Publication

Peer-Reviewed Papers

* UG: undergraduate student under my (co)supervision; * PG: postgraduate student under my (co)supervision

SCI(E)

Yoo, S., Kim, S., & Paik, K. (2024). Optimal combinations of global evapotranspiration and terrestrial water storage products for catchment water balance. International Journal of Remote Sensing, 45(9), 2865-2892.
Liu, S., Kim, S., Glamore, W., Tamburic, B., & Johnson, F. (2024). Remote sensing of water colour in small southeastern Australian waterbodies. Journal of Environmental Management, 352, 120096.
Zhang, R., Kim, S., Kim, H., Fang, B., Sharma, A., & Lakshmi, V. (2023). Temporal Gap‐Filling of 12‐Hourly SMAP Soil Moisture Over the CONUS Using Water Balance Budgeting, Water Resources Research, 59(12), e2023WR034457
Visser, J., Kim, S., Wasko, C., Nathan, R., & Sharma, A. (2022) The impact of climate change on operational estimates of Probable Maximum Precipitation, Water Resources Research, 58(11), e2022WR032247
He, W.[UG], Kim, S., Wasko, C., & Sharma, A. (2022). A global assessment of change in flood volume with surface air temperature, Advances in Water Resources, 165, 104241
Lee, S., Kim, S., & Moon, S. (2022). Development of Car-free Street Mapping (CfSM) Model using an Integrated System with Unmanned Aerial Vehicle, Aerial Mapping Camera and Deep Learning Algorithm. Journal of Computing in Civil Engineering, 36(3), 04022003
Kim, S., Sharma, A., Liu, Y., & Young, S.I. (2022). Rethinking Satellite Data Merging: From Averaging to SNR Optimization. IEEE Transactions on Geoscience and Remote Sensing, 60, 1-15
Yoon, H.N., Marshall, L., Sharma, A., & Kim, S. (2022). Bayesian model calibration using surrogate streamflow in ungauged catchments. Water Resources Research, 58(1), e2021WR031287
Kim, S., Sharma, A., Wasko, C., & Nathan R. (2022). Linking total precipitable water to precipitation extremes globally. Earth’s Future, 10(2), e2021EF002473
Kim, S.[PG], Mehrotra, R., Kim, S., & Sharma, A. (2021). Assessing countermeasure effectiveness in controlling cyanobacterial exceedance in riverine systems using probabilistic forecasting alternatives. Journal of Water Resources Planning and Management, 147(10), 04021062
Kim, S.[PG], Mehrotra, R., Kim, S., & Sharma, A. (2021). Probabilistic forecasting of cyanobacterial concentration in riverine systems using environmental drivers. Journal of Hydrology, 593, 125626.
Kim, S., Anabalon, A., & Sharma, A. (2021). An Assessment of Concurrency in Evapotranspiration Trends Across Multiple Global Datasets. Journal of Hydrometeorology, 22(1), 231-244.
Zhang, R.[PG], Kim, S., Sharma, A., & Lakshmi, V. (2021). Identifying relative strengths of SMAP, SMOS-IC, and ASCAT to capture temporal variability. Remote Sensing of Environment, 252, 112126.
Kim, S., Pham, H., Liu, Y., Marshall, L. & Sharma, A. (2020). Improving the combination of satellite soil moisture datasets by considering error cross-correlation: A comparison between triple collocation (TC) and extended double instrumental variable (EIVD) alternatives. IEEE Transactions on Geoscience and Remote Sensing, 59(9), 7285-7295
Kim, S., Ajami, H., & Sharma, A. (2020). Using Remotely Sensed Information to Improve Vegetation Parameterization in a Semi-Distributed Hydrological Model (SMART) for Upland Catchments in Australia. Remote Sensing, 12(18), 3051.
Magan, B.[UG], Kim, S., Wasko, C., Barbero, R., Moron, V., Nathan, R., & Sharma, A. (2020). Impact of atmospheric circulation on the rainfall-temperature relationship in Australia. Environmental Research Letters, 15(9), 094098.
Kim, S., Eghdamirad, S., Sharma, A., & Kim, J. H. (2020). Quantification of uncertainty in projections of extreme daily precipitation. Earth and Space Science, 7(8), e2019EA001052.
Hagan, D.F.T., Wang, G., Kim, S., Parinussa, R.M., Liu, Y., Ullah, W., Bhatti, A.S., Ma, X., Jiang, T. and Su, B., 2020. Maximizing temporal correlations in long-term global satellite soil moisture data-merging. Remote Sensing, 12(13), 2164.
Kim, S.[PG], Kim, S., Mehrotra, R., & Sharma, A. (2020). Predicting cyanobacteria occurrence using climatological and environmental controls. Water Research, 115639.
Kim, T., Ley, M. T., Kang, S., Davis, J. M., Kim, S., & Amrollahi, P. (2020). Using particle composition of fly ash to predict concrete strength and electrical resistivity. Cement and Concrete Composites, 107, 103493.
Pham, H. T., Kim, S., Marshall, L., & Johnson, F. (2019). Using 3D robust smoothing to fill land surface temperature gaps at the continental scale. International Journal of Applied Earth Observation and Geoinformation, 82, 101879.
Kim, S., Jun, H. D., Yoo, D. G., & Kim, J. H. (2019). A framework for improving reliability of water distribution systems based on a segment-based minimum cut-set approach. Water, 11(7), 1524.
Zhang, R.[PG], Kim, S., & Sharma, A. (2019). A comprehensive validation of the SMAP Enhanced Level-3 Soil Moisture product using ground measurements over varied climates and landscapes. Remote Sensing of Environment, 223, 82-94.
Kim, S., & Sharma, A. (2019). The role of floodplain topography in deriving basin discharge using passive microwave remote sensing. Water Resources Research, 55(2), 1707-1716.
Khan, U., Ajami, H., Tuteja, N. K., Sharma, A., & Kim, S. (2018). Catchment scale simulations of soil moisture dynamics using an equivalent cross-section based hydrological modelling approach. Journal of Hydrology, 564, 944-966.
Kim, S., Paik, K., Johnson, F. M., & Sharma, A. (2018). Building a flood-warning framework for ungauged locations using low resolution, open-access remotely sensed surface soil moisture, precipitation, soil, and topographic information. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 11(2), 375-387.
Kim, S., Balakrishnan, K., Liu, Y., Johnson, F., & Sharma, A. (2017). Spatial disaggregation of coarse soil moisture data by using high-resolution remotely sensed vegetation products. IEEE Geoscience and Remote Sensing Letters, 14(9), 1604-1608.
Kim, S., Parinussa, R. M., Liu, Y. Y., Johnson, F. M., & Sharma, A. (2016). Merging alternate remotely-sensed soil moisture retrievals using a non-static model combination approach. Remote Sensing, 8(6), 518.
Kim, S., Parinussa, R. M., Liu, Y. Y., Johnson, F. M., & Sharma, A. (2015). A framework for combining multiple soil moisture retrievals based on maximizing temporal correlation. Geophysical Research Letters, 42(16), 6662-6670.
Kim, S., Liu, Y. Y., Johnson, F. M., Parinussa, R. M., & Sharma, A. (2015). A global comparison of alternate AMSR2 soil moisture products: Why do they differ? Remote Sensing of Environment, 161, 43-62.

Others

Tie, J.[UG], Kim, S., & Sharma, A. (2023). How does increasing temperature affect the sub-annual distribution of monthly rainfall? Environmental Research: Climate, 2(1), 015004.
Kim, S., Dong, J., & Sharma, A. (2021). A triple collocation-based comparison of three L-band soil moisture datasets, SMAP, SMOS-IC, and SMOS, over varied climates and land covers. Frontiers in Water, 3, 64
Moradi, S., Agostino, A., Gandomkar, Z., Kim, S., Hamilton, L., Sharma, A., Henderson, R. & Leslie, G. (2020). Quantifying natural organic matter concentration in water from climatological parameters using different machine learning algorithms. h2oj, 3(1), 328-342.
Kim, S., Zhang, R.[PG], Pham, H., & Sharma, A. (2019). A Review of Satellite-Derived Soil Moisture and Its Usage for Flood Estimation. Remote Sensing in Earth Systems Sciences, 2(4), 225-246.
Silva, A., Subasinghe, K., Rajapaksha, C., Raveenthiran, K., Kim, S. H., Young, M., ... & Araki, S. (2016). Assessment of Design Alternation via 2D Physical Modelling in the Main Breakwater of Colombo Port Expansion Project. Journal of Japan Society of Civil Engineers, Ser. B2 (Coastal Engineering), 72(2), I_1129-I_1134.
Young, M., Hayman-Joyce, J., & Kim, S. (2012). Use of single layer concrete armour units as toe reinforcement. In Proceeding of International Conference on Coastal Engineering (pp. 48-59).

Domestic

Jun, H. D., Kim, S., Yoo, D. G., & Kim, J. H. (2009). Evaluation of the reliability improvement of a water distribution system by changing pipe. Journal of Korea Water Resources Association, 42(6), 505-511.

Conference Presentation (Selected)

Kim, S., Lee, G. & Sharma, A. Evaluating the impact of rainfall duration on the relationship between atmospheric moisture and extreme precipitation, MODSIM 2023, Darwin, Australia
Kim, S., Sharma, A., Wasko, C., & Nathan, R. How does total precipitable water link to precipitation extremes?, MODSIM 2021, Sydney, Australia
Kim, S., Zhang, R., Sharma, A., & Lakshmi, V. Improvements of satellite observations through data merging: status and challenges, AGU fall meeting 2020, San Francisco, CA, USA
Kim, S., Pham, H., Liu, Y., Sharma, A., & Marshall, L. Combining geophysical variables for maximizing temporal correlation without reference data, MODSIM 2019, Canberra, Australia
Kim, S. [Invited], Guo, Y., Wasko, C., & Sharma, A. On soil moisture, rain and flood extremes in a warming climate – using satellite remote sensing to define future antecedent conditions, KSCC 2018, Jeju, Republic of Korea
Kim, S., Ajami, H., & Sharma, A. Incorporating an operational satellite-derived leaf area index into a computationally efficient semi-distributed hydrologic modelling application (SMART), MODSIM 2017, Hobart, Australia
Kim, S., Liu, Y., Johnson, F., & Sharma, A. A temporal correlation-based approach for spatial disaggregation of remotely sensed soil moisture, AGU fall meeting 2016, San Francisco, CA, USA
Kim, S., Liu, Y., Johnson, F., Parinussa, R., & Sharma, A. Reducing Structural Uncertainty in AMSR2 Soil Moisture Using a Model Combination Approach, AGU fall meeting 2014, San Francisco, CA, USA
Kim, S., Liu, Y., Johnson, F., Parinussa, R., & Sharma, A. Improvement of Soil Moisture Dataset Combining AMSR2 Soil Moisture Products, OzEWEX 2014, Canberra, ACT, Australia