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

Energy and Water Cycles in the Third Pole

As the most prominent and complicated terrain on the globe, the Tibetan Plateau (TP) is often called the “Roof of the World”, “Third Pole” or “Asian Water Tower”. The energy and water cycles in the Third Pole have great impacts on the atmospheric circulation, Asian monsoon system and global climate change. On the other hand, the TP and the surrounding higher elevation area are also experiencing evident and rapid environmental changes under the background of global warming. As the headwater area of major rivers in Asia, the TP’s environmental changes—such as glacial retreat, snow melting, lake expanding and permafrost degradation—pose potential long-term threats to water resources of the local and surrounding regions. To promote quantitative understanding of energy and water cycles of the TP, several field campaigns, including GAME/Tibet, CAMP/Tibet and TORP, have been carried out. A large amount of data have been collected to gain a better understanding of the atmospheric boundary layer structure, turbulent heat fluxes and their coupling with atmospheric circulation and hydrological processes. The focus of this reprint is to present recent advances in quantifying land–atmosphere interactions, the water cycle and its components, energy balance components, climate change and hydrological feedbacks by in situ measurements, remote sensing or numerical modelling approaches in the “Third Pole” region

Water availability and demand analysis in the Kabul River Basin, Afghanistan

Kabul River Basin (KRB), the most populated and highly heterogenic river basin of Afghanistan is the lifeline of millions of people in terms of supplying them with water for agricultural, municipal, and industrial as well as hydropower production purposes. Unfortunately, KRB is facing a multiplicity of governance, management and development relevant challenges for the last couple of decades. Detailed and reliable assessments of land use and land cover, water demand (for different sectors) as well as the available water resources are prerequisites for Integrated Water Resources Management across the basin. To achieve increased accuracy for water availability and demand analysis across the KRB, the study area was segregated into different hydrological and administrative units (provincial level, subbasin level etc.) in order to capture the heterogeneity driven by complex physiographic conditions (mainly due to huge elevation differences) and resulting in diverse cropping pattern at different reaches of the river basin. The innovative part of this study has been the concept of introducing spatial segregation of the large heterogenic river basin and using crop phenological information for evapotranspiration and land cover analysis respectively; it gave a distinct value to the output of this study. Phenologically tuned normalized difference vegetation indices (NDVI) of Aqua and Terra platforms with moderate resolution (250 m) proved to be very effective in the estimation of the land cover across the KRB with high accuracy. The phenology based segregated spatial analyses of the LULC of KRB with reference to 2003 (the base year of the study) highlighted the change in the ground coverage of main crops across the KRB e.g. wheat, barley, maize and rice. Based on the evaluation of the above results referring to the period 2003 to 2013, the rise in wheat ground coverage has been compensated by the decline in barley cultivation; maize and rice share has been almost consistent among the dominant cereals production in KRB. Upon spatial segregation, across the sub-basins (Alingar, Chak aw Logar, Ghorband aw Panjshir, Gomal, Kabul, Kunar and Shamal) Shamal, Kunar and Kabul showed highest actual evapotranspiration (ETa) throughout the study period of 2003 to 2013. The later three sub-basin host relatively large irrigated areas and production of two crops per year due to relatively favorable climatic and geographic conditions. Besides the agricultural water demand (ETa), water availability estimation through rainfall-runoff modelling by the use of the Soil and Water Assessment Tool (SWAT) has been very useful in data scarce regions like KRB. The application of the hydrological model using remote sensing products as input is the only effective choice in data scarce regions and exhibited results which are required by policy makers and investors for the strategic and sustainable planning and management of land and water resources

The estimation and evaluation of a satellite-based drought index using rainfall and evapotranspiration.

Master of Science in Hydrology. University of KwaZulu-Natal. Pietermaritzburg, 2017.Abstract available in PDF file

Advances in Evaporation and Evaporative Demand

The importance of evapotranspiration is well-established in different disciplines such as hydrology, agronomy, climatology, and other geosciences. Reliable estimates of evapotranspiration are also vital to develop criteria for in-season irrigation management, water resource allocation, long-term estimates of water supply, demand and use, design and management of water resources infrastructure, and evaluation of the effect of land use and management changes on the water balance. The objective of this Special Issue is to define and discuss several ET terms, including potential, reference, and actual (crop) ET, and present a wide spectrum of innovative research papers and case studies

Simulation of forest evapotranspiration using time-series parameterization of the Surface Energy Balance System (SEBS) over the Qilian Mountains

© 2015 by the authors. We propose a long-term parameterization scheme for two critical parameters, zero-plane displacement height (d) and aerodynamic roughness length (z0m), that we further use in the Surface Energy Balance System (SEBS). A sensitivity analysis of SEBS indicated that these two parameters largely impact the estimated sensible heat and latent heat fluxes. First, we calibrated regression relationships between measured forest vertical parameters (Lorey's height and the frontal area index (FAI)) and forest aboveground biomass (AGB). Next, we derived the interannual Lorey's height and FAI values from our calibrated regression models and corresponding forest AGB dynamics that were converted from interannual carbon fluxes, as simulated from two incorporated ecological models and a 2009 forest basis map These dynamic forest vertical parameters, combined with refined eight-day Global LAnd Surface Satellite (GLASS) LAI products, were applied to estimate the eight-day d, z0m, and, thus, the heat roughness length (z0h). The obtained d, z0m and z0h were then used as forcing for the SEBS model in order to simulate long-term forest evapotranspiration (ET) from 2000 to 2012 within the Qilian Mountains (QMs). As compared with MODIS, MOD16 products at the eddy covariance (EC) site, ET estimates from the SEBS agreed much better with EC measurements (R2 = 0.80 and RMSE = 0.21 mm· day-1)

Simulating long-term food producing capacities in China using a Web-based land evaluation system

This dissertation presents a modeling approach to assess the long-term food producing capacities, and consequently food security, in China using a Web-based land evaluation system (WLES, http://weble.ugent.be). WLES implements a 3-step quantitative land evaluation model which evaluates the realistic yield of a field crop by considering the effects of (a) radiation and temperature regimes, (b) water stress, (c) limited soil fertility and (d) insufficient crop management. Homogeneous 5 km by 5 km grid datasets of climatic, soil, crop and management parameters were created. Food productions in 2030 and 2050 were simulated using production scenarios involving population growth, urbanization rate, cropland area, cropping intensity, management level and soil degradation. The model predicted that food crops may experience a 9.7% productivity loss by 2030 if the soil is degraded at the current rate (“business-as-usual” scenario, BAU); productivity loss will increase to an unbearable level of 36.7% by 2050, should the soil be twice more degraded than it is now (“double degradation” scenario, 2xSD). China's food producing capacity tends to decline in the long run if the general trend of soil degradation will not be reverted. China will be able to achieve a production of 430 million tons from food crops in 2030 and 410 million tons in 2050 under the BAU scenario, which are 11.5% and 15.5% lower than the 2005 level, respectively. In per capita terms, China will experience a food shortage of 9.8% in 2030 and 7.5% in 2050 even under the “zero-degradation” scenario (0xSD), compared to a 12.7% food surplus in 2005. Per capita food shortage in 2050 will be as high as 22.6% under the BAU scenario and 38.3% under the 2xSD scenario. The results suggest the present-day producing capacity (2005 level) will not be able to sustain the long-term needs under the current management level even if soil degradation is not becoming more limiting. The detrimental effect of soil degradation on food security is so evident that technical measures and policy levers must be activated today in order to avoid, or at least mitigate, the risks of food insecurity tomorrow

Simulation of Forest Evapotranspiration Using Time-Series Parameterization of the Surface Energy Balance System (SEBS) over the Qilian Mountains

We propose a long-term parameterization scheme for two critical parameters, zero-plane displacement height (d) and aerodynamic roughness length (z0m), that we further use in the Surface Energy Balance System (SEBS). A sensitivity analysis of SEBS indicated that these two parameters largely impact the estimated sensible heat and latent heat fluxes. First, we calibrated regression relationships between measured forest vertical parameters (Lorey’s height and the frontal area index (FAI)) and forest aboveground biomass (AGB). Next, we derived the interannual Lorey’s height and FAI values from our calibrated regression models and corresponding forest AGB dynamics that were converted from interannual carbon fluxes, as simulated from two incorporated ecological models and a 2009 forest basis map These dynamic forest vertical parameters, combined with refined eight-day Global LAnd Surface Satellite (GLASS) LAI products, were applied to estimate the eight-day d, z0m, and, thus, the heat roughness length (z0h). The obtained d, z0m and z0h were then used as forcing for the SEBS model in order to simulate long-term forest evapotranspiration (ET) from 2000 to 2012 within the Qilian Mountains (QMs). As compared with MODIS, MOD16 products at the eddy covariance (EC) site, ET estimates from the SEBS agreed much better with EC measurements (R2 = 0.80 and RMSE = 0.21 mm·day−1)