Mesoporous biochar reshapes soil water dynamics under shallow groundwater: interactions with nitrogen management

Shallow groundwater tables influence nearly one-quarter of global croplands, yet the role of biochar in such hydropedological settings remains poorly understood. This study investigated how mesoporous biochar interacts with nitrogen fertilization to modify soil properties, water dynamics, and irrigation requirements in a clay loam soil of the Nile Delta, Egypt. A two-season field experiment using randomized complete block design tested biochar (35 t ha^-1) combined with three nitrogen levels (100, 80, and 50% of the common farmer practice). Biochar significantly increased available N, Ca, and Mg and altered soil moisture profile: Instead of monotonic moisture increase typical of shallow groundwater conditions, an S-shaped distribution developed within the 0–30 cm layer. Drainage losses consistently declined when biochar was combined with moderate nitrogen input. Although crop yield and fruit quality responses were not statistically significant, the biochar-nitrogen combination reduced irrigation demand by ~82 m³ ha^-1 yr^-1 compared to conventional management. When scaled regionally under same environmental conditions, this strategy could save >80 million m³ of irrigation water annually in Egypt, assuming 100% irrigation efficiency. These findings show that mesoporous biochar can reshape root-zone water dynamics under shallow groundwater, offering a promising strategy to enhance water-use efficiency in water-scarce regions.

1 Introduction

Biochar, a carbon-rich by-product of biomass pyrolysis, is widely studied as a soil amendment for improving fertility, water retention, and soil structure (1–5). Its porous structure enables adsorption of nutrients and water, thereby reducing leaching and enhancing resilience to stresses such as salinity and drought (6–9). However, biochar effects are highly variable, depending on feedstock, pyrolysis conditions, and soil texture, with fine-textured soils often showing weaker or even negative responses compared to sandy soils (1, 10, 11). Recent research has also emphasized that biochar does not consistently improve soil physical properties, especially in fine-textured or clay-rich soils. Hydrophobicity, particle size, and pore structure can limit infiltration and water entry into biochar particles, reducing the expected gains in water retention and aggregate stability (12, 13). In some cases, biochar may decrease pore connectivity or alter cation exchange capacity, thereby restricting aeration and hydraulic conductivity and leading to neutral or even negative effects on soil structure (14, 15).

Most biochar research has been conducted under conventional irrigation and free-drainage conditions. In contrast, shallow groundwater table influence 22–32% of global croplands (16–18), including large areas of the Nile Delta, Argentine Pampas, US Corn Belt, and Western Siberia (19–23). Such hydrological settings affect soil water availability through capillary rise but can also cause waterlogging and salinization (24, 25). Biochar may alter hydraulic conductivity and moisture retention (26, 27), yet its performance under sustained shallow groundwater influence remains poorly understood.

Nitrogen fertilization is another key driver of soil–plant interactions. While essential for crop productivity (28–30), excessive nitrogen contributes to nitrate leaching and greenhouse gas emissions (31, 32). Biochar has the potential to improve nitrogen use efficiency by adsorbing ammonium and nitrate, supporting microbial cycling, and moderating leaching (33–36). Yet, the combined effects of biochar and nitrogen fertilization on soil water dynamics remain largely unexplored in shallow groundwater environments.

Long term studies indicate that biochar undergoes physical, chemical, and biological aging in soil leading to fragmentation and interactions that alter microbial activity and soil structure. Consequently, initial improvements in bulk density, porosity, and water retention may diminish over time, particularly in fine textured soils (37–39). However, most long-term assessments extend for less than a decade, and aging dynamics remain highly site-specific, depending on soil type, climate, and biochar properties. These uncertainties underscore the importance of evaluating how mesoporous biochar influence soil water behavior under field conditions affected by shallow groundwater.

This study addresses this gap through a two-season field experiment in the Nile Delta, Egypt. We tested the hypothesis that mesoporous biochar interacts with nitrogen fertilization to (i) modify soil physical and chemical properties, (ii) reshape soil water dynamics and irrigation requirements under shallow groundwater, and (iii) maintain crop performance while improving water use efficiency. By including a regional scaling analysis, we also evaluate the broader water-saving potential of this management strategy across Egypt and the Middle East and North Africa (MENA) region.

2 Materials and methods

2.1 Site description and baseline soil properties

The field experiment was conducted at the experimental farm of the Arid Lands Agricultural Studies and Research Institute (ALARI), Ain Shams University, Egypt (31.24475° E, 30.116° N, 21 m a.s.l.). The site is characterized by a clay loam soil texture (34.42% clay and 35.92% silt). It has an arid climate with negligible annual rainfall. Weather data were obtained from the ALARI weather station (https://ng.fieldclimate.com). Mean maximum and minimum air temperatures during season 1 (spring 2023) were 33. 5 ± 3.9 °C and 20.2 ± 3.3 °C, respectively, while during season 2 (autumn 2023) they were 26.0 ± 4.9 °C and 15.1 ± 5.1 °C, respectively. The average reference evapotranspiration ranged from 4.0 ± 0.6 mm day^-1 in season 1 to 1.5 ± 0.5 mm day^-1 in season 2)Supplementary Figure 1).

Before transplanting, the soil was ploughed and amended with 48 m³ ha^-1 compost and 950 kg ha^-1 calcium sulphate. A commercial corn cob-derived biochar, available in the Egyptian market, was incorporated into the 0–30 cm soil layer of the biochar plots at 35 t ha^-1 following (40). Following soil bed preparation and biochar incorporation, the field was left undisturbed for one week before transplanting to allow soil physical conditions to stabilize. The biochar was characterized prior to application to determine its surface area and pore structure. Nitrogen adsorption–desorption isotherms were obtained using a BELSORP-miniX analyzer at 77 K. The BET (Brunauer–Emmet–Teller) and BJH (Barrett–Joyner–Halenda) methods (41) were applied to determine surface area pore size distribution. The biochar exhibited a BET surface area of 3.53 m² g^-1, a total pore volume of 0.0076 cm³ g^-1, and an average pore diameter of 8.56 nm, confirming its mesoporous structure. Full isotherm and pore distribution data are provided in Supplementary Table 2 to ensure transparency and reproducibility. Since the biochar was commercially sourced, specific pyrolysis conditions were not available from the supplier.

2.2 Experimental design and treatment

A randomized complete block design (RCBD) with three replicates was employed (Figure 1). The experiment evaluated the interaction between biochar and application of nitrogen fertilization rate on soil moisture content, crop yield, water productivity, and irrigation water savings. Treatments combined two levels of biochar (absent or applied at 35 t ha^-1) with three nitrogen rates corresponding to 100%, 80%, and 50% of the common farmer practice. Accordingly, six treatments were established. Treatment W1: 100%N without biochar (control), W8: 80%N without biochar, W5: 50%N without biochar, B1: 100%N with biochar, B8: 80%N with biochar, and B5: 50%N with biochar. Each experimental plot measured 5.5 m × 2.3 m and was hydraulically isolated using 30cm-wide and 70 cm-deep ditches to prevent lateral movement between plots. All plots were initially irrigated to saturation before transplanting to ensure uniform soil moisture conditions at the start of the experiment.

Figure 1

Figure 1. Experiment RCBD statistical design. Treatments include biochar amended plots (B1, B8, and B5) and unamended plots (W8, and W5) vs the control treatment W1 (common practice).

Nitrogen was supplied as ammonium sulphate and ammonium nitrate in four splits at 15, 50, 70, and 90 days after transplanting (DAT). Seasonal totals were 300, 240, and 150 kg N ha^-1 for 100, 80, and 50% treatments, respectively. Detailed per-plot rates are shown in Supplementary Table 1. Micronutrients were foliar applied starting 30 DAT and repeated every 15 days until fruit ripening: 0.5 g L^-1 chelated Zn, Fe, and Mn, and 1.5 g L^-1 potassium sulphate.

2.3 Irrigation management and soil water monitoring

Irrigation was delivered weekly via a drip irrigation system with a dedicated valve for each subplot. Irrigation water volumes were calculated to restore the root zone field capacity using the following equation.

$$I=({\theta }_{fc}-{\theta }_i)\times A\times Z$$

where I is irrigation water (m³), ${\theta }_{fc}$ is volumetric soil water content at field capacity, ${\theta }_i$ is volumetric soil water content at irrigation time, A is plot area, and Z is effective root zone depth (m).

The applied irrigation water volume was measured using flowmeter installed on the submain irrigation line.

Volumetric SWC was monitored daily with a TDR (Time Domain Reflectometry) probe (PR2/6, Delta–T Devices Ltd., UK) at depths of 10, 20, 30, 40, 60, and 100 cm. Irrigation scheduling was based on maintaining root zone was considered 0–25 cm during the first 30 days after transplanting and 0–40 cm thereafter. This approach ensured SWC did not fall below 50% of available water, following recommendations for tomato (42).

Calibration was performed by taking soil samples simultaneously with TDR readings. Gravimetric water content was measured in the field laboratory following (43) and volumetric SWC was calculated as $\text{gravimetric }SWC \times (bulk density/water density)$. Calibration equation was derived by linear regression, and model fit assessed using R², RMSE, MAE, and residual diagnostics. Because SWC at 100 cm depth was consistently saturated, this layer was considered the shallow water table boundary.

2.4 Crop management, sampling and analysis

Tomato (Lycopersicon esculentum Mill.) cultivar K186 (Rich Zoan) seedlings were transplanted in two seasons. Season 1 (spring 2023) ran from 6 April to 9 July; season 2 (autumn 2023) from 25 September 2023 to 23 January 2024. Harvesting was conducted from the central 1 m² of each plot to minimize border effects. Fruit samples were analyzed for lycopene, moisture content, and total soluble solids (TSS) following standard procedures (44, 45).

Soil pH and EC were measured in a 1:2.5 soil–water suspension, while total available macronutrients were determined after extraction/digestion following established protocols (46, 47). Full details and instrument specifications are provided in [(48); Zenodo. https://doi.org/10.5281/zenodo.17195601].

2.5 Soil hydraulic properties

Composite soil samples (0–20 and 20–40 cm) were collected at the start of the experiment. Soil water content at field capacity (≈ −330 cm matric potential) and permanent wilting point (≈ −15, 000 cm) were measured using a pressure plate apparatus (49). Bulk density was determined by the core method (43).

Soil water flux was calculated dynamically using the Buckingham–Darcy law (50, 51) expressed as:

$$q=-K(\theta )\times (\frac{dh}{dz}+1)$$

where q is soil water flux (cm day^-1), defined as positive for upward capillary rise and negative for downward drainage, $K(\theta )$ denotes the unsaturated hydraulic conductivity (cm day^-1), and dh/dz is the matric potential gradient driving water movement.

Water retention characteristics were described using the van Genuchten model (52), with residual (θ_r) and saturated water content (θ_s) estimated from soil bulk density and particle size distribution. The shape parameters α and n were derived from pedotransfer functions based on sand and clay contents, while unsaturated conductivity functions were calculated following (53). For each depth and treatment, time-series of volumetric SWC obtained from calibrated TDR data (θ) is used to compute effective saturation, K(θ), matric gradients, and resulting fluxes.

2.6 Water productivity and irrigation water savings

Water productivity (WP) was calculated as yield per unit of applied irrigation (54).

$$W{P}_i=\frac{Y_i}{I_i}$$

where Y_i is yield (kg ha^-1) and I_i is applied irrigation (m³ ha^-1)

Irrigation water savings relative to the conventional agricultural practice (W1 = 100% N without biochar) was calculated as:

$$W{S}_t=I_{w1}-I_t$$

where $W{S}_t$ is mean water saved (m³ ha^-1), $I_{w1}$ is irrigation water for the relative baseline treatment, and $I_t$ mean irrigation water for t treatment.

2.7 Statistical analysis and visualization

All statistical analysis were conducted in R version 4.5.1 (R Core Team, 2024). Descriptive statistics (mean, standard error) were computed for all measured variables.

Tomato yield, fruit quality attributes (lycopene, total soluble solids, fruit moisture), and soil chemical properties (N, P, K, Mg, pH, EC) were analyzed using analysis of variance (ANOVA) within a split-plot RCBD framework. Biochar (with vs without), nitrogen fertilization rate (100, 80, 50% of the recommended dose), and season (spring vs autumn) were treated as fixed factors, and block was included as a random factor. When ANOVA indicated significant effects, pairwise comparisons among treatments were conducted using Tukey’s honestly significant difference (HSD) test at α = 0.05.

SWC calibration was first calibrated by linear regression of gravimetrically determined volumetric SWC against TDR probe output. Model performance was assessed using the coefficient of determination (R²), root mean square error (RMSE), mean absolute error (MAE), and residual diagnostics. Repeated SWC observations across depths (10–100 cm) were analyzed wit linear mixed-effects models (packages Ime4, ImerTest). Fixed effects included biochar treatment, nitrogen rate, season, and depth, with random intercepts specified to account for repeated measurements within plots. Competing models were compared using Akaike’s information criterion (AIC), and the best-fitting model was used to estimate marginal means and perform pairwise contrasts with Tukey adjustment (emmeans package). Model assumptions were checked by visual inspection of residual plots and tested formally with the Shapiro–Wilk test for normality and Levene’s test for homogeneity of variances. Soil water flux values were summarized by treatment and season, with mean ± standard error reported. Treatment effects were tested using analysis of variance (ANOVA) with biochar, nitrogen rate, and season as fixed factors, followed by Tukey’s HSD for pairwise comparisons.

Data visualization was performed using the ggplot2 package. Boxplots and line graphs were used to display treatment effects on SWC, yield, fruit quality traits, and soil chemical properties, with treatment means and standard errors overlaid. Diagnostic plots (residuals vs. fitted, Q-Q plots) were examined to confirm model assumptions. Full R scripts for ANOVA, mixed models, soil water parameters estimation, and diagnostic figures are provided in [(48); Zenodo. https://doi.org/10.5281/zenodo.17195601] to ensure reproducibility.

3 Results

3.1 Biochar characterization

The adsorption/desorption isotherms, BET and BJH plots for the applied biochar are illustrated in Figure 2. The summary of the physicochemical characterization data for biochar sample via nitrogen physisorption analysis is documented in Supplementary Table 2. The adsorption/desorption isotherms confirmed that the applied biochar was mesoporous, exhibiting a type IVa profile (55). Pore diameter averaged 8.56 nm, with a pore volume of 0.00756 cm³ g^-1, while the BET surface area was relatively low (3.53 m² g^-1). The hysteresis loop indicated capillary condensation in mesopores, consistent with nitrogen physisorption patterns (41). Although surface area was low, the predominance of mesopores suggested functional capacity for water and nutrient interactions.

Figure 2

Figure 2. (a) N₂ adsorption/desorption isotherms, (b) BET surface area, and (c) BJH pore distribution confirming the mesoporous structure of the applied biochar.

3.2 Soil nutrient retention and chemical properties

Biochar application significantly increased available N, Ca, and Mg (p<0.05), while pH, total N, total P, available P, and K remained largely unchanged. Soil parameters that significantly changed in response to biochar application are illustrated in Figure 3. Parameters with non-significant change in response to biochar application compared to control are presented in Supplementary Table 3. A slight increase in soil EC was observed due to higher Na and Cl concentrations.

Figure 3

Figure 3. Soil nutrient concentrations and EC significantly affected by biochar compared with control (p<0.05).

Soil properties before and after biochar application are summarized in Table 1. Biochar caused a slight, non-significant reduction in bulk density, reflecting the lower density of biochar particles and their role in aggregation. More importantly, soil water content at both field capacity (Θ_fc) and permanent witling point (Θ_PWP) increased with biochar incorporation (Table 1). However, total available water (TAW) decreased, indicating that the observed increase in Θ_fc and Θ_PWP did not translate into greater plant-available water in this fine-textured soil. This finding suggests a shift toward finer mesopores that retain water too tightly to be available to plants. Such pore scale changes correspond with the depth-specific hydraulic conductivity response, where conductivity decreased in the upper 0–20 cm layer but increased in the 20–40 cm layer.

Table 1

Table 1. Soil properties (bulk density, Θ_FC, Θ_PWP, TAW, conductivity, pH, EC) before and after biochar application at 0–20 and 0–40 cm depths.

In the surface layer (0–20 cm), soil hydraulic conductivity was reduced from 1.23 cm h^-1 in the control to 1.13 cm h^-1 in the biochar-amended soils. On the contrary, the deeper layer (20–40 cm) observed an improvement in soil hydraulic conductivity in biochar amended soil (1.24 cm h^-1) compared to the control treatment (1.04 cm h^-1).

3.3 Soil water flux

The regression analysis revealed a strong significant relationship between measured SWC and TDR readings (p<0.001, 95% CL = 0.75–0.93, Figure 4). the calibration equation was derived as:

Figure 4

Figure 4. Relationship between measured SWC in the laboratory and TDR field measurements used for calibration.

$$SWC=6.84+0.505\times TDR$$

This model explained 74% of the variance (R² = 0.74), with low prediction errors (RMSE = 6.4%, MAE = 5.0%). Diagnostic tests confirmed homoscedastic residuals (Breusch–Pagan p = 0.42) and only minor deviations from normality (Shapiro–Wilk p = 0.043). These results demonstrate that TDR provides a reliable proxy for SWC estimation in the studied soil profile.

Mean soil water fluxes are shown in Figure 5. The estimated marginal mean SWC values with their corresponding 95% confidence limits (CLs) are provided in Supplementary Table 4. Across both seasons, water fluxes were predominantly downward (negative values), consistent with drainage losses. Treatments differed significantly (p<0.05), and seasonal differences in drainage were dependent on treatment. Biochar combined with 80% nitrogen (B8) consistently minimized drainage, particularly in season 2, where losses were significantly lower (−0.012 cm d^-1, 95% CL: −0.025 to −0.001) compared with season 1 (−0.013 cm d^-1, 95% CL: −0.023 to 0.002). This indicates that moderate nitrogen supply optimized the soil–biochar interaction to reduce drainage losses under lower ET demand. Conversely, the B1 treatment exhibited greater drainage in season 1 (−0.034 cm d^-1, 95% CL: −0.044 to −0.023) than in season 2 (−0.021 cm d^-1, 95% CL: −0.035 to −0.008). The B5 treatment showed no significant seasonal variation. In contrast, the non-biochar treatments (W1, W5, and W8) exhibited minimal or statistically insignificant seasonal differences, indicating that the observed seasonal response was driven primarily by biochar–nitrogen interactions rather than irrigation regime alone.

Figure 5

Figure 5. Mean soil water flux and standard error per treatment during the two seasons. Different lowercase letters indicate significant difference at p<0.05.

3.4 Soil water content dynamics

Figure 6 illustrates vertical SWC distribution across soil depths in control and biochar-amended soils. Without biochar, SWC increased monotonically with depth, typical of shallow groundwater profiles. In contrast, biochar induced an S-shaped SWC profile, with greater retention in the 0–30 cm layer and a dip at 40 cm before rising again near the water table.

Figure 6

Figure 6. Vertical distribution of volumetric soil SWC (%vol.) across soil depths in control (left) and biochar-amended soils (right) for two seasons. Shaded bands represent 95% confidence intervals.

The interaction between treatments and soil depth is further shown in Figure 7. The estimated marginal mean (± standard error) of SWC under different combinations of biochar application and nitrogen levels is presented at Supplementary Table 4. Mixed-effects modeling confirmed a strong biochar × nitrogen interaction (F = 123, p< 0.0001). Among treatments, B8 exhibited the largest reduction in SWC relative to controls, particularly at intermediate depth (20–40 cm). This pattern highlights the capacity of biochar to reshape vertical water distribution even in shallow groundwater conditions. Model comparison further supported the inclusion of this interaction, as the depth–season interaction model (model 4) yielded the lowest AIC (10, 647.91) and BIC (10, 760.09), with a ΔAIC > 96 relative to the next best model (model 3), indicating strong support for model 4 as the best-fit structure (Supplementary Table 5). However, because irrigation replenished soil moisture to field capacity after each cycle, these hydrological adjustments influenced WUE rather than crop yield response.

Figure 7

Figure 7. Interaction between biochar–nitrogen treatments and soil depth on mean SWC (%vol) across the study period.

3.5 Yield, quality, and irrigation water savings

Yield, fruit quality, and irrigation performance are summarized in Table 2. No statistically significant differences were detected across treatments. The absence of significant yield differences is consistent with the soil water flux and nutrient retention results, indicating that neither water availability nor nitrogen supply was limited under the experimental conditions. Although yield responses were muted, irrigation savings at scale could be agronomically and environmentally significant. The conventional practice of full irrigation and N fertilization (W1) was used as the baseline. The treatment B1 required the lowest irrigation volume (2435 m³ ha^-1; WP = 36.75 kg m^-3), saving 82.43 m³ ha^-1 relative to W1, while maintaining a comparable fresh yield of 85, 174 kg ha^-1, with 1.88% below W1. By contrast, the W8 treatment achieved the highest fresh yield (105, 776 kg ha^-1; +21.85%) but required 23.80% more irrigation water, resulting in lower WP (35.50 kg m^-3), indicating reduced water use efficiency. A similar trend was observed for W5, which used 34.76% more irrigation water to achieve only a 12.01% yield increase (WP = 29.70 kg m^-3). This indicates that biochar’s primary benefit under the present shallow groundwater and irrigation scheduling conditions was improved water productivity and use efficiency rather than yield productivity.

Table 2

Table 2. Irrigation volume, fresh yield, water productivity, water savings, and fruit quality parameters (TSS, moisture, lycopene) ± standard error for all treatments.

4 Discussion

4.1 Effects of biochar on soil nutrients and chemistry

The increase in available N, Ca, and Mg (Figure 3) can be attributed to biochar’s inherent cation content and its surface functional groups that adsorb and retain cations (56, 57). Enhanced microbial activity in biochar amended soils may also contribute to N mineralization and cycling (58, 59).

Despite low BET surface area, biochar’s mesoporous structure supports water and ion retention, which is especially relevant in fine textured soils. This highlights a surface area paradox: although high surface biochar enhances retention of larger molecules and nutrient via pore-filling and van der waals forces (60, 61). Thus, even low-surface-area biochar can be effective if mesoporosity dominates its structure.

4.2 Soil water retention and hydraulic changes

The observed increase in θ_fc and θ_pwp (Table 1) aligns with studies reporting improved retention at specific matric potentials under biochar (62, 63). However, the concurrent reduction in TAW reflects the interaction of biochar with fine-textured soils, where high inherent water-holding capacity may be disrupted (10, 64).

Reduced hydraulic conductivity in the topsoil but increased conductivity at 20–40 cm (Table 1) suggests redistribution of flow pathways (65). Specifically, biochar incorporation in the surface layer (0–20 cm) likely reduced macropore continuity by partially filling or bridging larger pores, thereby slowing vertical water movement near the surface. Meanwhile, percolating dissolved biochar particles may have enhanced aggregation and pore connectivity at 20–40 cm, facilitating preferential percolation pathways at depth. These findings indicate that biochar modifies not only soil water holding capacity but also the depth-specific balance between retention and conductivity.

The observed reduction in TAW, despite increase in both θ_fc and θ_pwp, likely reflects a shift toward water being retained in finer pores where it is held at higher matric tension and therefore less available to plants. In fine-textured soils, biochar particles can occupy or partially occlude inter-aggregate macropores, reducing pore continuity and promoting water retention in smaller pores – a process often described as pore clogging (12, 13). This aligns with our finding that hydraulic conductivity decreased in the 0–20 cm layer where biochar was incorporated. In contrast, the increase in conductivity observed at 20–40 cm suggests improved pore connectivity at depth, consistent with reports that organic amendments promote subsoil structural development and preferential flow channel stabilization in fine textured soils (15). Thus, the redistribution of flow pathways is characterized by reduced near-surface hydraulic transmission and enhanced deeper percolation channels. These findings suggest that biochar application in clay loam soils should be carefully managed to avoid reduction in plant-available water in the surface layer, possibly by adjusting application depth or combining with structure promoting soil amendments. These contrasting depth-specific responses highlight that biochar does not uniformly increase soil hydraulic function but instead redistributes water retention and flow pathways within the profile.

4.3 Water flux and vertical soil moisture profiles

The S-shaped SWC distribution under biochar (Figures 5, 6) contrasts with the monotonic profile of unamended soil with biochar and reveals a shift in soil water dynamics. This agrees with (66), who found enhanced SWC in biochar–N combinations within the root zone. In the upper 0–20 cm, biochar incorporation enhanced water retention, resulting in higher near-surface SWC. The middle layer (20–40 cm) exhibited a relative plateau or local minimum SWC, indicating reduced downward transmission through this zone. Below 60 cm, SWC increased again, reflecting the influence of the shallow groundwater table and capillary return.

This pattern differs from biochar effects in free draining soils, where deeper percolation often increases SWC at depth due to unrestricted drainage (39). In contrast, in our shallow-groundwater setting, limited vertical drainage and upward capillary feedback produce an S-shaped moisture structure driven by retention above and re-wetting below the root zone.

Across seasons, the B8 treatment reduced downward flux by approximately 0.010–0.022 cm d^-1 relative to the control (Supplementary Table 4). Corresponding to a reduction of about 30–45% in drainage losses. This redistribution supports greater water availability within the primary rooting zone, which may be advantageous in shallow groundwater systems where managing vertical water distribution is more critical than maximizing total storage.

4.4 Crop response and irrigation water savings

Although yield and fruit quality responses were statistically non-significant (Table 2), numerical differences are meaningful under water-scarce conditions. As discussed in Section 4.2, the reduction in TAW was mainly associated with water held at higher matric tension in finer pores, while plant-available water in the effective root zone remained sufficient due to shallow groundwater buffering. Similar inconsistencies in biochar yield responses have been reported, with stronger effects in nutrient-poor or coarse soils (67–69). In the present study the shallow groundwater table may have partially moderated treatment differences by contributing supplementary moisture through capillary rise. While upward fluxes were not directly quantified and downward drainage remained the dominant flux pathway, the consistent presence of groundwater within the capillary influence zone can buffer crop water stress and help explain the muted yield response (70, 71). In addition, further studies reported that shallow groundwater, waterlogging and reduced aeration may attenuate yield benefits (20, 72).

Nevertheless, the irrigation savings observed in B1 (Table 2) highlight biochar’s potential for improving water productivity without compromising yields. This aligns with recent studies demonstrating that biochar can increase soil water retention and improve WUE in clay and clay loam soils (73, 74). When extrapolated to Egypt’s tomato cultivation area of 990, 476 ha (75), this corresponds to approximately 65.3 to 81.6 million m³ yr^-1 of water saved assuming 80% and 100% irrigation efficiency, respectively under similar hydrological and environmental conditions. Extending this to the MENA region, where tomato cultivation covers 1, 414, 057 ha (76), the savings could reach about 92.8–116 million m³ yr^-1. Although the per-hectare savings may appear modest, their cumulative regional impact highlights a significant opportunity for improved water resources management even under conservative efficiency scenarios, with no yield penalties.

However, these regional estimates should be interpreted with caution, as soil texture groundwater depth, and irrigation practices vary widely across the MENA region. Multi-site field validation under constructing agro-hydrological settings would be necessary to confirm the scalability of the observed biochar–water interaction and to refine region-specific recommendation.

4.5 Implications and future research

These results confirms that biochar–N interactions extend beyond nutrient cycling to hydrological regulation. By reshaping soil moisture profiles (Figures 5, 6), biochar offers a mechanism to adapt irrigation in regions where shallow groundwater interacts with agriculture. Long-term trials and modelling are needed to capture cumulative effects and to evaluate interactions under variable climate and cropping systems.

5 Conclusions

This study demonstrates that biochar with a mesoporous structure can substantially modify soil hydrology under shallow groundwater conditions. Biochar increased soil water retention at field capacity and wilting point and, more importantly, reshaped the vertical soil moisture profile, creating an S-shaped distribution distinct from the conventional pattern. These effects were most evident in the incorporation zone (0–30 cm) and were amplified when combined with full or moderate nitrogen fertilization.

While short-term effects on tomato yield and quality were limited, the biochar + full nitrogen treatment reduced irrigation demand without compromising production, highlighting its potential for improving water productivity. Extrapolation of these results indicates that modest field-level savings can translate into substantial regional water conservation across Egypt and MENA region.

Overall, mesoporous biochar integrated with nitrogen management offers a soil-based strategy to regulate water dynamics under shallow groundwater, providing both hydrological and agronomic benefits. Long-term trials and mechanistic modelling are needed to further elucidate biochar’s role in enhancing soil–water functions under diverse pedoclimatic conditions.

Data availability statement

The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/Supplementary Material.

Author contributions

ME: Conceptualization, Data curation, Formal Analysis, Investigation, Methodology, Resources, Software, Validation, Visualization, Writing – original draft, Writing – review & editing. RG: Conceptualization, Investigation, Methodology, Writing – review & editing. ME-S: Conceptualization, Investigation, Methodology, Visualization, Writing – review & editing. MR: Methodology, Writing – review & editing. YB: Methodology, Visualization, Writing – review & editing. AA: Conceptualization, Funding acquisition, Investigation, Methodology, Project administration, Supervision, Writing – review & editing.

Funding

The author(s) declare that financial support was received for the research and/or publication of this article. This research was funded by the Egyptian Academy of Scientific Research and Technology (ASRT) under the Climate Change Action Plan (COP27 and Beyond Program, SAM-EGY).

Acknowledgments

The authors express their sincere appreciation to the Arid Land and Agriculture Research Institute (ALARI), Ain Shams University, Egypt, for their invaluable support throughout the experimental phase of this study. The Institute’s provision of essential equipment and timely access to relevant data significantly contributed to the successful execution of the research.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fsoil.2025.1718929/full#supplementary-material

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