Comparative influence of land and sea surfaces on the Sahelian drought: a numerical study

The aim of this work is to compare the relative impact of land and sea surface anomalies on Sahel rainfall and to describe the associated anomalies in the atmospheric general circulation. This sensitivity study was done with the Météo-France climate model: ARPEGE. The sensitivity to land surface conditions consists of changes in the management of water and heat exchanges by vegetation cover and bare soil. The sensitivity to ocean surfaces consists in forcing the lower boundary of the model with worldwide composite sea surface temperature (SST) anomalies obtained from the difference between 4 dry Sahel years and 4 wet Sahel years observed since 1970. For each case, the spatiotemporal variability of the simulated rainfall anomaly and changes in the modelled tropical easterly jet (TEJ) and African easterly jet (AEJ) are discussed. The global changes in land surface evaporation have caused a rainfall deficit over the Sahel and over the Guinea Coast. No significant changes in the simulated TEJ and an enhancement of the AEJ are found; at the surface, the energy budget and the hydrological cycle are substantially modified. On the other hand, SST anomalies induce a negative rainfall anomaly over the Sahel and a positive rainfall anomaly to the south of this area. The rainfall deficit due to those anomalies is consistent with previous diagnostic and sensitivity studies. The TEJ is weaker and the AEJ is stronger than in the reference. The composite impact of SST and land surfaces anomalies is also analyzed: the simulated rainfall anomaly is similar to the observed mean African drought patterns. This work suggests that large-scale variations of surface conditions may have a substantial influence on Sahel rainfall and shows the importance of land surface parameterization in climate change modelling. In addition, it points out the interest in accurately considering the land and sea surfaces conditions in sensitivity studies on Sahel rainfall.     

Analysis of soil moisture dynamics beneath olive trees

Olive cultivation is a widespread land use in Mediterranean climates. The proper implementation of soil and water conservation practices in groves requires detailed knowledge of the governing hydrological processes. In this work topsoil moisture dynamics under wet and dry conditions and across a small catchment was investigated in the inter row (IR) and directly under the olive tree canopies (UC). We do this using a sensor network (11 stations) and a simple bucket model which was calibrated (June, 2011–2012) and validated (June, 2012–2013). During most of the year the normalized soil moisture contents (s) were greater in the IR than under UC, with an average normalized soil moisture difference of 0.12. The difference between UC and IR normalized soil moisture followed a seasonal pattern, reaching a maximum near 0.30 during spring. An analysis of the normalized soil moisture probability density functions (pdfs) was bimodal, showing characteristic dominant wet and dry soil moisture states, with the highest probability densities for the dry state. Overall the spatial variability of soil moisture was lower UC than in the IR. This was a result of the soil moisture buffering capacity of the canopy with respect to rainfall and evaporation, in addition to observed differences in soil properties. Hourly soil moisture data were successfully modelled (R² > 0.85), both UC and in the IR, yet with the inclusion of a simple formulation for canopy interception for the former. The results provide insight into how olive trees change hydrological processes in their neighbourhood. Copyright © 2016 John Wiley & Sons, Ltd.     

Event-based deep drainage and percolation dynamics in Vertosols and Chromosols

The quantification of percolation processes and deep drainage rates in cracking clays is challenging due to the existence of multiple flow pathways, including desiccation crack networks, and the effect of variability in antecedent soil moisture and rain event properties. While most previous research on this topic focuses on long-term average rates, this study focusses on inter-event dynamics. The study uses data from soil moisture sensors distributed vertically down 4 m profiles of Vertosol and Chromosol soils across 13 sites over an area of approximately 20 km². The objectives were to estimate the temporal and spatial variability of deep drainage rates and to investigate the effect of antecedent soil moisture conditions and rain event properties on deep drainage rates and percolation dynamics. 35 deep drainage events over a 40-month period contributed 78 % of the total deep drainage of 254 mm at 4 m depth. Average deep drainage estimates were about 15 % (ranging from 0 – 80 % between sites) of total rainfall and irrigation in the Vertosol and 8% (0 – 24 %) in the Chromosol. The event water travel times at 4 m depth were 0.25 – 38 hr and 14 – 39 hr in the Vertosol and Chromosol respectively. The event deep drainage rates averaged across sites were associated with event rainfall volumes (linear regression R² = 0.40), with the effect of antecedent conditions evident only when looking at inter-site differences. The percolation response time was strongly associated with higher rainfall intensities (R² = 0.33) with no evidence from the linear regression of an antecedent moisture effect.     

Is the soil moisture precipitation feedback enhanced by heterogeneity and dry soils? A comparative study

The interaction between the land surface and the atmosphere is a crucial driver of atmospheric processes. Soil moisture and precipitation are key components in this feedback. Both variables are intertwined in a cycle, that is, the soil moisture – precipitation feedback for which involved processes and interactions are still discussed. In this study the soil moisture – precipitation feedback is compared for the sempiternal humid Ammer catchment in Southern Germany and for the semiarid to subhumid Sissili catchment in West Africa during the warm season, using precipitation datasets from the Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS), from the German Weather Service (REGNIE) and simulation datasets from the Weather Research and Forecasting (WRF) model and the hydrologically enhanced WRF-Hydro model. WRF and WRF-Hydro differ by their representation of terrestrial water flow. With this setup we want to investigate the strength, sign and variables involved in the soil moisture – precipitation feedback for these two regions. The normalized model spread between the two simulation results shows linkages between precipitation variability and diagnostic variables surface fluxes, moisture flux convergence above the surface and convective available potential energy in both study regions. The soil moisture – precipitation feedback is evaluated with a classification of soil moisture spatial heterogeneity based on the strength of the soil moisture gradients. This allows us to assess the impact of soil moisture anomalies on surface fluxes, moisture flux convergence, convective available potential energy and precipitation. In both regions the amount of precipitation generally increases with soil moisture spatial heterogeneity. For the Ammer region the soil moisture – precipitation feedback has a weak negative sign with more rain near drier patches while it has a positive signal for the Sissili region with more rain over wetter patches. At least for the observed moderate soil moisture values and the spatial scale of the Ammer region, the spatial variability of soil moisture is more important for surface-atmosphere interactions than the actual soil moisture content. Overall, we found that soil moisture heterogeneity can greatly affect the soil moisture – precipitation feedback.     

Factors controlling the spatial variability of surface soil moisture within revegetated‐stabilized desert ecosystems of the Tengger Desert,Northern China

The spatial structure of surface soil moisture was investigated at a grid scale with 10 × 10 m intervals on a plot of 4500 m² in a re‐vegetated desert area in Shapotou, the Tengger Desert. The site topography varies from dune crest to dune hollow, and again to dune crest. Volumetric soil moisture contents were measured 21 times over 6 months in 2006 by using Delta‐T Theta‐Probes in the 0–6 cm surface soil layer before and after rainfall. At the same time, soil texture, relative elevation, and plant coverage were measured, to examine (i) the spatial variability of surface soil moisture; (ii) the main factors controlling the spatial variability patterns; and (iii) how the importance of these factors varies with the seasonal variations in soil moisture content. The results indicated that the normal distribution of surface soil moisture was more obvious in wet conditions than in dry conditions; the spatial variability of surface soil moisture was inherent and decreased with increased soil moisture content; and precipitation increased the spatial dependence of surface soil moisture. The relative elevation of the landscape, the shrub coverage of the community, and the soil texture were the main factors influencing surface soil moisture variability, while the effect of soil texture strengthened gradually following the heavy precipitation events. The correlation between the spatial variability of surface soil moisture and the environmental factors, such as, the dry and wet conditions, the landscape coverage and the relative elevation suggests that increasing stability of the soil moisture resulted in a significant increase of soil moisture. Copyright © 2009 John Wiley & Sons, Ltd.     

Modelling water erosion in the Sahel: application of a physically based soil erosion model in a gentle sloping environment

Water is a major limiting factor in arid and semi‐arid agriculture. In the Sahelian zone of Africa, it is not always the limited amount of annual rainfall that constrains crop production, but rather the proportion of rainfall that enters the root zone and becomes plant‐available soil moisture. Maximizing the rain‐use efficiency and therefore limiting overland flow is an important issue for farmers. The objectives of this research were to model the processes of infiltration, runoff and subsequent erosion in a Sahelian environment and to study the spatial distribution of overland flow and soil erosion. The wide variety of existing water erosion models are not developed for the Sahel and so do not include the unique Sahelian processes. The topography of the Sahelian agricultural lands in northern Burkina Faso is such that field slopes are generally low (0–5°) and overland flow mostly occurs in the form of sheet flow, which may transport large amounts of fine, nutrient‐rich particles despite its low sediment transport capacity. Furthermore, pool formation in a field limits overland flow and causes resettlement of sediment resulting in the development of a surface crust. The EUROSEM model was rewritten in the dynamic modelling code of PCRaster and extended to account for the pool formation and crust development. The modelling results were calibrated with field data from the 2001 rainy season in the Katacheri catchment in northern Burkina Faso. It is concluded that the modified version of EUROSEM for the Sahel is a fully dynamic erosion model, able to simulate infiltration, runoff routing, pool formation, sediment transport, and erosion and deposition by inter‐rill processes over the land surface in individual storms at the scale of both runoff plots and fields. A good agreement is obtained between simulated and measured amounts of runoff and sediment discharge. Incorporating crust development during the event may enhance model performance, since the process has a large influence on infiltration capacity and sediment detachment in the Sahel. Copyright © 2005 John Wiley & Sons, Ltd.     

Variability in surface moisture content along a hillslope transect: Rattlesnake Hill, Texas

Surface soil moisture content exhibits a high degree of spatial and temporal variability. The purpose of this study was (a) to characterize variations in moisture content in the 0–5 cm surface soil layer along a hillslope transect by means of intensive sampling in both space and time; and (b) to make inferences regarding the environmental factors that influence this variability. Over a period of seven months, soil moisture content was measured (gravimetric method) on a near-daily basis at 10 m intervals along a 200 m downslope transect at the Rattlesnake Hill field site in Austin, Texas. Results indicate that significant variability in soil moisture content exists along the length of the transect; that variability decreases with decreasing transect-mean moisture content as the hillslope dries down following rain events; and that the dominant influences on moisture content variability are dependent upon the moisture conditions on the hillslope. While topographic and soil attributes operate jointly to redistribute soil water following storm events, under wet conditions, variability in surface moisture content is most strongly influenced by porosity and hydraulic conductivity, and under dry conditions, correlations are strongest to relative elevation, aspect and clay content. Consequently, the dominant influence on soil moisture variability gradually changes from soil heterogeneity to joint control by topographic and soil properties as the transect dries following significant rain events.     

Aeolian sand strip mobility and protodune development on a drying beach: examining surface moisture and surface roughness patterns measured by terrestrial laser scanning

Ephemeral aeolian sand strips are commonplace on beaches. Their formation during high energy sand transport events often precedes the development of protodunes and their dynamics present interesting feedback mechanisms with surface moisture patterns. However, due to their temporary nature, little is known of their formation, mobility or the specifics of their interaction with beach surface characteristics. Similarly surface moisture has an important influence on sediment availability and transport in aeolian beach systems, yet it is difficult to quantify accurately due to its inherent variability over both short spatial and temporal scales. Whilst soil moisture probes and remote sensing imagery techniques can quantify large changes well, their resolution over mainly dry sand, close to the aeolian transport threshold is not ideal, particularly where moisture gradients close to the surface are large. In this study we employed a terrestrial laser scanner to monitor beach surface moisture variability during a three and a half hour period after a rain event and investigated relationships between bedform development, surface roughness and surface moisture. Our results demonstrate that as the beach surface dries, sand transport increases, with sediment erosion occurring at the wet/dry surface boundary, and deposition further downwind. This dynamic structure, dependent upon changing surface moisture characteristics, results in the formation of a rippled sand strip and ultimately a protodune. Our findings highlight dynamic mobility relationships and confirm the need to consider transient bedforms and surface moisture across a variety of scales when measuring aeolian transport in beach settings. The terrestrial laser scanner provides a suitable apparatus with which to accomplish this. Copyright © 2010 John Wiley & Sons, Ltd.     

Influence of rainfall and soil properties spatial aggregation on extreme flash flood response modelling: An evaluation based on the Sesia river basin,North Western Italy

High resolution radar rainfall fields and a distributed hydrologic model are used to evaluate the sensitivity of flood and flash flood simulations to spatial aggregation of rainfall and soil properties at catchment scales ranging from 75 to 983 km². Hydrologic modeling is based on a Hortonian infiltration model and a network-based representation of hillslope and channel flow. The investigation focuses on three extreme flood and flash flood events occurred on the Sesia river basin, North Western Italy, which are analysed by using four aggregation lengths ranging from 1 to 16 km. The influence of rainfall spatial aggregation is examined by using the flow distance as a spatial coordinate, hence emphasising the role of river network in the averaging of space–time rainfall. The effects of reduced and distorted rainfall spatial variability on peak discharge have been found particularly severe for the flash flood events, with peak errors up to 35% for rainfall aggregation of 16 km and at 983 km² catchment size. Effects are particularly remarkable when significant structured rainfall variability combines with relatively important infiltration volumes due to dry initial conditions, as this emphasises the non-linear character of the rainfall–runoff relationship. In general, these results confirm that the correct estimate of rainfall volume is not enough for the accurate reproduction of flash flood events characterised by large and structured rainfall spatial variability, even at catchment scales around 250 km². However, accurate rainfall volume estimation may suffice for less spatially variable flood events. Increasing the soil properties aggregation length exerts similar effects on peak discharge errors as increasing the rainfall aggregation length, for the cases considered here and after rescaling to preserve the rainfall volume. Moreover, peak discharge errors are roughly proportional to runoff volume errors, which indicates that the shape of the flood wave is influenced in a limited way by modifying the detail of the soil property spatial representation. Conversely, rainfall aggregation may exert a pronounced influence on the discharge peak by reshaping the spatial organisation of the runoff volumes and without a comparable impact on the runoff volumes.     

Vapour source and spatiotemporal variation of precipitation isotopes in Southwest Spain

The δ²H and δ¹⁸O composition of 77 precipitation samples collected between January 2014 and April 2019 from two sites across the Guadalquivir Basin, SW Spain, were analysed. The first site is located in an urban area of Seville at 100 km distance to the Atlantic coast and the second site is located in a dune area of the Doñana National Park a few kilometres from the coast. Sampling was performed within intervals of at least 14 days if rain occurred but frequently intervals were longer according to the rainfall incidence. Samples from both sites are available for the period February 2016 to June 2018 with six samples containing identical rain events at both locations. Precipitation weighted averages and local meteoric water lines produced by weighting and non-weighting regression methods are presented for its use in hydrological applications. Results show a remarkably high variability in δ²H and δ¹⁸O values and precipitation weighted average d-excess values of 11.8‰ and 13‰ at the sites Plaza de España and Doñana, respectively. Temperature and amount effects were found to be weak. A significant influence of secondary evaporation for single rainfall events during summer was identified by enriched isotopic signatures with reduced d-excess values plotting close or below the global meteoric water line. Backward trajectory analysis of 115 days with daily rainfall above 3 mm yield a predominant Atlantic Ocean vapour source with negligible Mediterranean influence and therefore, d-excess variability is attributed to the different ocean surface conditions of relative humidity and sea surface temperature. Parallel sampling indicate very similar isotopic signatures at both sites and point to the existence of thermal effects of the Plaza de España site in Seville city during the summer season.     

Spatial Variability of Surface Soil Moisture in a Depression Area of Karst Region

An understanding of soil moisture variability is necessary to characterize the linkages between a region's hydrology, ecology, and physiography. In subtropical karst region, the spatial variability of surface soil moisture is still unclear for the rocky ecological environment and intensive land uses. The purpose of this study was to characterize the variation and patterns of soil moisture content at depth of 0–16 cm and to investigate their influencing factors in a karst depression area of southwest China. Soil moisture content was measured at 20 m intervals by intensive sampling on March 11 (dry season) and August 30 (rainy season) in 2005, respectively. Surface soil moisture presented a moderate variability in the depression area at the sampling times. The variability was relatively higher in dry season with lower mean soil moisture, but lower in rainy season with higher mean soil moisture after heavy rain event. Similar results were also obtained from the mosaic patterns of soil moisture generated by ordinary Kriging interpolation with low standard deviations. This suggested that more soil samples might be required and the sampling interval should be shortened in dry season compared with rainy season. The dominant influencing factors on the variability of surface soil moisture were rainfall and land use types. However, altitude, bare‐rock ratio, and soil organic carbon were also important factors, and exerted jointly to control and redistribute the surface soil moisture either in dry or rainy season in the depression area. Such information provided some insights for the study on eco‐hydrological processes of vegetation restoration in the karst degraded ecosystem of southwest China.     

Regional scale spatial and temporal variability of soil moisture in a prairie region

Understanding the dynamics of spatial and temporal variability of soil moisture at the regional scale and daily interval, respectively, has important implications for remote sensing calibration and validation missions as well as environmental modelling applications. The spatial and temporal variability of soil moisture was investigated in an agriculturally dominated region using an in‐situ soil moisture network located in central Saskatchewan, Canada. The study site evaluated three depths (5, 20, 50 cm) through 139 days producing a high spatial and temporal resolution data set, which were analysed using statistical and geostatistical means. Processes affecting standard deviation at the 5‐cm depth were different from the 20‐cm and 50‐cm depths. Deeper soil measurements were well correlated through the field season. Further analysis demonstrated that lag time to maximum correlation between soil depths increased through the field season. Temporal autocorrelation was approximately twice as long at depth compared to surface soil moisture as measured by the e‐folding frequency. Spatial correlation was highest under wet conditions caused by uniform rainfall events with low coefficient of variation. Overall soil moisture spatial and temporal variability was explained well by rainfall events and antecedent soil moisture conditions throughout the Kenaston soil moisture network. It is expected that the results of this study will support future remote sensing calibration and validation missions, data assimilation, as well as hydrologic model parameterization for use in agricultural regions. Copyright © 2016 John Wiley & Sons, Ltd.     

MODELLING RUNOFF GENERATION ON SMALL AGRICULTURAL CATCHMENTS: CAN REAL WORLD RUNOFF RESPONSES BE CAPTURED?

This paper focuses on the problem of quantifying real world catchment response using a distributed model and discusses the ability of the model to capture that response. The rainfall–runoff responses of seven small agricultural catchments in the eastern wheatbelt region of south-western Australia are examined. The variability in runoff generation and the factors that contribute to that variability (i.e. rainfall intensity, soil properties and topography) are investigated to determine if their influence can be captured in a mathematical model. The spatially distributed rainfall–runoff model used in this study is based on the TOPMODEL concepts of Beven and Kirkby (1979), and simulates runoff generation by both the infiltration excess and saturation excess mechanisms. Simulations with the model revealed the highly complex nature of catchment response to rainfall events. Runoff generation was highly heterogeneous in both space and time, with the runoff response being governed by the spatial variability of soil properties and topography, and by the temporal variation in rainfall intensity. Although the model proved capable of simulating catchment response for many events, the investigation has demonstrated that not all aspects of the variability associated with agricultural catchments (particularly the effects of land management) can be captured using this relatively simple model. © 1997 by John Wiley & Sons, Ltd     

Storage,mixing, and fluxes of water in the critical zone across northern environments inferred by stable isotopes of soil water

Quantifying soil water storage, mixing, and release via recharge, transpiration, and evaporation is essential for a better understanding of critical zone processes. Here, we integrate stable isotope (²H and ¹⁸O of soil water, precipitation, and groundwater) and hydrometric (soil moisture) data from 5 long‐term experimental catchments along a hydroclimatic gradient across northern latitudes: Dry Creek (USA), Bruntland Burn (Scotland), Dorset (Canada), Krycklan (Sweden), and Wolf Creek (Canada). Within each catchment, 6 to 11 isotope sampling campaigns occurred at 2 to 4 sampling locations over at least 1 year. Analysis for ²H and ¹⁸O in the bulk pore water was done for >2,500 soil samples either by cryogenic extraction (Dry Creek) or by direct equilibration (other sites). The results showed a similar general pattern that soil water isotope variability reflected the seasonality of the precipitation input signal. However, pronounced differences among sampling locations occurred regarding the isotopic fractionation due to evaporation. We found that antecedent precipitation volumes mainly governed the fractionation signal, temperature and evaporation rates were of secondary importance, and soil moisture played only a minor role in the variability of soil water evaporation fractionation across the hydroclimatic gradient. We further observed that soil waters beneath conifer trees were more fractionated than beneath heather shrubs or red oak trees, indicating higher soil evaporation rates in coniferous forests. Sampling locations closer to streams were more damped and depleted in their stable isotopic composition than hillslope sites, revealing increased subsurface mixing towards the saturated zone and a preferential recharge of winter precipitation. Bulk soil waters generally comprised a high share of waters older than 14 days, which indicates that the water in soil pores are usually not fully replaced by recent infiltration events. The presented stable isotope data of soil water were, thus, a useful tool to track the spatial variability of water fluxes within and from the critical zone. Such data provide invaluable information to improve the representation of critical zone processes in spatially distributed hydrological models.     

Soil moisture variability of root zone profiles within SMEX02 remote sensing footprints

Remote sensing of soil moisture effectively provides soil moisture at a large scale, but does not explain highly heterogeneous soil moisture characteristics within remote sensing footprints. In this study, field scale spatio-temporal variability of root zone soil moisture was analyzed. During the Soil Moisture Experiment 2002 (SMEX02), daily soil moisture profiles (i.e., 0–6, 5–11, 15–21, and 25–31 cm) were measured in two fields in Walnut Creek watershed, Ames, Iowa, USA. Theta probe measurements of the volumetric soil moisture profile data were used to analyze statistical moments and time stability and to validate soil moisture predicted by a simple physical model simulation. For all depths, the coefficient of variation of soil moisture is well explained by the mean soil moisture using an exponential relationship. The simple model simulated very similar variability patterns as those observed.As soil depth increases, soil moisture distributions shift from skewed to normal patterns. At the surface depth, the soil moisture during dry down is log-normally distributed, while the soil moisture is normally distributed after rainfall. At all depths below the surface, the normal distribution captures the soil moisture variability for all conditions. Time stability analyses show that spatial patterns of sampling points are preserved for all depths and that time stability of surface measurements is a good indicator of subsurface time stability. The most time stable sampling sites estimate the field average root zone soil moisture value within ±2.1% volumetric soil moisture.     

Characterization of field scale soil variability using remotely and proximally sensed data and response surface method

Soil salinization of the reclaimed tidelands is problematic. Therefore, there is a need to characterize the spatial variability of soil salinity associated with soil moisture and other soil properties across the reclaimed tidelands. One approach is the use of easily-acquired ancillary data as surrogates for the arduous conventional soil sampling. In a reclaimed coastal tideland in the south of Hangzhou Gulf, backscattering coefficient (σ⁰) from remotely sensed ALOS/PALSAR radar imagery (HH polarization mode) and apparent soil electrical conductivity (ECa) from a proximally sensed EM38 were used to indicate the spatial distribution of soil moisture and salinity, respectively. After that, response surface methodology (RSM) was employed to determine an optimal set of 12 soil samples using spatially referenced σ⁰ and ECa data. Spatial distributions of three soil chemical properties [i.e. soil organic matter (SOM), available nitrogen (AN), and available potassium (AK)] were predicted using inverse distance weighted method based on the 12 samples and were then compared with the predictions generated using 42 samples obtained from a conventional grid sampling scheme. It was concluded that combination of radar imagery and EM induction data can delineate the spatial variability of two key soil properties (i.e. moisture and salinity) across the study area. Besides, RSM-based sampling using radar imagery and EM induction data was highly effective in characterizing the spatial variability of SOM, AN and AK, compared with the conventional grid sampling. This new approach may be used to assist site specific management in precision agriculture.     

A model to simulate recharge processes of karst massifs

The recharge processes have been evaluated for two karst massifs of southern Italy, the Mt Terminio and Mt Cervialto, characterized by wide endorheic areas. The annual mean recharge has been estimated by Geographic Information System (GIS) tools, from regression of annual mean values of different ground‐elevated rain gauges and thermometers. The recharge has been distinguished for endorheic areas and the other areas of spring catchment, and the ratio between the output spring and input rainfall has been also estimated (recharge coefficient). The annual recharge has been used to calibrate a daily scale model, which allows to estimate the amount of effective rainfall, which is retained as soil moisture; the amount reaching the water table (recharge s.s.); and the amount of rainfall, which develops the runoff and leaves the catchment. All these amounts vary through the hydrological year, in function of soil moisture deficit and daily rainfall intensity. The model allows estimating the recharge conditions through the hydrological year, and it is a useful tool for water management. Copyright © 2014 John Wiley & Sons, Ltd.