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Article

Estimation of Infiltration Volumes and Rates in Seasonally Water-Filled Topographic Depressions Based on Remote-Sensing Time Series

1
V. Dokuchaev Soil Science Institute, 109017 Moscow, Russia
2
Department of Geography, Lomonosov Moscow State University, 119991 Moscow, Russia
3
Agrophysical Research Institute, 195220 St. Petersburg, Russia
*
Author to whom correspondence should be addressed.
Academic Editors: Miquel Àngel Cugueró-Escofet and Vicenç Puig
Received: 14 September 2021 / Revised: 29 October 2021 / Accepted: 3 November 2021 / Published: 7 November 2021
In semi-arid ecoregions of temperate zones, focused snowmelt water infiltration in topographic depressions is a key, but imperfectly understood, groundwater recharge mechanism. Routine monitoring is precluded by the abundance of depressions. We have used remote-sensing data to construct mass balances and estimate volumes of temporary ponds in the Tambov area of Russia. First, small water bodies were automatically recognized in each of a time series of high-resolution Planet Labs images taken in April and May 2021 by object-oriented supervised classification. A training set of water pixels defined in one of the latest images using a small unmanned aerial vehicle enabled high-confidence predictions of water pixels in the earlier images (Cohen’s Κ = 0.99). A digital elevation model was used to estimate the ponds’ water volumes, which decreased with time following a negative exponential equation. The power of the exponent did not systematically depend on the pond size. With adjustment for estimates of daily Penman evaporation, function-based interpolation of the water bodies’ areas and volumes allowed calculation of daily infiltration into the depression beds. The infiltration was maximal (5–40 mm/day) at onset of spring and decreased with time during the study period. Use of the spatially variable infiltration rates improved steady-state shallow groundwater simulations. View Full-Text
Keywords: closed depressions; temporary water bodies; remote sensing; infiltration closed depressions; temporary water bodies; remote sensing; infiltration
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MDPI and ACS Style

Fil, P.P.; Yurova, A.Y.; Dobrokhotov, A.; Kozlov, D. Estimation of Infiltration Volumes and Rates in Seasonally Water-Filled Topographic Depressions Based on Remote-Sensing Time Series. Sensors 2021, 21, 7403. https://0-doi-org.brum.beds.ac.uk/10.3390/s21217403

AMA Style

Fil PP, Yurova AY, Dobrokhotov A, Kozlov D. Estimation of Infiltration Volumes and Rates in Seasonally Water-Filled Topographic Depressions Based on Remote-Sensing Time Series. Sensors. 2021; 21(21):7403. https://0-doi-org.brum.beds.ac.uk/10.3390/s21217403

Chicago/Turabian Style

Fil, Pavel P., Alla Y. Yurova, Alexey Dobrokhotov, and Daniil Kozlov. 2021. "Estimation of Infiltration Volumes and Rates in Seasonally Water-Filled Topographic Depressions Based on Remote-Sensing Time Series" Sensors 21, no. 21: 7403. https://0-doi-org.brum.beds.ac.uk/10.3390/s21217403

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