Soil Hydrology Research Articles

Spatial variation of net methane uptake in Arctic and subarctic drylands of Canada and Greenland

The importance of uptake of atmospheric methane (CH4) in dry Arctic soils for the total Arctic CH4 budget is unresolved. This is partly due to lack of data on the spatial variability of net CH4 consumption and understanding of the main process drivers. We measured net CH4 consumption in Arctic and subarctic landscapes located in in Disko Bay Area and Kangerlussuaq in Western Greenland and in the St. Elias Range in the Yukon, Canada, respectively. Our aim was to characterize the in situ spatial variability of net CH4 uptake in hitherto unexplored Arctic dry upland soils to explore possible limits and environmental drivers across the Arctic geodiversity. Furthermore, we sampled soil for incubation experiments to investigate how net CH4 oxidation responded to changes in soil moisture in contrasting geomorphic settings and parent geological parent materials. We used a laser-based fast deployable chamber system for flux measurements. All studied sites were net sinks of atmospheric CH4 with an average flux −7.5 ± 5.6 μmol CH4 m-2h−1, that are in the upper range of reported net CH4 uptake fluxes in similar soils of the Arctic. The large observed spatial variability within all studied sites (coefficient of variation 50 – 120 %) highlights the need for careful research design allowing for many spatial replicates to achieve representative values. Sites with an active geomorphic environment (abrasion plateau, riverbeds, mountain tops) generally had lower than average net CH4 uptake. Our incubation studies revealed that subsurface CH4 oxidation is the main driver of net surface-atmosphere exchange and that net CH4 oxidation in these layers responded more to changes to soil moisture than in near surface layers. Our study shows surprisingly similar flux magnitudes of net CH4 uptake across widely different landscape forms and geologic parent material, but responding similarly to soil hydrology and geomorphic disturbance, indicating global controls on the net CH4 oxidation in these dry upland environments.

Analyzing the Influence of Conservation Tillage and Manure on Soil Parameter Modulations in Croplands.

Nowadays, when the human impact on the environment becomes prominent daily, specific steps are needed to mitigate or halt those changes. By far, agricultural land is most affected by the degradation process, leading to soil erosion and decreased soil quality. Sustainable measures are needed to find a solution to that problem. This study, located in an agricultural area in northwestern Croatia, gives an insight into how different tillage systems (conventional and conservation) with the addition of manure will affect soil physicochemical properties, hydrology response, and overall yield. To assess hydrological response, a rainfall simulator was used; meanwhile, soil samples were taken to determine bulk density, soil water content, water-stable aggregates, and soil organic matter. Soil water content did not show significant differences, whereas bulk density and penetration resistance yielded significantly higher values at 15-30 cm depth compared to 0-15 cm depth. Also, the conservation manure recorded lower bulk density and penetration resistance values than conventional tilled treatments. Water-stable aggregates and soil organic matter were severely affected by manure addition and yielded an increase after harvest. Hydrological response was delayed for the treatments with manure addition. Crop yield was also significantly higher for the conventional treatment with manure addition, whereas the control plots had lower yields. The results of this study show the positive aspects of conservation tillage, especially with manure addition, where soil quality is preserved or even increased.

Soil Hydrology Characteristics among Forest Type, Stand Age and Successive Rotation in Eucalyptus Plantations in Southern China

The water holding capacity of forest soil plays a crucial role in ensuring forest productivity, particularly in Eucalyptus urophylla plantations. In this study, we investigated the soil water holding capacity and hydrological properties of Eucalyptus in a subtropical area of Guangxi, China. Different stand ages (five years old, seven years old, and 15 years old) and successive rotations (first, second, and third) of Eucalyptus plantations were compared, with Cunninghamia lanceolata (Chinese Fir) and Pinus massoniana (Pine) plantations serving as references. Soil physical properties, soil hydrological parameters, and litter characteristics were analyzed to assess soil water retention and conservation variations. Our findings revealed that Eucalyptus and Chinese Fir plantation forests exhibit superior soil physical characteristics compared to Pine plantations, resulting in better soil water retention. However, an increase in the age of Eucalyptus plantations significantly diminished the capillary water holding capacity of the soil, despite an increase in surface litter accumulation and litter moisture content. Furthermore, successive rotations led to a notable reduction in soil capillary porosity, soil moisture content, soil saturated permeability, and overall soil water holding capacity. In addition, soil bulk density emerged as a critical factor relating to the hydrological characteristics of Eucalyptus plantation forests. Decreasing soil bulk density in Eucalyptus forests may offer potential for optimizing their water retention function. These results reveal that Eucalyptus management practices significantly alter the hydrological properties of soil through their effects on soil and litter properties, and consequently, stand age, rotation, and species mixing should be given intensive attention in maintaining the maximization of soil water holding capacity.

Evaluation of classical correlation functions from 2/3D images on CPU and GPU architectures: Introducing CorrelationFunctions.jl

Correlation functions are becoming one of the major tools for quantification of structural information that is usually represented as 2D or 3D images. In this paper we introduce ▪ open-source package developed in Julia and capable of computing all classical correlation functions based on imaging input data. Images include both binary and multi-phase representations. Our code is capable of evaluating two-point probability S2, phase cross-correlation ρij, cluster C2, lineal-path L2, surface-surface Fss, surface-void Fsv, pore-size P and chord-length p distribution functions on both CPU and GPU architectures. Where possible, we presented two types of computations: full correlation map (correlations of each point with other points on the image, that also allows obtaining ensemble averaged CF) and directional correlation functions (currently in major orthogonal and diagonal directions). Such an implementation allowed for the first time to assemble a completely free solution to evaluate correlation functions under any operating system with well documented application programming interface (API). Our package includes automatic tests against analytical solutions that are described in the paper. We measured execution times for all CPU and GPU implementations and as a rule of thumb full correlation maps on GPU are faster than other methods. However, full maps require more RAM and, thus, are limited to available RAM resources. On the other hand, directional CFs are memory efficient and can be evaluated for huge datasets – this way they are the first candidates for structural data compression of feature extraction. The package itself is available through Julia package ecosystem and on GitHub, the latter source also contains documentation and additional helpful resources such as tutorials. We believe that a single powerful computational tool such as ▪ presented in this paper will significantly facilitate the usage of correlation functions in numerous areas of structural description and research of porous materials, as well as in machine learning applications. We also present some examples as applied to ceramic, soil composite and oil-bearing rock samples based on their 3D X-ray tomography and 2D scanning electron microscope images. Finally, we conclude our paper with discussion of possible ways to further improve presented computational framework. Program summaryProgram Title: CorrelationFunctions.jlCPC Library link to program files:https://doi.org/10.17632/6gb9gfm3dw.1Developer's repository link:https://github.com/fatimp/CorrelationFunctions.jlLicensing provisions: MITProgramming language: JuliaSupplementary material: Numerous Jupiter notebooks with examples are available on the GitHub pageNature of problem: Correlation functions are invaluable universal statistical descriptors of structures used in numerous scientific fields such as astronomy, material science, rock and soil physics, hydrology and biology, to name just a handful of examples. While computational approaches are available in the literature for some functions, they are fragmented and are usually implemented in proprietary interpreted languages for CPU architecture alone.Solution method: We contribute an open source and cross-platform solution with well documented API for computation of all classical correlation functions from both 2D and 3D images on CPU and GPU architectures. The package computes correlation functions using two approaches: computation of correlation maps and computation along predefined directions. These two approaches can be thought of as an execution time - memory trade-off, but the choice may also depend on the application. The computations are based on a) fast Fourier transform with preprocessing steps such as cluster labeling or edge detection, and b) linear scan approach to evaluate correlation functions along predefined directions. Where justified, the algorithms can be executed on both CPU and GPU which results in high execution speed on modern hardware.

FLOODING AND LANDSLIDE POTENTIAL MAPPING OF PUBLIC HOUSING AFTER LANDUSED CHANGE

Semarang City, the capital of Central Java Province, is divided into three parts based on its topography: hills, lowlands, and coastal areas. As a result, the city is at risk of natural disasters. According to BNPB data from 2014 to 2023, Semarang City has the second-highest disaster history in Central Java Province, with 741 disaster events recorded. Floods and landslides are the most common disasters in the area. Permata Jangli Housing is located in the hills, where changes in land use have transformed the surrounding forest into road infrastructure. An analysis of hydrological data and soil characteristics at the site indicates that these changes have led to increased surface flow, resulting in an increased flood discharge. This is one of the reasons for the high potential for disaster. Therefore, it is essential to map the disaster potential in Permata Jangli Housing. Factors such as land use, rainfall intensity, soil texture, slope, and soil elevation affect flooding disasters, while rainfall intensity, slope, soil texture, and land use affect landslides. To assess and map the potential for disasters, we used overlay techniques with the QGIS application. Our findings indicate that Permata Jangli Residential area has a moderate potential for flooding, covering 68% of the area or 1.1 ha, and a high potential of 32% or 0.5 ha. In contrast, the potential for landslides in Permata Jangli is medium, covering 74% or 1.2 ha of the area, and high potential of 26% or 0.4 ha. In conclusion, our study emphasizes the importance of mapping disaster potential in areas with a history of natural disasters. By doing so, we can take preventive measures and mitigate the impact of disasters in the future.

Brine formation in cold desert, shallow groundwater systems: Antarctic Ca-Cl brine chemistry controlled by cation exchange, microclimate, and organic matter

Groundwater in the McMurdo Dry Valleys of Antarctica is commonly enriched in calcium and chloride, in contrast to surface and groundwater in temperate regions, where calcium chemistry is largely controlled by the dissolution of carbonates and sulfates. These Antarctic Ca-Cl brines have extremely low freezing points, which leads to moist soil conditions that persist unfrozen and resist evaporation, even in cold, arid conditions. Several hypotheses exist to explain these unusual excess-calcium solutions, including salt deliquescence and differential salt mobility and cation exchange. Although the cation exchange mechanism was shown to explain the chemistry of pore waters in permafrost cores from several meters depth, it has not been evaluated for near-surface groundwater and wetland features (water tracks) in which excess-calcium pore-water solutions are common. Here, we use soluble salt and exchangeable cation concentrations to determine whether excess calcium is present in water-track brines and if cation exchange could be responsible for calcium enrichment in these cold desert groundwaters. We show that calcium enrichment by cation exchange is not occurring universally across the McMurdo Dry Valleys. Instead, evidence of the present-day formation of Ca-Cl−rich brines by cation exchange is focused in a geographically specific location in Taylor Valley, with hydrological position, microclimate, soil depth, and organic matter influencing the spatial extent of cation exchange reactions. Up-valley sites may be too cold and dry for widespread exchange, and warm and wet coastal sites are interpreted to host sediments whose exchange reactions have already gone to completion. We argue that exchangeable cation ratios can be used as a signature of past freeze-concentration of brines and exchange reactions, and thus could be considered a geochemical proxy for past groundwater presence in planetary permafrost settings. Correlations between water-track organic matter, fine sediment concentration, and cation exchange capacity suggest that water tracks may be sites of enhanced biogeochemical cycling in cold desert soils and serve as a model for predicting how active layers in the Antarctic will participate in biogeochemical cycling during periods of future thaw.

Land Use/Cover-Related Ecosystem Service Value in Fragile Ecological Environments: A Case Study in Hexi Region, China

The monetary value assigned to ecosystems and their essential goods and services is known as ecosystem service value (ESV). Fragile ecological environments, susceptible to climate change and human disturbances, require significant ecological protection. This protection is vital not only for stabilizing socio-economic conditions but also for fostering a positive feedback loop within natural systems. Looking ahead, identifying priority conservation areas and regions of particular concern in fragile environments based on ESV changes is a proactive approach. Until now, current studies on ESV in fragile ecological environments have been insufficient, falling short of adequately serving the purpose of ecological protection in such areas. The Hexi region (HXR), situated in the interlaced area of the Qilian Mountains and the Alxa Plateau in northwest China, possesses a fragile ecological environment. Due to the intricate interactions between humans and the environment, it stands out as a crucial area for studying ecosystem services in fragile habitats. Hence, this study aims to systematically analyze the ESV in the HXR over the past 30 years. Here, the values of 11 ecosystem service categories in HXR during 1990–2020 were calculated, clarifying their spatiotemporal difference and dynamic changes based on land use/cover (LULC) products for years 1990, 1995, 2000, 2005, 2010, 2015, and 2020, using an improved equivalent factors method. The findings revealed that the unit standard equivalent factor is 1.51 × 105 CNY·km−2·a−1, and the total ESV value has grown from CNY 182.50 to 185.48 billion from 1990 to 2020. Hydrologic regulation, climate regulation, and soil conservation service values are the principal single ESV categories across HXR. Over the past three decades, ESV changes in HXR have been primarily driven by water area, grassland, and wetland, with the sensitivity of ESV to LULC generally increasing (0.15~9.10%). Natural forcing and anthropogenic perturbations have combined to cause changes in LULC in HXR, influencing ESV fluctuations. Future ecosystem protection activities in HXR should prioritize the maintenance of grasslands, water regions, and wetlands to ensure the preservation of ESV. This study clarifies the impacts of LULC change on ESV in fragile natural environments and highlights the significance of focusing on ESV changes for the health promotion of natural-social systems. The findings provide a foundation for constructing a sustainable development model that is in harmony with both people and the environment.

Mapping SCS hydrological soil groups over South Africa at terrain unit spatial resolution

Given the many users in South Africa of the SCS (Soil Conservation Service) hydrograph-generating technique, which requires key soils information, this paper presents a methodology to develop a detailed map (at the spatial resolution of South Africa's 27 491 terrain units) of the SCS runoff-related soil groups. In order to achieve this objective, background is first provided on the soils context within the SCS technique, as well as on the approaches to defining SCS hydrological soil groups, by assigning SCS soil groups to South African soil series. Steps when mapping SCS soil groups across South Africa at terrain unit spatial resolution are then outlined. This is followed by the presentation and interpretation of the detailed terrain unit level map of SCS soil groups for South Africa. The detailed new map illustrates the finer detail across contributing catchments countrywide now obtained from the terrain unit approach, compared to the previous map of SCS soil groups based only on the coarser soil land types.

The Impact of Vegetation Types on Soil Hydrological and Mechanical Properties in the Hilly Regions of Southern China: A Comparative Analysis

Background: Vegetation roots are considered to play an effective role in controlling soil erosion by benefiting soil hydrology and mechanical properties. However, the correlation between soil hydrology and the mechanical features associated with the variation root system under different vegetation types remains poorly understood. Methods: We conducted dye-tracer infiltration to classify water flow behavior and indoor experiments (including tests on soil bulk density, soil organic carbon, mean weight diameter, soil cohesion, root density, etc.) to interpret variation patterns in three forest systems (coniferous and broad-leaved mixed forest, CBF; coniferous forest, CF; Phyllostachys edulis, PF) and fallow land (FL). Results: Based on the soil dye-tracer infiltration results, the largest dyeing area was observed in CF (36.96%), but CF also had the lowest infiltration rate (60.3 mm·min−1). The soil under CBF had the highest shear strength, approximately 25% higher than other vegetation types. CF exhibited the highest aggregate stability, surpassing CBF by 98.55%, PF by 34.31%, and FL by 407.41%, respectively. Additionally, PF forests showed the greatest root biomass and length. The results of correlation analysis and PCA reveal complex relationships among hydrological and mechanical soil traits. Specifically, soil cohesion does not exhibit significant correlations with hydrological traits such as the dyeing area, while traits like MWD and PAD show either positive or negative associations with hydrological traits. Root traits generally exhibit positive relationships with soil mechanical traits, with limited significant correlations observed with hydrological traits. Conversely, we found that root biomass contributes significantly to the dyeing area (accounting for 51.48%). Conclusions: Our findings indicate that the reforestation system is a successful approach for conserving water and reducing erosion by increasing soil-aggregated stability and shear strength, causing water redistribution to be more homogenized across the whole soil profile.

Spatial variation of soil organic matter and metal mobility in wetland soils: Implications for biogeochemical processes in lateritic landscape

The evolution of the lateritic landscape over time changes the path of pedogenesis and soil hydrology. The occurrence of upland wetlands in the savannah flat plateau transforms well-drained lateritic soils into hydric soils enriched in organic matter. We investigated the composition of soil organic matter (SOM) produced in a wetland and their link with the mineral constituents of soil and their contribution to the mobility of Si, Fe, and Al in the soil. Six tranches were opened in a soil catena located from the plateau toward the center of the wetland, representing different hydromorphic features. Soil morphology was described, and chemical, physical and mineralogical analyses were performed to evaluate soil properties. Chemical fractionation of Soil Organic Matter (SOM) was performed and total organic carbon (TOC), dissolved organic carbon (DOC), particulate organic carbon (POC), and water-extractable organic matter (WEOM) were determined in the soil horizons. Metal complexing properties of DOM were determined using an excitation-emission matrix of fluorescence. The occurrence of Fe eluviation in the superficial horizons, Fe2O3 enrichment in the mottled horizons, and ferricrete formation in the center of the wetland were observed. Geochemical transfer assessment and the variation of oxides within the horizons showed that Fe2O3 and SiO2 were more mobile than Al2O3, whose variability in the gley horizon reflected the mobility of Fe2O3 and SiO2. The stability constants of Al and Cu showed an increase with the depth for WEOM and SOM. The pattern of the organic carbon fraction varied according to the level of hydromorphy and soil depth. It was also observed an increase in the C/N ratio with depth, possibly related to the reduced bioavailability of DOC due to its adsorption with soil solids.

Hygroscopic Growth of Adsorbed Water Films on Smectite Clay Particles.

Hygroscopic growth of adsorbed water films on clay particles underlies a number of environmental science questions, from the air quality and climate impacts of mineral dust aerosols to the hydrology and mechanics of unsaturated soils and sedimentary rocks. Here, we use molecular dynamics (MD) simulations to establish the relation between adsorbed water film thickness (h) and relative humidity (RH) or disjoining pressure (Π), which has long been uncertain due to factors including sensitivity to particle shape, surface roughness, and aqueous chemistry. We present a new MD simulation approach that enables precise quantification of Π in films up to six water monolayers thick. We find that the hygroscopicity of phyllosilicate mineral surfaces increases in the order mica < K-smectite < Na-smectite. The relationship between Π and h on clay surfaces follows a double exponential decay with e-folding lengths of 2.3 and 7.5 Å. The two decay length scales are attributed to hydration repulsion and osmotic phenomena in the electrical double layer (EDL) at the clay-water interface.

Extreme Learning Machine Predicts High-Frequency Stream flow and Nitrate-N Concentrations in a Karst Agricultural Watershed

Highlights A novel high-frequency dataset of streamflow, nitrate-N concentration, and soil moisture at depths throughout and below the root zone highlighted tight connectivity between soil moisture dynamics and nitrate-N concentrations spanning event to seasonal timescales. A TELM model successfully predicted both flow rate and nitrate exports from these complex systems because the time lag associated with the soil conditions was represented in model training. The inclusion of soil moisture and temperature data below the effective root zone was important to accurately capture the storm event hysteresis dynamics observed in the exported nitrate signals. Abstract. Efforts to reduce nitrogen contributions from karst agroecosystems have had variable success, in part due to an incomplete understanding of nitrogen source, fate, and transport dynamics in karst watersheds. Recent advancements in environmental sensors and data-driven artificial intelligence models may be useful in improving our understanding of system behavior and the linkages between soil hydrologic processes and karst nitrate loading dynamics. We collected 35 months of high-resolution streamflow, nitrate-N concentration, soil moisture and temperature (from 10-100 cm depths), and meteorological data in a karst agricultural watershed in the Inner-Bluegrass region of Central Kentucky. Two-layer extreme learning machine (TELM) models were developed to predict nitrate-N concentrations and flow rates as a function of meteorological and soil parameter inputs. Results suggest tight linkages between soil moisture gradients at different depths and nitrate-N concentrations at the watershed outlet. TELM modeling results supported visual observations from the high-frequency data and suggest that inclusion of both soil moisture and temperature parameters at all soil depths improved predictions of both flow rate and nitrate-N concentration (with optimal NSE values of 0.93 and 0.94, respectively, when all inputs were considered). Hysteresis analysis suggested that inclusion of the deepest soil layer (100 cm) was necessary to predict hysteresis observed during storm events. The findings of the study highlight the importance of variable activation of matrix waters in preferential flows throughout events and seasons and its subsequent impacts on nitrate-N concentrations. Results suggest that management models should incorporate vertical variability in soil hydrology to accurately characterize nitrate source and transport dynamics. Further, the results of hysteresis analysis underscore the importance of inclusion of hysteresis indices, in addition to typical model evaluation statistics, to ensure accurate representation of nutrient flow pathways. Keywords: Extreme learning machine, Karst agroecosystem, Nitrate, Water resources.

Combinando modelos hidrológicos tradicionais e aprendizado de máquina para previsão de vazão

ABSTRACT Traditional hydrological models have been widely used in hydrologic studies, providing credible representations of reality. This paper introduces a hybrid model that combines the traditional hydrological model Soil Moisture Accounting Procedure (SMAP) with the machine learning algorithm XGBoost. Applied to the Sobradinho watershed in Brazil, the hybrid model aims to produce more precise streamflow forecasts within a three-month horizon. This study employs rainfall forecasts from the North America Multi Model Ensemble (NMME) as inputs of the SMAP to produce streamflow forecasts. The study evaluates NMME forecasts, corrects bias using quantile mapping, and calibrates the SMAP model for the study region from 1984 to 2010 using Particle Swarm Optimization (PSO). Model evaluation covers the period from 2011 to 2022. An XGBoost model predicts SMAP residuals based on the past 12 months, and the hybrid model combines SMAP's streamflow forecast with XGBoost residuals. Notably, the hybrid model outperforms SMAP alone, showing improved correlation and Nash-Sutcliffe index values, especially during periods of lower streamflow. This research highlights the potential of integrating traditional hydrological models with machine learning for more accurate streamflow predictions.

Characterization of landuse and landcover dynamics and their impact on runoff generation patterns in dam catchments of Northern Ghana

Landuse alteration is a critical factor that exerts influence over hydrological mechanisms and the oversight of water resources across the globe. Northern Ghana is characterized by erratic rainfall, leading to the intense construction of small dams and dugouts. This study investigated historical landuse/cover (LULC) changes and physical factors associated with surface runoff generation within eight (8) sub-catchments namely; Guno, Gbahali, Sambu, Duago, Denugo, Kwisini, Sandu, and Nyeko, with areas of 29.5, 110, 38.5, 106.04, 67.81, 2.59, 10.56 and 120.65 km2, respectively, located in four (4) regions of northern Ghana. For LULC change detection, historical satellite imagery and geospatial data were used with the aid of remote sensing and applying supervised maximum likelihood classification to Landsat images of 1995, 2005, 2015, and 2023. Runoff factors and depths were identified based on LULC classes, hydrologic soil groups, and precipitation conditions prevailing in the areas, based on the curve number (CN) method. With regards to LULC, the results from the overall analysis gave an insight into the rampant conversion, where grassland/mix vegetation witnessed significant declines, with decreases ranging from 150 to 395.25% in different catchments. Agricultural and arable lands emerged as the dominant landuse category, indicating a remarkable expansion of 11.61–51.17 km2, from 1995 to 2023 respectively, followed by built-up areas. While grassland decreased in all catchments over the same period, in some places, open tree (savannah woodland) increased, which confirmed the implementation of the afforestation policy. The CN values offered essential insights into the hydrological characteristics of each catchment. In addition to the impact of LULC and watershed characteristics on runoff, the observed variations in runoff patterns can be attributed to interannual variability in total annual precipitation which is critical driver of runoff. The findings hold significant importance for developing effective strategies and integrated watershed management policies to contribute to better water resource management and inform sustainable landuse planning in the face of changing environmental conditions.

Effects of land use and land cover on Soil-Water Infiltration: A Literature Review and Bibliometric Analysis

The impact of land use and land cover (LULC) on hydrology is gaining increased attention due to global concerns about water sustainability. Although various studies have been conducted related to the topic, there were only a few publications that specifically focused on the effects of LULC on soil water infiltration. This study gathered and synthesized relevant research publications and performed co-occurrence and co-citation analyses to identify the existing themes and the research development trend on LULC-soil infiltration relation. Analysis of 103 Scopus-indexed articles from as early as 2000 revealed four major themes: soil characteristics, hydrology and watershed, hydrology and management, and groundwater and LULC. These findings highlight key areas of focus and can assist in identifying research gaps and topics requiring further exploration. The paper offers a concise overview of the current research trajectory in the realm of LULC and soul water infiltration.

An evaluation on the parameters used in flood susceptibility analysis

Taşkınlar her geçen gün artan büyüklük ve sıklıklarına bağlı olarak dünyada ve ülkemizde önemi giderek artan afetlerden birisidir. Bu çalışmadaki temel amaç, taşkın duyarlılık ile ilgili uluslararası ve ulusal literatürün değerlendirilmesi ve duyarlılık çalışmalarına yeni bir yaklaşım olarak sel ve taşkınların meydana geldiği yerleşmelerin su toplama havzaları temelli taşkın duyarlılık parametrelerinin belirlenmesini gerçekleştirmektir. Bu kapsamda çalışmada tarihsel taşkın envanterine bağlı olarak Bursa ili sınırları içerisinde vadi tabanı ve akarsu kenarında sel ve taşkınların yaşandığı yerleşmelerin havzalarına bağlı olarak taşkın duyarlılık analizi parametreleri belirlenmiştir. Çalışmada kullanılan temel altlık veriler, Bursa iline ait 5m çözünürlüklü Sayısal Yükseklik Modeli (SYM), 1956-2022 yılları arasını kapsayan envanter verileri, litoloji, hidrolojik toprak grupları (HTG) ve yağış (WorldClim) verileridir. Bursa il sınırları içerisinde meydana gelen tarihsel sel ve taşkın envanterine bağlı olarak 28 yerleşme ve bu yerleşmelerin su toplama havzaları belirlenmiş ve bu havzalara sel ve taşkının oluşmasında hazırlayıcı 12 parametre uygulanmıştır. Taşkın hazırlayıcı parametreler sınıflandırma aşamasında 0-1 arasında normalize edilerek ortaya çıkan sonuca göre taşkın duyarlılık için parametre katsayıları oluşturulmuştur. Sonuç olarak envantere göre maksimum etkiye sahip parametreler; çatallanma oranı (R_b), drenaj yoğunluğu (D_d), akım toplanma zamanı (T_c), eğim, topografik nemlilik indeksi, akarsu güç indeksi, hidrolojik toprak grupları, olarak belirlenmiştir. Bu çalışma ile taşkın duyarlılık analizinde önceki çalışmalardan farklı olarak envantere bağlı ve yerleşim temelli havzalardan taşkın duyarlılık parametreleri belirlenmiştir.

Hydrological Implications of Recent Droughts (2004–2022): A SWAT-Based Study in an Ancient Lowland Irrigation Area in Lombardy, Northern Italy

This study examines the hydrological dynamics of the Ticino irrigation cascade in northern Italy from 2004 to 2022. The region, which is shaped by human activity, is characterized by its flat topography and complex management of water resources, featuring a unique historic irrigation cascade. Utilizing the Soil and Water Assessment Tool (SWAT), we investigated the water availability during recent severe droughts in this complex agricultural environment, which lacks natural drainage. This area faces risks due to increasing temperatures and increased rainless days. Therefore, understanding the soil water dynamics is essential for maintaining the system’s sustainability. Calibrating and validating the SWAT model with runoff data was challenging due to the absence of natural drainage. Thus, we utilized MOD16 evapotranspiration (AET) data for calibration. Generally, the calibration and validation of the SWAT model yielded satisfactory results in terms of the Kling–Gupta efficiency (KGE). Despite some discrepancies, which were mainly related to the data sources and resolution, the calibrated model’s outputs showed increased actual evapotranspiration that was influenced by climate and irrigation, leading to water deficits and droughts. The soil water content (SWC) decreased by 7% over 15 years, impacting crop productivity and environmental sustainability. This also resulted in rising water stress for crops and the ecosystem in general, highlighting the direct impact of adverse climate conditions on soil hydrology and agriculture. Our research contributes to the understanding of soil–water dynamics, as it specifically addresses recent droughts in the Lombardy lowlands.

Site matters - Canopy conductance regulation in mature temperate trees diverges at two sites with contrasting soil water availability

Tree-specific canopy conductance (Gc) and its adjustment play a critical role in mitigating excess water loss in changing environmental conditions. However, the change of Gc sensitivity to environmental conditions due to drought remains unclear for European tree species. Here we quantified the environmental operational space of Gc, i.e., the water supply (soil moisture, tree water deficit) and demand conditions (vapor pressure deficit) under which Gc ≥ 50% is possible (Gc50OS), at two sites with different soil water availability for three common European tree species. We collected sap flow and dendrometer measurements for co-occurring Pinus sylvestris, Fagus sylvatica and Quercus petraea growing under different soil hydrological conditions (drier/wetter). These measurements were combined with meteorological variables and soil moisture conditions in five depths. Dendrometer measurements were used to confirm soil water availability patterns. For all analyses, the contrasting soil hydrology between sites was the main driver of Gc response. At the drier sites, F. sylvatica and P. sylvestris reduced their water consumption in response to decreasing soil water supply earlier in the growing season than Q. petraea. However, our analysis on the Gc50OS revealed that at the drier sites, F. sylvatica and Q. petraea reduced the extent of their Gc50OS to a higher degree than P. sylvestris. This indicates a higher level of Gc50OS adjustment to the drier site conditions for the two broadleaved species. These differences were more pronounced when using the dendrometer-derived tree internal water status as proxy for tree water supply. Our results provide preliminary evidence for diverging short-term Gc responses when temperate trees are exposed to prolonged reduction in water availability. These findings suggest that Gc50OS can help to constrain species-specific predictions of water use by mature trees, especially when combined with high-resolution water potential measurements.

Application of Machine Learning in Modeling the Relationship between Catchment Attributes and Instream Water Quality in Data-Scarce Regions.

This research delves into the efficacy of machine learning models in predicting water quality parameters within a catchment area, focusing on unraveling the significance of individual input variables. In order to manage water quality, it is necessary to determine the relationship between the physical attributes of the catchment, such as geological permeability and hydrologic soil groups, and in-stream water quality parameters. Water quality data were acquired from the Iran Water Resource Management Company (WRMC) through monthly sampling. For statistical analysis, the study utilized 5-year means (1998-2002) of water quality data. A total of 88 final stations were included in the analysis. Using machine learning methods, the paper gives relations for 11 in-stream water quality parameters: Sodium Adsorption Ratio (SAR), Na+, Mg2+, Ca2+, SO42-, Cl-, HCO3-, K+, pH, conductivity (EC), and Total Dissolved Solids (TDS). To comprehensively evaluate model performance, the study employs diverse metrics, including Pearson's Linear Correlation Coefficient (R) and the mean absolute percentage error (MAPE). Notably, the Random Forest (RF) model emerges as the standout model across various water parameters. Integrating research outcomes enables targeted strategies for fostering environmental sustainability, contributing to the broader goal of cultivating resilient water ecosystems. As a practical pathway toward achieving a delicate balance between human activities and environmental preservation, this research actively contributes to sustainable water ecosystems.

Biocrust-reduced soil water retention and soil infiltration in an alpine Kobresia meadow

Abstract. Biocrust is a key component of ecosystems and plays a vital role in altering hydrological processes in terrestrial ecosystems. The impacts of biocrust on hydrological processes in arid and semi-arid ecosystems have been widely documented. However, the effects and mechanisms of biocrust on soil hydrological processes in alpine ecosystems are still poorly understood. In this study, we selected two meadow types from the northern Qinghai–Tibet Plateau: normal Kobresia meadow (NM) and biocrust meadow (BM). Both the soil hydrological and physicochemical properties were examined. We found that, in the 0–30 cm soil layer, soil water retention and soil water content in NM were higher than those in BM, whereas the 30–40 cm layer's soil water retention and soil water content in NM were lower than those in BM. The topsoil infiltration rate in BM was lower than that in NM. Furthermore, the physicochemical properties were different between NM and BM. The 0–10 cm soil layer's clay content in BM was 9 % higher than that in NM, whereas the 0–30 cm layer's soil capillary porosity in NM was higher than that in BM. In addition, the 0–20 cm layer's soil total nitrogen (TN) and soil organic matter (SOM) in NM were higher than those in BM, implying that the presence of biocrust may not favor the formation of soil nutrients owing to its lower soil microbial biomass carbon and microbial biomass nitrogen. Overall, soil water retention was determined by SOM by altering the soil capillary porosity and bulk density. Our findings suggest that the establishment of cyanobacteria crust biocrust may not improve soil water retention and infiltration, and the soil in cyanobacteria crust meadows could be more vulnerable to runoff generation and consequent soil erosion. These results provide a systematic and comprehensive understanding of the effects of biocrust on the soil hydrology of alpine ecosystems.