Electrical Conductivity (EC) has been used to analyze the content of dissolved salts in water. EC refers to the ability to transmit electricity (Ikeda et al. 1991). Pure water has low values of EC because the electricity is conducted by the ions in solution; therefore, the greater the concentration of ions in water, the greater the value of EC. This tutorial explains how to analyze the EC of a river using the Profile Tool plugin in QGIS 3.0.

Time series in hydrology can be analyzed to a) detect a trend due to another random hydrologic variable, b) develop and calibrate a model, c) predict future characteristics of a variable (Machiwal & Jha 2012). The application of time series analysis is diverse; for instance, it can be used to evaluate global trends of soil moisture (Dorigo et al. 2012), to analyze river discharges (Papa et al. 2012), to detect glacial lake outburst floods (Veh et al. 2018) or to detect rainfall patterns (Wang et al. 2016).

The visualization of the data variability over the time can be a useful tool to identify patterns or to compare the behavior of different samples. The use of software for Geographic Information Systems (GIS) allows to identify the location of the samples and to compile the information that the samples have. Open-source software like QGIS offers excellent tools to achieve this objective. This tutorial will explain how to use the Time Manager Plugin.

There are tools for temporal data analysis like Python, IPython and Jupyter; there are tools for spatial data analysis like QGIS. But, are there tools for spatio-temporal analysis? Unfortunately no, but there are good approaches to manage spatial data in Jupyter or to run IPython in QGIS3. These approaches aren't a complete ansqwe to the current demands of big data processing in few computational time with simple scripts, but by sure it will help to shape better solutions.

The new version of QGIS is QGIS3 and it runs with Python 3 which introduces some change on the interaction with webservers with package “requests”. For those that are new to the IMERG images, those are some kind of the new TRMM images with precipitation estimation from multiple passive microwave (PMW) sensors on various precipitation-relevant satellites starting in March 2014. The IMERG images have a pixel resolution of 0.1 degrees and a temporal scale of 30 minutes; on the current panorama of precipitation estimates based on satellite-gauge, the IMERG data product with the highest spatial and temporal resolution available over the last 4 years.

There are new available tools and resources to understand climate change, land use dynamics, water cycle and other parts of our physical environment. Many spatial data come on raster format and are available on web servers, those servers have a image register every year, every month, every day, hour, half hour or minute. If we want to assess a physical phenomena we have to be able to analyze large set of data.

LocClim is a software developed by the Agrometeorology Group of the Food and Agriculture Organization of the United Nations. The software provides an estimate of climatic conditions at different location regardless of the availability of observations. This software is of great importance if you want to know the climatic conditions of certain location and you do not have available observation points. It is possible to modify the stations that provide the data, so you can control the accuracy of the estimates. This tutorial demonstrates how to download the New LocClim software, how to find a location and how to export the resulting data.

Sentinel-2 carries an innovative wide swath high-resolution multispectral imager with 13 spectral bands (443–2190 nm) (European Space Agency). Sentinel images have a swath width of 290 km and a spatial resolution of 10 m (four visible and near-infrared bands), 20 m (six red edge and shortwave infrared bands) and 60 m (three atmospheric correction bands) (Satellite Imaging Coorporation).The images are very powerful and are of great relevance for land and water management because analyses can be done from the spectral bands, natural color and false color image can be visualized and spectral indices can be obtained. Therefore, downloading them for free is an incredible opportunity for scientists and analysts to meet their goals. This tutorial demonstrates how to download and preprocess Sentinel 2 images using the Semi-Classification Plugin in QGIS 3.0. In addition, how to install the plugin is explained.

Presenting Geographic Information Systems (GIS) is of great importance to transmit the correct ideas of the analyzed information. QGIS 3.0 is a powerful software to design and present maps. GIS can contain diverse and vast information; however, the analyst should decide what to present and how to present it. Therefore, labelling is a skill that must be developed when creating maps. This tutorial shows how to clip features to the shape of the study area and how to label the features of interest. The study area is a basin within the state of Tlaxcala, Mexico and it has a channel network shapefile and points with the name of the channel network features. The explanation includes how to create an expression to label the features using conditionals and how to change the style of the labels using QGIS 3.0.

A basin is defined as a topographic region in which all water drains to a common area. Identifying basins within a study area can be beneficial for land and water management because priority areas can be defined and the hydrology of the area can be visualized. Delimiting a basin can be done by using Geographic Information Systems such as QGIS and SAGA GIS. To do so, a Digital Elevation Model (DEM) is required since the drainage network is determined by the elevation and slope of the terrain. This tutorial demonstrates how to reproject a DEM raster in QGIS, how to fill the sinks of a DEM, to calculate flow accumulation, to obtain the channel network and the basin limits with SAGA GIS based on the DEM using the Upslope Area interactive tool.

The terrain properties of a study area are of great importance due to the vast information they provide for water and land management. The elevation values can be obtained by advanced spaceborn techniques such as the use of remote sensing from satellites. On June 29, 2009, NASA and the Ministry of Economy, Trade, and Industry (METI) of Japan released a Global Digital Elevation Model (GDEM) to users worldwide at no charge as a contribution to the Global Earth Observing System of Systems (METI and NASA, 2011). This tutorial is a demonstration of how to download a Digital Elevation Model (DEM) from the ADVANCED SPACEBORNE THERMAL EMISSION AND REFLECTION RADIOMETER (ASTER) Version 2. In addition, how to merge two DEM rasters and how to change the style of them in QGIS 2.15 will be shown.