The Land IQ Data Driven Method (LDDM) was developed for determining evapotranspiration at a detailed, field-scale level for water use tracking by irrigation districts, groundwater sustainability agencies, and sub watersheds. The LDDM is used to interpret image data and leverages robust and repeated ground station data with direct image analysis. The approach can utilize a variety of image and ground data sources and yields more accurate results because ground calibration data are available. It is also less labor-intensive, less costly, and more accurate than other remote sensing methods at the refined field scale level.
The LDDM is differentiated from other models due to the following:
Primary unit of analysis is at the field scale
Integrates repeated and rigorous ground truthing environmental stations (currently 50+)
Incorporates Land IQ field level crop mapping at 97+% accuracy
Differentiates permanent crop age in the analysis process
Integrates other agronomic features of modern cropping systems
Primary Unit of Analysis
Unlike other models that start at a regional level, the LDDM begins at the field level and can be rolled up into the larger unit of analysis desired.
Rigorous Ground Truthing
The LDDM utilizes ground monitoring stations for calibration of ET analysis, as well as validation to help quantify accuracy levels. The ground monitoring stations generate hourly ET data that is correlated back to satellite imagery and used as a dependent variable in the modeling process.
Ground monitoring stations are distributed to correspond with the dominant crop types in the service area. Stations are continuously monitored via telemetered systems with alerts to detect inconsistencies in collection or outages, thus preventing the loss of data.
Highly Accurate Land Use and Agronomic Data
The LDDM utilizes the same land use data the Department of Water Resources (DWR) provides for the implementation of the Sustainable Groundwater Management Act (SGMA). These data also are provided as a deliverable with the consumed water from the same field. Thus, we can ensure consistency of acreage that is maintained between public mapping used by SGMA of an area and internal mapping.
Utilizing remote sensing technologies, statistical and temporal analysis methods, Land IQ’s spatial database of crop acreage exceeds 97% accuracy on the classification of crops. Baseline statewide crop mapping was conducted in 2014 and 2016 for the DWR, and continues with multi-cropping in 2018 and 2019. As a result, the land use drives and enhances the analysis of consumed water by the crops, is highly accurate, approved by DWR and the State of California, and forms one of the foundational elements of the accurate ET results.
Unlike other methods, the Land IQ land use data is derived from and guided by our understanding of agricultural systems, landscape processes, production systems, crop phenology and detailed ground truthing. In addition to basic land use data, the LDDM also incorporates the following data sets:
Permanent crop age
Permanent crop density
Unique field conditions, including irrigation method