Estimation of Infiltration Volumes and Rates in Seasonally Water-Filled Topographic Depressions Based on Remote-Sensing Time Series
| Autor: | Alexey Dobrokhotov, Alla Yurova, Daniil Kozlov, Pavel P. Fil |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
closed depressions
temporary water bodies TP1-1185 infiltration Biochemistry Article Analytical Chemistry remote sensing Spring (hydrology) Electrical and Electronic Engineering Digital elevation model Ponds Instrumentation Groundwater Hydrology geography Series (stratigraphy) geography.geographical_feature_category Pixel Depression Chemical technology Water Groundwater recharge Atomic and Molecular Physics and Optics Infiltration (hydrology) Snowmelt Environmental science Seasons |
| Zdroj: | Sensors (Basel, Switzerland) Sensors, Vol 21, Iss 7403, p 7403 (2021) Sensors Volume 21 Issue 21 |
| ISSN: | 1424-8220 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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