SY035-0008
On-farm reservoir monitoring using Landsat inundation datasets
On-farm reservoir monitoring using Landsat inundation datasets
Thursday, 10 December 2020
Poster
Abstract:
On-farm reservoirs (OFRs) – artificial water impoundments that retain water from rainfall and
run-off – enable farmers to store water during the wet season for crop irrigation during the dry
season. However, monitoring the inter- and intra-annual change in size of these water bodies
remains a challenging task because they are typically small (<10 ha) and occur in high numbers.
Therefore, we used two existing Landsat inundation datasets – the U.S. Geological Survey
Dynamic Surface Water Extent (DSWE) and the European Commission’s Joint Research Centre
(JRC) Global Monthly Water History – to assess surface water area change of OFRs located in
Eastern Arkansas, the third most irrigated state in the U.S. that has seen a rapid increase of OFRs
occurrence. The location of the OFRs were obtained from an existing reservoir dataset derived
from digitized orthoimages, and we used this dataset as ground truth. We aimed (i) to compare
the performance of the DSWE and the JRC when characterizing OFRs of varied sizes and (ii) to
assess the impact of climate variables (i.e. precipitation and temperature) and discharge on
surface water area of OFRs. We found the highest mean percent errors (MPE) in size (~20%) for
OFRs between 0-5 ha, the smallest size class in our study. The DSWE had a smaller MPE and
higher agreement with the ground truth dataset when compared to the JRC for OFRs smaller than
15 ha (p-value < 0.05). Both inundation datasets enabled us to estimate the seasonality in surface
area change of OFRs, with the highest surface water extent between March-May, the months
when the region receives most of the annual precipitation. Our results showed that these
inundation datasets can be used to enhance hydrological assessments in poorly monitored basins
that have a concentration of OFRs.
run-off – enable farmers to store water during the wet season for crop irrigation during the dry
season. However, monitoring the inter- and intra-annual change in size of these water bodies
remains a challenging task because they are typically small (<10 ha) and occur in high numbers.
Therefore, we used two existing Landsat inundation datasets – the U.S. Geological Survey
Dynamic Surface Water Extent (DSWE) and the European Commission’s Joint Research Centre
(JRC) Global Monthly Water History – to assess surface water area change of OFRs located in
Eastern Arkansas, the third most irrigated state in the U.S. that has seen a rapid increase of OFRs
occurrence. The location of the OFRs were obtained from an existing reservoir dataset derived
from digitized orthoimages, and we used this dataset as ground truth. We aimed (i) to compare
the performance of the DSWE and the JRC when characterizing OFRs of varied sizes and (ii) to
assess the impact of climate variables (i.e. precipitation and temperature) and discharge on
surface water area of OFRs. We found the highest mean percent errors (MPE) in size (~20%) for
OFRs between 0-5 ha, the smallest size class in our study. The DSWE had a smaller MPE and
higher agreement with the ground truth dataset when compared to the JRC for OFRs smaller than
15 ha (p-value < 0.05). Both inundation datasets enabled us to estimate the seasonality in surface
area change of OFRs, with the highest surface water extent between March-May, the months
when the region receives most of the annual precipitation. Our results showed that these
inundation datasets can be used to enhance hydrological assessments in poorly monitored basins
that have a concentration of OFRs.