ORCID Profile
0000-0001-5991-733X
Current Organisation
The University of Newcastle
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Research Topics
In Research Link Australia (RLA), "Research Topics" refer to ANZSRC FOR and SEO codes. These topics are either sourced from ANZSRC FOR and SEO codes listed in researchers' related grants or generated by a large language model (LLM) based on their publications.
Top 5 Research Topics
ANZSRC Field of Research (FoR)
Water Resources Engineering | Photogrammetry and Remote Sensing | Geomatic Engineering | Surfacewater Hydrology | Environmental Management | Environmental Engineering Modelling | Agricultural Spatial Analysis and Modelling | Civil Engineering
ANZSRC Socio-Economic Objective (SEO)
Farmland, Arable Cropland and Permanent Cropland Water Management | Land and Water Management of environments not elsewhere classified | Water Allocation and Quantification | Effects of Climate Change and Variability on Australia (excl. Social Impacts) | Weather | Rehabilitation of Degraded Fresh, Ground and Surface Water Environments |
Related Links
Publications
Revisiting the forest transition theory with historical records and geospatial data: A case study from Mississippi (USA)
Publisher: Elsevier BV
Date: 05-2013
Estimating catchment scale soil moisture at a high spatial resolution: Integrating remote sensing and machine learning
Publisher: Elsevier BV
Date: 07-2021
Improving the catchment scale wetland modeling using remotely sensed data
Publisher: Elsevier BV
Date: 12-2019
Assessing the cumulative impacts of geographically isolated wetlands on watershed hydrology using the SWAT model coupled with improved wetland modules
Publisher: Elsevier BV
Date: 10-0005
DOI: 10.1016/J.JENVMAN.2018.06.006
Abstract: Despite recognizing the importance of wetlands in the Coastal Plain of the Chesapeake Bay Watershed (CBW) in terms of ecosystem services, our understanding of wetland functions has mostly been limited to in idual wetlands and overall catchment-scale wetland functions have rarely been investigated. This study is aimed at assessing the cumulative impacts of wetlands on watershed hydrology for an agricultural watershed within the Coastal Plain of the CBW using the Soil and Water Assessment Tool (SWAT). We employed two improved wetland modules for enhanced representation of physical processes and spatial distribution of riparian wetlands (RWs) and geographically isolated wetlands (GIWs). This study focused on GIWs as their hydrological impacts on watershed hydrology are poorly understood and GIWs are poorly protected. Multiple wetland scenarios were prepared by removing all or portions of the baseline GIW condition indicated by the U.S. Fish and Wildlife Service National Wetlands Inventory geospatial dataset. We further compared the impacts of GIWs and RWs on downstream flow (i.e., streamflow at the watershed outlet). Our simulation results showed that GIWs strongly influenced downstream flow by altering water transport mechanisms in upstream areas. Loss of all GIWs reduced both water routed to GIWs and water infiltrated into the soil through the bottom of GIWs, leading to an increase in surface runoff of 9% and a decrease in groundwater flow of 7% in upstream areas. These changes resulted in increased variability of downstream flow in response to extreme flow conditions. GIW loss also induced an increase in month to month variability of downstream flow and a decrease in the baseflow contribution to streamflow. Loss of all GIWs was shown to cause a greater fluctuation of downstream flow than loss of all RWs for this study site, due to a greater total water storage capacity of GIWs. Our findings indicate that GIWs play a significant role in controlling hydrological processes in upstream areas and downstream flow and, therefore, protecting GIWs is important for enhanced hydrological resilience to extreme flow conditions in this region.
LiDAR derived terrain wetness indices to infer soil moisture above underground pipelines
Publisher: Walter de Gruyter GmbH
Date: 2020
Abstract: Corrosion of external cast-iron pipe surfaces, a major contributor to pipe failure, has been attributed to the free water in the soil surrounding the pipe. Because observation at pipe depth is difficult, a potential proxy is the soil surface moisture. Herein highly accurate elevation data derived from airborne light detection and ranging is used to model the distribution of soil water in urban catchments containing pipe infrastructure. The results are compared with local soil moisture Theta Probe measurements along the pipe. The results show potential to identify wetter spots above underground infrastructure, which may inform its corrosion potential, without digging up the asset.
Toward P-Band Passive Microwave Sensing of Soil Moisture
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-2020
Supplementary material to "Enhanced Watershed Modeling by Incorporating Remotely Sensed Evapotranspiration and Leaf Area Index"
Publisher: Copernicus GmbH
Date: 12-01-2021
Enhanced Watershed Modeling by Incorporating Remotely Sensed Evapotranspiration and Leaf Area Index
Publisher: Copernicus GmbH
Date: 12-01-2021
Abstract: Abstract. Remotely sensed evapotranspiration (RS-ET) products have been widely adopted as additional constraints on hydrologic modeling to enhance the model predictability while reducing predictive uncertainty. However, vegetation parameters, responsible for key time/space variation in evapotranspiration (ET), are often calibrated without the use of suitable constraints. Remotely sensed leaf area index (RS-LAI) products are increasingly available and provide an opportunity to assess vegetation dynamics and improve calibration of associated parameters. The goal of this study is to assess the Soil and Water Assessment Tool (SWAT) predictive uncertainty in estimates of ET using streamflow and two remotely sensed products (i.e., RS-ET and RS-LAI). We explore how the application of RS-ET and RS-LAI products contributes to 1) reducing the parameter uncertainty 2) improving the model capacity to predict the spatial distribution of ET and LAI at the sub-watershed level and 3) assessing the model predictions of ET and LAI at the basic modeling unit (i.e., the hydrologic response unit [HRU]) under the assumption that ET and LAI are related in croplands. Our results suggest that most of the parameter sets with acceptable performances for two constraints (i.e., streamflow and RS-ET 12 parameter sets) are also acceptable for three constraints (i.e., streamflow, RS-ET, and RS-LAI 11 parameter sets) at the watershed level. This finding is likely because both the ET simulation algorithm and the RS-ET products consider LAI as an input variable. Relative to the watershed-level assessment, the number of parameter sets that satisfactorily characterize spatial patterns of ET and LAI at the sub-watershed level are reduced from 11 to 6. Among the 11 parameter sets acceptable for three constraints (i.e., streamflow, RS-ET and RS-LAI) at the sub-watershed level, two parameter sets appear to provide high spatial and temporal consistency between ET and LAI at the HRU level. These results suggested that use of multiple remotely sensed products as model constraints enables model evaluations at finer scales – thereby constraining acceptable parameter sets and accurately representing the spatial characteristics of hydrologic variables. As such, this study highlights the potential of remotely sensed data to increase the predictability and utility of hydrologic models.
Effects of subsurface soil characteristics on wetland–groundwater interaction in the coastal plain of the Chesapeake Bay watershed
Publisher: Wiley
Date: 28-11-2018
DOI: 10.1002/HYP.13326
Optimizing Patterns of Land Use to Reduce Peak Runoff Flow and Nonpoint Source Pollution with an Integrated Hydrological and Land-Use Model
Publisher: American Meteorological Society
Date: 05-2004
Enhanced Watershed Modeling by Incorporating Remotely Sensed Evapotranspiration and Leaf Area Index
Publisher: Copernicus GmbH
Date: 28-06-2022
Abstract: Abstract. To improve the capacity of watershed modeling, remotely sensed products are frequently used to reduce the uncertainty resulting from data limitations. Although remotely sensed evapotranspiration (RS-ET) products are widely used, vegetation parameters governing spatial and temporal variations in evapotranspiration (ET) are often not constrained by benchmark data. Recently, remotely sensed leaf area index (RS-LAI) products are becoming increasingly available, providing an opportunity to assess and improve simulated vegetation dynamics. The objective of this study is to assess the role of the two remotely sensed products (i.e., RS-ET and RS-LAI) in improving the accuracy of watershed model predictions. Specifically, we investigated the role of RS-ET and RS-LAI products in 1) reducing parameter uncertainty and 2) improving model capacity to predict the spatial distribution of ET and LAI at the sub-watershed level. The watershed-level assessment of the degree of equifinality (denoted as the number of parameter sets that produce equally acceptable model simulations) shows that less than half of the acceptable parameter sets for two constraints (streamflow and RS-ET 14 parameter sets) are acceptable for three constraints (streamflow, RS-ET, and RS-LAI six parameter sets). Among those six parameter sets, only three can satisfactorily characterize spatial patterns of ET and LAI at the sub-watershed level. Our results suggest that the use of multiple remotely sensed datasets holds great potential to reduce parameter uncertainty and increase the credibility of watershed modeling, particularly for characterizing spatial variability of hydrologic fluxes that are relevant to agricultural management.
Estimating the effect of winter cover crops on nitrogen leaching using cost-share enrollment data, satellite remote sensing, and Soil and Water Assessment Tool (SWAT) modeling
Publisher: Soil and Water Conservation Society
Date: 2020
Assessment of Wetland Change on the Delmarva Peninsula from 1984 to 2010
Publisher: Coastal Education and Research Foundation
Date: 05-2020
Comparative analyses of hydrological responses of two adjacent watersheds to climate variability and change scenarios using SWAT model
Publisher: Copernicus GmbH
Date: 19-04-2017
Abstract: Abstract. Water quality problems in the Chesapeake Bay Watershed (CBW) are expected to exacerbate under climate variability and change. However, climate impacts on agricultural lands and resultant nutrient loads into surface water resources are largely unknown. This study evaluates the impacts of climate variability and change on two adjacent watersheds in the Coastal Plain of the CBW, using Soil and Water Assessment Tool (SWAT) model. We prepared six climate sensitive scenarios to assess the in idual effects of variations in CO2 concentration (590 and 850 ppm), precipitation increase (11 and 21 %) and temperature increase (2.9 and 5.0 °C), and considered the predicted climate change scenario using five general circulation models (GCMs) under the Special Report on Emissions Scenarios (SRES) A2 scenario. Using SWAT model simulations from 2001 to 2014, as a baseline scenario, the predicted water and nitrate budgets under climate variability and change scenarios were analyzed at multiple temporal scales. Compared to the baseline scenario, precipitation increase of 21 % and elevated CO2 concentration of 850 ppm significantly increased stream flow and nitrate loads by 50 % and 52 %, respectively, while, temperature increase of 5.0 °C reduced stream flow and nitrate loads by 12 % and 13 %, respectively. Under the climate change scenario, annual stream flow and nitrate loads showed an average increase of nearly 40 %, relative to the baseline scenario. Differences in hydrological responses observed from the two watersheds were primarily attributed to contrasting land use and soil characteristics. The watershed with larger percent croplands indicated increased nitrate yield of 0.52 kg N ha−1 compared to the one with less percent croplands under the climate change scenario, due to increased export of nitrate derived from fertilizer. The watershed dominated by poorly-drained soils showed a lower increase in nitrate yield than one dominated by well-drained soils, due to a high potential of nitrate loss in surface runoff and enhanced denitrification. To mitigate increased nitrate loads potentially caused by climate change, the enhanced implementation of conservation practices would be necessary for this region in the future. These findings assist watershed managers and regulators as they seek to establish effective adaptation strategies to mitigate water quality degradation in this region.
Assessing climate change impacts on winter cover crop nitrate uptake efficiency on the Coastal Plain of the Chesapeake Bay Watershed using SWAT model
Publisher: American Society of Agricultural and Biological Engineers
Date: 2017
Disaggregating satellite soil moisture products based on soil thermal inertia: A comparison of a downscaling model built at two spatial scales
Publisher: Elsevier BV
Date: 03-2021
Mapping landscape-level hydrological connectivity of headwater wetlands to downstream waters: A catchment modeling approach - Part 2
Publisher: Elsevier BV
Date: 02-2019
DOI: 10.1016/J.SCITOTENV.2018.11.237
Abstract: In Part 1 of this two-part manuscript series, we presented an effective assessment method for mapping inundation of geographically isolated wetlands (GIWs) and quantifying their cumulative landscape-scale hydrological connectivity with downstream waters using time series remotely sensed data (Yeo et al., 2018). This study suggested strong hydrological coupling between GIWs and downstream waters at the seasonal timescale via groundwater. This follow-on paper investigates the hydrological connectivity of GIWs with downstream waters and cumulative watershed-scale hydrological impacts over multiple time scales. Modifications were made to the representation of wetland processes within the Soil and Water Assessment Tool (SWAT). A version of SWAT with improved wetland function, SWAT-WET, was applied to Greensboro Watershed, which is located in the Mid-Atlantic Region of USA, to simulate hydrological processes over 1985-2015 under two contrasting land use scenarios (i.e., presence and absence of GIWs). Comparative analysis of simulation outputs elucidated how GIWs could influence partitioning of precipitation between evapotranspiration (ET) and terrestrial water storage, and affect water transport mechanisms and routing processes that generate streamflow. Model results showed that GIWs influenced the watershed water budget and stream flow generation processes over the long-term (30 year), inter-annual, and monthly time scales. GIWs in the study watershed increased terrestrial water storage during the wet season, and buffered the dynamics of shallow groundwater during the dry season. The inter-annual modeling analysis illustrated that densely distributed GIWs can exert strong hydrological influence on downstream waters by regulating surface water runoff, while maintaining groundwater recharge and ET under changing (wetter) climate conditions. The study findings highlight the hydrological connectivity of GIWs with downstream waters and the cumulative hydrological influence of GIWs as hydrologic sources to downstream ecosystems through different runoff processes over multiple time scales.
Mapping landscape-level hydrological connectivity of headwater wetlands to downstream waters: A geospatial modeling approach - Part 1
Publisher: Elsevier BV
Date: 02-2019
DOI: 10.1016/J.SCITOTENV.2018.11.238
Abstract: Headwater wetlands affect ecosystem integrity of downstream waters however, many wetlands - particularly geographically isolated wetlands (GIWs) - continue to be at risk. A significant portion of US federal policy is based on the jurisdictional status of wetlands, which is partly determined by the relationship between wetlands and downstream waters, including the cumulative impact of wetlands on those waters. We present a novel multi-phase geospatial modeling method to help elucidate hydrological relationship between GIWs and downstream waters at the landscape scale. The presented approach in this study used inundation maps derived from time series remotely sensed data between 1985 and 2010, weather and hydrological records, and ancillary geospatial data including information from the US Fish and Wildlife Service National Wetlands Inventory (NWI). The study site was a headwater catchment (292 km
A hierarchical optimization approach to watershed land use planning
Publisher: American Geophysical Union (AGU)
Date: 11-2007
DOI: 10.1029/2006WR005315
Impacts of Global Circulation Model (GCM) bias and WXGEN on Modeling Hydrologic Variables
Publisher: MDPI AG
Date: 12-06-2018
DOI: 10.3390/W10060764
Wetland inundation mapping and change monitoring using Landsat and airborne LiDAR data
Publisher: Elsevier BV
Date: 02-2014
Movement of Amazon surface water from time‐variable satellite gravity measurements and implications for water cycle parameters in land surface models
Publisher: American Geophysical Union (AGU)
Date: 09-2010
DOI: 10.1029/2010GC003214
Towards Soil Moisture Retrieval Using Tower-Based P-Band Radiometer Observations
Publisher: IEEE
Date: 07-2018
Multivariate data assimilation of GRACE, SMOS, SMAP measurements for improved regional soil moisture and groundwater storage estimates
Publisher: Elsevier BV
Date: 2020
Towards Multi-Frequency Soil Moisture Retrieval Using P- and L-Band Passive Microwave Sensing Technology
Publisher: IEEE
Date: 07-2018
Quantifying irrigation water use with remote sensing: Soil water deficit modelling with uncertain soil parameters
Publisher: Elsevier BV
Date: 02-2022
Topographic Metrics for Improved Mapping of Forested Wetlands
Publisher: Springer Science and Business Media LLC
Date: 12-12-2012
Seasonal drivers of geographically isolated wetland hydrology in a low-gradient, Coastal Plain landscape
Publisher: Elsevier BV
Date: 04-2020
Monitoring of wetland inundation dynamics in the Delmarva Peninsula using Landsat time-series imagery from 1985 to 2011
Publisher: Elsevier BV
Date: 03-2017
Assessing winter cover crop nutrient uptake efficiency using a water quality simulation model
Publisher: Copernicus GmbH
Date: 16-12-2014
DOI: 10.5194/HESS-18-5239-2014
Abstract: Abstract. Winter cover crops are an effective conservation management practice with potential to improve water quality. Throughout the Chesapeake Bay watershed (CBW), which is located in the mid-Atlantic US, winter cover crop use has been emphasized, and federal and state cost-share programs are available to farmers to subsidize the cost of cover crop establishment. The objective of this study was to assess the long-term effect of planting winter cover crops to improve water quality at the watershed scale (~ 50 km2) and to identify critical source areas of high nitrate export. A physically based watershed simulation model, Soil and Water Assessment Tool (SWAT), was calibrated and validated using water quality monitoring data to simulate hydrological processes and agricultural nutrient cycling over the period of 1990–2000. To accurately simulate winter cover crop biomass in relation to growing conditions, a new approach was developed to further calibrate plant growth parameters that control the leaf area development curve using multitemporal satellite-based measurements of species-specific winter cover crop performance. Multiple SWAT scenarios were developed to obtain baseline information on nitrate loading without winter cover crops and to investigate how nitrate loading could change under different winter cover crop planting scenarios, including different species, planting dates, and implementation areas. The simulation results indicate that winter cover crops have a negligible impact on the water budget but significantly reduce nitrate leaching to groundwater and delivery to the waterways. Without winter cover crops, annual nitrate loading from agricultural lands was approximately 14 kg ha−1, but decreased to 4.6–10.1 kg ha−1 with cover crops resulting in a reduction rate of 27–67% at the watershed scale. Rye was the most effective species, with a potential to reduce nitrate leaching by up to 93% with early planting at the field scale. Early planting of cover crops (~ 30 days of additional growing days) was crucial, as it lowered nitrate export by an additional ~ 2 kg ha−1 when compared to late planting scenarios. The effectiveness of cover cropping increased with increasing extent of cover crop implementation. Agricultural fields with well-drained soils and those that were more frequently used to grow corn had a higher potential for nitrate leaching and export to the waterways. This study supports the effective implementation of cover crop programs, in part by helping to target critical pollution source areas for cover crop implementation.
Improved detection of inundation below the forest canopy using normalized lidar intensity data
Publisher: MDPI AG
Date: 21-02-2020
DOI: 10.3390/RS12040707
Abstract: To best conserve wetlands and manage associated ecosystem services in the face of climate and land-use change, wetlands must be routinely monitored to assess their extent and function. Wetland extent and function are largely driven by spatial and temporal patterns in inundation and soil moisture, which to date have been challenging to map, especially within forested wetlands. The objective of this paper is to investigate the different, but often interacting effects, of evergreen vegetation and inundation on leaf-off bare earth return lidar intensity within mixed deciduous-evergreen forests in the Coastal Plain of Maryland, and to develop an inundation mapping approach that is robust in areas of varying levels of evergreen influence. This was achieved through statistical comparison of field derived metrics, and development of a simple yet robust normalization process, based on first of many, and bare earth lidar intensity returns. Results demonstrate the confounding influence of forest canopy gap fraction and inundation, and the effectiveness of the normalization process. After normalization, inundated deciduous forest could be distinguished from non-inundated evergreen forest. Inundation was mapped with an overall accuracy between 99.4% and 100%. Inundation maps created using this approach provide insights into physical processes in support of environmental decision-making, and a vital link between fine-scale physical conditions and moderate resolution satellite imagery through enhanced calibration and validation.
Assessing the Impacts of Future Climate Conditions on the Effectiveness of Winter Cover Crops in Reducing Nitrate Loads into the Chesapeake Bay Watersheds Using the SWAT Model
Publisher: American Society of Agricultural and Biological Engineers (ASABE)
Date: 2017
DOI: 10.13031/TRANS.12390
Abstract: Winter cover crops (WCCs) have been widely implemented in the Coastal Plain of the Chesapeake Bay Watershed (CBW) due to their high effectiveness in reducing nitrate loads. However, future climate conditions (FCCs) are expected to exacerbate water quality degradation in the CBW by increasing nitrate loads from agriculture. Accordingly, the question remains whether WCCs are sufficient to mitigate increased nutrient loads caused by FCCs. In this study, we assessed the impacts of FCCs on WCC nitrate reduction efficiency in the Coastal Plain of the CBW using the Soil and Water Assessment Tool (SWAT). Three FCC scenarios (2085-2098) were prepared using general circulation models (GCMs), considering three Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) greenhouse gas emission scenarios. We also developed six representative WCC implementation scenarios based on the most commonly used planting dates and species of WCCs in this region. Simulation results showed that WCC biomass increased by ~58% under FCC scenarios due to climate conditions conducive to WCC growth. Prior to implementing WCCs, annual nitrate loads increased by ~43% under FCC scenarios compared to the baseline scenario (2001-2014). When WCCs were planted, annual nitrate loads were substantially reduced by ~48%, and WCC nitrate reduction efficiency was ~5% higher under FCC scenarios relative to the baseline scenario. The increase in WCC nitrate reduction efficiency varied with FCC scenario and WCC planting method. As CO 2 concentrations were higher and winters were warmer under FCC scenarios, WCCs had greater biomass and thus demonstrated higher nitrate reduction efficiency. In response to FCC scenarios, the performance of less effective WCC practices (i.e., barley, wheat, and late planting) under the baseline scenario indicated a ~14% higher increase in nitrate reduction efficiency compared to WCC practices with greater effectiveness under the baseline scenario (i.e., rye and early planting) due to warmer temperatures. The SWAT simulation results indicated that WCCs were effective in mitigating nitrate loads accelerated by FCCs, suggesting the role of WCCs in mitigating nitrate loads will likely be even more important under FCCs. Keywords: Future climate conditions (FCCs), SWAT, Water quality, Winter cover crops (WCCs).
Improved Understanding of Suspended Sediment Transport Process Using Multi-Temporal Landsat Data: A Case Study From the Old Woman Creek Estuary (Ohio)
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 02-2014
GRACE Follow-On revealed Bangladesh was flooded early in the 2020 monsoon season due to premature soil saturation
Publisher: Proceedings of the National Academy of Sciences
Date: 16-11-2021
Abstract: We report how much water flooded Bangladesh during the 2020 wet monsoon period and explain why the 2020 monsoonal flooding started unusually early, lasted longer, and was more severe than flooding in other years. The laser-ranging instrument on GRACE Follow-On spacecraft detected the size and timing of this unusual flooding event, and we found that the 2020 flooding was worsened by soils saturated earlier than usual by a premonsoon cyclone. We highlight the importance of including the antecedent soil moisture condition in the present flood forecasting and warning practices in Bangladesh.
On the use of the GRACE normal equation of inter-satellite tracking data for estimation of soil moisture and groundwater in Australia
Publisher: Copernicus GmbH
Date: 13-03-2018
DOI: 10.5194/HESS-22-1811-2018
Abstract: Abstract. An accurate estimation of soil moisture and groundwater is essential for monitoring the availability of water supply in domestic and agricultural sectors. In order to improve the water storage estimates, previous studies assimilated terrestrial water storage variation (ΔTWS) derived from the Gravity Recovery and Climate Experiment (GRACE) into land surface models (LSMs). However, the GRACE-derived ΔTWS was generally computed from the high-level products (e.g. time-variable gravity fields, i.e. level 2, and land grid from the level 3 product). The gridded data products are subjected to several drawbacks such as signal attenuation and/or distortion caused by a posteriori filters and a lack of error covariance information. The post-processing of GRACE data might lead to the undesired alteration of the signal and its statistical property. This study uses the GRACE least-squares normal equation data to exploit the GRACE information rigorously and negate these limitations. Our approach combines GRACE's least-squares normal equation (obtained from ITSG-Grace2016 product) with the results from the Community Atmosphere Biosphere Land Exchange (CABLE) model to improve soil moisture and groundwater estimates. This study demonstrates, for the first time, an importance of using the GRACE raw data. The GRACE-combined (GC) approach is developed for optimal least-squares combination and the approach is applied to estimate the soil moisture and groundwater over 10 Australian river basins. The results are validated against the satellite soil moisture observation and the in situ groundwater data. Comparing to CABLE, we demonstrate the GC approach delivers evident improvement of water storage estimates, consistently from all basins, yielding better agreement on seasonal and inter-annual timescales. Significant improvement is found in groundwater storage while marginal improvement is observed in surface soil moisture estimates.
Improved water storage estimates within the North China Plain by assimilating GRACE data into the CABLE model
Publisher: Elsevier BV
Date: 11-2020
<i>Analyzing the impacts of a perched layer on wetland hydrology within the Coastal Plain of the Chesapeake Bay Watershed</i>
Publisher: American Society of Agricultural and Biological Engineers
Date: 2018
Global spatial optimization with hydrological systems simulation: application to land-use allocation and peak runoff minimization
Publisher: Copernicus GmbH
Date: 18-02-2010
Abstract: Abstract. A general methodology is presented to integrate complex simulation models of hydrological systems into optimization models, as an alternative to scenario-based approaches. A gradient-based hill climbing algorithm is proposed to reach locally optimal solutions from distinct starting points. The gradient of the objective function is estimated numerically with the simulation model. A statistical procedure based on the Weibull distribution is used to build a confidence interval for the global optimum. The methodology is illustrated by an application to a small watershed in Ohio, where the decision variables are related to land-use allocations and the objective is to minimize peak runoff. The results suggest that this specific runoff function is convex in terms of the land-use variables, and that the global optimum has been reached. Modeling extensions and areas for further research are discussed.
Comparative analyses of hydrological responses of two adjacent watersheds to climate variability and change using the SWAT model
Publisher: Copernicus GmbH
Date: 25-01-2018
Abstract: Abstract. Water quality problems in the Chesapeake Bay Watershed (CBW) are expected to be exacerbated by climate variability and change. However, climate impacts on agricultural lands and resultant nutrient loads into surface water resources are largely unknown. This study evaluated the impacts of climate variability and change on two adjacent watersheds in the Coastal Plain of the CBW, using the Soil and Water Assessment Tool (SWAT) model. We prepared six climate sensitivity scenarios to assess the in idual impacts of variations in CO2 concentration (590 and 850 ppm), precipitation increase (11 and 21 %), and temperature increase (2.9 and 5.0 ∘C), based on regional general circulation model (GCM) projections. Further, we considered the ensemble of five GCM projections (2085–2098) under the Representative Concentration Pathway (RCP) 8.5 scenario to evaluate simultaneous changes in CO2, precipitation, and temperature. Using SWAT model simulations from 2001 to 2014 as a baseline scenario, predicted hydrologic outputs (water and nitrate budgets) and crop growth were analyzed. Compared to the baseline scenario, a precipitation increase of 21 % and elevated CO2 concentration of 850 ppm significantly increased streamflow and nitrate loads by 50 and 52 %, respectively, while a temperature increase of 5.0 ∘C reduced streamflow and nitrate loads by 12 and 13 %, respectively. Crop biomass increased with elevated CO2 concentrations due to enhanced radiation- and water-use efficiency, while it decreased with precipitation and temperature increases. Over the GCM ensemble mean, annual streamflow and nitrate loads showed an increase of ∼ 70 % relative to the baseline scenario, due to elevated CO2 concentrations and precipitation increase. Different hydrological responses to climate change were observed from the two watersheds, due to contrasting land use and soil characteristics. The watershed with a larger percent of croplands demonstrated a greater increased rate of 5.2 kg N ha−1 in nitrate yield relative to the watershed with a lower percent of croplands as a result of increased export of nitrate derived from fertilizer. The watershed dominated by poorly drained soils showed increased nitrate removal due do enhanced denitrification compared to the watershed dominated by well-drained soils. Our findings suggest that increased implementation of conservation practices would be necessary for this region to mitigate increased nitrate loads associated with predicted changes in future climate.
Terrain wetness indices derived from LiDAR to inform soil moisture and corrosion potential for underground infrastructure
Publisher: Elsevier BV
Date: 02-2021
Forest dynamics in Mississippi, USA: a hybrid statistical and geospatial analysis
Publisher: Springer Science and Business Media LLC
Date: 17-08-2012
An in-situ data based model to downscale radiometric satellite soil moisture products in the Upper Hunter Region of NSW, Australia
Publisher: Elsevier BV
Date: 05-2019
Assessing the suitability of the Soil Vulnerability Index (SVI) on identifying croplands vulnerable to nitrogen loss using the SWAT model
Publisher: Elsevier BV
Date: 08-2018
Dynamics of surface water storage in the Amazon inferred from measurements of inter‐satellite distance change
Publisher: American Geophysical Union (AGU)
Date: 05-2009
DOI: 10.1029/2009GL037910
Soil Moisture Retrieval Depth of P- and L-Band Radiometry: Predictions and Observations
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 08-2021
Land-Use Optimization for Controlling Peak Flow Discharge and Nonpoint Source Water Pollution
Publisher: SAGE Publications
Date: 12-2006
DOI: 10.1068/B31185
Abstract: In this paper we present and apply a modeling methodology to reduce stormwater runoff through land-use planning, in order to mitigate the impact of nonpoint source pollution. A stormwater-runoff simulation model is used to generate peak discharge pseudodata, that are inputted into a regression analysis, in which the functional relationship between peak discharge and land-use variables is approximated as a quadratic function ( R 2 = 0.98). This function is then used in an optimization model to allocate future land uses (urban, conservation, and agriculture) at the subwatershed level, in a way that minimizes the resulting peak discharge at the watershed outlet. A discharge reduction of 44% is achieved, compared with the discharge resulting from the present (actual) land-use pattern. The most downstream and upstream areas are to be protected with more conservation, and most urban activities are allocated to the minimal impact subwatershed. Sensitivity analyses are performed and suggest maintaining at least 25% of the land in a conservation state, developing no more than 12% for urban purposes, and no more than 70% for agricultural purposes.
Inclusion of Riparian Wetland Module (RWM) into the SWAT Model for Assessment of Wetland Hydrological Benefits
Publisher: American Society of Agricultural and Biological Engineers
Date: 29-11-2016
The Application of CYGNSS Data for Soil Moisture and Inundation Mapping in Australia
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2021
Monitoring irrigation using landsat observations and climate data over regional scales in the Murray-Darling Basin
Publisher: Elsevier BV
Date: 11-2020
Novel Along‐Track Processing of GRACE Follow‐On Laser Ranging Measurements Found Abrupt Water Storage Increase and Land Subsidence During the 2021 March Australian Flooding
Publisher: American Geophysical Union (AGU)
Date: 11-2021
DOI: 10.1029/2021EA001941
Abstract: Following extreme drought during the 2019–2020 bushfire summer, the eastern part of Australia suffered from a week‐long intense rainfall and extensive flooding in March 2021. Understanding how much water storage changes in response to these climate extremes is critical for developing timely water management strategies. To quantify prompt water storage changes associated with the 2021 March flooding, we processed the low‐latency (1–3 days), high‐precision intersatellite laser ranging measurements from GRACE Follow‐On spacecraft and determined instantaneous gravity changes along spacecraft orbital passes. Such new data processing detected an abrupt surge of water storage approaching 60–70 trillion liters (km 3 of water) over a week in the region, which concurrently caused land subsidence of ∼5 mm measured by a network of ground GPS stations. This was the highest speed of ground water recharge ever recorded in the region over the last two decades. Compared to the condition in February 2020, the amount of recharged water was similar but the recharge speed was much faster in March 2021. While these two events together replenished the region up to ∼80% of the maximum storage over the last two decades, the wet antecedent condition of soils in 2021 was distinctly different from the dry conditions in 2020 and led to generating extensive runoff and flooding in 2021.
Improving model prediction reliability through enhanced representation of wetland soil processes and constrained model auto calibration – A paired watershed study
Publisher: Elsevier BV
Date: 10-2016
Impact of random and periodic surface roughness on P- and L-band radiometry
Publisher: Elsevier BV
Date: 02-2022
Use of multiple modules and Bayesian Model Averaging to assess structural uncertainty of catchment-scale wetland modeling in a Coastal Plain landscape
Publisher: Elsevier BV
Date: 03-2020
Impacts of Watershed Characteristics and Crop Rotations on Winter Cover Crop Nitrate-Nitrogen Uptake Capacity within Agricultural Watersheds in the Chesapeake Bay Region
Publisher: Public Library of Science (PLoS)
Date: 28-06-2016
From hillslope to catchment scale hydrologic prediction in a semi-arid region with in-situ observations, satellite soil moisture products, and a distributed catchment model
Publisher: Copernicus GmbH
Date: 23-03-2020
DOI: 10.5194/EGUSPHERE-EGU2020-21765
Abstract: & & The water-limited region frequently experiences extreme climate variability.& This region, however, has relatively little hydrological information to characterize the catchment dynamics and its feedback to the climate system. This study assesses the relative benefits of using remotely sensed soil moisture, in addition to sparsely available in-situ soil moisture and stream flow observations, to improve the hydrologic understanding and prediction.& We propose a multi-variable approach to calibrate a hydrologic model, Soil and Water Assessment Tool (SWAT), a semi-distributed, continuous catchment model, with observed streamflow and in-situ soil moisture.& The satellite& span& soil moisture products (~ 5 cm top soil) from the Soil Moisture and Ocean Salinity (SMOS) and the Soil Moisture Active Passive (SMAP) are then used to evaluate the model estimates of soil moisture over the spatial scales through time.& The results show the model calibrated against streamflow only could provide misleading prediction for soil moisture. & Long term in-situ soil moisture observations, albeit limited availability, are crucial to constrain model parameters leading to improved soil moisture prediction at the given site.& & /span& & span& Satellite soil moisture products & /span& & span& rovide useful information to assess simulated soil moisture results across the spatial domains, filling the gap on the soil moisture information at landscape scales.& /span& & span& The preliminary results from this study suggest the potential to produce robust soil moisture and streamflow estimates across scales for a semi-arid region, using a distributed catchment model with in-situ soil network and remotely sensed observations and enhance the overall water budget estimations for multiple hydrologic variables across scales.& & /span& This research is conducted on Merriwa catchment, a semi-arid region located in the Upper Hunter Region of NSW, Australia.& &
Eco-hydro-geomorphic evolution of the Sandal Divlit cinder cone, Kula, Turkey
Publisher: Copernicus GmbH
Date: 28-03-2022
DOI: 10.5194/EGUSPHERE-EGU22-12374
Abstract: & & In semi-arid ecosystems, microclimatic variations may lead to topographic asymmetry over geologic time scale due to uneven distribution of incoming solar radiation as a function of slope aspect. This phenomenon has long been recognized in geomorphology and mostly studied in catchments where may have a wide range of spatial heterogeneity in climate forcing and underlying lithology. The formation age and the size of the catchments add another level of complexity and uncertainty due to the fluctuations in prevailing climate and lithological differences in the studied catchments. However, cinder cones are natural laboratories to better understand the eco-hydro-geomorphic evolution resulted from the nonlinear interactions between vegetation, climate, and soil due to their small size, uniform lithology, well-constrained initial morphology, and relatively young age. The Sandal Divlit cinder cone located in the Kula volcanic field, western Turkey, is an inactive volcano and formed in the last stage of volcanism in the region. The climax vegetation in the primary succession following the volcanic eruption is observed on the north-facing slopes which host trees. The north-facing slopes have relatively deeper soils than south-facing slopes where host sparsely herbaceous plants and shrubs associated with thin and weakly developed soils. Airborne-LiDAR surveys and the digital elevation models having 5 m and 12.5 m spatial resolution were used to analyze the geomorphic descriptors and canopy structure of the cone as a function of aspect. The results show that north-facing slopes are steeper than south-facing ones due to better erosion protection as a result of denser vegetation. Despite its young age (& ka), the cone has developed topographic asymmetry and is imprinted with the signature of aspect-related vegetation difference. This finding is further evaluated and with the results of landscape evolution models to assess the role of microclimate due to vegetation on the development of asymmetric geomorphological features.& & & & This study has been produced benefiting from the 2232 International Fellowship for Outstanding Researchers Program of the Scientific and Technological Research Council of Turkey (TUBITAK) through grant 118C329. The financial support received from TUBITAK does not indicate that the content of the publication is approved in a scientific sense by TUBITAK.& &
A Random Forest-Based Multi-Index Classification (RaFMIC) Approach to Mapping Three-Decadal Inundation Dynamics in Dryland Wetlands Using Google Earth Engine
Publisher: MDPI AG
Date: 24-02-2023
DOI: 10.3390/RS15051263
Abstract: Australian inland riparian wetlands located east of the Great Dividing Range exhibit unique, hydroecological characteristics. These flood-dependent aquatic systems located in water-limited regions are declining rapidly due to the competitive demand for water for human activities, as well as climate change and variability. However, there exist very few reliable data to characterize inundation change conditions and quantify the impacts of the loss and deterioration of wetlands. A long-term time record of wetland inundation maps can provide a crucial baseline to monitor, assess, and assist the management and conservation of wetland ecosystems. This study presents a random forest-based multi-index classification algorithm (RaFMIC) on the Google Earth Engine (GEE) platform to efficiently construct a temporally dense, three-decadal time record of inundation maps of the southeast Australian riparian inland wetlands. The method was tested over the Macquarie Marshes located in the semiarid region of NSW, Australia. The results showed a good accuracy when compared against high-spatial resolution imagery. The total inundated area was consistent with precipitation and streamflow patterns, and the temporal dynamics of vegetation showed good agreement with the inundation maps. The inundation time record was analysed to generate inundation probability maps, which were in a good agreement with frequently flooded areas simulated by a hydrodynamic model and the distribution of flood-dependent vegetation species. The long-term, time-dense inundation maps derived from the RaFMIC method can provide key information to assess the condition and health of wetland ecosystems and have the potential to improve wetland inventory with spatially explicit water regime information. RaFMIC can be adapted over other dryland wetlands, as an effective semiautomated method of mapping long-term inundation dynamics.
Corrigendum to: “Monitoring irrigation using landsat observations and climate data over regional scales in the Murray-Darling Basin” [J. Hydrol. 590 (2020) 125356]
Publisher: Elsevier BV
Date: 05-2022
A co-evolutionary modelling framework for water-soil-vegetation interactions in Turkish semiarid landscapes for sustainable natural resources under climate change
Publisher: Copernicus GmbH
Date: 23-03-2020
DOI: 10.5194/EGUSPHERE-EGU2020-21689
Abstract: & & This multidisciplinary project investigates the implications of aridification induced by climate change and human-induced land-cover land-use change in semiarid landscapes of Turkey on erosion dynamics and landscapes patterns and morphology. Deviations from climate mean states will result in loss of vegetation productivity and soil fertility in these water-limited ecosystems and exacerbate the natural conditions in terms of natural land& #8209 cover and soil protection for natural resources sustainability. Here, we offer a comprehensive modelling framework to explore the water-soil-vegetation interactions under climate change for the following decades.& & & & Remotely& #8209 sensed vegetation indices and maps will be used to identify the regions where are prone to land& #8209 cover change under climate change. Hence, the climate projections for the 21& sup& st& /sup& century taken from CMIP6 model experiments will be used for anticipating the potential changes in ecosystem dynamics and boundaries in these water-limited ecosystems. Moreover, these climate projections will be used as forcing data in a vegetation-coupled landscape evolution model to understand how the landscape morphology and erosion dynamics interact with changing climate in Turkish arid lands. Besides erosion dynamics, the future of the unique geomorphic landscape feature of these regions, the Turkish badlands, will be investigated based on climate projections.& & & & The outcomes of this project will enhance the comprehension of the effects of geomorphic, hydrological, and ecological processes on natural resources under climate change in semiarid Turkish landscapes.& & & & & br& & br& & &
Monitoring irrigation water use over paddock scales using climate data and landsat observations
Publisher: Elsevier BV
Date: 07-2019
Ground-Based Remote Sensing of Soil Moisture Using Lower Frequency Microwave Radiometers
Publisher: IEEE
Date: 03-2019
IPEAT+: A built-in optimization and automatic calibration tool of SWAT+
Publisher: MDPI AG
Date: 14-08-2019
DOI: 10.3390/W11081681
Abstract: For almost 30 years, the Soil and Water Assessment Tool (SWAT) has been successfully implemented to address issues around various scientific subjects in the world. On the other hand, it has been reaching to the limit of potential flexibility in further development by the current structure. The new generation SWAT, dubbed SWAT+, was released recently with entirely new coding features. SWAT+ is designed to have far more advanced functions and capacities to handle challenging watershed modeling tasks for hydrologic and water quality processes. However, it is still inevitable to conduct model calibration before the SWAT+ model is applied to engineering projects and research programs. The primary goal of this study is to develop an open-source, easy-to-operate automatic calibration tool for SWAT+, dubbed IPEAT+ (Integrated Parameter Estimation and Uncertainty Analysis Tool Plus). There are four major advantages: (i) Open-source code to general users (ii) compiled and integrated directly with SWAT+ source code as a single executable (iii) supported by the SWAT developer group and, (iv) built with efficient optimization technique. The coupling work between IPEAT+ and SWAT+ is fairly simple, which can be conducted by users with minor efforts. IPEAT+ will be regularly updated with the latest SWAT+ revision. If users would like to integrate IPEAT+ with various versions of SWAT+, only few lines in the SWAT+ source code are required to be updated. IPEAT+ is the first automatic calibration tool integrated with SWAT+ source code. Users can take advantage of the tool to pursue more cutting-edge and forward-thinking scientific questions.
Supplementary material to "Enhanced Watershed Modeling by Incorporating Remotely Sensed Evapotranspiration and Leaf Area Index"
Publisher: Copernicus GmbH
Date: 28-06-2022
Quantifying Irrigation Water Use over Regional Scales with Landsat and Climate Data
Publisher: Copernicus GmbH
Date: 23-03-2020
DOI: 10.5194/EGUSPHERE-EGU2020-21255
Abstract: & & Irrigated agriculture has been identified as using approximately 72% of water globally. Australia, like many places in the world, is subject to water sharing plans that cross government boarders and are subject to a mixture of management policies. There is a pressing need to develop a method to monitor irrigation water use to aid in water resource assessments and monitoring. This paper aims to test a previously developed method which monitors irrigation water use using remotely sensed observations over the catchment scale, without the need for in-situ observations, ground data or in& #8209 depth knowledge of crops and their planting dates. Using conservative assumptions about agricultural land management practice, irrigation is calculated as Irr=AET-P. The method tests three vegetation indices derived from Landsat 5/7/8 images to calculate crop coefficients (K& sub& c& /sub& ) based on multiple published relationships. These are combined through the FAO56 methodology using gridded rainfall and two reference evapotranspiration (ET& sub& & /sub& ) products to find actual evapotranspiration as AET=ET& sub& & /sub& xK& sub& c& /sub& , providing six ET& sub& & /sub& -K& sub& c& /sub& combinations. Validation data is sourced from Irrigation Infrastructure Operators (IIO) from across the Murray-Darling Basin, Australia which are required to record irrigation water deliveries for billing purposes. The majority of these regions are in arid or semi-arid regions. Data periods used in this study range from 2003/04 to 2016/17. Results indicate this method can effectively assess irrigation water use over a range of catchment sizes from ~6,000 to ~600,000 ha. The best results returned a monthly irrigation RMSE ranging from 1.13 to 2.42 mm/month. Issues arise when regions have a designated low water allocation volume for that season (& %). The allocation percentage is a function of water storage levels, demand and forecasts. Comparisons with the Standardised Precipitation Index (SPI) and Evaporative Stress Index (ESI) show that the proposed method is robust to the rapid onset and short-term droughts. However, its performance was poor during the long term droughts with low water allocation years. The study results during these years has been predominately attributed to water stress in certain crops being undetected, agricultural managers skipping annual crop commodities as well as stock and domestic water use making up larger portions of total water use. This is a limitation of this approach, although when only comparing results in years with greater than 40% allocations, the results improved significantly showing it can monitor water use effectively. When adequate water is available, this approach is able to accurately predict irrigation water use for the sites examined.& &
A decadal record of soil moisture space–time variability over a south‐east Australian catchment
Publisher: Wiley
Date: 12-2022
DOI: 10.1002/HYP.14770
Abstract: Semi‐arid to temperate south‐east Australian catchments with agricultural landscapes demonstrate unique hydro‐climatic characteristics. Understanding the behaviour of soil moisture over such catchments and the influence of driving factors are crucial for hydrologic, climatic and agricultural applications. However, this is challenging due the complex, non‐linear relationship between these factors and soil moisture, and the lack of long‐term catchment scale data records. To address this, spatial and temporal patterns of soil moisture over two south‐east Australian river catchments (i.e., Krui and Merriwa) and the influence of soil texture, topography, vegetation and rainfall on soil moisture variability were evaluated using a decadal in‐situ dataset. This unique in‐situ soil moisture monitoring network is established over a semi‐arid to temperate catchment representing typical south‐east Australian agricultural landscape and the data record has captured some major climatic events. Time stability of catchment‐scale soil moisture and the potential of predicting catchment mean soil moisture content using one representative station were also examined using a linear regression model. Soil texture was found as the dominating factor driving the spatial variability of soil moisture in the area. The temporal patterns of soil moisture showed a positive agreement with vegetation dynamics and rainfall at topsoil layers (0–5 cm and 0–30 cm). A higher spatial variability of soil moisture was observed during dry catchment conditions compared to wet catchment conditions. The deeper soil layers (30–60 cm and 60–90 cm) showed highly stable soil moisture values, which might be the driving force of the agriculture in the area. A linear regression based prediction model demonstrated a good potential in estimating spatial mean soil moisture content from one representative station. The results are useful in parameterization of soil moisture variability in land surface, climatic and hydrologic models, agricultural applications and in remote sensing of soil moisture.
Influence of Hillslope Aspect on a Cinder Cone Evolution: The Sandal Divlit example, Kula, Turkey
Publisher: Copernicus GmbH
Date: 15-05-2023
DOI: 10.5194/EGUSPHERE-EGU23-15745
Abstract: Microclimatic variations in semi-arid ecosystems can cause topographic asymmetry over geologic time scales due to uneven distribution of incoming solar radiation as a function of slope aspect. This phenomenon has long been recognized in geomorphology and has been studied primarily in catchments with high spatial heterogeneity in climate forcing and underlying lithology. Due to fluctuations in prevailing climate and lithological differences in the studied catchments, the formation age and size of the catchments add another level of complexity and uncertainty. Due to their small size, uniform lithology, well-constrained initial morphology, and relatively young age, cinder cones are natural laboratories for better understanding the eco-hydro-geomorphic evolution caused by nonlinear interactions between vegetation, climate, and soil. The Sandal Divlit cinder cone located in the Kula volcanic field, western Turkey, is an inactive volcano and formed in the last stage of volcanism in the region. The climax vegetation in the primary succession following the volcanic eruption can be seen on north-facing slopes with trees. North-facing slopes have deeper soils than south-facing slopes, which have sparsely herbaceous plants and shrubs and thin, weakly developed soils. Airborne-LiDAR surveys and the digital elevation models having 5 m and 12.5 m spatial resolution were used to analyze the geomorphic descriptors and canopy structure of the cone as a function of aspect. In the summer and winter seasons, the surface temperatures of the cone were measured using a thermal-imaging drone. The results show that north-facing slopes are much cooler and have less evaporative demand than south-facing ones. As a result of denser vegetation attributed to relatively more available soil moisture, they are steeper than south-facing ones due to better erosion protection. Despite its young age ( ka), the cone has developed topographic asymmetry and is imprinted with the signature of aspect-related vegetation difference. This finding is further evaluated and with the results of landscape evolution models to assess the role of microclimate due to vegetation on the development of asymmetric geomorphological features.This study has been produced benefiting from the 2232 International Fellowship for Outstanding Researchers Program of the Scientific and Technological Research Council of Turkey (TUBITAK) through grant 118C329. The financial support received from TUBITAK does not indicate that the content of the publication is approved in a scientific sense by TUBITAK.
Evaluation of the tau-omega model over bare and wheat-covered flat and periodic soil surfaces at P- and L-band
Publisher: Elsevier BV
Date: 05-2022
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