Adaptation to climate change demands the optimal and sustainable water management in agriculture, with an inevitable focus on soil moisture conditions. In the current study we developed an ArcGIS 10.4. platform-based application (software) to model spatial and temporal changes in soil moisture in a soy field. Six SENTEK Drill & Drop soil moisture sensors were deployed in an experimental field of 4.3 hectares by the contribution of Elcom Ltd. Soil moisture measurement at each location were taken at six depths (5, 15, 25, 35, 45 and 55 cm) in 60-minute intervals. The model is capable to spatially interpolate monitored soil moisture using the technique. The time sequence change of soil moistures can be tracked by a Time Slider for both the 2D and 3D visualization. Soil moisture temporal changes can be visualized in either daily or hourly time intervals, and can be shown as a motion figure. Horizon average, maximum and minimum values of soil moisture data can be identified with the builtin tool of ArcGIS. Soil moisture spatial distribution can be obtained and plotted at any cross sections, whereas an alarm function has also been developed for tension values of 250, 1,000 and 1,500 kPa.

Studying the relationship between river water and shallow groundwater (SGW) during flood events is a research topic receiving increasing attention for many reasons. This phenomenon was studied with respect to Mohács Island of the Danube (Hungary) in an area protected by a levee. Floods only infiltrate into the island through the aquifer, where production wells for drinking water supply are located. Our objective was to reveal how the Danube and water abstraction from production wells control groundwater levels in the observation wells, and we also studied the effect of the precipitation events and the lag times of the influencing variables compared to the peak of groundwater waves in observation wells. The effects of these factors were summarized by a linear regression model (LM) with lag times. We developed an application because we had time-series for thirty groundwater wells and five major flood events of the Danube. Kriging was used to generate impact maps of the Danube and production wells. A propagation map of the Danube flood wave into the groundwater aquifer was also generated. We used geological information to explain the findings that the river flood waves propagate with the same wavelength and decreasing amplitude in the covered aquifer and with an elongated wavelength in uncovered conditions.