Wind and rainfall regulation of the diffuse attenuation coefficient in large, shallow lakes from long‐term MODIS observations using a semianalytical model

Abstract

Knowledge of the variation and regulation of the diffuse attenuation coefficient is important for management of lake water quality and ecological environments. Data were collected seven times (378 samples) from 2006 to 2011 in Lake Taihu to improve the existing semianalytical model of diffuse attenuation coefficient at 490 nm (Kd(490)) by measuring in situ Kd(490) and remote sensing reflectance (Rrs). This semianalytical model was applied to determine the long‐term variation of Kd(490) and its driving factors from Moderate Resolution Imaging Spectroradiometer (MODIS) images. Our semianalytical model of Kd(490) improves the retrieval accuracy of Kd(490) from 29.60% to 22.58% (root‐mean‐square percentage error) and 24.28 ± 18.54% (mean value ± standard deviation) to 19.29 ± 14.34% (mean absolute relative error). The Kd(490) from maps produced from MODIS images clearly present the temporal and spatial variations of Kd(490). This indicates the suitability of using the improved semianalytical model and MODIS to observe Kd(490) in turbid shallow inland waters. Long‐term MODIS observation of Kd(490) shows distinct seasonal and spatial variations. Temporally, the highest and the lowest Kd(490) were found in winter and in summer, respectively. Spatially, high Kd(490) values were primarily distributed in the southwestern and northwestern Lake Taihu, and relatively low Kd(490) values were distributed in Meiliang Bay and Gonghu Bay (the eastern part of the lake and East Bay were excluded in this study due to invalid retrieval results of Kd(490)). Many covarying points were found between Kd(490) and maximum wind speed from long‐term observations, suggesting that wind‐induced sediment resuspension is the principal driver of high Kd(490). Correlation was also observed between Kd(490) and heavy rainfall events, suggesting the regulating effect of heavy rainfall.

Determination of the Downwelling Diffuse Attenuation Coefficient of Lake Water with the Sentinel-3A OLCI

“…Note that heavy rainfall events may have a great impact on the K d (490) of Lake Taihu through rivers plums [61,70,71]. But unfortunately, we did not observe this phenomenon due to the unavailability of OLCI data during precipitation events.…”

“…Because the reflection of water at 754 nm mainly relies on the SPM concentration and is the least sensitive to algal pigments [60], the effects of changes in the algal concentration can be reduced by using another band ratio (754 nm/560 nm) to compensate for the deficiency in the 681-nm/560-nm band ratio. Although algal bloom-covered areas were mostly masked off in research on the estimation of Kd [61], it was difficult to completely remove these areas in practice; in addition, the algal particle concentrations in the waters surrounding the algal bloomcovered areas were still high. Therefore, the dual band ratio algorithm was more suitable for eutrophic lakes with a wide distribution of algae.…”

“…Wind-and wave-induced sediment resuspension will increase the SPM concentration in the water and thereby increase light attenuation in the water [52,67,68]. Several studies have demonstrated that the wind-induced resuspension is important in sediment related turbulence, the main driving factor for the spatial and temporal variations in K d for Lake Taihu [27,61,69].…”

“…To further confirm the accuracy of the spatial distribution of the OLCI-derived K d (490) values, the K d (490) values for Lake Taihu derived from Terra-MODIS using a newly proposed K d (490) semi-analytical algorithm [61] were used as quasi-reference values and compared with those derived from Sentinel-3A-OLCI. A total of 18 OLCI-MODIS image matchups were used, and six matchups with large uncertainties in the MODIS atmospheric correction were excluded.…”

Semi-Analytical Retrieval of the Diffuse Attenuation Coefficient in Large and Shallow Lakes from GOCI, a High Temporal-Resolution Satellite

“…Consequently, two bands (R rs (660), R rs (660)/R rs (555)) were used to estimate Figure 4B). The parameters of K d (490) algorithm for MODIS were confirmed by using a method similar to the one used for GOCI [27]. …”