Estimation of groundwater recharge via percolation outputs from a rainfall/runoff model for the Verlorenvlei estuarine system, west coast, South Africa

Abstract

11Wetlands are conservation priorities worldwide, due to their high biodiversity and productivity, but are 12 under threat from agricultural and climate change stresses. To improve the water management practices 13 and resource allocation in these complex systems, a modelling approach has been developed to estimate 14 potential recharge for data poor catchments using rainfall data and basic assumptions regarding soil and 15 aquifer properties. The Verlorenvlei estuarine lake (RAMSAR #525) on the west coast of South Africa 16 is a data poor catchment where rainfall records have been supplemented with farmer's rainfall records. 17The catchment has multiple competing users. To determine the ecological reserve for the wetlands, the 18 spatial and temporal distribution of recharge had to be well constrained using the J2000 rainfall/runoff 19 model. The majority of rainfall occurs in the mountains (±650 mm/yr) and considerably less in the 20 valley (±280 mm/yr). Percolation was modelled as ~3.6% of rainfall in the driest parts of the catchment, 21 ~10% of rainfall in the moderately wet parts of the catchment and ~8.4% but up to 28.9% of rainfall in 22 the wettest parts of the catchment. The model results are representative of rainfall and water level 23 measurements in the catchment, and compare well with water table fluctuation technique, although 24 30 31 4 groundwater level. This approach can also be called actual recharge, as it determines the amount of 59 water that reaches the groundwater table (Rushton, 1997), but in doing so it neglects any processes that 60 occur in the unsaturated zone, thereby reducing its spatial and temporal extent. However, for numerical 61 modelling of recharge, it is not possible to neglect what is happening in the unsaturated zone, as most 62 models require information on the physical and chemical pathways of recharge. Therefore, this type of 63 approach is rather defined as potential recharge, which is constrained by the amount of water that has 64 percolated through the unsaturated zone, contributing to the saturated zone (Rushton, 1997), and hence 65 requires knowledge of the percolation rate. 66Within numerical modelling, the percolation rate (Scanlon et al., 2002) can be modelled either by 67 looking at variably saturated flow or rainfall/runoff partitioning. Both these methods use a water-68 balance to determine the percolation volume using input data, such as climate (rainfall, temperature), 69 vegetation (interception) and biosphere (soil texture) to partition water into runoff, infiltration, 70 evaporation and recharge. These two methods differ in their ability to simulate soil moisture. Variably 71 saturated flow models can simulate vertical distributions of soil moisture and estimate recharge by 72 routing water through the soil column using soil hydraulic conductivities. Many rainfall/runoff models 73 partition infiltrated water into storages based on soil type parameters (J2000: Krause, 2001; and ACRU: 74 Schulze, 1995) . This makes variably saturated flow more favoura...

Cryptosporidium spp. and Giardia duodenalis emissions from humans and animals in the Three Gorges Reservoir in Chongqing, China

“…To our knowledge, the GloWPa-TGR-Crypto model cannot be validated through the direct comparison of measured surface water values because this method ignores certain factors, such as the infiltration pathways and transport via soils and shallow groundwater to surface water ( Bogena et al, 2005 ; Vermeulen et al, 2017 ; Watson et al, 2018 ), the overflow of sewage treatment plants during the flood period ( Xiao et al, 2017 ), traditional dispersive small-scale peasant production ( Li et al, 2016 ), and the excretion of wildlife ( Atwill, Phillips & Rulofson, 2003 ). The pathogen loading data of these factors are not readily available.…”

Determining Hydrological Variability Using a Multi-Catchment Model Approach for the Western Cape, South Africa

“…Daily totals of precipitation and solar radiation, mean daily relative humidity, temperature, windspeed and maximum and minimum daily temperature were collected for the period 1988-2002 (including a 2-year initialization period). The data were attained from the World Meteorological Organisation (WMO) as global surface summary of the day (GSOD) data [23], as well as the Agricultural Research Council (ARC), the South African Weather Services (SAWS), the Department of Water Affairs and Sanitation, South Africa (DWS), the South African Earth Observation Network [45] and previous JAMS/J2000 model data [18,[46][47][48][49][50]. In total, 97 precipitation, 24 temperature, 12 relative humidity, 15 windspeed and seven solar radiation stations were used (Table 2).…”

“…The model calibration was performed using a semi-automated procedure (e.g., [66]), which utilized the non-dominated sorting genetic algorithm (NSGA-II) [67] to explore the 'optimal' parameter space and model expertise from other applications [18,46,48,49,68,69] to finally select quantifiable model parameters for the region. For the calibration and validation of the Velorenvlei, Berg, Bot and Breede catchments, the time series was split into two (e.g., [70]), with (1) calibration from 01-01-1990 to 31-12-1995 and (2) validation from 01-01-1996 to 01-01-2002.…”

Distributive rainfall/runoff modelling to determine runoff to baseflow proportioning and its impact on the determination of the ecological reserve

“…In this study, parameters that 323 were used to control the ratio of interflow to percolation were adjusted, which in the J2000 324 model include a slope (SoilLatVertDist) and max percolation value. The sensitivity analysis 325 conducted by Watson et al, (2018) showed that for high flow conditions (E2) (Nash-Sutcliffe 326 efficiency in its standard squared), model outputs are most sensitive to the slope factor, while 327 for low flow conditions (E1) (modified Nash-Sutcliffe efficiency in a linear form) the model 328 outputs were most sensitive to the maximum infiltration rate of the soil (ie. the parameter 329 maxInfiltrationWet) (Supplementary: Figure 1).…”

“…Agriculture is the 148 dominant water user in the sub-catchment with an estimated usage of 20 % of the total recharge 149 (DWAF, 2003;Watson et al, submitted), with the main food crop being potatoes. For further 150 information regarding the study site refer to Watson et al, (2018). 151…”