Fine-resolution profile-scale data to depict the impact of tillage treatment and machine traffic on agricultural soil structure and hydrologic properties.

This data article provides high spatial resolution (1 cm) datasets and related figures of the penetrometer resistance (PR) and soil bulk density (BD) data of nine agricultural 50 × 160 cm soil profiles exposed to three tillage treatments and including a wheel track. Soil treatments are moldboard plowing (MP), deep loosening (DL), and minimum tillage (MT). It also provides bulk density data, soil moisture content at various suctions and the parameters of van Genuchten's model for 27 soil cores, and saturated hydraulic conductivity (Ks) of 49 soil cores. Both sample sets were sampled to cover the profile heterogeneity in two agricultural plots subjected to moldboard plowing and minimum tillage. Examples of reuse potential include (i) the use of these spatially explicit data in studies seeking to understand better and integrate the effect of treatment and machine traffic-induced soil structure in soil hydraulic and soil physical quality, and (ii) the development of pedotransfer functions with data incorporating the soil structural heterogeneity. This Data in Brief article complements the companion paper by Alonso et al. (2021) "A hybrid method for characterizing tillage-induced soil physical quality at the profile scale with fine spatial detail" in Soil and Tillage Research[1].

Disaggregating SDG-6 water stress indicator at different spatial and temporal scales in Tunisia.

The recently adopted UN Sustainable Development Goals (SDGs) encompasses a specific goal for water (SDG-6). The target 6.4 deals with water scarcity and refers to two main indicators: water use efficiency and water stress (WS), monitored by the UN statistical services yearly at the country level. Yet, for more efficient development planning, indicators should also be provided with higher spatial and temporal resolutions. This study presents a data-driven method allowing to disaggregate the WS indicator at higher spatial and temporal resolution. We applied the method for the Medjerda catchment in Tunisia, known as being severely water-stressed. We disaggregated the WS indicator from the overall catchment to the administrative regional level at yearly and monthly scales. In order to overcome poorly documented irrigation water withdrawals, two approaches were adopted: 1) we used yearly governmental data at both catchment and regions scales; 2) we replaced governmental irrigation data by remote sensing-based irrigation estimation. First Order Uncertainty Analysis (FOUA) was performed to characterize the uncertainty associated with the assessment of WS. Results reveal that the WS at the scale of the catchment increases considerably in recent years, exceeding 50% from 2005 and surpassing the 100% threshold in 2015 and 2016 (102%, 108% respectively). The two adopted approaches result in similar WS trends. However, the second approach yields higher WS values compared to the first approach (144% versus 108% in 2016). The monthly-disaggregated WS at catchment scale exhibits a similar increasing trend. The highest WS values are at the end of the fall and during the summer season, which is mainly due to the increasing demand for irrigation and drinking water. Siliana region is the most affected by WS, while Beja is the least affected. The FOUA shows that the integration of remote sensing-based irrigation data reduces the WS uncertainty.

Validating a continental-scale groundwater diffuse pollution model using regional datasets.

In this study, we assess the validity of an African-scale groundwater pollution model for nitrates. In a previous study, we identified a statistical continental-scale groundwater pollution model for nitrate. The model was identified using a pan-African meta-analysis of available nitrate groundwater pollution studies. The model was implemented in both Random Forest (RF) and multiple regression formats. For both approaches, we collected as predictors a comprehensive GIS database of 13 spatial attributes, related to land use, soil type, hydrogeology, topography, climatology, region typology, nitrogen fertiliser application rate, and population density. In this paper, we validate the continental-scale model of groundwater contamination by using a nitrate measurement dataset from three African countries. We discuss the issue of data availability, and quality and scale issues, as challenges in validation. Notwithstanding that the modelling procedure exhibited very good success using a continental-scale dataset (e.g. R2 = 0.97 in the RF format using a cross-validation approach), the continental-scale model could not be used without recalibration to predict nitrate pollution at the country scale using regional data. In addition, when recalibrating the model using country-scale datasets, the order of model exploratory factors changes. This suggests that the structure and the parameters of a statistical spatially distributed groundwater degradation model for the African continent are strongly scale dependent.

Assessing cover crop management under actual and climate change conditions.

The termination date is recognized as a key management factor to enhance cover crops for multiple benefits and to avoid competition with the following cash crop. However, the optimum date depends on annual meteorological conditions, and climate variability induces uncertainty in a decision that needs to be taken every year. One of the most important cover crop benefits is reducing nitrate leaching, a major concern for irrigated agricultural systems and highly affected by the termination date. This study aimed to determine the effects of cover crops and their termination date on the water and N balances of an irrigated Mediterranean agroecosystem under present and future climate conditions. For that purpose, two field experiments were used for inverse calibration and validation of the WAVE model (Water and Agrochemicals in the soil and Vadose Environment), based on continuous soil water content data, soil nitrogen content and crop measurements. The calibrated and validated model was subsequently used in advanced scenario analysis under present and climate change conditions. Under present conditions, a late termination date increased cover crop biomass and subsequently soil water and N depletion. Hence, preemptive competition risk with the main crop was enhanced, but a reduction of nitrate leaching also occurred. The hypothetical planting date of the following cash crop was also an important tool to reduce preemptive competition. Under climate change conditions, the simulations showed that the termination date will be even more important to reduce preemptive competition and nitrate leaching.

Mapping the groundwater vulnerability for pollution at the pan African scale.

We estimated vulnerability and pollution risk of groundwater at the pan-African scale. We therefore compiled the most recent continental scale information on soil, land use, geology, hydrogeology and climate in a Geographical Information System (GIS) at a resolution of 15 km × 15 km and at the scale of 1:60,000,000. The groundwater vulnerability map was constructed by means of the DRASTIC method. The map reveals that groundwater is highly vulnerable in Central and West Africa, where the watertable is very low. In addition, very low vulnerability is found in the large sedimentary basins of the African deserts where groundwater is situated in very deep aquifers. The groundwater pollution risk map is obtained by overlaying the DRASTIC vulnerability map with land use. The northern, central and western part of the African continent is dominated by high pollution risk classes and this is very strongly related to shallow groundwater systems and the development of agricultural activities. Subsequently, we performed a sensitivity analysis to evaluate the relative importance of each parameter on groundwater vulnerability and pollution risk. The sensitivity analysis indicated that the removal of the impact of vadose zone, the depth of the groundwater, the hydraulic conductivity and the net recharge causes a large variation in the mapped vulnerability and pollution risk. The mapping model was validated using nitrate concentration data of groundwater as a proxy of pollution risk. Pan-African concentration data were inferred from a meta-analysis of literature data. Results shows a good match between nitrate concentration and the groundwater pollution risk classes. The pan African assessment of groundwater vulnerability and pollution risk is expected to be of particular value for water policy and for designing groundwater resources management programs. We expect, however, that this assessment can be strongly improved when better pan African monitoring data related to groundwater pollution will be integrated in the assessment methodology.

Quantifying hydrological responses of small Mediterranean catchments under climate change projections.

Catchment flow regimes alteration is likely to be a prominent consequence of climate change projections in the Mediterranean. Here we explore the potential effects of climatic change on the flow regime of the Thau and the Chiba catchments which are located in Southern France and Northeastern Tunisia, respectively. The Soil and Water Assessment Tool (SWAT) hydrological model is forced with projections from an ensemble of 4 climate model (CM) to assess changes and uncertainty in relevant hydrological indicators related to water balance, magnitude, frequency and timing of the flow between a reference (1971-2000) and future (2041-2071) periods. Results indicate that both catchments are likely to experience a decrease in precipitation and increase in temperature in the future. Consequently, runoff and soil water content are projected to decrease whereas potential evapotranspiration is likely to increase in both catchments. Yet uncertain, the projected magnitudes of these changes are higher in the wet period than in the dry period. Analyses of extreme flow show similar trend in both catchments, projecting a decrease in both high flow and low flow magnitudes for various time durations. Further, significant increase in low flow frequency as a proxy for hydrological droughts is projected for both catchments but with higher uncertainty in the wet period than in the dry period. Although no changes in the average timing of maximum and minimum flow events for different flow durations are projected, substantial uncertainty remains in the hydrological projections. While the results in both catchments show consistent trend of change for most of the hydrologic indicators, the overall degree of alteration on the flow regime of the Chiba catchment is projected to be higher than that of the Thau catchment. The projected magnitudes of alteration as well as their associated uncertainty vary depending on the catchment characteristics and flow seasonality.

Indirect estimation of the Convective Lognormal Transfer function model parameters for describing solute transport in unsaturated and undisturbed soil.

Solute transport in partially saturated soils is largely affected by fluid velocity distribution and pore size distribution within the solute transport domain. Hence, it is possible to describe the solute transport process in terms of the pore size distribution of the soil, and indirectly in terms of the soil hydraulic properties. In this paper, we present a conceptual approach that allows predicting the parameters of the Convective Lognormal Transfer model from knowledge of soil moisture and the Soil Moisture Characteristic (SMC), parameterized by means of the closed-form model of Kosugi (1996). It is assumed that in partially saturated conditions, the air filled pore volume act as an inert solid phase, allowing the use of the Arya et al. (1999) pragmatic approach to estimate solute travel time statistics from the saturation degree and SMC parameters. The approach is evaluated using a set of partially saturated transport experiments as presented by Mohammadi and Vanclooster (2011). Experimental results showed that the mean solute travel time, µ(t), increases proportionally with the depth (travel distance) and decreases with flow rate. The variance of solute travel time σ²(t) first decreases with flow rate up to 0.4-0.6 Ks and subsequently increases. For all tested BTCs predicted solute transport with µ(t) estimated from the conceptual model performed much better as compared to predictions with µ(t) and σ²(t) estimated from calibration of solute transport at shallow soil depths. The use of µ(t) estimated from the conceptual model therefore increases the robustness of the CLT model in predicting solute transport in heterogeneous soils at larger depths. In view of the fact that reasonable indirect estimates of the SMC can be made from basic soil properties using pedotransfer functions, the presented approach may be useful for predicting solute transport at field or watershed scales.

Identification of the nitrate contamination sources of the Brusselian sands groundwater body (Belgium) using a dual-isotope approach.

Isotopic fingerprinting is an advanced technique allowing the classification of the nitrate source pollution of groundwater, but needs further development and validation. In this study, we performed measurements of natural stable isotopic composition of nitrate ((15)N and (18)O) in the groundwater body of the Brussels sands (Belgium) and studied the spatial and temporal dynamics of the isotope signature of this aquifer. Potential nitrogen sources sampled in the region had isotopic signatures that fell within the corresponding typical ranges found in the literature. For a few monitoring stations, the isotopic data strongly suggest that the sources of nitrate are from mineral fertiliser origin, as used in agriculture and golf courses. Other stations suggest that manure leaching from unprotected stockpiles in farms, domestic gardening practices, septic tanks and probably cemeteries contribute to the nitrate pollution of this groundwater body. For most monitoring stations, nitrate originates from a mixing of several nitrogen sources. The isotopic signature of the groundwater body was poorly structured in space, but exhibited a clear temporal structure. This temporal structure could be explained by groundwater recharge dynamics and cycling process of nitrogen in the soil-nitrogen pool.

Solid respirometry to characterize nitrification kinetics: a better insight for modelling nitrogen conversion in vertical flow constructed wetlands.

We developed an original method to measure nitrification rates at different depths of a vertical flow constructed wetland (VFCW) with variable contents of organic matter (sludge, colonized gravel). The method was adapted for organic matter sampled in constructed wetland (sludge, colonized gravel) operated under partially saturated conditions and is based on respirometric principles. Measurements were performed on a reactor, containing a mixture of organic matter (sludge, colonized gravel) mixed with a bulking agent (wood), on which an ammonium-containing liquid was applied. The oxygen demand was determined from analysing oxygen concentration of the gas passing through the reactor with an on-line analyzer equipped with a paramagnetic detector. Within this paper we present the overall methodology, the factors influencing the measurement (sample volume, nature and concentration of the applied liquid, number of successive applications), and the robustness of the method. The combination of this new method with a mass balance approach also allowed determining the concentration and maximum growth rate of the autotrophic biomass in different layers of a VFCW. These latter parameters are essential inputs for the VFCW plant modelling.

Including spatial variability in Monte Carlo simulations of pesticide leaching.

A methodology is developed to quantify the uncertainty in a pesticide leaching assessment arising from the spatial variability of non-georeferenced parameters. A Monte Carlo analysis of atrazine leaching is performed in the Dyle river catchment (Belgium) with pesticide half-life (DT50) and topsoil organic matter (OM) content as uncertain input parameters. Atrazine DT50 is taken as a non-georeferenced parameter, so that DT50 values sampled from the input distribution are randomly allocated in the study area for every simulation. Organic matter content is a georeferenced parameter, so that a fixed uncertainty distribution is given at each location. Spatially variable DT50 values are found to have a significant influence on the amount of simulated leaching. In the stochastic simulation, concentrations exist above the regulatory level of 0.1 microg L(-1), but virtually no leaching occurs in the deterministic simulation. It is axiomatic that substance parameters (DT50, sorption coefficient, etc.) are spatially variable, but pesticide registration procedures currently ignore this fact. Including this spatial variability in future registration policies would have significant consequences on the amount and pattern of leaching simulated, especially if risk assessments are implemented in a spatially distributed way.

Discriminating between point and non-point sources of atrazine contamination of a sandy aquifer.

This study analyses the sources of atrazine contamination in the Brusselian sandy aquifer of central Belgium. Atrazine has in the past been used for both agricultural and non-agricultural applications, but it is difficult to distinguish the contamination originating from these two sources. The spatial and temporal covariance of atrazine concentrations was studied by fitting semi-variogram models to monitoring data. Correlation ranges were found to be 600 m and 600-700 days, respectively. The results were used to apply a declustering algorithm before examining the distribution of atrazine concentrations measured in groundwater. Monitoring data appeared to follow a pseudo-lognormal distribution, as a lognormality test was negative. An inflexion point on the cumulative density function was thought to indicate the two different pollution processes, i.e., agricultural and non-agricultural contamination sources. A non-parametric one-way analysis of variance suggested that the vast majority of atrazine in groundwater was from non-agricultural, point sources. This was supported by the strong relationship between mean concentrations and land use, whilst other environmental variables, such as soil organic matter or groundwater depth, produced less meaningful results.