Big data, known as the exponential growth and availability of data, is becoming the new trending topic in agriculture. Adasa will be shortly presenting a paper about Big Data, Analytics and Business Intelligence at the 2016 Irrigation Australian International Conference held in Melbourne between the 24th and 26th of May. Also, over the last few months, we also have introduced this new field of study in our Rural Water Intelligence Blog with the example of the NFF (National Farmers Federation) in Australia.
Environmental sciences are quickly growing on the amount of new data available both dimensionally and spatially. Most importantly, this environmental data is also fast improving in its quality and resolution which facilitates the implementation of complex algorithms to analyse patterns, make predictions and quantify uncertainties.
Here are 5 applications of Big Data Analysis for hydrological purposes:
1. Expected Runoff and Storage Opportunities
Weather data is possibly one of the largest datasets available in history, and predictive models of rainfall have already existed for many years. This long term know-how of meteorological data contributes to the ability of performing multiple-day weather forecasts which can be used in hydrology to develop models to estimate expected runoff and to improve water storage opportunities.
2. Calculation and Prediction of Field Evapotranspiration
Remote sensing is a powerful tool based on the interpretation of satellite imagery that can be used, for instance, to evaluate field evapotranspiration. Better resolution images combined with enhanced statistical algorithms facilitate the analysis of water losses through evapotranspiration even at a property scale.
3. Expected Water Demands
Remote sensing can also be used to calculate expected water demands by farmers. Crop development is obtained through photo interpretation of satellite imagery and correlation of this data with historical water demands and meteorological forecasts can provide the means to determine the volume of water needed for irrigation and other purposes.
4. Water Losses
Soil data type, meteorological conditions or crop-related data can be used to calculate total water losses from infiltration and evaporation in the irrigation scheme.
5. Water Quality
Although water supply is the focus of irrigating corporations, water quality in drain systems is also a key issue for sustainable rural development. Patterns of chemical, physical and biological quality parameters can be obtained through the analysis of historical recorded data. These analyses, in turn, could be used to forecast water quality under several management scenarios.