronous climates with Mediterranean-type settings. Unfortunately, these location-specific deep-soil water stores are rarely measured du...

Accurate, spatially extensive, and frequent assessments of plant nitrogen (N) enabled by remote sensing allow growers to optimize fertilizer applications and reduce environmental impacts. Standard remote sensing methods for N assessment typically involve the use of chlorophyll-sensitive vegetation indices calculated from multispectral or hyperspect...

The Millennium Drought lasted more than a decade, and is notable for causing persistent shifts in the relationship between rainfall and runoff in many south-east Australian catchments. Research to date has successfully characterised where and when shifts occurred and explored relationships with potential drivers, but a convincing physical explanati...

Missing data and low data quality are common issues in field observations of actual evapotranspiration (ETa) from eddy-covariance systems, which necessitates the need for gap-filling techniques to improve data quality and utility for further analyses. A number of models have been proposed to fill temporal gaps in ETa or latent heat flux observation...

Mapping irrigated areas using remotely sensed imagery has been widely applied to support agricultural water management; however, accuracy is often compromised by the in-field heterogeneity of and interannual variability in crop conditions. This paper addresses these key issues. Two classification methods were employed to map irrigated fields using...

Skilful subseasonal forecasts are crucial for issuing early warnings of extreme weather events, such as heatwaves and floods. Operational subseasonal climate forecasts are often produced by global climate models not dissimilar to seasonal forecast models, which typically fail to reproduce observed temperature trends. In this study, we identify that...

The conventional Land Surface Temperature (LST)–Normalized Difference Vegetation Index (NDVI) trapezoid model has been widely used to retrieve vegetation water stress. However, it has two inherent limitations: (1) its complex and computationally intensive parameterization for multi-temporal observations and (2) deficiency in canopy water content in...

Accurate nitrogen (N) assessment is crucial for precise and sustainable agricultural management. Understanding crop nutrient status in a timely manner is essential to improve the efficiency of fertilizer application throughout the growing season across the entire farm. Standard remote sensing methods for N assessment are built upon empirical relati...

Remotely sensed geophysical datasets are being produced at increasingly fast rates to monitor various aspects of the Earth system in a rapidly changing world. The efficient and innovative use of these datasets to understand hydrological processes in various climatic and vegetation regimes under anthropogenic impacts has become an important challeng...

CONTEXT: Process-based crop models provide ways to predict crop growth, evaluate environmental impacts on crops, test various crop management options, and guide crop breeding. They can be used to explore options for mitigating climate change impacts when combined with climate projections and explore mitigation of environmental impacts of production...

Rainfall-runoff models are generally calibrated by using continuous stream discharge data. However, most catchments around the globe remain ungauged due to the difficulty in installing gauges in river channels with complex morphology and due to the high costs of installation and maintenance. Recently, new calibration methods that use water level da...

Standard remote sensing methods for nitrogen (N) assessment in precision agriculture rely on empirical relationships built with chlorophyll a+b (Cab) sensitive vegetation indices. Nevertheless, methods of N estimation based on the Cab vs. N relationships are strongly affected by the saturation of these indices at high N levels, and by canopy struct...

Unmanned aerial vehicle (UAV) remote sensing has become a readily usable tool for agricultural water management with high temporal and spatial resolutions. UAV-borne thermography can monitor crop water status near real-time, which enables precise irrigation scheduling based on accurate decision-making strategy. The crop water stress index (CWSI) is...

Canopy conductance, one of the key variables in simulating evapotranspiration, is strongly influenced by the physiological status of a plant and environmental factors, including photosynthetically active radiation, vapor pressure deficit, air temperature, soil moisture and so on. However, the restrictive functions used to represent these factors ra...

For managing climate variability and adapting to climate change, seasonal forecasts are widely produced to inform decision making. However, seasonal forecasts from global climate models are found to poorly reproduce temperature trends in observations. Furthermore, this problem is not addressed by existing forecast post-processing methods that are n...

Stream water quality is highly variable both across space and time. Water quality monitoring programmes have collected a large amount of data that provide a good basis for investigating the key drivers of spatial and temporal variability. Event-based water quality monitoring data in the Great Barrier Reef catchments in northern Australia provide an...

Water quality monitoring programs often collect large amounts of data with limited attention given to the assessment of the dominant drivers of spatial and temporal water quality variations at the catchment scale. This study uses a multi-model approach: a) to identify the influential catchment characteristics affecting spatial variability in water...

Knowledge about spatiotemporal error characteristics of remotely sensed soil moisture (SM) products is essential for correctly interpreting observational information and optimally assimilating them into hydrological models. This work aims to (i) investigate the relative difference between time-invariant and time-variant daily SM errors of Advanced...

There is a growing concern about water scarcity and the associated decline in Australia’sagricultural production. Efficient water use as a natural resource requires more precise and adequatemonitoring of crop water use and irrigation scheduling. Therefore, accurate estimations of evapo-transpiration (ET) at proper spatial–temporal scales are critic...

Domestic water use is one of India's primary water uses that also includes irrigation, industrial, and environmental water uses. However, there is a lack of reliable data that hinders the estimation of domestic water use in India. Previous large-scale assessments often estimated domestic water use using population alone as a predictor. Economic and...

Remotely sensed (RS) observations are becoming prevalent for hydrological model calibration in sparsely monitored regions. In this study, the parameter uncertainty associated with a hydrological model calibrated with RS evapotranspiration (ET) and soil moisture (SM) is investigated in detail using a Markov chain Monte Carlo (MCMC) approach. The dai...

Canopy nitrogen concentration (CNC) is an important crop yield regulator. Mapping CNC using hyperspectral remote sensing has the potential to markedly improve the management of economically and environmentally costly nitrogen fertiliser through rapid, non-destructive and cost-effective monitoring. One important challenge is developing robust and tr...

In precision farming, accurate estimation of canopy nitrogen concentration (CNC) is valuable for effective crop growth monitoring and nitrogen (N) fertiliser management. To date, many canopy multispectral indices have been proposed as indicators for CNC; however, many of these indices have also shown sensitivity to biomass and their performance dro...

The incorporation of a comprehensive crop module in land surface models offers the possibility to study the effect of agricultural land use and land management changes on the terrestrial water, energy, and biogeochemical cycles. It may help to improve the simulation of biogeophysical and biogeochemical processes on regional and global scales in the...

Due to the limited availability of Root-Zone Soil Moisture (RZSM) information at the regional scale, this paper explores the use of thermal infrared remote sensing to estimate RZSM in agricultural fields. This study presents the Crop Water Stress Index (CWSI) derived from thermal infrared data used as an indicator to estimate root zone soil moistur...