Soil Water Storage Research Articles

Urban trees left high and dry – Modelling urban trees´ water supply and evapotranspiration under drought

Abstract Long-lasting extreme weather conditions are expected to occur more frequently in the future owing to climate change, as demonstrated by the recent heat waves. In particular, the decrease in precipitation during the summer months had a significant impact on urban tree water availability. Therefore, it is imperative to develop methodologies for determining the available water supply and evaporation rates for urban trees. We mapped data from 49 urban small-leaved linden trees with varying characteristics including groundwater levels, shading situations, tree pit sizes, pavement materials, and sealing ratios. By combining these data with an adapted Penman-Monteith method to calculate evapotranspiration, we simulated the soil water storage and evapotranspiration rates of these trees during the very dry year of 2018 as an example. Model validations were performed using lysimeter and sap-flow studies on Tilia cordata trees in 2022.
During the growing season, most trees experienced water stress on > 85% of the days because of weak precipitation events that failed to refill soil water storage. In contrast, trees with additional water supply through capillary rise reached water stress approximately 45 d later. The model results suggest that many trees will require additional water supply during predicted droughts in the future, which could have significant implications for urban forestry management. This model approach can be used to test and refine future water supply management strategies, making it a useful planning tool for improving the water efficiency of trees in urban areas and blue-green infrastructure.

Distribution characteristics of soil moisture and temperature under different land use types in the deep profile of loess area in northern Shaanxi, China.

Understanding the effects of different land use modes on the spatial and temporal variations of soil moisture and temperature in the deep profile and revealing the regulatory effects of various vegetation covers on regional water and heat resources can provide a theoretical basis for the optimization of land management and vegetation restoration. Taking the advantage of different land use patterns in the Liudaogou watershed in the northern part of Loess Plateau, we monitored soil moisture content as well as temperature in the 0-1000 cm soil layer in 2022 to analyze the temporal variation and vertical profile distribution characteristics of soil moisture and temperature under four land use modes (woodland, grassland, farmland, and wild grassland). The results showed that soil moisture and temperature distributions varied significantly across different land use types. In the growing season (April-October), total soil water storage in the 0-1000 cm soil layer of the four land use types, in a descending order, was as follows: soybean farmland (1393 mm), wild grassland (1374 mm), Caragana korshinkii forest (1218 mm), and alfalfa grassland (557 mm). Soil moisture of C. korshinkii forest and soybean farmland changed obviously in the 0-300 cm soil layer, and that of wild grassland and alfalfa grassland was in 0-500 and 0-200 cm soil layers, respectively, while soil moisture of deep soil layers fluctuated little. The impact of land use modes on soil temperature was primarily manifested in the 0-200 cm soil layer, and the depth was up to 300 cm. The depth of precipitation infiltration replenishment of the four land use modes was approximately 200 cm. The depth of soil moisture depletion was 200 cm in both C. korshinkii forest and alfalfa grassland, and was 100 cm in soybean farmland and wild grassland. Soil hydrothermal processes in the deep profile varied across vegetation types.

Assessing the change in soil water deficit characteristics from grassland to forestland on the Loess Plateau

Soil moisture is an important factor that affects terrestrial ecosystems and biological growth and development, and water deficit is one of the major environmental factors threatening vegetation restoration on the Loess Plateau. The purpose was to identify the change in the soil water deficit characteristics from grassland to forestland on the Loess Plateau. In this study, we measured the soil water storage and deficit in abandoned grassland, shrubland, pioneer forestland and climax forestland along with vegetation succession in situ monitor. The results showed that the soil water content and the soil water storage with natural vegetation recovery from the abandoned grassland to shrubland and forestland showed a gradual declining trend. While on the contrary, the soil water deficit was increasing during succession, it was more severe in the deep soil than in the shallow soil layers. And the soil water deficit in July and September of the rainy season as well as that the vigorous growing period of plants was more serious than that in May and November, which are in the non-rainy season on the Chinese Loess Plateau. The vegetation types and soil depth were the key factors affecting the soil water deficiency status in the process of vegetation succession. Water-saving measures should be taken during the vigorous growing period of plants especially for those forest with natural restoration ages >50a on the Loess Plateau. The results could have great potential in the sustainable development of forestry and provide a theoretical basis for effective water management and reasonable vegetation restoration in semiarid loess regions.

Integrating calibrated PTFs and modified OpenKarHydro framework to map the responses of ecohydrological processes to climate change across the Loess Plateau

Climate change is exacerbating the risk of soil water stress, soil erosion and ecological degradation in the Loess Plateau (CLP). However, the spatiotemporal dynamics of ecohydrological processes, including soil water balance (SWB), soil erosion (SE) and vegetation net primary productivity (NPP), in response to climate change remain isolated and ambiguous. Additionally, existing studies often rely on limited measured data from specific watersheds with particular land use/cover types to establish the pedotransfer functions (PTFs) for single soil hydraulic parameter (SHP). There is a notable lack of comprehensive studies that explore PTFs encompassing all SHPs applicable to the entire CLP, predict the spatiotemporal response of ecohydrological processes to climate change, and identify future risk periods and regions for SWB, SE, and NPP. To address these gaps, we first screened the PTFs applicable for the whole CLP, and then projected the spatiotemporal dynamics of ecohydrological processes from 2020 to 2030 under CMIP6 scenarios by integrating the PTFs with the OpenKarHydro, RUSLE, and CASA model, and finally classified the soil water content, SE and NPP to identify their risk periods and regions. The results showed that the PTFs achieved satisfactory accuracy, with RMSEs for Ks, θs, θr, α, n, θfc and θw being 2.682, 0.109, 0.016, 0.111, 0.897, 0.060 and 0.058, BIASs of 1.365, 0.182, 0.012, 0.031, 0.214, 0.057 and 0.048, R2s of 0.445, 0.500, 0.430, 0.400, 0.694, 0.453 and 0.453, and NSEs of 0.645, 0.737, 0.874, 0.349, 0.567, 0.756 and 0.458, respectively. SE decreased significantly from 2020 to 2030, with an average annual rate of −6.18 %. Soil water storage decreased significantly between 2020 and 2030, and declining from southeast to northwest. The proportion of area in the wet zone decreased by 4 %, while the proportion of area in the dry zone increased by 11.9 % from 2020 to 2030. The average NPP in 2020–2030 is 320.07 gC·m−2·a−1, with the largest in summer and smallest in winter, and decreasing from southeast to northwest. The NPP increased significantly in 2020–2030, with average annual value and rate of 19.61 gC·m−2·a−1 and 70.84 %, respectively. The NPP increased significantly in spring, summer and autumn, but remained stable in winter. This investigation bridges the gap between existing soil properties, missing SHPs, the strong regional applicability of PTFs, and isolated ecohydrological processes. It is promises to provide valuable insights into the response to climate change in the CLP and another water-limited regions.

Does afforestation increase soil water buffering? A demonstrator study on soil moisture variability in the Alpine Geroldsbach catchment, Austria

This study employed an operational monitoring network to measure soil moisture and runoff behaviour continuously in the Alpine catchment Geroldsbach-Götzens, Austria. We hypothesize that afforestation can have a positive impact on soil water buffering. To analyse the impact of soil properties and vegetation cover changes on soil water dynamics, four experimental plots were established on grassland and monitoring stations were installed in the forest. The rainfall test site is equipped with an automatic weather station to obtain meteorological observations, and weirs to measure surface runoff of natural occurring precipitation events and artificial rainfall simulations. In the plots, 200 soil moisture sensors were installed at five different depths, aimed to track and visualize infiltration and subsurface flow processes. Another twenty sensors monitored soil moisture at different afforestation stages in the forested part of the catchment. The measurements show that soils covered with young and old-growth forest have a higher and more stable soil moisture content than grassland and soils with a lack of vegetation throughout the seasons. We observed large spatial differences at plot scale, where the spatial variability of soil moisture increases with depth and is highest during convective precipitation. The initial conditions and rainfall characteristics play an important role in infiltration processes and soil water storage. Our rainfall test site demonstrated the challenges of innovative monitoring techniques and that it offers opportunities for more experiments to gather evidence-based data as input for flood models. Overall findings confirm the sponge effect of forest soils and indicate that afforestation as Nature-Based Solution reduces the temporal soil moisture variability, buffering soil water during precipitation events, which can be beneficial for runoff reduction in Alpine catchments.

Changes and driving factors of soil water in mixed-species plantations and different precipitation scenarios on the Loess Plateau of China

The implementation of the “Grain-for-Green” program in China led to the extensive introduction of artificial vegetation, thereby intensifying evapotranspiration and the overuse of water resources. Thus, selecting suitable ecological vegetation and planting patterns to save water is a major challenge in the region. Three typical plants were selected in the Loess Plateau of China. The plants had been growing for 13 years. The soil water dynamics were studied based on measurements and Hydrus-1D modeling simulations under different precipitation scenarios (wet, normal, and dry years) and planting patterns (Stipa monoculture (S), a mixture of Stipa and Medicago (SM), and a mixture of Stipa, Medicago, and Caragana (SMC)). The results indicated that the soil water contents with S and SM were 25 % and 8 % higher than the stable field water capacity (SFC), respectively, whereas the SMC was 33 % lower than the SFC in the 0–100 cm depth in relatively normal precipitation years. The evapotranspiration was lowest under S (296–524 mm), followed by SM (351–628 mm) and SMC (368–669 mm). The soil water storage were 19–91 % and 12–58 % higher under S and SM than SMC. The soil desiccation intensity was more severe under SMC (0.3–0.5) than SM (0.5–1.1) and S (0.6–1.4). The soil water storage increased significantly with the annual precipitation (P<0.05), and increased by 54–85 % in relatively abundant water scenarios compared with scarce water scenarios according to Hydrus-1D model simulations. Partial least squares path modeling demonstrated that the soil saturated hydraulic conductivity (path coefficient = 0.478) and soil porosity (–0.703) had significant effects on soil water storage (P<0.01). The results further suggested that using shallow-rooted grass as the dominant plant would reduce water usage in areas with water scarcity, and mixed-species plantations (i.e., a mixture of shallow-rooted and deep-rooted grass) could reduce the loss of sediment in regions.

Soybean Yield Simulation and Sustainability Assessment Based on the DSSAT-CROPGRO-Soybean Model.

In order to ensure national grain and oil security, it is imperative to expand the soybean planting area in the Xinjiang region. However, the scarcity of water resources in southern Xinjiang, the relatively backward soybean planting technology, and the lack of a supporting irrigation system have negatively impacted soybean planting and yield. In 2022 and 2023, we conducted an experiment which included three irrigation amounts of 27 mm, 36 mm, and 45 mm and analyzed the changes in dry mass and yield. Additionally, we simulated the potential yield using the corrected DSSAT-CROPGRO-Soybean model and biomass based on the meteorological data from 1994 to 2023. The results demonstrated that the model was capable of accurately predicting soybean emergence (the relative root mean square error (nRMSE) = 0, the absolute relative error (ARE) = 0), flowering (nRMSE = 0, ARE = 2.78%), maturity (nRMSE = 0, ARE = 3.21%). The model demonstrated high levels of accuracy in predicting soybean biomass (R2 = 0.98, nRMSE = 20.50%, ARE = 20.63%), 0-80 cm soil water storage (R2 = 0.64, nRMSE = 7.78%, ARE = 3.24%), and yield (R2 = 0.81, nRMSE = 10.83%, ARE = 8.79%). The biomass of soybean plants increases with the increase in irrigation amount. The highest biomass of 63 mm is 9379.19 kg·hm-2. When the irrigation yield is 36-45 mm (p < 0.05), the maximum yield can reach 4984.73 kg·hm-2; the maximum efficiency of soybean irrigation water was 33-36 mm. In light of the impact of soybean yield and irrigation water use efficiency, the optimal irrigation amount for soybean cultivation in southern Xinjiang is estimated to be between 36 and 42 mm. The simulation results provide a theoretical foundation for soybean cultivation in southern Xinjiang.

Responses of hydrological processes to vegetation greening and climate change in subtropical watersheds

Study regionXiangjiang River Basin (XRB) in subtropical China. Study focusVegetation changes have a substantial impact on the water cycle in watersheds. However, the responses of hydrological processes to vegetation changes in subtropical regions have not yet been thoroughly clarified. The primary objectives of this study were to quantify the sensitivity of hydrological variables to vegetation changes and to elucidate the contributions of vegetation greening and climatic changes to alterations in hydrological variables in the Xiangjiang River Basin (XRB). New hydrological insights for the regionEvapotranspiration (ET) exhibits a significant positive sensitivity to alterations in Leaf Area Index (LAI) in the XRB, while soil water storage (SW) and flow depth (Q) showed a significant negative sensitivity to LAI changes. Changes in LAI primarily result in increased ET and reduced SW and Q, while increased in precipitation leads to augmented ET, SW, and Q. Alterations in potential evapotranspiration have been associated with heightened ET and reduced SW and Q. From the perspective of relative contributions, LAI predominantly influences alterations in ET within the XRB; P and PET are the primary driver of shifts in SW; and P chiefly governs the variations in Q. Our results highlight the important impact of vegetation changes on hydrological variables in subtropical watersheds.

Optimization of soil hydrological properties in degraded grasslands by soil amendments

Soil amendments facilitate the restoration of degraded soil fertility and vegetation productivity. Soil hydrological functions are crucial for assessing soil degradation and restoration in grassland ecosystems. However, the manner in which soil amendments drive changes in the hydrological properties of grassland ecosystems at different soil depths remains unclear. In this study, we conducted a five-year soil amendment experiment in a semi-arid grassland of the Loess Plateau to evaluate the impact of aluminum sulfate (AS) and biochar (BC), both individually and in combination, on the hydrological properties of soil profiles. The results showed that AS significantly increased saturated water-holding capacity (SWHC) by 19.04 %, field capacity (FC) by 27.39 %, soil water storage (SWS) by 1.57 %, and saturated hydraulic conductivity (Ks) by 19.03 % in the upper soil layer (0–40 cm). BC application increased SWHC by 20.09 %, FC by 17.56 %, SWS by 12.94 %, and Ks by 16.66 % in the 0–40 cm soil layers. The combined effects of AS and BC optimized the soil hydrological properties by increasing SWHC, FC, SWS, and Ks by 25.74 %, 35.45 %, 18.47 %, and 25.80 %, respectively. These improvements were driven by significant changes in the soil organic matter, fine root biomass, total porosity, clay content, and soil bulk density. Notably, the soil amendments did not significantly affect the hydrological properties of the deep soil layer (40–80 cm). Our study demonstrated that the strategic use of AS and BC, particularly in combination, effectively enhanced soil fertility and hydrological functions, thereby increasing grassland ecosystem productivity. These findings offer critical insights for sustainable grassland management and highlight the potential of tailored soil amendments to restore and improve soil fertility and plant productivity in degraded grassland ecosystems.

Hydrological and pedological effects of combining Italian alder and blackberries in an agroforestry windbreak system in South Africa

Abstract. The Western Cape in South Africa is a water-scarce region which will likely receive less rainfall and higher air temperatures under projected climate change scenarios. The integration of trees within agricultural systems provides an effective measure for improving water retention on agricultural land. Studying an established and irrigated agroforestry system (AFS) combining alder (Alnus cordata (Loisel.) Duby) as a linear windbreak with a blackberry (Rubus fructicosus L.) crop, we explore the water use dynamics of the intercrop as influenced by the windbreak element by combining methods from hydrology, soil science and forestry disciplines. Our objective is to explore whether the AFS positively impacts the water balance by combining measurement campaigns to characterise the spatial variability of various key system properties with continuous monitoring. The campaigns encompassed extensive soil sampling to determine soil characteristics (nutrient concentrations, hydraulic conductivity, texture, water retention) in the laboratory as well as terrestrial laser scans of the field site, especially of the windbreaks. The continuous measurements covered meteorological, soil water content and soil water potential observations over a 6-month period (in summer). These were applied to understand soil water dynamics during rainstorms and dry spells, including root water uptake as well as soil water storage. We recorded a total of 13 rainfall events delivering 2.5–117.6 mm of rainfall with maximum intensities of 4.1 to 82.6 mm h−1. Further analyses showed that infiltration is likely dominated by preferential flow, with root water uptake potentially occurring in two depth zones corresponding to different plant communities. While soil water content varied by depth and was influenced by physical and environmental factors, it was generally higher in the intercrop zone than within the windbreak-influenced zone. During dry spells, soil water content did not drop below the water content of the permanent wilting point (&lt;-1500 kPa). Values corresponding to soil water tensions above 1000 kPa were recorded on several occasions; these were mitigated by irrigation and, thus, did not result in water stress. Nutrient distribution and soil physical properties differed near the windbreak in comparison to the blackberry crop, and the carbon sequestration potential is great in comparison to monoculture farming. We could demonstrate positive effects of the windbreak on the water balance and dynamics in the blackberry field site, even though questions remain as to the extent of these benefits and how they compared to disadvantageous aspects brought about by the presence of the trees (e.g. increased water usage). Irrigation did, in fact, shift the AFS from a water-limited regime to an energy-limited one.

A dataset of soil water storage of typical ecosystems in arid and semi-arid areas in China, 2005-2017

Soil water is one of the important components of the earth's water resources, and also the main source of water directly consumed by vegetation and crops. Therefore, the storage, recharge, consumption, renewal and balance of soil water are of great significance to agriculture, animal husbandry, forestry, ecological environment and water resources balance, especially for the arid and semi-arid region of China. We collect and sort out the long-term observation data of soil moisture from eight ecosystem observation and research stations of the Chinese Ecosystem Research Network (CERN) located in the arid and semi-arid region of China during 2005 - 2017, and generates the corresponding soil water storage dataset through quality control, spatial and temporal normalization, statistical calculation, in order to provide long-term data support for understanding distribution and change of soil water storage in typical ecosystems in arid and semi-arid areas of China.

Modeling the impact of long-term land use changes on deep soil hydrological processes in the Loess Plateau, China

Land use change can significantly affect soil hydrology in arid and semi-arid regions, making it crucial to understand the relationship between vegetation roots and soil moisture. Current models often fail to predict root growth and its impacts on water dynamics accurately. Our work presents a novel model that seamlessly integrates the Community Land Model (CLM) with the Soil & Water Assessment Tool (SWAT). Furthermore, it enhances the root module within the CLM, enabling more accurate simulations of dynamic root depth and distribution across varying tree ages. This improvement particularly considers the crucial processes of dormancy and plant maturity. Soil moisture and root patterns under apple trees of varying ages and in wheat fields on the Loess Plateau was analyzed. Our findings indicate that our dynamic root depth model outperforms traditional static models, and can accurately reflect soil moisture levels with high precision (R2 = 0.80–0.81; Nash-Sutcliffe efficiency (NSE) = 0.65–0.75). In contrast to methods that utilize fixed root depths, dynamic root simulation can provide new insights. As apple orchards mature, the roots of 22-year-old apple trees have been found to reach a depth of 21 m in the soil. Conversely, the maximum root depth of wheat is limited to 1.9 m. This latter finding aligns more closely with the measured root depths, highlighting the accuracy of dynamic simulations. This model reveals that older apple orchards show decreased soil moisture at greater depths (>20 m), contrasting with wheat fields that affect moisture mostly within the top 2 m. Our results underscore the crucial role of dynamic modeling in comprehending root-soil water interactions. Furthermore, they imply that extended orchard cultivation practices can lead to a substantial depletion of deep soil moisture. Specifically, over a period of 1 to 22 years, a water deficit of up to 85 mm yr−1 has been observed. For a 22-year-old forest, the D-D (dynamic distributions of coarse and fine roots) method calculates a significant cumulative deep Soil Water Storage loss. Over the course of 22 years, this loss amounts to 1664 mm, which is almost three times compare to the annual rainfall recorded. Such a large loss has the potential to significant impact on groundwater recharge. This highlights the need for careful consideration in future afforestation efforts to prevent increased soil aridity.

Old-growth Ficus trees provide soil water and carbon storage to urban greenspaces in a Brazilian metropolis

Urban flooding has been considered one of the most severe natural disasters around the world, and urban greenspaces can provide important flood regulation ecosystem services. In Belo Horizonte (Brazil), the woody vegetation, especially the old-growth Ficus trees, appears to protect an urban park against the flooding of the Arrudas river. Thus, we compared the soil water content, soil water-holding capacity, soil aggregation and porosity among a highly permeable urban park planted with herbaceous and woody species, including Ficus, a semi-permeable parking lot with only Ficus and an impermeable site without trees (Disturbed Site-DS). The soil water content and water holding capacity of the urban park did not differ from that of the Ficus site, but it was lower than DS. These results were correlated with soil organic matter (SOM) content, soil aggregation and porosity, suggesting that Ficus trees play an important role in the hydrological cycle. To understand how the Fiscus species provide such soil permeability, we compared the aboveground plant biomass, soil fertility and soil carbon sequestration (total soil carbon, soil organic matter, humic and fulvic acids and soil isotopic δ13 C) in plots with Ficus and without this species within the park as well as in a preserved urban forest and a disturbed square. The outstanding plant biomass produced by Ficus species explained the high soil carbon sequestration, particularly in humic organic matter, favouring soil aggregation, porosity and water retention. Therefore, Ficus species may be considered an exceptional C-sequestering species, contributing for soil stabilization and the hydrological cycle in urban greenspaces.

Modeling of cotton yield responses to different irrigation strategies in Southern Xinjiang Region,China

Southern Xinjiang region represents a prototypical oasis agricultural area, and cotton is the primary cash crop. The current cotton water productivity for this area remains room for improvement. In order to refine cotton drip irrigation strategy in Southern Xinjiang, this study combined field experiment with crop model simulation and prediction. In this experiment, two irrigation methods, furrow irrigation and drip irrigation, and different degrees of deficit irrigation were set up. The impacts of soil moisture on cotton yield and quality were assessed, with the additional utilization of the Root Zone Water Quality Model (RZWQM2) for simulating irrigation scenarios and predicting cotton yield field data showed that during the 2021–2022 growing season, drip irrigation significantly increased boll weight, yield, and Water Productivity compared to furrow irrigation. The deficit irrigation with 90 % of full irrigation during the flowering period resulted in the highest yield among all drip irrigation treatments, while simultaneously improving the fiber quality. The RZWQM2 model was calibrated and validated using 2021 and 2022 cotton field experimental data, respectively. The calibrated and verified RZWQM2 model shows good performance. In terms of soil water storage, cotton yield and evapotranspiration. The simulated value output by the model is close to the measured value in the field. Model prediction data suggest that there is still room for improvement in cotton yield, accompanied by an increase in evapotranspiration. But deficit irrigation below 80 % of the full irrigation quotas poses a notable risk of yield reduction. Targeting higher yields, the predicted scenario suggests an increase in water application (irrigation quota:314.8 mm). Additionally, this study proposes irrigation regimes with water savings of 10 % and 20 %, with irrigation quotas of 290.5 mm and 266.5 mm during the growth period, respectively. Based on this study, we provide a more detailed and reliable water-saving scheme for cotton drip irrigation in southern Xinjiang region.

Regenerative Practices Show Promise in Dryland Cotton Systems

AbstractRegenerative practices, such as no‐till and cover crops, are advocated for their positive impacts on soil health and the environment. Nevertheless, there are challenges associated with implementing these practices. The objective of this simulation study was to assess the potential for soil carbon sequestration, soil water storage, and cotton yield response when implementing regenerative practices in the water‐limited environment of the Texas Rolling Plains region. Earn 1 CEU in Sustainability by reading this article and taking the quiz.

Can rock surface flow derived from outcrops generate surface runoff in a rocky desertified area?

Rock surface flow, formed from exposed rock surfaces, is a unique form of runoff in rocky desertified areas with massive bedrock outcrops. The question of whether the rock surface flow promotes surface runoff formation continues to puzzle us. To address this problem, four sites with notable bedrock outcrops and different land use types were selected from a typical desertified area in Guizhou, China. Straight and concave rock-surface shapes that were the most capable of collecting rainwater were selected at each site. Soil infiltration and water storage capacity experiments were conducted to observe the infiltration and water storage properties of the soil closely adhering to the rock–soil interface (CRSI) of the bedrock outcrops by taking the soils far from the outcrops horizontally (FRSI) as the control, and to further explain the conditions for surface runoff formation via rock surface flow. Our results showed that the CRSI is more prone to producing surface runoff than the FRSI, which is attributed to its lower infiltration (stable infiltration rate of 0.2 to 192.6 mm/min) and water storage capacity (total reservoir 441.6 to 613.6 t/hm2) than that of FRSI (4.50 to 272.8 mm/min, 458.8 to 635.4 t/hm2). This phenomenon would be intensified after receiving the rock surface flow input. Concurrently, concave rock surfaces are more likely to promote surface runoff formation than straight rock surfaces, which are affected by the accumulation of rock surface shapes on rainwater. A discriminating condition for whether rock surface flow produces surface runoff at the CRSI is proposed based on the inversely proportional functional relationship between rainfall (rainfall intensity RI and amount RA) and the effective rock surface rainfall catchment area (ARS). When RI or RA exceeds the critical threshold, the surface runoff with mechanisms of excess infiltration or excess saturation is generated around bedrock outcrops. The discriminating equation will help increase surface runoff prediction accuracy in rocky desertified areas with exposed bedrock outcrops. These results help understand the importance and role of rock surface flow hydrologic processes in karst areas.

Combining signal decomposition and deep learning model to predict noisy runoff coefficient

Predicting runoff coefficient (Rc), as an indicator of the catchment’s response to the rainfall-runoff process, remains a persistent challenge using different modelling techniques, especially in catchments with strong human manipulation. This study investigates the efficiency of the Long Short-Term Memory (LSTM) method in predicting Rc for the Rur catchment, in Germany. The period from 1961 to 2021 is considered, which is subject to human intervention and significant urbanization especially in the northern part of the catchment. An LSTM structure is defined by employing inputs at a monthly resolution including temperature, precipitation, soil water storage, and total evaporation with a look-back window of 1 to 6 months to model noisy Rc data of the study area. Two approaches using either undecomposed or decomposed Rc were employed in conjunction with the LSTM method, to mitigate the impact of noise associated with Rc. The results show that in the case of undecomposed Rc, the best performance of the LSTM structure was obtained with a 4-month look-back window, yielding Nash-Sutcliffe efficiency (NSE) of 0.55, 0.46, and 0.15 for training, validation, and test sets, respectively. These results highlight inadequate accuracy in accounting for the presence of noise in Rc. Therefore, in the second novel approach, we used maximal overlap discrete wavelet transform (MODWT) to decompose the Rc up to level 3 to reduce the complexity and distribute the noise effects across each level. The new approach showed high accuracy in modelling noisy data of Rc with NSE values of 0.97, 0.95, and 0.90 for training, validation, and test sets, respectively. The obtained results underscore the pivotal role of decomposition techniques in conjunction with LSTM to account for the presence of noise, especially in catchments with strong human manipulation.

Divergent rainfall infiltration patterns on the Chinese Loess Plateau between growing and non-growing seasons after long-term revegetation

Rainfall infiltration into hillslopes on the Chinese Loess Plateau (CLP) undergoes noticeable changes during the growing season following long-term revegetation. However, infiltration patterns during the non-growing season have been understudied. In this study, we monitored soil moisture over three years (May 2016-December 2018) at 10-minute intervals, spanning five soil depths (10, 20, 40, 60, and 100 cm). Monitoring was conducted in both a forestland catchment and an adjacent grassland catchment on the CLP, with two monitoring sites per catchment: one downhill in the gully, and the other uphill on the slope. Our findings reveal pronounced seasonal variations in meteorological conditions and vegetation index. We observed divergent rainfall infiltration patterns and their governing factors between the growing (May to October) and non-growing seasons (November to April). During the growing season, rainfall facilitated a quicker response with shorter lag time (23.34 h vs. 56.84 h in the non-growing season) and noticeable soil moisture increments (up to 35.7 % cm3/cm3 vs. only up to 6.4 % cm3/cm3). The wetting depth often extended to 40–100 cm (compared to 10–40 cm in the non-growing season), with a higher wetting front velocity (17.44 mm/h vs. 6.24 mm/h) and an increased occurrence frequency of preferential flow (19.77 % vs. 9.72 %). The impact of rainfall amount and peak intensity on infiltration was more pronounced during the non-growing season, whereas, in the growing season, infiltration was additionally influenced by antecedent moisture conditions and vegetation type. Notably, in the growing season, the enhanced soil moisture recharge due to rainfall infiltration exceeded the rise in evapotranspiration, resulting in higher soil water storage. The findings of this study shed new light on seasonal infiltration dynamics on the greening CLP, contributing valuable insights into hillslope hydropedological processes post-revegetation.

Soil water dynamics and plant water uptake: Primeval mature vs. debris flow-developed half-mature subalpine fir stands in the eastern Tibetan Plateau

Natural disaster can disrupt soil structure and replace established vegetation with younger plants, altering the local hydrological processes. We used hydrogen and oxygen stable isotopes to examine soil water dynamics and plant water uptake patterns in two adjacent fir stands in the eastern Qinghai-Tibet Plateau: a primeval mature stand (MF, finer- textured soil) and a debris flow-developed half-mature stand (HMF, coarser-textured soil). Our results showed that the isotopic composition and soil gravimetric water content (SWC) in deep soil water in MF exhibited a more pronounced hysteresis pattern in response to precipitation compared to HMF, indicating lower turnover rate of soil water in MF. This was also confirmed by a smaller contribution of preferential flow to deep soil water in MF compared to HMF. The higher water storage (higher SWC values) and lower turnover rate of soil water suggest a higher soil water buffer capacity in MF. Additionally, both stands showed no significant difference in plant water sources, but plants in MF used more winter precipitation due to the lower soil water turnover rate. These differences suggest MF may be more vulnerable to water disasters, while HMF may be more susceptible to seasonal droughts under climate change. Our insights enhance understanding of hydrological processes linked to changing surface conditions and offer valuable information for managing forest water resources in mountainous regions.

Effects of Carbon-Based Modified Materials on Soil Water and Fertilizer Retention and Pollution Control in Rice Root Zone

To seek an appropriate stabilization and remediation scheme for cadmium (Cd) and arsenic (As) pollution in farmland, a typical polluted soil sample was selected from a mining area in Southwest China for a soil box simulation experiment. Biochar (BC), a modified type of biochar made from rice husk with different mass ratios of ferric chloride and rice husk, was set up (the mass ratio of ferric chloride to rice husk was 1:9 (defined as LFB), 3:7 (defined as MFB), and 5:5 (defined as HFB) and the control group (BL)) to explore the effects of soil water and fertilizer loss, the bioavailability of Cd and As, and the bioenrichment effects of plant organs during the growth period of rice. The results showed that the porous structure and large specific surface area of biochar effectively regulated soil aggregate composition and improved soil water holding capacity. Compared to the BL treatment, soil water storage under the four carbon-based material control modes increased from 8.98% to 14.52%. Biochar has a strong ion exchangeability and can absorb soil ammonium, nitrogen, and phosphoric acid groups, effectively inhibiting the loss of soil fertilizer. Biochar improves soil pH and reduces the specific gravity of exchangeable Cd. In addition, the oxygen-containing functional groups in biochar can react with metals in a complex manner. The diethylenetriaminepentaacetic acid (DTPA) concentrations of Cd in soils treated with BC, LFB, MFB, and HFB were 79.69%, 72.92%, 64.58%, and 69.27% lower, respectively, than those treated with BL. In contrast, the Fe3+ in ferric chloride combines with As after hydrolysis and oxidation to form amorphous ferric arsenate precipitates or insoluble secondary minerals. Therefore, the curing effect of the modified biochar on As was more potent than that of applied biochar alone. In conclusion, ferric chloride-modified biochar can effectively inhibit the effects of water and fertilizer loss in farmland soil and realize cross-medium long-term inhibition and control of combined Cd and As pollution.