Mean Soil Moisture Research Articles

Soil moisture memory and soil properties: An analysis with the stored precipitation fraction

It is of primary interest to determine the extent that natural processes are linked to understand natural system dynamics. There is growing interest in investigating the coupling and coevolution occurring between natural processes and the interaction between natural systems. Soil moisture is a variable that is at the core of the interaction between multiple physical and biological processes; therefore, it is very important to understand the influence of soil moisture dynamics on that coevolution. Soil moisture memory (SMM) shows soil moisture dynamics and the nature of their interaction with other related processes.Several studies have recognized that SMM depends on soil properties and some other meteorological and biophysical variables; however, there has not been a study specifically devoted to studying the relationship between SMM and the main soil properties. The present study analyzes the relationship between several relevant soil properties (texture, bulk density and organic matter content) involved in soil water dynamics and the stored precipitation fraction (Fp) as a suitable expression of the SMM. The relationship between SMM and precipitation and soil water content was also analyzed. These relationships were analyzed both at the surface layer and at several soil layer depths and with four soil moisture sampling frequencies (3 and 12 h, and 1 and 3 days). The study was conducted with data collected over a period of 12 years, at two soil moisture monitoring networks (REMEDHUS and SCAN) located in Spain and the USA, respectively, covering a wide range of soil characteristics and environmental conditions.The results showed that soil texture plays the main role in understanding SMM dynamics and that organic matter content has a good relationship with Fp. The sand fraction is the variable more correlated with Fp, with a clear inverse relationship (correlation coefficient, from −0.62 to −0.92 in REMEDHUS, and from −0.65 to −0.76 in SCAN). The variations in Fp observed with the different soil layer depths are also mainly correlated with texture and organic matter content, but only for sampling intervals of 1 and 3 days. The temporal variability of Fp in the different soil layers is more correlated with the soil water content than with annual precipitation, especially in the surface layer. At 0–5 depth, R ranges between 0.42 and 0.82. For sampling intervals of 1 and 3 days, the R values between Fp and mean soil moisture are always significant (p < 0.01) and higher than 0.66 in all soil layers. Therefore, in view of the cases studied and the results obtained, the most critical aspect of understanding SMM dynamics is precise characterization of the water storage conditions, especially in terms of texture and organic matter content.

Effects of rainwater harvesting system on soil moisture in rain-fed orchards on the Chinese Loess Plateau

Rainwater is a primary water source for the hilly and gully region of the Loess Plateau where an improved efficiency of rainwater utilization is crucial for sustainable agricultural development. A new system, comprised of rainwater harvesting, concentrating infiltration with multi-holed pipe and mulching (RIM), was designed to sustain soil moisture at a proper level in rain-fed orchards in the hilly and gully loess region of China. This study monitored changes in soil moisture and distribution over soil profiles using four treatments: (a) RIM1 with two rainwater harvesting areas, two infiltration pipes and film mulching, (b) RIM2 with one rainwater harvesting area, one infiltration pipe and film mulching, (c) film mulching (FM) only and (d) traditional apple orchard as a control treatment (CK) as a baseline in this experiment. The results showed that mean soil moisture content (SMC) in a range of soil layer between 0 cm and 300 cm for RIM1 and RIM2 treatments increased by 43.01% and 34.78% in 2018 and 30.55% and 26.41% in 2019, respectively. Dividing the soil vertical profile into three layers, i.e., an easy-changing layer (0−60 cm), an increasing or decreasing layer (60−180 cm), and a relatively steady layer (180−300 cm), this study examined the vertical changes of soil moisture. The RIM1 and RIM2 treatments induced a large increase in the size and depth of wetted areas over the whole soil layers. The soil moisture was replenished to a horizontal distance of 1.5 m and 2.5 m apart from the trunk within the soil layer between 60 cm and 300 cm under the RIM1 treatment while only the horizontal distance of 1.5 m apart from the trunk under the RIM2 treatment. While the seasonal variation of SMC in the easy-changing soil layer (0−60 cm) corresponded to precipitation consistently, the SMC in the deep soil layers (60−300 cm) was not sensitive to precipitation. As a result, the treatments of RIM1, RIM2 and FM improved apple yield and crop water productivity compared with those under the control treatment. In particular, the RIM1 treatment performed the best among the treatments investigated in this study. The results highlighted the efficiency of the RIM system in enhancing the soil moisture, which may be useful to improve an orchard production for rain-fed orchards in the loess hilly and gully region of China.

Evaluation and validation of TAMSAT‐ALERT soil moisture and WRSI for use in drought anticipatory action

AbstractReliable information on the likelihood of drought is of crucial importance in agricultural planning and humanitarian decision‐making. Acting based upon probabilistic forecasts of drought, rather than responding to prevailing drought conditions, has the potential to save lives, livelihoods and resources, but is accompanied by the risk of acting in vain. The suitability of a novel forecasting tool is assessed in the present paper in terms of its ability to provide skilful information of the likelihood of drought impacts on crops and pasture within a timeframe that allows for anticipatory action. The Tropical Applications of Meteorology using SATellite data—AgriculturaL Early waRning sysTem (TAMSAT‐ALERT) tool provides forecasts of seasonal mean soil moisture and the water requirement satisfaction index (WRSI). TAMSAT‐ALERT metrics were found to be strongly correlated with pasture availability and maize yield in Kenya and provided skilful forecasts early in key seasons, allowing sufficient time for preparatory actions. Incorporating TAMSAT‐ALERT forecasts in a layered approach, with actions triggered by spatiotemporally varying triggers and fundamentally informed by humanitarian actors, will provide reliable information on the likelihood of drought, ultimately mitigating food insecurity.

Effects of soil heterogeneity on subsurface water movement in agricultural fields: A numerical study

This study aims to numerically examine the effects of soil heterogeneity on subsurface water movement in agricultural fields under wheat (Triticum aestivum L.) and rice (Oryza sativa L.) crop covers. The 3-D Richards equation that accounts for root water uptake was coupled with a random field generation method to produce realizations of soil hydraulic properties, and the effects of soil heterogeneity were analyzed under realistic atmospheric boundary conditions. Four soil types and three different soil heterogeneity levels were considered to investigate the response of soil heterogeneity on soil water dynamics. It was observed that the effect of soil heterogeneity varies across soil types and its effect was more pronounced in silty clay loam soils. Further, an increase in soil heterogeneity level can increase or decrease the mean soil moisture, hydraulic conductivity, and flow velocity based on land cover, upper boundary condition, and atmospheric demand, and its effect was higher during irrigation periods. A maximum difference of 30% in soil moisture values was observed near the surface soil layers due to an increase in soil heterogeneity on irrigation days. The mean soil moisture content under rice crop cover was always lower than that of wheat crop cover due to higher atmospheric demand in the former. Soil layering effect on soil moisture dynamics, which is related to capillary and hydraulic barrier formation, was found to depend on the layering configuration, available soil moisture, and land cover. The numerical experiments provided useful insights into the complex soil moisture dynamics in agricultural fields.

Forecasting low flow conditions months in advance through teleconnection patterns, with a special focus on summer 2018

Over the past decades, Europe has been affected by several low flow periods which had substantial impacts on the hydrology of the rivers themselves as well as on the society and economy. Low flow periods have a direct impact on the environment, on the inland waterway navigation, on the hydropower production as well as on the sediment management, among others. Similar to floods, low flows are naturally occurring phenomena which can significantly hinder different uses and functions of the rivers and impact the aquatic system and the water quality. Moreover, it is projected that, in the future, climate change might lead to drier summers over the European region and therefore to more frequent and severe low flow periods. The results presented here show that the summer 2018 low flow situation, over the Rhine and Elbe Rivers basin, could have been predicted up to two seasons ahead by using previous months' sea surface temperature, sea level pressure, precipitation, mean air temperature and soil moisture. The lagged relationship between the predictand (e.g. seasonal streamflow) and the climate and oceanic predictors varies between 1 month (e.g. precipitation) up to 6 months (e.g. sea surface temperature). Taking into account that all predictors are available in real-time, the forecast scheme can be used to provide early warnings for the upcoming low flow situations, thus offering the possibility for better management of the water resources.

DEFICIT IRRIGATION OF SUBSURFACE DRIP-IRRIGATED GRAPE TOMATO

ABSTRACT Agriculture is one of the segments that most uses water and developments have been made to save irrigation water. Deficit irrigation is a technique that can contribute to production and water saving in agriculture. This study aimed to evaluate the viability of deficit irrigation in tomato production irrigated by subsurface drip in a greenhouse and estimate water saving. The experiment was conducted at the CCA/UFSCar, in Araras, Sao Paulo, Brazil, with grape tomato cultivation. It consisted of three treatments, 100 % water depth and deficit irrigation (75 and 50 % of water depth), with a randomized block design. Irrigation management was performed using mean soil moisture data collected through TDR probes installed in each treatment. Tomato plants were cultivated for 137 days and conducted vertically with one stem and six bunches. Fruit size, number and mass of fruits per plant, fruit pH and soluble solids were attributes measured and analyzed weekly. The deficit irrigation of 50 % treatment presented lower values in all attributes evaluated and 90.6 % of water saving. The 75 % treatment showed lower value only for pH and fruit diameter and 70.4 % of water saving. Deficit irrigation of 75 % was viable for tomato cultivation in greenhouse and for water saving in crop cycle.

Estimating the Number of Reference Sites Necessary for the Validation of Global Soil Moisture Products

The Committee on Earth Observation Satellites (CEOS) Land Product Validation (LPV) subgroup has been established to coordinate the development of standardized validation across the satellite-derived products from different platforms, sensors, and algorithms with reference measurements from the in situ networks. Soil moisture exhibits a high variability in space that challenges the in situ validation. One of the main drivers for this variability is the characteristic heterogeneity in the soil texture. By the machine learning methods using the soil profile measurements and the remotely sensed predictors, spatially continuous maps of basic soil properties such as soil texture and bulk density are available. Those can be used to estimate soil moisture variability within a satellite product grid cell, here exemplarily shown for the Soil Moisture Active Passive (SMAP) 36-km product. The soil moisture standard deviation is described as a function of the mean soil moisture, whereby the approach needs the mean and standard deviation of the hydraulic parameters as input. The resulting global data set helps identifying the number of in situ stations necessary to validate the coarse soil moisture products. For most SMAP grid cells, three to four stations are adequate to estimate the mean soil moisture for validation; however, also regions were identified where 80 stations are necessary.

Numerical investigation of streamtube approach to model flow in heterogeneous unsaturated sandy soils

The streamtube approximation has been commonly used for upscaling of flow and transport in spatially heterogeneous unsaturated soils. This study investigates the prediction ability of streamtube approach to model flow in heterogeneous unsaturated sandy soils under a rainfall event at a plot scale. Towards this aim, a numerical model for solving 3-D Richards’s equation was developed and verified for 1-D and 3-D cases. Turning band method was used to generate the random field of soil hydraulic parameters. The 3-D soil field heterogeneity was represented by considering variation in both van Genuchten parameter (α) and Ks. For streamtube models, two cases of heterogeneity were investigated: i) variability in Ks only, and ii) variability in both Ks and α. Both the parameters were assumed to follow a log-normal distribution. For different boundary conditions at the soil surface and varying soil heterogeneity, the average Darcy's flux and mean field-scale soil moisture obtained using streamtube approach were compared with 3-D numerical solutions. The results identify that for high recharge rate at the soil surface, streamtube model is a good approximation of the 3-D heterogeneous soil field, and the average difference in mean soil moisture obtained from 3-D model and streamtube based 1-D model was below 10% when variability in both Ks and α was considered for all timesteps. The inclusion of variability in α leads to improvement in prediction capability of streamtube model. Further, regression equations were developed that can be utilized to predict the mean field soil moisture for heterogeneous 3-D sandy soil fields given the mean field soil moisture obtained from streamtube approach for both the cases. The regressions equations follow exponential model for case-1 and linear model for case-2 with R2 values 0.80 and 0.99, respectively. The developed equations can be reliably used to predict mean field soil moisture for heterogeneous sandy soil fields.

Assessment of Remotely Sensed and Modelled Soil Moisture Data Products in the U.S. Southern Great Plains

Soil moisture (SM) plays a crucial role in the water and energy flux exchange between the atmosphere and the land surface. Remote sensing and modeling are two main approaches to obtain SM over a large-scale area. However, there is a big difference between them due to algorithm, spatial-temporal resolution, observation depth and measurement uncertainties. In this study, an assessment of the comparison of two state-of-the-art remotely sensed SM products, Soil Moisture Active Passive (SMAP) and European Space Agency Climate Change Initiative (ESACCI), and one land surface modeled dataset from the North American Land Data Assimilation System project phase 2 (NLDAS-2), were conducted using 17 permanent SM observation sites located in the Southern Great Plains (SGP) in the U.S. We first compared the daily mean SM of three products with in-situ measurements; then, we decompose the raw time series into a short-term seasonal part and anomaly by using a moving smooth window (35 days). In addition, we calculate the daily spatial difference between three products based on in-situ data and assess their temporal evolution. The results demonstrate that (1) in terms of temporal correlation R, the SMAP (R = 0.78) outperforms ESACCI (R = 0.62) and NLDAS-2 (R = 0.72) overall; (2) for the seasonal component, the correlation R of SMAP still outperforms the other two products, and the correlation R of ESACCI and NLDAS-2 have not improved like the SMAP; as for anomaly, there is no difference between the remotely sensed and modeling data, which implies the potential for the satellite products to capture the variations of short-term rainfall events; (3) the distribution pattern of spatial bias is different between the three products. For NLDAS-2, it is strongly dependent on precipitation; meanwhile, the spatial distribution of bias represents less correlation with the precipitation for two remotely sensed products, especially for the SMAP. Overall, the SMAP was superior to the other two products, especially when the SM was of low value. The difference between the remotely sensed and modeling products with respect to the vegetation type might be an important reason for the errors.

Evaluation of ESACCI satellite soil moisture product using in-situ CTCZ observations over India

Recently available European Space Agency Climate Change Initiative (ESACCI) soil moisture dataset, derived by merging soil moisture values calculated using measurements from satellite-based active and passive sensors, is validated over the Indian region using in-situ observations from 117 Continental Tropical Convergence Zone (CTCZ) Programme stations spread across India. The dataset is compared for the monsoon season (June–September: JJAS) of two years – 2011–2012, over six regional domains which differ in soil characteristics and mean soil moisture values, thus taking the spatial heterogeneity into account. Evaluation shows that the mean JJAS ESACCI volumetric soil moisture is 25.5% ( $$\hbox {m}^{3}\,\hbox {m}^{-3}$$ ), with an intra-seasonal standard deviation of 6%. The root mean squared difference (RMSD) between ESACCI soil moisture product and CTCZ observations is 10% over the Indian region. Over smaller homogeneous regions, the RMSD values between the two products are smaller than 5%, except over southern India and north-east India. Overall, the ESACCI soil moisture dataset is in good agreement with the CTCZ in-situ soil moisture observations, and has relatively higher accuracy over the plains of northern and central India, as compared to other regions. However, the ESACCI soil moisture dataset shows higher intra-seasonal variability at shorter time-scale of 2–4 days, as compared to the CTCZ observations, possibly due to the difference in the soil sampling depths between the two datasets.

Response of Soil Moisture to Rainfall Event in Black Locust Plantations at Different Stages of Restoration in Hilly-gully Area of the Loess Plateau, China

Precipitation plays an important role in the water supplies that support ecological restoration by sustaining large-scale artificial plantations in arid and semiarid regions, especially black locust (Robinia pseudoacacia) plantations (RP plantations), which are widely planted due to R. pseudoacacia being an excellent pioneer species. Characterizing the response of soil moisture to rainfall events at different stages of restoration is important for assessing the sustainability of restoration in RP plantations. In this study, we quantified the response of soil moisture to rainfall events at different years of restoration (15, 20 and 30 yr) representing different restoration stages in RP plantations in a typical hilly-gully area, i.e., the Yangjuangou Catchment, of the Loess Plateau, China. Over the growing season (June to September) of 2017, smart probes were placed at nine depths (10, 20, 40, 60, 80, 100, 120, 150, and 180 cm below the soil surface) to obtain volumetric soil water information at 30-min intervals in the three RP plantations. The advance of the wetting front was depicted, and the total cumulative water infiltration was measured. Soil moisture was mainly replenished by eight heavy rainfall events (mean rainfall amount = 46.3 mm), accounting for 88.7% of the rainfall during the growing season. The mean soil moisture content profiles of RP plantations at the three restoration stages were ordered as 30-yr (14.07%) > 20-yr (10.12%) > 15-yr (8.03%), and this relationship displayed temporal stability. Soil moisture was primarily replenished by rainfall at the 0–60 cm soil depth, and soil moisture remained stable below the 100-cm soil depth. The rainfall regime influenced the advancement of the wetting front. Here, a single rainfall event of 30 mm was the rainfall threshold for infiltration into the 60-cm soil layer. The total infiltration time ranged from 310.5–322.0 h, but no significant differences were found among RP plantations at different restoration stages. Young and old RP plantations had more total infiltration (more than 228.2 mm) and deeper infiltration depths (80–100 cm) than middle-aged plantations. The RP plantation at the intermediate restoration stage exhibited minimal total infiltration (174.2 mm) and a shallow infiltration depth (60 cm) due to the soil physical structure of the plot, which may have limited rain infiltration. More stand conditions that may affect infiltration should be considered for priority afforestation areas.

Evaluation of Satellite-Derived Surface Soil Moisture Products over Agricultural Regions of Canada

Soil moisture is a critical indicator for climate change and agricultural drought, but its measurement is challenging due to large variability with land cover, soil type, time, space and depth. Satellite estimates of soil moisture are highly desirable and have become more widely available over the past decade. This study investigates and compares the performance of four surface soil moisture satellite datasets over Canada, namely, Soil Moisture and Ocean Salinity Level 3 (SMOS L3), versions 3.3 and 4.2 of European Space Agency Climate Change Initiative (ESA CCI) soil moisture product and a recent product called SMOS-INRA-CESBIO (SMOS-IC) that contains corrections designed to reduce several known sources of uncertainty in SMOS L3. These datasets were evaluated against in situ networks located in mostly agricultural regions of Canada for the period 2012 to 2014. Two statistical comparison methods were used, namely, metrics for mean soil moisture and median of metrics. The results suggest that, while both methods show similar comparisons for regional networks, over large networks, the median of metrics method is more representative of the overall correlation and variability and is therefore a more appropriate method for evaluating the performance of satellite products. Overall, the SMOS products have higher daily temporal correlations, but larger biases, against in situ soil moisture than the ESA CCI products, with SMOS-IC having higher correlations and smaller variability than SMOS L3. The SMOS products capture daily wetting and drying events better than the ESA CCI products, with the SMOS products capturing at least 75% of observed drying as compared to 55% for the ESA CCI products. Overall, for periods during which there are sufficient observations, both SMOS products are more suitable for agricultural applications over Canada than the ESA CCI products, even though SMOS-IC is able to capture soil moisture variability more accurately than SMOS L3.

Bias-adjusted seasonal forecasts of soil moisture for forestry applications in Finland

Abstract. Seasonal forecasts for forestry have been developed in the Finnish Meteorological Institute in cooperation with Finnish end-users. Such forecasts could help forest companies in preparing for adverse conditions of timber harvesting operations. Bearing capacity for harvesting operations is dependent on soil moisture, and skillful forecasts have potentially large economic value. Using the ECMWF seasonal forecasts, we evaluated the monthly mean soil moisture forecasts for four different start months, with lead times from 0 to 2 months. Forecasts were bias adjusted, and showed skill in the first month for all four months. After the first lead month, winter months fared a bit better than summer months.

Effect of agri-silvi-horticultural system on soil moisture content at different depths

The present study was conducted at Research Farm, Department of Forestry CCS HAU, Hisar to analyze the effect of agri-silvi-horticultural system (Kinnow +Eucalyptus+ Wheat, Kinnow+ Wheat and sole crop on soil moisture content at0-15, 15-30, 30-60 and 60-90 cm soil depths). Total five irrigations at an interval of one month were applied from sowing to harvesting stage. Soil moisture content was measured gravimetrically before each irrigation. Moisture content was increased significantly with increase in soil depth but it decreased under tree integrated system and maximum decrease was observed under Kinnow + Eucalyptus + wheat system. There was slight difference between first and second irrigation which shows more moisture content relative to succeeding 3 irrigations. During first irrigation, mean soil moisture content was significantly higher under control (12.6%) followed by Kinnow+Wheat (11.7%) and it was lowest under Kinnow+Eucalyptus+Wheat system (10.7%). Similarly at second irrigation, mean soil moisture content was significantly higher under control (11.7%) followed by Kinnow+Wheat (10.7%). Significantly lowest was under Kinnow+Eucalyptus+Wheat system (10.0%) as compared to control. In succeeding three irrigations, mean soil moisture content was statistically at par with each other in all the systems. Based on above study, results showed that there was more uptake of moisture under tree based system which is due to deep and proliferated root system of tree component as compared to sole crop.

The spatial variability of soil water content in a potato field before and after spray irrigation in arid northwestern China

Abstract Assessing the spatial variability of soil water content is important for precision agriculture. To measure the spatial variability of the soil water content and to determine the optimal number of sampling sites for predicting the mean soil water content at different stages of the irrigation cycle, field experiments were carried out in a potato field in northwestern China. The soil water content was measured in 2016 and 2017 at depths of 0–20 and 20–40 cm at 116 georeferenced locations. The average coefficient of variation of the soil water content was 20.79% before irrigation and was 16.44% after irrigation at a depth of 0–20 cm. The spatial structure of the soil water content at a depth of 20–40 cm was similar throughout the irrigation cycle, but at a depth of 0–20 cm a relatively greater portion of the variation in the soil water content was spatially structured before irrigation than after irrigation. The autocorrelation of soil water contents was influenced by irrigation only in the surface soil layer. To accurately predict mean soil moisture content, 40 and 20 random sampling sites should be chosen with errors of 5% and 10%, respectively.

Vegetation dynamics and their drivers in the Haihe river basin, Northern China, 1982–2012

In this study, we quantified the vegetation changes in the Haihe river basin (HRB) and analyzed their drivers during 1982–2012 by using satellite normalized difference vegetation index (NDVI) data, observation-based climate data, satellite vegetation continuous fields (VCF) data, and soil moisture (SM) data. The results showed that the increases in NDVI was the largest in autumn (2.12 × 10−3), followed by growing-season (1.97 × 10−3), spring (1.82 × 10−3), annual (1.35 × 10−3), summer (1.15 × 10−3), and winter (0.32 × 10−3). The VCF, mean annual temperature (MAT), SM, and mean annual precipitation (MAP) determined the NDVI changes in 44.43%, 27.69%, 5.33%, and 2.01% of the HRB, respectively. In the western and southern HRB, MAT and VCF were the dominant factors, besides, SM was one of the important factors in the western HRB. Therefore, the study identified that SM, MAT, and human activities (Changes in VCF) were the main factors that determined the changes in vegetation over HRB.

Characteristics of Bandicota bengalensis burrows during different growth stages of wheat crop in Punjab

Burrowing is an activity used by rodents for resting, sleeping and food hoarding purposes and is affected by different abiotic and biotic factors. In the present study, an attempt has been made to describe the burrow structure of Bandicota bengalensis in relation to different crop stages of wheat crop. We observe that as the growth stages of wheat crop change from tillering to lean period, there is change in pattern of burrow structure by rodents. The length of burrow was maximum (200.80±2.84cm) during tillering stage and minimum (172.40±2.97cm) during lean period, whereas the depth of burrow was minimum (52.50 ±1.65cm) during tillering and maximum (68.90±2.83cm) in lean period to keep the environment of burrow optimum when mean soil moisture (%) and soil temperature recorded were 25.62%, 14.72°C and 14.88%, 25.84°C, respectively. The mean number of open ends, blind ends, number of nest chambers and number of burrow branches were highest during dough stage and lowest during lean period. Present study will help in development of policies that include strategies for rodent pest management i.e. for placing poison baits in burrows so that the rodent damage to crops may be reduced to a minimum level and farm income may be increased.

Soil moisture and a legacy of prehistoric human activities have contributed to the extraordinary plant species diversity of grasslands in the White Carpathians

The factors that determine the unique species richness and composition of some temperate grasslands are poorly known. Uniqueness of the extraordinarily species-rich grasslands in the White Carpathian mountain range (Czech Republic, Slovakia), with many disjunct occurrences of species, have been previously attributed to intermittently wet deep soils, which facilitate the co-occurrence of steppe and wet-grassland species, and Holocene continuity of open land, resulted in large species pools. Based on a detailed investigation of 23 well-preserved regularly mown grasslands differing in their vegetation composition and species richness, we tested the relative importance of the hypothetical determinants of compositional variability within semi-dry grasslands. For the first time we included measurements of seasonal moisture at different soil depths and landscape differences in the intensity of the effect of prehistoric humans. Soil moisture was measured using the frequency-domain reflectometry based Profile Probe PR2 sensor at depths of 10, 20, 30, 40 and 60 cm in the soil, repeatedly every four weeks from April to November. Soil samples were taken from the same depths in order to determine soil basicity and nutrient content. As a proxy of the intensity of the effect of prehistoric human activities, mean distances between sampled localities and the five nearest Neolithic or Aeneolithic settlements were used. The species richness was best explained by mean soil moisture, which increased towards the most species-rich grasslands, whereas the distance from prehistoric settlements had no effect. Basicity, moisture and the distance from prehistoric settlements had significant conditional effects on species composition. There was a high frequency of species of intermittently wet soils, thermophilous oak forests and forest fringes in the most valuable grasslands, which are located mostly in the south-western part of the area where the soils were moister and closer to prehistoric settlements, but the seasonal variation in moisture was not high. We conclude that coexistence of species from different habitats is dependent on regular management and high soil moisture throughout the growing season. Due to intermediate moisture conditions that are tolerated by multiple ecological groups of species, many species may locally coexist and form a species-rich grassland community of unique species composition. In addition, prehistoric human activities contributed to landscape openness and helped maintain a forest-steppe species pool during the Holocene forest optimum. Our results indicate that although this historical determinant shapes predominantly the species composition pattern, the extraordinarily species-rich spots are determined rather by abiotic factors, such as intermediate moisture and biotic interactions resulting from the type and duration of management practices.

Ensemble long-term soil moisture forecast using hydrological modeling

ABSTRACT Long-term soil moisture forecasting allows for better planning in sectors as agriculture. However, there are still few studies dedicated to estimate soil moisture for long lead times, which reflects the difficulties associated with this topic. An approach that could help improving these forecasts performance is to use ensemble predictions. In this study, a soil moisture forecast for lead times of one, three and six months in the Ijuí River Basin (Brazil) was developed using ensemble precipitation forecasts and hydrologic simulation. All ensemble members from three climatologic models were used to run the MGB hydrological model, generating 207 soil moisture forecasts, organized in groups: (A) for each model, the most frequent soil moisture interval predicted among the forecasts made with each ensemble member, (B) using each model’s mean precipitation, (C) considering a super-ensemble, and (D) the mean soil moisture interval predicted among group B forecasts. The results show that long-term soil moisture based on precipitation forecasts can be useful for identifying periods drier or wetter than the average for the studied region. Nevertheless, estimation of exact soil moisture values remains limited. Forecasts groups B and D performed similarly to groups A and C, and require less data management and computing time.

Responses of soil carbon decomposition to drying-rewetting cycles: A meta-analysis

Drying-rewetting cycles (DWC) is an important climate change factor in this century. The rewetting of dry soil stimulates carbon dioxide emission into the atmosphere, which is called the Birch effect. Although a large number of studies have been conducted to quantify the effect of DWC on cumulative soil respiration (CSR), their results are often contradictory, which offers us an opportunity to explore potential influencing factors and variability among studies. Using a meta-analysis including 524 observations from studies across different ecosystems and soil types, we investigated the responses of CSR to DWC. Our results indicated that DWC led to 72% stimulation of CSR compared with lower constant-moisture control (LC), 25% inhibition compared with upper constant-moisture control (UC), but minimal difference with mean constant-moisture control (MC), respectively. The meta-regression analysis showed that the DWC effect on CSR depended on mean annual precipitation, soil properties (clay content, C/N ratio, TN, pH), and the duration of drying in the DWC treatment. In addition, the effect size of CSR relative to UC was positively correlated with the number of DWC, suggesting that the slower-cycling soil carbon may be more vulnerable to DWC than the faster-cycling soil carbon and the “physical mechanism” may play a role in substrate release and CO2 emission after multiple DWC. Overall, our study provided a comprehensive analysis of the effects of DWC on CSR and showed that frequent drying-rewetting cycles induced by climate change might stimulate the loss of soil carbon to the atmosphere. Moreover, the similar CSR between DWC and MC (which have the same mean soil moisture content) suggests that the CO2 pulse after rewetting may be compensated by the low CO2 emission during the drying phase. Further research is needed to explore the responses of SOC pools with different turnover times to DWC and to investigate the DWC effects on soil respiration by in situ experiments and long-term studies.