Infiltration and hydraulic conductivity ( K) play a key role in streamflow generation and groundwater recharge. The impact of agriculture on soil infiltration and K has been widely investigated. While many studies show decreases in infiltration and K, others show an increase or no change in both parameters. These variations highlight the importance of conducting local scale investigations. We investigated the impact of agricultural development and land cover changes on infiltration and K. Unsaturated hydraulic conductivity (K unsat) was measured at the soil surface during both dry and wet seasons and saturated hydraulic conductivity (K sat) was measured at 25, 45, and 65 cm below the surface. Our results show that there were no significant differences in K unsat between perennial crop cover and natural forests; however, agroforests did have significantly higher K unsat than natural forests, which was attributed to higher soil moisture. There were no significant differences in K sat among the perennial crops, agroforests and natural forests at the 45 and 65 cm depths; however, at 25 cm natural forests had significantly higher K sat, which was attributed to the higher soil organic matter and lower bulk density in natural forest. The study showed that the impacts of agriculture and land cover change on K sat does not extend to deeper soil layers. We used two years of rainfall intensity data, observed K unsat and K sat , and HYDRUS-1D modelling to infer any changes to runoff. We show that footpaths and perennial crop cover may generate more surface runoff than natural forests. This study adds to the literature on agricultural impacts on infiltration and K. More importantly it shows that differences in crop type, management practices and topographic location all play an important role on infiltration and K, showing the need for local field based studies.

“‘latex The capacity of peatlands to sequester and store atmospheric carbon is coupled to their hydrological functioning but is threatened by increases in the frequency and severity of extreme weather. The hydrological functioning of a near-intact water-shedding ombrotrophic blanket bog is characterised here using a decade-long (2010 – 2021) hydro-meteorological series. This period includes the substantial drawdown of water tables during the 2018 UK summer heatwave. Annual peatland water balances were calculated for three consecutive hydrological years (2017/18, 2018/19 and 2019/20) and comprised, on average, 930 mm of precipitation (P), 335 mm evapotranspiration (ET), 371 mm runoff and −7 mm change in water storage (ΔS). Average annual water table depth (WTD) relates primarily to available energy (net radiation – soil heat flux), while monthly average WTD is driven mainly by the vapour pressure deficit (VPD). Summer water availability (P – ET) is controlled more by precipitation than evapotranspiration and drives much of summer changes in ΔS. Deeper summer WTD patterns associate with greater incidence of warm, highly evaporative days, and the 2018 summer drawdown (−427 mm) reflects both low water availability (P – ET) and high incidence of evaporative days. By winter 2018/19 the water balance had recovered, demonstrating the resilience of this near-intact blanket bog to hydrological extremes. However, the increased risk of summer heatwaves, milder winters and trends towards reduced winter-spring precipitation will impact interannual hydrological regimes, particularly affecting the extent of winter recharge and summer water table drawdown potentially jeopardising the longer-term stability of peatlands.

The ongoing and persistent drought in Central-western Argentina since 2010 is leading to a water crisis in the region. Despite the crucial importance of the Andean water resources for natural ecosystems and socio-economic activities few studies have focused on the relative contributions of snow and ice on the hydrology of the main regional watersheds such as the Mendoza River, which is the main water supply for the most extensive and densely populated irrigated oasis in central-western Argentina. To better understand snow and glacier temporal storage-and-release processes and its impact on the seasonal and inter-annual variability of the Mendoza Riverwe we provide an up-to-date modeling work using the numerical model HBV.IANIGLA which specifically incorporates separate snow and glacier components into the hydrological simulations. Modeled snow accumulation values show that the lower eastern sectors of the Mendoza watershed usually receive five times less snow than the westernmost areas bordering Chile. Model outputs from the adjacent Maipo and Aconcagua watersheds in Chile indicate almost 3.5 times more snow than the Mendoza River basin, corroborating the marked west-east precipitation gradient in this region. During the last 40 years, snow has been the main source of meltwater for the Mendoza river but glaciers have contributed, on average, ca. 18% of the annual discharges. Maximum values that exceed 40% in glacier contribution were modeled in years with very low winter snow accumulation. This is particularly evident during the extended dry period that started in 2010, when the glacier contribution averaged ca. 30% compared to ca. 15% prior to that period. These very dry years usually concentrate the bulk of the annual discharges later than normal during the warm melting season. These results provide an improved understanding of the surface water variability in this semiarid region for the last 40 years.

“‘latex An appropriate soil configuration is essential in hydrological models given the role of subsurface processes in the hydrological functioning of a catchment. Hydrological models are typically set up with shallow soil depths as restricted by measurements and soil datasets that are often unavailable in greater depths. While this may be sufficient for some catchments, in some areas the water table is located deeper and thus the shallow groundwater and its link with the rest of the hydrological processes may not be captured well by the model. An important soil parameter, that is known to vary with soil depth, is the saturated hydraulic conductivity (K sat). In this study, we assessed different vertical profiles of K sat which exceed the typical soil measurement depths. The K sat profiles were implemented in wflow.jl for the distributed hydrological model wflow_sbm and tested for the Vecht catchment. Results demonstrated that increasing the soil thickness and implementing any of the K sat profiles assessed improved the discharge and mean groundwater depth predictive capabilities, albeit altering the groundwater dynamics. A sensitivity analysis revealed the respective influence of four model parameters on the groundwater dynamics which can be used as basis to optimize the model performance further.

This study assesses the effectiveness of Sustainable Urban Drainage Systems (SuDS) in mitigating urban flooding and enhancing stormwater management in Machala, Ecuador. The implementation of SuDS resulted in a 57.64% reduction in flood volume and a decrease in peak flow from 10.50 m 3s -1 to 5.91 m 3s -1. Infiltration capacity improved from 0.75 mm to 2.43 mm, while average surface runoff was nearly halved from 19.27 mm to 10.48 mm. A specially designed porous concrete with approximately 30% porosity showed optimal performance. These findings indicate that SuDS can significantly contribute to urban planning and flood management in coastal developing cities. The study recommends prioritizing rain gardens and porous pavements, creating local SuDS guidelines, integrating these systems into urban planning, establishing long-term monitoring, and involving local communities. The insights gained here offer valuable guidance for other coastal cities in Ecuador and similar regions, demonstrating a sustainable approach to managing urban flooding and enhancing water resilience.

Runoff generation and concentration are essential processes of the hydrological cycle. Understanding runoff generation patterns is crucial for improving the accuracy of hydrological forecasting and regional water resource assessment. This research aims to explore runoff generation mechanisms in the plains’ farmlands of North China and analyze the impact of wheat growth on runoff generation in typical slope farmland. Seven scenarios of experiments were designed on two soil tanks as the farm-sample of different slopes, which are 2° and 4° separated. These scenarios took into account local climate types, cropping structures, and slope by setting a uniform rainfall intensity of 60 mm/h through an artificial rainfall device located in Yongnian County, Hebei Province, China. These experiments were conducted, and the runoff generation process in different scenarios were observed from October 2019 to June 2021. Through the comparison of the observed runoff processes, the results indicate that surface runoff varies significantly, while interflow remains relatively stable. Vegetation cover has a greater impact than slope on runoff process. As winter wheat grew, the initial time of surface runoff was delayed, and runoff yield decreased, whereas the runoff generation of interflow exhibited the opposite trend. Under the same vegetation cover conditions, the increase in slope led to an advance in the T Rs and an increase in runoff volume and peak value, while the interflow findings were inverse. The bare land in the winter wheat scenario has a significantly greater runoff volume, likely benefiting from the impact of the crop rotation system on soil characteristics in North China. The findings of this research provide insight into understanding runoff patterns in North China, reducing the uncertainty between runoff model parameters and watershed characteristics, and offering beneficial references for research and practice in related fields.

not-yet-known not-yet-known not-yet-known unknown The ecological effects of sediment flushings from artificial reservoirs have been widely documented, but the underlying sediment dynamics are less known. We investigated sediment dynamics associated with a long flushing event divided into two periods (2 and 1 week) in an Alpine river, each followed by a clear water release (“washing”) from the reservoir. Suspended sediment dynamics were investigated at the event and annual time scale, and at the river segment (~1000 channel widths) and reach (~100 channel widths or less) spatial scales. Analysis of suspended sediment concentration (SSC) and streamflow time series from 5 in-situ calibrated optical turbidity sensors reveals a downstream decrease in the total passing sediment fluxes, a spatial trend that is paralleled by the theoretical suspended sediment transport capacity, allowing for the estimation of the deposited fine sediment volume in different reaches. Washing events result in variable effects among reaches, with some experiencing net sediment entrainment and others net deposition. Out of 16 quantified sediment fluxes, 5 were statistically significant with p<0.05, with an average uncertainty of 23\% in fine sediment flux quantification. Georeferenced analysis of colored gravel-cobble plots before and after the two flushing events revealed partial reach-scale mobility of the coarse bed surface material, particularly in the geomorphic units located at lower elevations and more exposed to higher flows (edges of side bars nearby riffles or rapids), while local fine sediment deposition was observed at less exposed units, as side channels or point bars in river bends. Grain size distributions of surface sediments taken in the same locations before and 1 month after the flushing reveal a clear shift towards a finer sediment composition, which is partially retrieved also 1 year after the event. Event-averaged SSC values during the flushing are considerably higher compared to natural flood events in such a regulated river, with SSC-streamflow relations being highly irregular and event-dependent, especially during the flushing. The work shows the relevance of multi-scale (time and space) investigation of sediment dynamics for planning and monitoring sediment flushing from artificial reservoirs.

Abstract Although the importance of dynamic water storage and flowpath partitioning on discharge behavior has been well recognized within the critical zone community, there is still little consensus surrounding the question, “ How do climate factors from above and land characteristics from below dictate dynamic storage, flowpath partitioning, and ultimately regulate hydrological dynamics?” Answers to this question have been hindered by limited and inconsistent spatio-temporal data and arduous-to-measure subsurface data. Here we aim to answer this question above by using a semi-distributed hydrological model (HBV model) to simulate and understand the dynamics of water storage, groundwater flowpaths, and discharge in 15 headwater catchments across the contiguous United States. Results show that topography, precipitation falling as snow, and catchment soil texture all influence catchment dynamic storage, storage-discharge sensitivity, flowpath partitioning, and discharge flashiness. Flat, rain-dominated sites (< 30% precipitation as snow) with finer soils exhibited flashier discharge regimes than catchments with coarse soils and/or significant snowfall (>30% precipitation as snow). Rain-dominated sites with clay soils (indicative of chemical weathering) showed lower dynamic storage and discharge that was more sensitive to changes in dynamic storage than rainy sites with coarse soils. Steep, snowy sites with coarse soils (more mechanical weathering) had lowest dynamic storage and deep groundwater fed discharge that was less sensitive to changes in dynamic storage than fine-soil snowy or rainy catchments. These results highlight aridity and precipitation (snow versus rain) as the dominant climate controls from above and topography and soil texture as the dominant land controls from below. The study challenges the traditional view that climate controls water balance while subsurface structure dictates subsurface flow path. Rather, it shows that climate and land characteristics jointly regulate water balance, groundwater flowpath partitioning, and discharge responses. These findings have important implication for the projection of the future of water resources, especially as climate change and human activities continue to intensify.

This study focuses on the design, implementation and performance evaluation of a new irrigation and open-channel module into the well-known Topkapi distributed model. The Topkapi was implemented through the PyTopkapi library. The research framework encompasses the integration of an irrigation simulation module alongside a sophisticated kinematic wave model, designed to emulate the intricate dynamics of surface flow transport in irrigation channels, thereby enriching the structural composition of the overall model. The performance of the improved model was tested in the Achibueno River basin (Chile) strategically positioned in the southern reaches of the Maule region, encompassing a substantial land expanse of 1578 km 2 with a very important agricultural activity and a subsequent important presence of open-channels for its water distribution network. The dataset utilized for this comprehensive assessment spans a temporal continuum from 1979 to 2005 and has been meticulously curated from the historical archives of the CR2 institution. The evaluation of model performance is executed through the application of the Nash and Nash-ln coefficients, enabling a nuanced understanding of the model’s proficiency. Two distinct scenarios are meticulously considered throughout the assessment: one wherein the irrigation module is absent from the model configuration, and another wherein the irrigation module is integrated into the model’s structural framework. The findings emanating from our results underscore a discernible augmentation in the operational efficiency of PyTopkapi to the extent of approximately 17% when the irrigation module is applied (NSE moving from 0.63 to 0.74 for the calibration period and 0.54 to 0.64 for the validation period). This heightened efficiency manifests notably during the transport of flow through channels, where the kinematic wave model plays a pivotal role in orchestrating the dynamics of surface water movement.

Preferential flow plays an important role in the ecosystem. In order to understand the influence of enclosure on the root-soil structure in the preferential flow region, and to understand the difference of root-soil structure between the preferential flow region and the matrix flow region. In this paper, the soil in the preferential flow region of Caragana korshinskii shrub under enclosure or grazing measures in Yanchi, Ningxia, China was selected as the research object. The geometric distribution and topological indexes of root-soil structure (aggregates, macropores and roots) were obtained by CT scanning and three-dimensional image processing. The results showed that the enclosed natural grassland had the highest staining area ratio (40.38%) and staining depth (271 mm). The distribution of soil aggregates and macropores in grazing artificial C. korshinskii shrub and enclosed natural C. korshinskii shrub was more uniform. Enclosure significantly reduced the number density and volume density of soil aggregates, macropores and roots in the preferential flow region (p<0.05). Compared with the matrix flow region, the number density of soil aggregates in the preferential flow region increased significantly (p<0.05), and the average equivalent diameter decreased significantly (p<0.05). Enclosure negatively affects soil aggregates and macropores. Aggregates directly promote the preferential flow process, and macropores indirectly affect the preferential flow process through aggregates. Clarifying the relationship between enclosure, root-soil structure and preferential flow can provide a basis for vegetation restoration management in arid and semi-arid areas.

Tropical peatlands are characterized by highly organic, heterogeneous, and compressible peat soils. Without sampling and disturbing the soil, peat hydraulic and discharge parameters can be estimated from analyzing the in situ water level rise and recession. Such an analysis allows for the representation of the hydraulic behavior of a peatland from water level, precipitation, and topography data. Water level is measured in several remote tropical peatlands, whereas in situ precipitation is often not. Gridded satellite precipitation products provide an alternative, but are coarse and highly uncertain. Here, we introduce an algorithm for the hydrological parameterization of water level dynamics using satellite-based precipitation, and apply it to a tropical peatland in Brunei, while accounting for representativeness errors in the precipitation data. First, we adapt the rise and recession analysis developed by Cobb & Harvey (2019) for use with Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement mission (IMERG) precipitation estimates. The adapted rise analysis reduces the average error in the slope of the master rise curve with IMERG data from 21% to 3%. The average daily recession overestimation with IMERG data is reduced from 0.45 cm day -1 to 0.18 cm day -1. We also quantify the sensitivity of our rise analysis to precipitation errors using an ensemble of erroneous precipitation time series. Second, the adapted master rise and recession curves are used to fit soil hydraulic and discharge function parameters within the peatland-specific module of the NASA Catchment Land Surface Model. Our method enables the retrieval of accurate hydrological parameters for our case study, and should be tested in other peatland regions and with other satellite-based precipitation products.

An agricultural experimental setup has been constructed with the aim of assessing the impact of soil conservation practices on surface runoff and water quality. The site is located at Saint-Lambert-de-Lauzon (near Québec City, Canada) and is composed by twelve 624 m 2 catchments for which surface and tillage runoffs, water quality (suspended matter, phosphorus, nitrate-nitrite, dissolved metals), soil physical and chemical properties, and crop yields are monitored. The experimental design allows the comparison of four agricultural treatments: two compaction treatments (with and without soil compaction) and two conservation regimes (conventional and soil conservation agricultural practices), each regime being duplicated three times. Generalized Additive Mixed Model (GAMM) highlighted significant relations between the conservation regimes and suspended matter charges, and surface runoff. In other words, conservation practices allow a significant short-term reduction of suspended matter at the field scale. On the other hand, they appear to favour an increase of surface runoff in the springtime. Since only one three-year rotation cycle has been conducted, no effect was observed on soil properties, and crop yields. Long term impacts of soil conservation practices were estimated by implementing a physically based hydrologic model SWAT over each catchment. Restored soil properties were scenarized using measurements conducted over surrounding unperturbed sites. Modelling results suggest that a restoration of soil physical properties would translate into a moderate decrease surface runoff (-5%) at the field scale. The study brings an advanced and multidimensional understanding of the field-scale processes driving soil health, quantitative hydrology, and water quality. It also quantifies potential long-term benefits of implementing soil conservation practices.

Under the more frequent and extreme global drought events, utilizing stable isotopes to quantify soil evaporation losses ( SEL) is of great significance for understanding the water supply capacity from soil to plants. From March 2017 to September 2019, we continuously monitored meteorological factors, soil temperature and humidity, and collected precipitation and soil water stable isotope data. Used the Craig-Gordon (C-G) model and the line-conditioned excess (lc-excess) couple with Rayleigh fractionation (RL) model to quantify SEL in subtropical secondary forests. The results showed: (1) The theoretical Evaporation Line (EL) slope correlated negatively with air temperature ( AT). Water source isotopic values were more positive in autumn and more negative in spring. The aridity index ( AI) and soil evaporation loss ratio ( f) from both models indicated drier conditions from March to September 2018 compared to 2017 and 2019; (2) Comparative analysis showed the C-G model agreed more closely with measured evapotranspiration ( ET0) and water surface evaporation ( E) than the RL model, indicating its better suitability for the study region; (3) Because the “inverse temperature effect” of the precipitation isotopes, the linear fitting method was not suitable for determining the water source in spring, summer, autumn, and on the annual scale, while the EL slope obtained by the fitted slope was consistent with the basic principle of soil evaporation in winter. Thus, the theoretical method was more suitable for determining the EL slope in such regions; (4) because the different fundamentals, the C-G model was positively correlated with air temperature and negatively with relative humidity ( h), while the RL model showed the opposite, indicating different applicability. Meanwhile, SEL is influenced by soil thickness, atmospheric evaporation, and soil water supply capacities. These findings support using stable isotope techniques to quantify SEL and are important for analyzing soil water resources in subtropical secondary forests.

The nonlinearity of soil moisture content, water potential, and unsaturated hydraulic conductivity in soil layers makes it difficult to simulate wetting-drying cycles using conventional means. We addressed this issue using physics-informed neural networks (PINNs). Based on the van Genuchten model, we solved the Richards equation with soil matric potential as the primary variable within the PINNs framework. The proposed approach was applied and validated in a typical deep-buried area at the Luancheng Experimental Station. We found that the PINNs method was as accurate as the finite difference method in simulating the vertical infiltration of soil moisture in a non-laboratory environment. Moreover, the model exhibited swift performance when the soil layer parameters were fine-tuned. Overall, this model accurately characterizes hydrological elements using minimal data, thereby providing a new approach for simulating related hydrological processes.

This study investigates the impact of spatial resolution on urban pluvial flood modelling, focusing on the implications of high-resolution topography data for flood inundation mapping. We employed the physically-based urban flood model, H12, to simulate a past pluvial flooding event that occurred from 6-8 December 2015 in a sub-watershed in Portland, Oregon. We compared the temporal evolution of inundation maps from a benchmark 1 m resolution model with those from coarser resolutions (ranging from 2 m to 50 m). We evaluated the accuracy of the modelling results using water depth error measures and grid-based inundation extent error metrics to investigate the main causes of the differences. Our results show that the accumulated inundated water volume significantly increases with coarser grid resolutions, leading to larger discrepancies in pluvial flood inundation maps across the modelling domain. Additionally, coarser-resolution grids result in the overprediction of inundation extents, except in the 2 m model. Accuracy metrics decrease with coarser modelling grid resolutions; the hit rate (H) and critical success index (C) both decline as resolution coarsens. Notably, H rapidly drops below 0.7 and C to 0.5 or less when the resolution exceeds 7 m. Furthermore, multi-directional flow path analyses reveal that the spatial ranges of inundation expand as grid resolution becomes coarser. On the other hand, computational efficiency improves as grid resolutions become coarser. One of the main causes of accuracy degradation is the inherent limitation of coarse-resolution data in depicting topographical details. Although there is no single optimal resolution that suits all urban conditions, it is important to note that grid resolutions must be fine enough to accurately represent major urban features, such as road networks, which affect water flows during flood events.

Agricultural soil erosion is largely attributed to arable extensification and increased mechanisation. Runoff from arable land and intensively managed grassland transports sediment and contaminants across the landscape and into watercourses, causing crop loss, land degradation and water quality issues. One low-cost and low-maintenance nature-based mitigation approach is the implementation of vegetated buffer strips (VBS): grassland sited along field margins to trap sediment and contaminants, reducing transportation and diffuse pollution rates. GIS modelling using remotely sensed landscape indices and land parcel data can provide an efficient means of identifying priority areas for intervention at sub-catchment or farm system scales. We develop and test a scalable runoff risk model in the lower Rother catchment, West Sussex. The model uses the Normalised Difference Vegetation Index (NDVI) applied to satellite images as an erodibility proxy and identifies locations along pathways that are conceivably at greatest risk of sediment accumulation and transfer, guided by field observations. Current and historical field boundaries near high-risk locations are evaluated for their potential capacity to reduce runoff using an innovative ranking system. Recommendations are made for VBS implementation and utility of historical field margin restoration is discussed. Our method offers a rapid approach with minimal data requirements to identify high-risk erosion locations and priority sites for intervention. The tool has the potential to guide decision-makers responsible for targeting and implementing soil erosion control measures such as VBS, while also maximising agri-environmental and cultural benefits.

Non-perennial streams play a crucial role in ecological communities. However, the key parameters and processes involved in stream intermittence remain poorly understood. While climate conditions, geology and land use are well identified, assessing and modeling the groundwater controls on streamflow intermittence remains a challenge. In this study, we explore new opportunities to calibrate process-based 3D groundwater flow models designed to simulate stream intermittence in groundwater-fed headwaters. Streamflow measurements and stream network maps are jointly considered to constrain aquifer’s effective hydraulic properties in hydrogeological models. The simulations were then validated using visual observations presence/absence of water, provided by a national monitoring network in France (ONDE). We tested the methodology on two pilot catchments with unconfined shallow crystalline aquifer, the Canut and Nançon (Brittany, France). We found that streamflow and expansion/contraction dynamics of the stream network are both necessary to calibrate simultaneously hydraulic conductivity K and porosity θ with low uncertainties. Conversely, calibration resulted in accurate prediction of stream intermittence - in terms of flow and spatial extent. For the two catchments studied, the Canut and Nançon, hydraulic conductivity is close reaching 1.5 x 10 -5 m/s and 4.5 x 10 -5 m/s respectively. However, they differ more by their storage capacity, with porosity estimated at 0.1 % and 2.2 % respectively. Lower storage capacities lead to higher fluctuations in the water table, increasing the proportion of intermittent streams and reducing perennial flow. This new modeling framework allowing to predict streamflow intermittence in headwaters can be deployed to improve our understanding of groundwater controls in different geomorphological, geological, and climatic contexts. It will benefit from advances in remote sensing and crowdsourcing approaches that generate new observed data products with high spatial and temporal resolution.

A document by Chris Soulsby. Click on the document to view its contents.