Spatio-temporal analysis of remotely sensed and hydrological model soil moisture in the small Jičinka River catchment in Czech Republic

Abstract

The knowledge of spatio-temporal dynamics of soil moisture within the catchment is very important for rainfall–runoff modelling in flood forecasting. In this study the comparison between remotely sensed soil moisture and soil moisture estimated from the SHETRAN hydrological model was performed for small and flashy Jičinka River catchment (75.9 km2) in the Czech Republic. Due to a relatively coarse spatial resolution of satellite data, the satellite soil moisture data were downscaled, by applying the method developed by Qu et al. (2015). The sub-grid variability of soil moisture was estimated on the basis of the mean soil moisture for the grid cell and the known hydraulic soil properties. The SHETRAN model was calibrated and verified to the observed streamflow hydrographs at the catchment outlet. The good correlation between the two different soil moisture information was obtained according to the majority of applied criteria. The results of the evaluation criteria indicate that the downscaled remotely sensed soil moisture data can be used as additional criteria for the calibration and validation of hydrological models for small catchments and can contribute to a better estimation of parameters, to reduce uncertainties of hydrological models and improve runoff simulations.

Adaptive Water Management-land Use Practice for Improving Ecosystem Services – a Hungarian Modelling Case Study

“…For instance, for the small (75.9 km 2 ) and flashy (time of concentration is less than 1 hour for all sub-catchments) Jičinka River catchment [38] set up a lumped (HEC-HMS) and distributed parameter (SHETRAN) hydrologic model and reported NSME between 0.88 and 0.95 for calibration and NSME between 0.53 and 0.91 for validation events. For the same catchment Đukić et al [38,39] also presented that lumped and distributer parameter models can provide reasonable estimates also for soil moisture: both the cellbased maps and the catchment scale averages of simulated soil moisture showed good agreement with downscaled satellite data.…”

Evaluation and Prediction of Water Yield Services in Shaanxi Province, China

“…The traditional water yield evaluation method is usually realized by using measured data, such as the soil water storage capacity method, the canopy interception surplus method, the precipitation storage method, the annual runoff method, and the underground runoff growth method [12]. With the continuous progress and upgrading of remote sensing and geographic information system (GIS) technology, hydrological models have played an essential role in the fields of ecology and hydrology [13][14][15]. More and more models can realize the simulation and evaluation of watershed water yield services, such as the Soil and Water Assessment Tool (SWAT) model [16][17][18], ARIES model [19,20] and the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model [21][22][23].…”

Changes in crack width on the surface of heavy soils during drought, determined by precise measurement and calculation

“…It is one of the soil type characteristics features. In contrast, soil moisture changes by hydro-meteorological conditions in the area, the depth of the unsaturated soil zone and anthropogenic activity (Almikaeel et al, 2022;Baroková et al, 2020;Čubanová et al, 2022;Đukić et al, 2021;Kuban et al, 2022) in the area. This is reflected in the dynamics of hydrological processes.…”