Validation of remotely-sensed evapotranspiration and NDWI using ground measurements at Riverlands, South Africa

Quantification of the water cycle components is key to managing water resources. Remote sensing techniques and products have recently been developed for the estimation of water balance variables. The objective of this study was to test the reliability of LandSAF (Land Surface Analyses Satellite Applications Facility) evapotranspiration (ET) and SPOT-Vegetation Normalised Difference Water Index (NDWI) by comparison with ground-based measurements. Evapotranspiration (both daily and 30 min) was successfully estimated with LandSAF products in a flat area dominated by fynbos vegetation (Riverlands, Western Cape) that was representative of the satellite image pixel at 3 km resolution. Correlation coefficients were 0.85 and 0.91 and linear regressions produced R2 of 0.72 and 0.75 for 30 min and daily ET, respectively. Ground-measurements of soil water content taken with capacitance sensors at 3 depths were related to NDWI obtained from 10-daily maximum value composites of SPOT-Vegetation images at a resolution of 1 km. Multiple regression models showed that NDWI relates well to soil water content after accounting for precipitation (adjusted R2 were 0.71, 0.59 and 0.54 for 10, 40 and 80 cm soil depth, respectively). Changes in NDWI trends in different land covers were detected in 14-year time series using the breaks for additive seasonal and trend (BFAST) methodology. Appropriate usage, awareness of limitations and correct interpretation of remote sensing data can facilitate water management and planning operations.Fil: Jovanovic, Nebo. Natural Resources and Environment; SudáfricaFil: García, César Luis. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Católica de Córdoba; ArgentinaFil: Bugan, Richard DH. Natural Resources and Environment; SudáfricaFil: Teich, Ingrid. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Córdoba. Facultad de Ciencias Agropecuarias. Departamento de Desarrollo Rural. Area de Estadística y Biometría; ArgentinaFil: Garcia Rodriguez, Carlos Marcelo. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Córdoba; Argentin

Effects of land use change on streamflow and stream water quality of a coastal catchment

This study aimed to link land cover/use change to water quality in an important water supply coastal catchment. The approach followed a spatial and temporal analysis of historical catchment land use change to assess how changes influenced water quality and river flow in the Touws and Duiwe Rivers, southwestern Cape, South Africa. Each sub-catchment has unique characteristics which influence land use and water quality and the purpose was to analyse each one separately. Historical water quality and flow analysis were based on the records available (Duiwe River: 1998-2013; Touws River: 1980-2013) together with rainfall data. Records were analysed to detect trends over time, which were linked to changes in land use activities. Agriculture intensified rapidly in the Duiwe River catchment with most arable land cultivated by 1960 and water storage as farm dams escalating. Concentrations of nutrients and electrical conductivity were higher in the Duiwe River than in the more natural Touws River, and were positively correlated to river flows. Mean values for total nitrogen and electrical conductivity were 0.03 mg/L and 16.7 mg/L, respectively, in the Touws River and 0.25 mg/L and 127 mg/L, respectively, in the Duiwe River. Nutrient concentrations decreased in the Duiwe River after 2006 as fertilizer applications to pastures were reduced. The South African Target Water Quality Ranges were exceeded at times and in the Touws catchment this appears to have been due to extensive fires. For instance, sodium concentrations reached a maximum of 1 874.5 mg/L in 1996 compared to a usual average concentration of 20.8 mg/L where the guidelines are between 0 and100 mg/L. The link between land cover/use and water quality was demonstrated and when spatial heterogeneity of the catchments was altered by human or natural events, this was reflected in changes in the water quality.IS

A comparison of ensemble and deep learning algorithms to model groundwater levels in a data-scarce aquifer of Southern Africa

Machine learning and deep learning have demonstrated usefulness in modelling various groundwater phenomena. However, these techniques require large amounts of data to develop reliable models. In the Southern African Development Community, groundwater datasets are generally poorly developed. Hence, the question arises as to whether machine learning can be a reliable tool to support groundwater management in the data-scarce environments of Southern Africa. This study tests two machine learning algorithms, a gradient-boosted decision tree (GBDT) and a long short-term memory neural network (LSTM-NN), to model groundwater level (GWL) changes in the Shire Valley Alluvial Aquifer

Dynamics of MODIS evapotranspiration in South Africa

This paper describes the dynamics of evapotranspiration (ET) in South Africa using MOD16 ET satellite-derived data, and analyses the inter-dependency of variables used in the ET algorithm of Mu et al. (2011). Annual evapotranspiration is strongly dependent on rainfall and potential evapotranspiration (PET) in 4 climatically different regions of South Africa. Average ET in South Africa (2000–2012) was estimated to be 303 mm·a-1 or 481.4 x 109 m3·a1 (14% of PET and 67% of rainfall), mainly in the form of plant transpiration (T, 53%) and soil evaporation (Soil E, 39%). Evapotranspiration (ET) showed a slight tendency to decrease over the period 2000–2012 in all climatic regions, except in the south of the country (winter rainfall areas), although annual variations in ET resulted in the 13-year trends not being statistically significant. Evapotranspiration (ET) was spatially dependent on PET, T and vapour pressure deficit (VPD), in particular in winter rainfall and arid to semi-arid climatic regions. Assuming an average rainfall of 450 mm·a-1, and considering current best estimates of runoff (9% of rainfall), groundwater recharge (5%) and water withdrawal (2%), MOD16 ET estimates were about 15% short of the water balance closure in South Africa. The ET algorithm can be refined and tested for applications in restricted areas that are spatially heterogeneous and by accounting for soil water supply limiting conditions

Use of multi-source remotely sensed data in monitoring the spatial distribution of pools and pool dynamics along non-perennial rivers in semi-arid environments, South Africa

This study explored the use of multi-source remotely sensed data in monitoring the spatial distribution of pools and pool dynamics in two distinct semi-arid sites in South Africa. The factors that control the pool dynamics were also examined. Three water extraction indices were used, these included Normalised Difference Water Index (NDWI), Modified NDWI and Normalised Difference Vegetation Index. In addition, random forest classifier and Sentinel-1 SAR data were used in mapping pools and pools dynamics for both sites

Using the water balance approach to understand pool dynamics along non-perennial rivers in the semi-arid areas of South Africa

The Touws River in the Klein Karoo region of South Africa Study focus: This study sought to improve the understanding of pool dynamics along non-perennial rivers (NPRs) by utilising the water balance approach to assess the water fluxes that influence pool dynamics in the Touws River. The water balance model made use of various in-situ and satellite-derived data. New hydrological insights: The analysis of the water losses from the pool showed that most of the water was lost through evaporation. The interaction between the pool and groundwater is dependent on the water levels, as the pool loses water to the subsurface up to a certain depth then it starts gaining. When the Wolverfontein 2 pool is full, it can retained water for approximately 258 days without having a surface water inflow

Application of the rainfall infiltration breakthrough (RIB) model for groundwater recharge estimation in west coastal South Africa

Recharge estimation in arid and semi-arid areas is very challenging. The chloride mass balance method applied in western South Africa fails to provide reliable recharge estimates near coastal areas. A relationship between rainfall events and water level fluctuations (WLF) on a monthly basis was proposed in the rainfall infiltration breakthrough (RIB) model for the purpose of groundwater recharge estimation. In this paper, the physical meaning of parameters in the CRD and previous RIB models is clarified, and the RIB model is reviewed with the algorithm improved to accommodate various time scales, namely, daily, monthly and annual scales. Recharge estimates on a daily and monthly basis using the revised RIB approach in 2 study areas, one in a sandy alluvial aquifer (Riverlands) and the other in the Table Mountain Group (TMG) shallow unconfined aquifer (Oudebosch), are presented, followed by sensitivity analysis. Correlation analysis between rainfall and observed WLF data at daily scale and monthly scale, together with recharge estimates obtained from other methods, demonstrates that the RIB results using monthly data are more realistic than those for daily data, when using long time series. Scenarios using the data from Oudebosch with different rainfall and groundwater abstraction inputs are simulated to explore individual effects on water levels as well as recharge rate estimated on a daily basis. The sensitivity analysis showed that the recharge rate by the RIB model is specifically sensitive to the parameter of specific yield; therefore, the accurate representative specific yield of the aquifer needs to be selected with caution. The RIB model demonstrated in these two cases can be used to estimate groundwater recharge with sufficiently long time series of groundwater level and rainfall available in similar regions. In summary, the RIB model is best suited for shallow unconfined aquifers with relatively lower transmissiv - ity; the utility of the RIB model for application in different climatic areas under different hydrogeological conditions needs to be further explored.Web of Scienc

Assessing the Effects of Land Use on Surface Water Quality in the Lower uMfolozi Floodplain System, South Africa

This study investigated the impacts of cultivation on water and soil quality in the lower uMfolozi floodplain system in KwaZulu-Natal province, South Africa. We did this by assessing seasonal variations in purposefully selected water and soil properties in these two land-use systems. The observed values were statistically analysed by performing Student’s paired t-tests to determine seasonal trends in these variables. Results revealed significant seasonal differences in chloride and sodium concentrations and electrical conductivity (EC) and the sodium adsorption ratio (SAR) with cultivated sites exhibiting higher values. Most of the analyzed chemical parameters were within acceptable limits specified by the South African agricultural-water-quality (SAWQ) water quality guidelines for irrigation except for sodium adsorption ratio (SAR), chloride, sodium and EC. EC, pH and nitrate content which were higher than the specified SAWQ limits in cultivated sites. Quantities of glyphosate, ametryn and imidacloprid could not be measured because they were below detectable limits. The study concludes that most water quality parameters met SAWQ’s standards. These results argue for concerted efforts to systematically monitor water and soil quality characteristics in this environment to enhance sustainability by providing timely information for management purposes