Identification of an appropriate method for assessing large-scale and long-term recharge in Mediterranean karst aquifers

<p>Groundwater recharge is an important variable for sustainable groundwater resources management in regions affected by water scarcity. The specifics of the Mediterranean require adapted techniques to also account for climate change implying a higher frequency of extreme events. Appropriate techniques are highly relevant for recharge with low rates. We compare three methods for the Western Mountain Aquifer, a karst in Israel: soil moisture budget calculations at basin scale, empirical functions, and machine learning algorithms. Resulting recharge are compared with measured spring discharge.</p><p><strong>Neural networks</strong> have the advantage of not requiring much knowledge about physical processes or hydrogeological and hydrological conditions, nor about model parameters. This data-driven machine learning algorithms learn the non-linear relationship between precipitation events and spring water discharge given a sufficient amount of training data is available. After training, the neural network could be used as a nonlinear function to model recharge of any predicted precipitation time series. However, this approach does not allow for any quantitative analysis of external forcing, such as land use, or internal parameter, such as soil characteristics, nor does it account for any expected future change in precipitation pattern.</p><p><strong>Hydro-pedotransfer functions (HPTF)</strong> are based on empirical relationships between precipitation and recharge. HPTFs account for potential evapotranspiration, annual precipitation, land cover, and a critical water supply (a threshold when actual evapotranspiration depends only on atmospheric conditions). Resulting percolation rates consider i) vegetation types, ii) precipitation during the vegetation growth period, iii) runoff, iv) plant available soil water, and v) capillary rise. The application of HPTF to a karst aquifer has the advantage that only limited input data are required. However, our results indicate that HPTFs are not able to capture the rapid recharge component observed in karst systems and thus underestimate recharge.</p><p>The <strong>Soil Water Assessment Tool (SWAT) </strong>employs a hydrological and soil moisture budget calculations. Objective functions are actual evapotranspiration and surface runoff. Evapotranspiration is obtained from MODIS remote sensing data. Calibration of actual evapotranspiration is especially challenging for summer periods due to the impact of vegetation and irrigation. However, the most relevant parameter determining daily recharge rates are water loss by surface-runoff and surface water storage in wadi beds generating episodic recharge.</p><p>Impact of shifts in climate is considered by climate projections obtained with the RCM COSMO-CLM at resolution of 3 km, under the IPCC RCP4.5 scenario, nested into the MENA-CORDEX domain. However, we believe that changes in land use from natural vegetation (trees, grass-, and shrublands) to rain-fed agricultural area could possibly shift the water budget from deficit to surplus conditions (recharge dominated). During the period 1992 to 2015 natural vegetation decreased by 8% and urban areas increased by up to 6%, while (rain-fed) agricultural areas remained almost constant. We investigate if land use changes might have (a much) larger impact on percolation rates than the predicted climate change effect. Thus, in future recharge may be controlled and enhanced in regions with water scarcity by better management of land use employing an optimized combination between precipitation, irrigation, and crop type.</p>

Improved characterization of frozen soil processes in the Versatile Soil Moisture Budget model

Mohammed, G. A., Hayashi, M., Farrow, C. R. and Takano, Y. 2013. Improved characterization of frozen soil processes in the Versatile Soil Moisture Budget model. Can. J. Soil Sci. 93: 511–531. Soil freezing and thawing influence the infiltration of rain and snow melt water and subsequent redistribution, runoff generation, and a host of other processes. Accurate characterization of frozen soil processes in hydrological models is important for their use in managing agricultural activities and water resources. The Versatile Soil Moisture Budget (VSMB) is a relatively simple soil water balance model, which has been widely used in Canada for several decades, but its application has primarily been for crop-growing seasons. We have modified the VSMB to include new algorithms for snow accumulation and melt, soil freezing and thawing, and snowmelt infiltration and runoff; and evaluated its performance using field data from a grassland site in Alberta. The new VSMB model simulates snow processes with reasonable accuracy and predicts the day of thawing within several days of observation. It also estimates the amount of runoff and its inter-annual variability reasonably well, although the model still has limitations in accurately predicting the vertical distribution of water content. Despite these limitations, the model will be useful for estimating the amount of snowmelt runoff that provides the critical water inputs to wetlands and dugouts, and for understanding the effects of landuse variability on these processes.

Modelling nitrogen leaching in Prince Edward Island under climate change scenarios

Projected climate change in Canada and its impact on crop yield and production have been studied, but the impacts on soil and water quality are less well known. The objective of this study was to model and evaluate the potential impacts of climate change on soil nitrogen (N) leaching in Prince Edward Island. Residual soil nitrogen (RSN), the quantity of inorganic soil N at the time of harvest, was calculated from an annual N budget, based on Census of Agriculture data. RSN was "added" to the soil in the fall and subject to leaching until the start of the next growing season. Water and N movement in and through the soil were calculated with a modified version of the Versatile Soil Moisture Budget. The provincial averages of RSN and N leaching under historic (1971–2000) climate and management conditions were calculated to be 30.8 kg N ha-1 and 27.9 kg N ha-1, i.e. , 91% of the RSN was lost via leaching. With no changes in agricultural practices, N leaching under four climate change (2040–2069) scenarios remained very similar (± 1%) to that simulated under historic climatic conditions. With agricultural intensification, in response to climate change and economic conditions, RSN levels increased to 35.7 kg N ha-1 and estimates of soil N leaching increased by 5 to 30% beyond historic levels. Key words: Residual soil nitrogen, versatile soil moisture budget, climate change impacts, agricultural adaptation, water contamination

Patterns and simulation of soil water under different grazing management systems in central Alberta

A study was conducted at the Lacombe Research Centre to quantify and simulate the impacts of forage and grazing systems on soil water content. Four forages used in the study were alfalfa (Medicago sativa L.), a mixture of meadow bromegrass (Bromus riparius L.) and alfalfa, an annual pasture and an old grass pasture that was composed of mainly quackgrass (Elytrigia repens L.), smooth bromegrass (Bromus inermis L.) and Kentucky bluegrass (Poa pratensis L .). Within each 1.2-ha paddock were two grazing treatments: rotational grazed and ungrazed. Soil water measurements to a 65-cm depth were conducted between May and October of 1999 and 2000 using a neutron moisture probe. Total soil water was affected by forage species more than grazing. Actual evapotranspiration rates were 3-4 mm d-1 in both years. Simulation of daily volumetric soil water content (%) for each year was conducted using the Versatile Soil Moisture Budget (VB2000) model on grazed alfalfa, ungrazed alfalfa, grazed annual and ungrazed annual treatments. During calibration year of 1999, the overall modeling efficiency (EF) was 0.58 while, during the evaluation year it was 0.43. Further, simulations for alfalfa were better than those for annual treatments. These EF values are relatively low indicating substantial discrepancies between observed and simulated results, which could have been attributed to a combination of input data errors, model errors and propagation errors in output. Key words: Evapotranspiration, forages, model calibration, model evaluation, versatile soil moisture budget model

Soil moisture modelling — conception and evolution of the VSMB

The Versatile Soil Moisture Budget (VSMB), including the background leading to its development in the "early days" meaning around 30 yr ago, is described. National and international efforts before that time created a healthy climate for the development of agrometeorology in Canada and the pioneering work in soil moisture and crop-weather modelling.Events in the early days leading to a concerted endeavour of soil moisture modelling included: (i) a small group of highly qualified professionals from different disciplines, as well as support staff, had been established under the guidance of a team leader at the then Plant Research Institute (PRI); ii) a Canada wide crop-weather study had produced daily climatological and crop data at nine Canada Department of Agriculture establishments over 10 yr (1953–1962); iii) a computer became available to PRI staff (IBM 1620 with 16K); and (v) several sub-models providing the necessary input to the soil moisture model were at various stages of development (e.g. the "latent" evaporation and the biometeorological time scale sub-models).This paper presents an overview of the development of the VSMB using standard climatological data for generating daily soil moisture estimates under crops. Its concept, design and widespread applications in Canada and abroad are discussed. A more detailed analysis is left to the other presentations at this Symposium. Key words: Soil moisture, modelling, applications

Estimation of snowmelt runoff in the Peace River region using a soil moisture budget

Rainfall and snowmelt runoff on soil frozen below the surface are recognized as important factors contributing to soil loss in Canada. The risk of rain on frozen soil has been quantified, and the amount of snowmelt on frozen soil has been estimated. This study extends such research to derive a climate-based model to estimate winter and spring runoff. This could result in a more accurate erosion prediction for areas where snowmelt is a major source for runoff. Selected components of the Water Erosion Prediction Project (WEPP) model and the versatile soil moisture budget (VB) were tested on observed data for two study sites in the Peace River region. The version of the WEPP model available to us estimated snow depth, soil frost depth and frequency of freeze–thaw cycles. However, the results did not adequately match observed data. The VB was modified in this study to improve the estimate of potential winter and spring runoff, and it was shown that incorporating observations of snow depth improved the estimate of the time and amount of snowmelt runoff. The modified runoff model was validated with data collected in the Peace River area of northern Alberta and British Columbia and with published data from the Prairies. Key words: Snowmelt, runoff, soil moisture budget

ESTIMATED LONG-TERM SOIL MOISTURE VARIABILITY ON THE CANADIAN PRAIRIES

Soil water contents under wheat production systems on the Canadian prairies were estimated using the Versatile Soil Moisture Budget, which was modified to include an estimated seeding date and a biometeorological time scale. Large year-to-year variability required the use of long term (60 yr) data to describe seasonal and probable occurrences of soil water contents for 27 stations. Regression and correlation analyses were used to simplify presentation of the data and to display their spatial distribution. On average, summerfallowing was most effective in conserving water in areas with intermediate spring soil water contents and on soils with a higher available water-holding capacity (AWC). In abnormally dry years (i.e., 10% probability) summerfallowing conserved more water in the wetter areas while increasing the AWCs had the greatest effect on conserved water in the intermediate areas. Soil water contents at heading were greater under wheat-fallow rotation compared to continuous wheat and increased with increasing AWCs. Water contents of less than 50% of AWC at heading occurred with a probability of 80% or higher in most areas, indicating some stress is experienced in most years. Summerfallowing lowered the probability only slightly on soils with a low AWC, but by 10–20% on the higher AWC soils. The probability of extreme water stress at heading (i.e. water contents ≤ 10% of AWC) ranged from 0% in the wettest areas to 40–60% in the driest climatic area. Key words: Soil water content, versatile soil moisture budget, summer fallowing, zonation, wheat (spring), seeding date