@article{faraji2018electrospray, title={Electrospray Characteristics of Aqueous KCl Solutions with Various Electrical Conductivities}, author={Faraji, Sahand and Sadri, Behnam and Hokmabad, Babak Vajdi and Esmaeilzadeh, Esmaeil and Jadidoleslam, Navid}, year={2018}, publisher={engrXiv} } @article{Jadidoleslam2021a, author = {Jadidoleslam, Navid and Hornbuckle, Brian K. and Krajewski, Witold and Mantilla, Ricardo and Cosh, Michael}, doi = {10.1109/jstars.2021.3131133}, issn = {1939-1404}, journal = {IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing}, month = {nov}, pages = {1--1}, publisher = {Institute of Electrical and Electronics Engineers (IEEE)}, title = {{Analyzing Effects of Crops on SMAP Satellite-based Soil Moisture using a Rainfall-Runoff Model in the U.S. Corn Belt}}, year = {2021}, url = {}, } @article{Ghimire2021, author = {Ghimire, Ganesh R. and Jadidoleslam, Navid and Goska, Radoslaw and Krajewski, Witold F.}, doi = {10.1016/j.jhydrol.2021.126683}, issn = {00221694}, journal = {Journal of Hydrology}, month = {jul}, pages = {126683}, title = {Insights into Storm Direction Effect on Flood Response}, url = {}, year = {2021} }

@article{jadidoleslam2016wave, title={Wave Power Potential Assessment of Aegean Sea with an Integrated 15-year Data}, author={Jadidoleslam, Navid and Ozger, Mehmet and Agiralioglu, Necati}, journal={Renewable energy}, volume={86}, pages={1045--1059}, year={2016}, publisher={Pergamon} }

@inproceedings{eseller2016numerical, title={Numerical Modelling of Liquefaction Tests of Fully Saturated Sands in CSSLB}, author={Eseller-Bayat, E and Nateghi, Ataollah and Viand, AS and Jadidoleslam, N}, booktitle={4 th International Conference on New Developments in Soil Mechanics and Geotechnical Engineering, Near East University, Nicosia, North Cyprus}, year={2016} }

@article{faraji2017experimental, title={Experimental Study on the Role of Electrical Conductivity in Pulsating Modes of Electrospraying}, author={Faraji, S and Sadri, B and Hokmabad, B Vajdi and Jadidoleslam, N and Esmaeilzadeh, E}, journal={Experimental Thermal and Fluid Science}, volume={81}, pages={327--335}, year={2017}, publisher={Elsevier} }

@article{jadidoleslam2019data, title={Data-driven Stochastic Model for Basin and Sub-grid Variability of SMAP Satellite Soil moisture}, author={Jadidoleslam, Navid and Mantilla, Ricardo and Krajewski, Witold F and Cosh, Michael H}, journal={Journal of Hydrology}, volume={576}, pages={85--97}, year={2019}, publisher={Elsevier} }

@article{jadidoleslam2019investigating, title={Investigating the Role of Antecedent SMAP Satellite Soil moisture, Radar Rainfall and MODIS Vegetation on Runoff Production in an Agricultural Region}, author={Jadidoleslam, Navid and Mantilla, Ricardo and Krajewski, Witold F and Goska, Radoslaw}, journal={Journal of Hydrology}, volume={579}, pages={124210}, year={2019}, publisher={Elsevier} }

@inproceedings{jadidoleslam2017using, title={Using SMAP Data to Investigate the Role of Soil Moisture Variability on Realtime Flood Forecasting}, author={Jadidoleslam, Navid and Krajewski, Witold F and Mantilla, Ricardo}, booktitle={2017 AGU Fall Meeting}, year={2017}, organization={AGU} }

@article{Jadidoleslam2020, abstract = {The authors developed a non-proprietary web-browser based open-source software that allows users to visualize and evaluate hydrologic space-time data in an interactive environment. Hydrovise is client-side browser-based software that interprets a configuration file to construct control elements in the Graphical User Interface for visualizations of space-time data and model simulation evaluations. It leverages the concept of three-dimensional data cubes that facilitate query in space, time, and variable dimension(s) without the requirement for a database system. Using a configuration file, users can define data sources as local file system resources and or external data sources (e.g., online data services). This capability makes Hydrovise a flexible and portable solution where users can share their hydrologic data in an interactive web environment. This paper provides the software description with four distinct example use cases including, but not limited to, time-series data visualization and evaluation, grid-based and river network-based data visualizations.}, author = {Jadidoleslam, Navid and Goska, Radoslaw and Mantilla, Ricardo and Krajewski, Witold F.}, doi = {10.1016/j.envsoft.2020.104853}, issn = {13648152}, journal = {Environmental Modelling and Software}, keywords = {Data management,Environmental science,Evaluation,Hydrology,Web application}, pages = {104853}, publisher = {Elsevier Ltd}, title = {{Hydrovise: A Non-proprietary Open-source Software for Hydrologic Model and Data Visualization and Evaluation}}, url = {}, volume = {134}, year = {2020} }

@inproceedings{jadidoleslam2019exploring, title={Exploring Application of Satellite-based Soil Moisture in Streamflow Predictions}, author={Jadidoleslam, Navid and Mantilla, Ricardo and Krajewski, Witold F}, booktitle={2019 AGU Fall Meeting}, year={2019}, organization={AGU} }

@article{Ghimire2020, abstract = {Streamflow is a dynamical process that integrates water movement in space and time within basin boundaries. The authors characterize the dynamics associated with streamflow time series data from about seventy-one U.S. Geological Survey (USGS) stream-gauge stations in the state of Iowa. They employ a novel approach called visibility graph (VG). It uses the concept of mapping time series into complex networks to investigate the time evolutionary behavior of dynamical system. The authors focus on a simple variant of VG algorithm called horizontal visibility graph (HVG). The tracking of dynamics and hence, the predictability of streamflow processes, are carried out by extracting two key pieces of information called characteristic exponent, {{}\(\backslash\)lambda{}} of degree distribution and global clustering coefficient, GC pertaining to HVG derived network. The authors use these two measures to identify whether streamflow process has its origin in random or chaotic processes. They show that the characterization of streamflow dynamics is sensitive to data attributes. Through a systematic and comprehensive analysis, the authors illustrate that streamflow dynamics characterization is sensitive to the normalization, and the time-scale of streamflow time-series. At daily scale, streamflow at all stations used in the analysis, reveals randomness with strong spatial scale (basin size) dependence. This has implications for predictability of streamflow and floods. The authors demonstrate that dynamics transition through potentially chaotic to randomly correlated process as the averaging time-scale increases. Finally, the temporal trends of {{}\(\backslash\)lambda{}} and GC are statistically significant at about 40{\%} of the total number of stations analyzed. Attributing this trend to factors such as changing climate or land use requires further research.}, archivePrefix = {arXiv}, arxivId = {1912.03343}, author = {Ghimire, Ganesh R and Jadidoleslam, Navid and Krajewski, Witold F. and Tsonis, Anastasios A.}, doi = {10.3389/frwa.2020.00017}, eprint = {1912.03343}, issn = {2624-9375}, journal = {Frontiers in Water}, keywords = {Complex Network,HVG,Streamflow dynamics,Visibility graph,degree distribution}, pages = {17}, publisher = {Frontiers}, title = {Insights on Streamflow Predictability Across Scales Using Horizontal Visibility Graph Based Networks}, volume = {2}, year = {2020} }

@article{Jadidoleslam2021, author = {Jadidoleslam, Navid and Mantilla, Ricardo and Krajewski, Witold F}, doi = {10.3390/hydrology8010052}, url={}, issn = {2306-5338}, journal = {Hydrology}, keywords = {data assimilation,ensemble kalman filter,flood prediction,satellite soil moisture}, month = {mar}, number = {1}, pages = {52}, title = {{Data Assimilation of Satellite-Based Soil Moisture into a Distributed Hydrological Model for Streamflow Predictions}}, url = {}, volume = {8}, year = {2021} }

@inproceedings{ghimire2020basinrotationAGU, title={Basin Rotation Method to Quantify the Effect of Rainstorm Movement on Flood Peak Response}, author={Ghimire, Ganesh and Jadidoleslam,Navid and Goska, Radoslaw and Krajewski,Witold F}, booktitle={2020 AGU Fall Meeting}, year={2020}, organization={AGU} } @inproceedings{ghimire2021irrigationAGU, title={Quantifying Net Irrigation from SMAP Retrievals}, author={Soylu, Mehmet Evren and Jadidoleslam,Navid and Bras, Rafael L}, booktitle={2021 AGU Fall Meeting}, year={2021}, organization={AGU} } @inproceedings{ghimire2020EGU, title={Inference On Streamflow Predictability Using Horizontal Visibility Graph Based Networks}, author={Ghimire,Ganesh and Jadidoleslam,Navid and Krajewski,Witold F and Tsonis,Anastasios}, booktitle={EGU General Assembly}, year={2020}, organization={EGU} }