Development of a 10-year (2001-2010) 0.1° data set of land-surface energy balance for mainland China

© Author(s) 2014. In the absence of high-resolution estimates of the components of surface energy balance for China, we developed an algorithm based on the surface energy balance system (SEBS) to generate a data set of land-surface energy and water fluxes on a monthly timescale from 2001 to 2010 at a 0.1 x 0.1° spatial resolution by using multi-satellite and meteorological forcing data. A remote-sensing-based method was developed to estimate canopy height, which was used to calculate roughness length and flux dynamics. The landsurface flux data set was validated against "ground-truth" observations from 11 flux tower stations in China. The estimated fluxes correlate well with the stations' measurements for different vegetation types and climatic conditions (average bias = 11.2 Wm-2, RMSE = 22.7 Wm-2). The quality of the data product was also assessed against the GLDAS data set. The results show that our method is efficient for producing a high-resolution data set of surface energy flux for the Chinese landmass from satellite data. The validation results demonstrate that more accurate downward long-wave radiation data sets are needed to be able to estimate turbulent fluxes and evapotranspiration accurately when using the surface energy balance model. Trend analysis of land-surface radiation and energy exchange fluxes revealed that the Tibetan Plateau has undergone relatively stronger climatic change than other parts of China during the last 10 years. The capability of the data set to provide spatial and temporal information on water-cycle and land-atmosphere interactions for the Chinese landmass is examined. The product is free to download for studies of the water cycle and environmental change in China

Developing a method to estimate the water use of South African natural vegetation using remote sensing.

Master of Science in Hydrology. University of KwaZulu-Natal, Pietermaritzburg 2016.The scarcity of water is a growing concern throughout the world. It is essential to accurately determine the quantity and quality of this valuable resource to aid in water resource planning and management. For this purpose a hydrological baseline is required to compare against the water use of other land uses. Currently, the Acocks (1988) Veld Type is the baseline land cover used for hydrological studies. However, there are several shortcomings associated with this baseline land cover that may be overcome by using the recently released natural land cover map produced by South African National Biodiversity Institute (SANBI) 2012. A barrier to the use of the SANBI (2012) vegetation map is that, the water use parameters have not been determined for the various vegetation units defined. Vegetation water use can be determined by estimating the total evaporation (ET). There are a number of in-situ methods available to estimate ET. However, these methods estimate ET based on point or line averaged measurements which are only representative of local scales and cannot be extended to large areas because of land surface heterogeneity. The application of remote sensing energy balance models has the potential to overcome these limitations. Remote sensing has the ability to produce large spatial scale estimates of ET. It can also provide information at remote sites where it is difficult to install instruments. The focus of this study was to develop a method to estimate ET for natural vegetation of South Africa using remote sensing. The Surface Energy Balance System (SEBS) model in conjunction with Landsat 7 ETM+ and 8 OLI/TRS images was first used to validate point-based ET from various biomes across the country. The results from the study indicate a fair comparison between the in-situ ET data and the evaporation estimates produced using the SEBS model with coefficient of determination value of 0.66 being achieved and a RMSE of 1.74 mm.day-1. The highest RMSE was attained for the Ingeli forest site whilst the lowest belonged to the Nama Karoo site of 2.2 mm.day-1 and 0.5 mm.day-1, respectively. The SEBS model was able to estimate ET which mimics the trend of in-situ ET well. However, the model tends to over-estimate ET in comparison to in-situ ET data. Following the validation of the in-situ and SEBS ET, the SEBS model was applied to model ET for a year. For this investigation, cloud free Landsat 8 OLI/TRS images was obtained for each biome for the period between 1 July 2014 to 31 June 2015. The highest ET value of 8.7 mm/day was obtained from the Forest biome on the 12 January 2015 and the lowest ET estimate of 0.09 mm/day was on the 17 January 2015 for the Nama Karoo biome. The Forest biome recorded the highest mean ET value of 4.9 mm/day whilst the lowest mean ET value was 0.71 mm/day attained from the Nama Karoo biome. Satellite derived ET using the SEBS model produced reliable estimates when compared to in- situ ET. The spatial and temporal resolution of ET can be achieved using remote sensing. The ET estimates from SEBS compared well to the in-situ ET measurements and followed the seasonal trend, however an over-estimation of ET was present in some cases. Overall, remote sensing proves a viable option to estimate ET over large areas. This method can be applied to derive the water use which can be used to determine water use parameters

An assessment of satellite derived total evaporation data as a data source to the ACRU hydrological model.

M. Sc. Eng. University of KwaZulu-Natal, Pietermaritzburg 2014.Hydrological models and tools are often used as decision support systems to inform water resources management. The successful application of these systems is largely dependent on the quality of data being incorporated into them. Accurate information with regards to total evaporation is of paramount importance to water resources managers, as it is a key indicator in determining if water resources are being used for their specific purposes. Due to the inherent spatial limitations associated with conventional techniques to estimate total evaporation, the application of satellite earth observation as a tool to estimate total evaporation is being advocated more frequently. The focus of this Dissertation was to develop an approach which would allow for the incorporation of total evaporation estimates from an existing evaporation model that incorporates satellite earth observation data i.e. the SEBS model, into a hydrological simulation model i.e. ACRU, to simulate streamflow. The SEBS model was first validated in the Komatipoort study site against the surface renewal system. The results of this investigation indicated that the SEBS model over-estimated total evaporation by approximately 47% and produced R2 and RMSE values of 0.33 and 2.19, respectively, when compared to total evaporation estimates obtained from the surface renewal system. Once, the model had been validated, it was then applied to estimate total evaporation for quarternary catchment X23_A for the period 01st December 2011 to 25th November 2012. These estimates were used to create a continuous total evaporation time series, which was used as an input to ACRU to model streamflow. The EVTR3 approach was derived to allow for the incorporation of the aforementioned SEBS total evaporation estimates in ACRU and to estimate streamflow amongst other hydrological parameters. The simulated streamflow for this technique was under-estimated by approximately 10% and produced R2 and RMSE values of 0.41 and 1.05, respectively, when compared to observed streamflow. Although these results appear to be satisfactory at best, similar results were obtained when using the conventional evaporation routine in ACRU to estimate streamflow. This occurrence circuitously highlights the potential of utilizing satellite earth observation data as a data source for a hydrological model