Satellite remote sensing has brought an unprecedented opportunity to hydrologic community. The availability of satellite data helps us understand some of the main controls on the runoff production in any region in the world. Yes! That is the power of satellite remote sensing.
In this new study, we have investigated the role of antecedent soil moisture, event-scale rainfall and vegetation on the runoff generation. Our study domain is the state of Iowa where we have used SMAP satellite data, MODIS vegetation index and radar rainfall to find the main factors that control the runoff production.
Main finding is that although there are issues with the sensitivity of L-band microwave to vegetation, still we have found a strong relationship soil moisture estimated from SMAP (Soil Moisture Active Passive) satellite data. Interestingly, we have shown that we should expect higher runoff ratios for the rainfall events with larger total rainfall depth. We combine soil moisture and rainfall into one measure so called "Soil Moisture Deficit Normalized Rainfall". We defined it as the ratio of event-scale rainfall to available space in the soil prior to intiation of the rainfall.
Well, lets say you have a bucket and you want to fill it with water. if you fill it more than the available space, then it will overflow. On the other hand, if you fill it less than the available space, then you will be able to carry it easier. Similarly, if rainfall is more than available space in the top soils, then the water will runoff. "Deficit-normalized rainfall" can help us find the total runoff. However, we save this for another day!
We finally study the annual cycles of runoff ratio and vegetation by using 17 years of data from MODIS (Moderate Resolution Imaging Spectroradiometer). We found that vegetation plays a major role in decreaseing the runoff ratio. The findings of our study can be used for hydrologic assessment of watershed management over long time periods. Also, the impact of vegetation on runoff is significant that we need to think and incorporate these dynamics in the hydrologic modeling frameworks so as to account for the dynamics of the runoff.
We estimate the soil moisture variability for basin and SMAP sub-grid using radar rainfall and soil properties.
We drive the statistical information for dry-down and wetting of soils and we use this information to estimate the spatial and temporal variability of soil moisture at the basin and satellite sub-grid. Our methods and results is useful where higher resolution soil moisture data is needed. On the other hand, we show that the variance (and standard deviation) of a bounded variable should be bounded. However, our methodology leads to an estimation of variability and skewness of soil moisture.
As there is precipitation event over the basin, the soil moisture tends to increase and the mean value increases. At the same time, standard deviation of soil moisture decreases for wetter conditions. This phase is more rapid than dry-downs and changes the state of the soils faster. I have created these a video for a demonstration of how the soil moisture distribution changes over time as the wetting and dry-down events occur.
For example, in here I am showing an animation of the soil moisture distribution over time for Turkey River basin, located in North East of State of Iowa, USA.
While satellite-based soil moisture estimations are coarse in spatial resolution, our methods could be used for estimating variability of soil moisture at a given pixel or watershed.
For more details, you can download our paper in the attachment.
This is very simple and the most straightforward flow modeling using HEC-RAS 5.0 which is capable of hydraulic modeling in 2-dimensional space. The input files are not that much accurate and you may double check it again from the technical aspect. There are different parameters that should be defined and given as input to HEC-RAS 5.0.
The screen recording was done by the Webinaria program which is a free and open source program.
The background image of the desktop is Berlin, Germany(Source ESA : http://www.esa.int/spaceinimages/content/search?SearchText=IOW&img=1?collection=&mission=&keyword=IOW&idf=+--%3E+ID&Ic=on&Vc=on&Ac=on&subm3=GO)
There are many problems that could be solved by using GIS techniques more easily. GIS could be useful in every aspect of science which deals with location and space. Hydrology,Transportation, historical map, urban design, and etc.
Everyone could need GIS knowledge in his graduate studies related to the aspects mentioned above. I want to introduce a free web-based book that could be useful for engineers, especially civil engineers. Geospatial Analysis - A comprehensive guide is a web-based GIS resource written by Dr. Michael de Smith and Prof. Paul Longley, University College London, and Prof. Mike Goodchild, UC Santa Barbara.
This book consists of different comprehensive GIS techniques. I would like to list the main topics that are covered by this book here. It could be called as a reference book for undergraduate or graduate students who have started using GIS or they want to refresh their knowledge on GIS.
You can access to the web-based version of this book for free and if you like you can purchase it from its website.
Today, I would like to introduce you HEC-RAS 5.0 which is capable of 2-dimensional modeling of hydraulic problems. This could be called a milestone for HEC-RAS program which is very popular among hydraulic engineers. The new version of HEC-RAS could be used for 2D only or combined 2D and 1D modeling. Also the RASMapper is very useful part of this program that could be used for creating the computational domain from Raster files, viewing the output data or exporting data from HEC-RAS to other GIS software. You can download the latest version of HEC-RAS from
You can download the latest version of HEC-RAS from link below:
Don't forget to read the documentation and hydraulic manual of this program before starting to work on your problem.
I have published a new article in Renewable Energy Journal of Elsevier which is an outcome of my Master's Thesis. You could refer to my article and ask any questions regarding to the wave modeling with MIKE 21 SW.
In this study, wave power atlas is generated for Aegean Sea for years from 1999 to 2013 using a third-generation spectral wave model MIKE 21 SW. Wind data was obtained from ECMWF(ERA-Interim) with 0.125◦ spatial resolution and 6 hourly temporal resolution which was then interpolated to 10 minutes interval data. Distribution plots and statistical parameters were used to evaluate the performance of the model.
Calibration results with 9 observational buoy data show high accuracy of the model. Analyses of the proposed model are done for oﬀshore in this study. Analysis in time domain is divided into 15-year, seasonal and monthly mean wave height and wave powers. For analysis in space domain, wave characteristics are calculated on 4 bands with diﬀerent widths parallel to Turkish coast. Moreover, 10 separate points were selected in diﬀerent locations of the domain to derive wave roses and scatter diagrams. Maximum wave power values occur in Winter in northern part of the Aegean Sea with more than 8 kW/m. Maximum mean wave power occurrence location changes from north to middle southern part of the study region between Crete and Kasos islands in the period of Winter to Spring season.
Abstract of this research is as below: For further information on this research you could reach to its full-text:
N. Jadidoleslam, et al., Wave power potential assessment of Aegean Sea with an integrated 15-year data, Renewable Energy (2015), http://dx.doi.org/10.1016/j.renene.2015.09.022Wave power potential assessment of Aegean Sea with an integrated 15-year data