Understanding the change in hydrological response due to urban dynamics is important for better flood preparedness and future sustainable urban planning. This study investigated the influence of ...urban land cover change on spatiotemporal changes in flood peak discharge and flood volume within a rapidly urbanizing catchment located in Beijing, China. We used Landsat satellite data ranging from 1986 to 2017 to monitor and quantify urban growth. Moreover, the Hydrological Modeling System (HEC-HMS) coupled with meteorological data was utilized to examine the impact of urban growth on hydrological responses. The results revealed that major changes in land use/cover (LULC) were detected in the urban landscape, which increased from 25.22% to 65.48% of the total catchment area, while agricultural land decreased from 64.85% to 25.28% during 1986–2017. The flood peak discharge and flood volume average of the three rainstorms events reached 7.02% and 11.93%, respectively. Furthermore, the changes in flood peak discharge and flood volume were more obvious at the sub-catchment scale. These findings indicate that urban growth enhanced the possible flooding risk in the study catchment. This study improves the understanding of the isolated impacts of urbanization on flooding and provides essential information for sustainable urban planning.
Understanding the effect of land use and land cover (LULC) type change on watershed hydrological response is essential for adopting applicable measures to control floods. In China, the Grain to Green ...Program (GTGP) and the Natural Forest Conservation Program (NFCP) have had a substantial impact on LULC. We investigate the effect of these conservation efforts on flood peak discharge in two mountainous catchments. We used a series of Landsat images ranging from 1990 to 2016/2017 to evaluate the LULC changes. Further to this, the hydrological responses at the basin and sub-basin scale were generated by the Hydrologic Modeling System (HEC-HMS) under four LULC scenarios. Between 1990 and 2016/2017, both catchments experienced an increase in forest and urban land by 18% and 2% in Yanhe and by 16% and 8% in Guangyuan, respectively. In contrast, the agricultural land decreased by approximately 30% in Yanhe and 24% in Guangyuan, respectively. The changes in land cover resulted in decrease in flood peak discharge ranging from 14% in Yanhe to 6% in Guangyuan. These findings provide a better understanding on the impact of reforestation induced LULC change on spatial patterns of typical hydrological responses of mountainous catchment and could help to mitigate flash flood hazards in other mountainous regions.
Satellite remote sensing is an important tool to retrieve terrestrial evapotranspiration (ET). Widely-used MOD16 ET product (MOD-ET) is a representative of Penman-Monteith method coupled with ...MODerate Resolution Imaging Spectroradiometer (MODIS) optic observations. Although MOD-ET has been extensively evaluated over the world, its accuracy under various cloud conditions remains unevaluated. Combining MODIS-observed cloud cover (Frc) and in-situ measurements at sixteen forests sites in East Asia, we evaluated 8-day MOD-ET and its primary MODIS inputs (i.e. LAI, FPAR and albedo) from clear to cloudy sky. A new satellite microwave ET method based on microwave Emissivity Difference Vegetation Index (EDVI-ET) was also compared with MOD-ET. Results showed that the accuracy of MOD-ET was highly variable under the changing Frc over the forests. The largest bias (>30%) in MOD-ET was found under Frc < 10%, while slight increase of Frc (10%–30%) reduced the bias (10%–20%). Further increase of Frc (>30%) deteriorated the bias in MOD-ET (20%–30%). In contrast, EDVI-ET performed stably with lower bias (<13%) under similar sky conditions. A higher Taylor score (0.84) for EDVI-ET was found under Frc of 4% than MOD-ET (0.66), while two ET had close scores (>0.81) under other sky conditions. Further investigation found that MOD-ET over four tropical coastal forests contributed most to the bias, especially under least cloudy sky. A case study at a tropical forest showed that MODIS LAI/FPAR and surface albedo products were overestimated, which could directly cause the overestimation of canopy-scale conductance and the underestimation of net solar radiation in MOD-ET method, respectively. Analysis showed that the bias in MOD-ET was significantly related to the bias in MODIS LAI under various Frc, but it was weakly related to that in MODIS albedo, suggesting that LAI-based conductance might dominate the overestimation of MOD-ET. During a consecutive cloud cover period when fewer reliable MODIS pixels are available, slight increase of clouds partly reduced MODIS-observed signals of LAI/FPAR and increased those of albedo over the tropical forest, resulting in the lower bias in MOD-ET. More clouds reduced surface MODIS albedo and might increase the uncertainty in all-sky shortwave radiation from reanalysis data, which deteriorated MOD-ET accuracy under overcast sky. Our study highlighted the importance of cloud impacts on the satellite ET estimation.
•MOD16 ET showed the largest bias under clear sky conditions.•Clouds exerted significant impacts on MOD16 ET estimations.•Errors in the MODIS inputs of LAI, FPAR, Albedo were the main reasons.•Microwave ET performed more stably under changing cloud cover conditions.
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