Seasonal Variation Of Soil Moisture Research Articles

Links between seasonal suprapermafrost groundwater, the hydrothermal change of the active layer, and river runoff in alpine permafrost watersheds

Abstract. The seasonal dynamic of the suprapermafrost groundwater significantly affects the runoff generation and confluence in permafrost basins and is a leading issue that must urgently be addressed in hydrological research in cold and alpine regions. In this study, the seasonal dynamic process of the suprapermafrost groundwater level (SGL), vertical gradient changes of soil temperature (ST), moisture content in the active layer (AL), and river level changes were analyzed at four permafrost watersheds in the Qinghai–Tibet Plateau using comparative analysis and the nonlinear correlation evaluation method. The impact of freeze–thaw processes on seasonal SGL and the links between SGL and surface runoff were also investigated. The SGL process in a hydrological year can be divided into four periods: (A) a rapid falling period (October to mid-November), (B) a stable low-water period (late November to May), (C) a rapid rising period (approximately June), and (D) a stable high-water period (July to September), which synchronously respond to seasonal variations in soil moisture and temperature in the AL. The characteristics and causes of SGL changes significantly varied during these four periods. The freeze–thaw process of the AL regulated SGL and surface runoff in permafrost watersheds. During period A, with rapid AL freezing, the ST had a dominant impact on the SGL. In period B, the AL was entirely frozen due to the stably low ST, while the SGL dropped to the lowest level with small changes. During period C, ST in the deep soil layers of AL (below 50 cm depth) significantly impacted the SGL (nonlinear correlation coefficient R2 > 0.74, P < 0.05), whereas the SGL change in the shallow soil layer (0–50 cm depth) showed a closer association with soil moisture content. Rainfall was the major cause for the stable high SGL during period D. In addition, the SGLs in periods C and D were closely linked to the retreat and flood processes of river runoff. The SGL contributed approximately 57.0 %–65.8 % of the river runoff changes in the period D. These findings will help to facilitate future hydrological research in the permafrost basins and the development and utilization of water resources in cold and alpine regions.

Topographic Wetness Index as a Proxy for Soil Moisture in a Hillslope Catena: Flow Algorithms and Map Generalization

Topographic wetness index (TWI) is used as a proxy for soil moisture, but how well it performs across varying timescales and methods of calculation is not well understood. To assess the effectiveness of TWI, we examined spatial correlations between in situ soil volumetric water content (VWC) and TWI values over 5 years in soils at 42 locations in an agroforestry catena in Fayetteville, Arkansas, USA. We calculated TWI 546 ways using different flow algorithms and digital elevation model (DEM) preparations. We found that most TWI algorithms performed poorly on DEMs that were not first filtered or resampled, but DEM filtration and resampling (collectively called generalization) greatly improved the TWI performance. Seasonal variation of soil moisture influenced TWI performance which was best when conditions were not saturated and not dry. Pearson correlation coefficients between TWI and grand mean VWC for the 5-year measurement period ranged from 0.18 to 0.64 on generalized DEMs and 0.15 to 0.59 for on DEMs that were not generalized. These results aid management of crop fields with variable moisture characteristics.

The Seasonal and Diurnal Variation Characteristics of Soil Moisture at Different Depths from Observational Sites over the Tibetan Plateau

Using observational data of soil moisture from the third Tibetan Plateau Experiment for atmospheric science (TIPEX III), the seasonal and diurnal variations characteristics of soil moisture at different depths of 5–160 cm from seven stations were analyzed, with emphasis on the comparative analysis of the differences of soil moisture between different sites and the differences of the synergistic relationship between soil moisture and temperature. The soil moisture was wet in the southeast and dry in the northwest. The studied sites were Lhari, Biru, Nyainrong, Amdo, Nagqu, Baingoin and Seng-ge Kambab in descending order, according to the soil moisture. The seasonal variation of soil moisture at the different sites showed a significant three-peak structure, which was more obvious in the shallow layer than in the deep layer. The first peak occurred from March to May, which was mainly due to the soil thawing in spring. The other two peaks corresponded to the two rainy seasons in the plateau. Soil moisture was the greatest during this rainy period. The diurnal variations of soil moisture and temperature in Amdo, Nagqu, Nyainrong and Baingoin showed a significant positive correlation in the four seasons. The soil moisture and temperature in Lhari and Biru were significantly positively correlated in winter and spring but negatively correlated in summer and autumn. The profiles of the soil moisture with depth varied greatly at different stations in different seasons. The distribution of soil water content at each observational site did not increase or decrease with depth but showed a certain high aquifer, which might be related to the types of the underlying surface and physical properties of soil. During the summer monsoon period, soil moisture in the shallow layer of 5–10 cm was higher at all observational sites. The spatial distribution of soil moisture in the plateau was more heterogeneous than that in the plain area, and only in the central part of the Tibetan Plateau, the soil moisture varied greatly from site to site. This also indicated that it was unreasonable to only use the soil moisture of several stations to represent the overall soil moisture of the region. The results provided a multi-angle observational basis for the validation of satellite data and parameterization of the numerical model of soil moisture over the Tibetan Plateau.

Evaluation and Comparison of the Common Land Model and the Community Land Model by Using In Situ Soil Moisture Observations from the Soil Climate Analysis Network

Soil moisture is a key state variable in land surface processes. Since field measurements of soil moisture are generally sparse and remote sensing is limited in terms of observation depth, land surface model simulations are usually used to continuously obtain soil moisture data in time and space. Therefore, it is crucial to evaluate the performance of models that simulate soil moisture under various land surface conditions. In this work, we evaluated and compared two land surface models, the Common Land Model version 2014 (CoLM2014) and the Community Land Model Version 5 (CLM5), using in situ soil moisture observations from the Soil Climate Analysis Network (SCAN). The meteorological and soil attribute data used to drive the models were obtained from SCAN station observations, as were the soil moisture data used to validate the simulation results. The validation results revealed that the correlation coefficients between the simulations by CLM5 (0.38) and observations are generally higher than those by CoLM2014 (0.11), especially in shallow soil (0–0.1016 m). The simulation results by CoLM2014 have smaller bias than those by CLM5 . Both models could simulate diurnal and seasonal variations of soil moisture at seven sites, but we found a large bias, which may be due to the two models’ representation of infiltration and lateral flow processes. The bias of the simulated infiltration rate can affect the soil moisture simulation, and the lack of a lateral flow scheme can affect the models’ division of saturated and unsaturated areas within the soil column. The parameterization schemes in land surface models still need to be improved, especially for soil simulations at small scales.

Estimation and Validation Study of Soil Moisture Using GPS-IR Technique Over a Tropical Region: Variability of SM With Rainfall and Energy Fluxes

Soil Moisture (SM) data play an important role in different fields of research like hydrology, agriculture, climatology, etc. In this article, global positioning system interferometric reflectometry technique was used to estimate SM. Estimated SM data have been validated and compared with collocated <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in situ</i> probe, Soil Moisture and Ocean Salinity (SMOS) satellite measurements, ECMWF ERA-5, and NASA Global Land Data Assimilation System (GLDAS); the former shows a good correlation of 0.98 but the magnitudes of SMOS, ERA-5 are overestimated and GLDAS data are underestimated. Variability of SM with rainfall and energy fluxes like latent and sensible heat fluxes from ERA-5 and GLDAS data are investigated. Observed SM values are positively correlated with rainfall during the study period. Seasonal variations of SM with rainfall in different monsoons are clearly noticed. Latent heat fluxes are more during spring, summer months and positively correlated with rainfall, whereas sensitive heat fluxes show negative correlation.

Negative‐pressure irrigation improves water and fertilizer use efficiencies and fruit yield of greenhouse tomato on the North China Plain*

AbstractWater and fertilizer supply are the main factors limiting greenhouse vegetable production on the North China Plain. This study tested the hypothesis that negative‐pressure irrigation is advantageous for reducing water and fertilizer application compared with drip irrigation in a greenhouse. Three treatments (drip irrigation + optimal fertilizer [DOF], drip irrigation + Yamazaki tomato nutrient solution [DNS], and negative‐pressure irrigation + Yamazaki tomato nutrient solution [NNS]) were applied in a greenhouse tomato double‐cropping system conducted in consecutive spring–summer and autumn–winter seasons. Soil moisture content, nitrate‐nitrogen (N) concentration, fruit yield, total N uptake (Nu), irrigation water productivity, and partial factor productivity of applied fertilizer were analysed. The seasonal variation of soil moisture and nitrate‐N contents in the 0–20‐cm soil layer for NNS treatment was stable. Nitrate‐N accumulated after the final harvest in the autumn–winter season of NNS treatment was significantly less than under DOF and DNS. Despite lower water and nutrient inputs, NNS showed higher Nu and fruit yield than DOF and DNS. These results demonstrated that negative‐pressure irrigation can reduce irrigation water and nutrient inputs and nitrate‐N accumulation in the soil, and significantly improve water and fertilizer use efficiency in greenhouse‐grown tomato compared with those under drip irrigation.

A New Drought Index for Soil Moisture Monitoring Based on MPDI-NDVI Trapezoid Space Using MODIS Data

The temperature vegetation dryness index (TVDI) has been commonly implemented to estimate regional soil moisture in arid and semi-arid regions. However, the parameterization of the dry edge in the TVDI model is performed with a constraint to define the maximum water stress conditions. Mismatch of the spatial scale between visible and thermal bands retrieved from remotely sensed data and terrain variations also affect the effectiveness of the TVDI. Therefore, this study proposed a new drought index named the condition vegetation drought index (CVDI) to monitor the temporal and spatial variations of soil moisture status by substituting the land surface temperature (LST) with the modified perpendicular drought index (MPDI). In situ soil moisture observations at crop and pasture sites in Victoria were used to validate the effectiveness of the CVDI. The results indicate that the dry and wet edges in the parameterization scheme of the CVDI formed a better-defined trapezoid shape than that of the TVDI. Compared with the MPDI and TVDI for soil moisture monitoring at crop sites, the CVDI exhibited a performance superior to the MPDI and TVDI in most days where the coefficients of determination (R2) achieved can reach to 0.67 on DOY023, 137, 274 and 0.71 on DOY 322 and reproduced more accurate spatial and seasonal variation of soil moisture. Moreover, the CVDI showed higher correlation with the Australian Water Resource Assessment Landscape (AWRA-L) soil moisture product on temporal scales. The R2 can reach to 0.69 and the root mean square error (RMSE) is also much better than that of the MPDI and TVDI. Overall, it can be concluded that the CVDI appears to be a feasible method and can be successfully used in regional soil moisture monitoring.

Vertical distribution and seasonal variation of soil moisture after drip-irrigation affects greenhouse gas emissions and maize production during the growth season

Providing enough food for the increasing global population is difficult due to water shortages, which can be partially resolved by regulating soil moisture. Soil moisture influences soluble nutrient uptake and microbial activity, which determine crop growth, but also affects greenhouse gas (GHG) emissions. Farming is increasingly contributing to GHG emission, but little is known about the effects of the vertical soil moisture distribution on GHG or maize (Zea mays L.) yield over the growth season. In this study, there were five irrigation treatments: no irrigation (NI), and irrigation of the top (0–30 cm) (TI), middle (30–60 cm) (MI), bottom (60–90 cm) (BI), and all (0–90 cm) (AI) soil layers. The results showed that TI, MI, BI, and AI increased CO2 (25–60%), CH4 (80–270%), and N2O (17–96%) emissions, and the global warming potential (25–63%), while also increasing grain yield (13–119%) and reducing GHG intensity by 12–27%. While higher soil moisture in the shallow soil layer increased grain yield and GHG emissions, GHG intensity was lowest. Subsurface irrigation or control of the “drip irrigation interval” improve grain yield and resource use efficiency with lower environmental costs contributing agricultural sustainable development.

Dynamic variations in soil moisture in an epikarst fissure in the karst rocky desertification area

Epikarst fissures filled with soil (EFS) are important factors controlling karst hydrological processes and ecological hydrological functions. The EFS are common in karst rocky desertification areas, and it is important to understand the hydraulic properties and hydrological characteristics of EFS for vegetation restoration. In this study, we analysed the soil moisture content dynamics of surface soil and EFS in a rocky desertification environment to explore the influencing factors of soil moisture variation. A typical epikarst fissure was selected as the sample site in the rocky desertification area of the Karst Plateau Gorge (Beipanjiang catchment, Guizhou Province) in Southwest China, and surface soil was used as the control site. From May 12, 2018 to January 10, 2020, soil moisture content data for the EFS profile (20, 80, 140, 200, and 260 cm) and the surface soil profile (20 and 40 cm) were monitored synchronously at 30-min intervals. Simultaneously, soil samples were collected to measure the physical properties. The results show that the difference in vegetation cover and soil physical properties is the main reason for the difference in soil water dynamics between the shallow EFS and surface soil. The shallow EFS hydraulic connectivity is better, and the mean values of total porosity and saturated hydraulic conductivity of shallow EFS are 15.6% and 69.5% higher than those of the surface soil, respectively. The seasonal variations in soil moisture in the shallow EFS are obvious, the soil moisture rainfall response and dry-wet alternation are fast, the seasonal variations in soil moisture in the surface soil are relatively stable, and the soil water retention time is long. In the EFS profile, the hydraulic connectivity of the shallow soil (0–40 cm) are obviously better than those in the middle and lower layers (40–280 cm), which affected the response speed and retention time of soil water at different depths. In conclusion, the vertical hydraulic connectivity of the EFS profile is quite different and is shown to be significantly different from the surface soil hydrology. These results are helpful for understanding the ecohydrological process of epikarst.

Characterization of the seasonal variation of soil moisture in Argentina

AbstractSoil moisture is an essential variable for both the agricultural production and the functioning of natural ecosystems, as well as one of the main variables regulating the climate system. Like precipitation, soil moisture has a marked annual cycle that depends mainly on the behaviour of precipitation and evapotranspiration. In this study, we developed a methodology that allows describing and characterizing the annual cycle of soil moisture in Argentina. For this purpose, we estimated soil moisture at 121 sites of Argentina by means of a simple hydrological balance (the BHOA, an acronym for its name in Spanish: “Balance Hidrológico Operativo para el Agro”) and analysed its intra‐annual variability by means of different indices. This methodology allowed recognizing five different annual behaviours, with a consistent geographical pattern throughout Argentina. The characterization was based mainly on the time of occurrence of the annual maximum and minimum values of soil moisture, and secondly by the annual soil moisture content and seasonality. The northwest and part of the centre of Argentina present the minimum soil moisture values in spring and the maximum ones in autumn, while the east and south present the minimum values in summer and the maximum ones in winter. In general, sites with higher soil water content were found to have lower seasonality and vice‐versa.

Development of a daily soil moisture product for the period of 2002–2011 in Chinese mainland

Soil moisture is an essential climate variable (ECV) concerned widely. Due to its high spatial variability, it is costly to measure soil moisture at tens of kilometers scale. In this study, a ten-year (2002–2011) daily soil moisture dataset at 0.25° spatial resolution for Chinese mainland was produced through assimilating the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) brightness temperature (TB) data into a land surface model (LSM). The obtained soil moisture data was evaluated against soil moisture-measuring networks deployed in two wet areas and one dry area of the Tibetan Plateau. The results show that for the wet areas the accuracy of the soil moisture product obtained from the assimilation is considerably higher than that of both AMSR-E official soil moisture products and land surface simulation results, and for the dry area their accuracy is comparable to each other. The spatial pattern of the soil moisture from the new product is consistent with that of soil porosity from an independent survey-based dataset, further confirming the credibility of the new product. According to this product, the transition regions in China show stronger seasonal variation of soil moisture than dry and wet regions, and drier regions have stronger inter-annual variability of soil moisture than wetter regions, particularly during transitional seasons (spring and autumn). The soil moisture product is accessible at the National Tibetan Plateau Data Center.

Understanding the dynamic nature of Time-to-Peak in UK streams

In flood forecasting and design for peak flows, understanding and characterizing the hydrologic response to rainfall events is vitally important. One of the key parameters utilized to characterize the catchment response time is the Time-to-Peak (Tp), which represents the net rise time of a storm hydrograph, or the time from when a precipitation event begins to contribute to stream discharge, to the time that peak flow (Qp) is reached. Previously, influencing factors on Tp have been static in nature with no consideration of the variability in Tp due to size of the storm event and the antecedent moisture conditions of the watershed (seasonal effects). Using ~1400 storm event observations and the corresponding catchment characteristics of 153 stream gauges across the United Kingdom (UK), the importance of different factors on estimating Tp are evaluated. These data points span three decades, and this breadth of temporal data allowed meaningful annual trends to be observed, and seasonal variations in soil moisture to be identified and applied. A new “wetness coefficient” is applied herein, to reflect the antecedent conditions within a catchment. The Qp is selected as a dynamic variable, utilized to represent the magnitude of a given storm, due to the demonstrated correlation with Tp. An explicit equation based on gene expression programming is designed, which accounts for the dynamic nature of Tp through Qp and seasonal moisture effects. The results of the proposed model are compared to the results of the existing equation for Tp prediction in the UK, outlined by the Flood Estimation Handbook (FEH). The proposed equation (with Nash-Sutcliffe Coefficient, R2 and RMSE values equal to 0.60, 0.66 and 3.64, respectively), has improved characteristics compared with the traditional FEH equation (Nash = 0.42, R2 = 0.54, and RMSE = 4.37). A forensic analysis of the contributing factors for Tp involves development of an empirical model with improved prediction accuracy, by accounting for the dynamic inputs, improving previous models both statistically, as well as in the hydrologic understanding of the catchment response.

Impact of Different Yearly Rainfall Patterns on Dynamic Changes of Soil Moisture of Fixed Sand Dune in the Horqin Sandy Land

The in-situ monitoring method was used for studying the spatio-temporal variation of soil moisture in the growing season of different precipitation years in fixed dunes of Horqin Sandy Land. The results showed that different precipitation years have a certain influence on both seasonal variation and vertical variation of soil moisture in the fixed dunes of the study area. (1) During the normal year, the seasonal variation of soil moisture was relatively flat. During the dry year, the soil moisture gradually decreased before the rainy season and increased significantly after the rainy season. During both normal and dry years, heavy rainfall can significantly recharge the soil moisture content in all soil layers. During the wet year, the rapid recharge effect of soil moisture from heavy rainfall in the shallow layer was better than that in the deep layer. (2) During the normal and wet years, the soil moisture was at a relatively low level in May and changed little with the soil depth. In different months of other precipitation years, the soil moisture changes with soil depth all showed the trend of “first increase, then decrease, and finally slow increase”. Higher soil moisture were generally in the soil layer of 30∼70 cm, the soil moisture below 70 cm changed little with the soil depth and tended to be stable below 110 cm. (3) Under the influence of heavy rainfall, the vertical variation of soil moisture tended to be active in the wet year, showing three variation layers, i.e. quickly changing layer, active variable layer and sub-active variable layer. During the normal and dry years, the soil moisture showed small vertical changes, and it was divided into only two layers. For the dry year, only the surface layer showed active variation of soil moisture; for the normal year, the soil layer above 70cm showed active variation of soil moisture.

Characteristics of soil moisture variation in different land uses in a small catchment on the Loess Plateau, China

Understanding how soil moisture changes under different land uses is essential to ensure effective utilization of water and soil resources and to facilitate vegetation restoration in arid and semiarid ecosystems. Soil moisture content in the 0 to 160 cm soil profile in a sloping cropland, terraced cropland, jujube (Ziziphus jujuba) orchard, and natural grassland was monitored in a small catchment on China9s Loess Plateau, using EC-5 soil moisture sensors, during the 2014 and 2015 growing seasons (May to October). The results demonstrated that the vertical distribution and seasonal variation in soil moisture and the characteristics of soil water storage under different land uses varied in years with different hydrological characteristics. During the persistent drought after heavy rainfall in 2014, the soil moisture loss rate under the terraced cropland increased slowly with time and was much lower than under the other land use types. In the drought year (2015), water storage in the 0 to 160 cm depth range under the terraced cropland was 36.9, 25.1, and 11.7 mm higher than that associated with the sloping cropland, jujube orchard, and grassland, respectively. In the normal year (2014), the average moisture content in the 0 to 60 cm depth range in the jujube orchard was 2.9%, 3.7%, and 4.5% lower than that of the sloping cropland, terraced cropland, and grassland, respectively (p

Development and evaluation of the MTVDI for soil moisture monitoring

AbstractSeveral parameterization schemes have been developed to retrieve the soil moisture information involved in the remotely sensed surface temperature‐vegetation index (Ts − VI) space. However, most of them are performed with the constraint of the dry edge of the Ts − VI space to define the maximum water stressed conditions. In view of the subjectivity and uncertainty involved in the determination of the dry edge, a new index termed as the Modified Temperature‐Vegetation Dryness Index (MTVDI) was developed in this paper to reduce the reliance of the parameterization scheme on the dry edge. In the parameterization scheme of MTVDI, isopleth lines of soil moisture involved in the feature space were retrieved by the temperature‐vegetation index method, and only the maximum surface temperature of bare soil (Tsmax) was indispensable in the definition of maximum water stressed conditions. For evaluation purpose, the MTVDI was demonstrated in the Southern Great Plains region of the U.S. and was compared with two other traditional soil moisture indexes developed under the constraint of dry edge. The comparison confirmed the effectivity of the MTVDI in monitoring the spatial pattern and seasonal variation of soil moisture. Our analyses also suggest that Tsmax, the only parameter needed in the definition of maximum water stressed conditions, can be retrieved directly from the parameterization scheme itself. Therefore, the retrieval of MTVDI can be performed independent of the dry edge, which is a significant improvement to the traditional parameterization schemes of soil moisture from the Ts − VI feature space.

Seasonal Shifts in Soil Moisture throughout a Semiarid Hillslope Ecotone during Drought: A Geoelectrical View

Core Ideas Resistivity imaging revealed dynamic subsurface response to drought across an ecotone. Resistivity responses restricted to rooting zones of vegetation type on each slope. Drought led to a deepening of interpreted soil moisture losses. Rewetting after drought did not immediately return to pre‐drought conditions. This study investigated the spatial distribution and seasonal variation of soil moisture during a drought year throughout a first‐order drainage basin whose hillslopes have different vegetation and soil. The north‐facing slope has juniper trees [Juniperus monosperma (Engelm.) Sarg.] and finer soil textures, while the south‐facing slope has creosote bushes [Larrea tridentata (DC.) Coville]. Time‐lapse, two‐dimensional electrical resistivity measurements, which can detect changes due to soil moisture, were conducted to capture subsurface moisture changes across the ecotone, from one hillslope to the other and along the ecotone down the valley axis. After the onset of the drought, the upper 3 m of the entire hillslope was mostly drying (resistivity was increasing). As the drought progressed and when there was less available shallow soil moisture, the resistivity profiles suggested that both juniper and creosote bushes sequestered moisture stored from increasingly greater depths, eventually reaching their respective average maximum rooting depths of ∼6 m for juniper and ∼3 m for creosote. However, this was also accompanied by decreases in resistivity (increases in soil moisture) at shallower depths, suggesting hydraulic redistribution. With shallow rewetting of the hillslope following storm events near the end of the study period, shallow areas could once again support vegetation on both hillslopes. Electrical resistivity imaging is effective for studying the spatiotemporal dynamics of soil moisture throughout the critical zone in response to water stress and can be used to inform ecohydrologic connections.

Validation of two gridded soil moisture products over India with in-situ observations

Surface level soil moisture from two gridded datasets over India are evaluated in this study. The first one is the UK Met Office (UKMO) soil moisture analysis produced by a land data assimilation system based on Extended Kalman Filter method (EKF), which make use of satellite observation of Advanced Scatterometer (ASCAT) soil wetness index as well as the screen level meteorological observations. Second dataset is a satellite soil moisture product, produced by National Remote Sensing Centre (NRSC) using passive microwave Advanced Microwave Scanning Radiometer 2 measurements. In-situ observations of soil moisture from India Meteorological Department (IMD) are used for the validation of the gridded soil moisture products. The difference between these datasets over India is minimum in the non-monsoon months and over agricultural regions. It is seen that the NRSC data is slightly drier (0.05%) and UKMO soil moisture analysis is relatively wet during southwest monsoon season. Standard AMSR-2 satellite soil moisture product is used to compare the NRSC and UKMO products. The standard AMSR-2 and UKMO values are closer in monsoon season and AMSR-2 soil moisture is higher than UKMO in all seasons. NRSC and AMSR-2 showed a correlation of 0.83 (significant at 0.01 level). The probability distribution of IMD soil moisture observation peaks at 0.25 m3/m3, NRSC at 0.15 m3/m3, AMSR-2 at 0.25 m3/m3 and UKMO at 0.35 m3/m3 during June–September period. Validation results show UKMO analysis has better correlation with in-situ observations compared to the NRSC and AMSR-2 datasets. The seasonal variation in soil moisture is better represented in UKMO analysis. Underestimation of soil moisture during monsoon season over India in NRSC data suggests the necessity of incorporating the actual vegetation for a better soil moisture retrieval using passive microwave sensors. Both products have good agreement over bare soil, shrubs and grassland compared to needle leaf tree, broad leaf tree and urban land cover types.

Edaphic properties override the influence of crops on the composition of the soil bacterial community in a semiarid agroecosystem

Annual cropping systems are dynamic environments where soil bacterial communities are responsive to various management practices such as crop rotations, and to seasonal fluctuations of edaphic properties. However, in semiarid regions the impact of crops on the soil bacterial community appears to be modulated or affected by edaphic properties such as soil moisture availability. Therefore the objective of this study was to determine the relative influence of crops (wheat, lentil, field pea, canola, and a fallow treatment), soil chemistry, and edaphic properties on the diversity and composition of soil bacterial communities in a semiarid agroecosystem. We used a temporal sampling strategy and high throughput sequencing approach to monitor changes in the soil bacterial community in relation to crop host identity and phenology and soil properties. Structuring of the bacterial community across the 20 experimental plots was driven primarily by soil pH which varied strongly (min: 5.25, max: 6.97) across the site. Weak temporal shifts in the bacterial community were observed across the growing season and were related to seasonal variation in soil moisture (min: 8.3%, max: 20.3%), soil temperature (min. daily mean: 3.3°C, max. daily mean: 21.1°C), and fluctuation in available phosphate in the soil (min: 0.003μgcm−2day−1, max: 0.290μgcm−2day−1). These temporal and spatial shifts were not influenced by crop host identity as similar bacterial communities were observed among the crops and fallow treatment. Variance partitioning revealed that soil pH and soil moisture accounted for a high proportion of the variation of the soil bacterial community, while crops had no significant impact in the study. Edaphic factors appeared to override or level the effect of crops on the soil bacterial community. These results highlight the importance of accounting for edaphic properties for managing soil bacterial communities in agroecosystems.

Seasonal Variation of Soil Moisture in Irrigated Olive Trees

Olive growing counts as one of the most significant agricultural activities in Greece, from a financial, social and ecological point of view. Modern olive culture often includes exhaustive use of the available water resources having as a result adverse effects for production cost and the environment. This paper evaluates seasonal soil moisture content at three different soil depths (10, 30, 40cm), in relation with rainfall and irrigation in an olive cultivar “Kalamon” orchard. Our results indicate strong variation of soil moisture as affected by season and irrigation. In addition, the role of drip-irrigation on soil moisture content appears to be more significant at soil depths up to 30cm compared to lower soil zones. Specifically, at soil depth of 40cm the soil moisture curves close to irrigation lines seems to coincide compared to these far away from the irrigation line.

Incorporating seasonality into event-based joint probability methods for predicting flood frequency: A hybrid causative event approach

Summary Flood extremes are driven by highly variable and complex climatic and hydrological processes. Observational evidence has identified that seasonality of climate variables has a major impact on flood peaks. However, event-based joint probability approaches for predicting the flood frequency distribution (FFD), which are commonly used in practice, do not commonly incorporate climate seasonality. This study presents an advance in event-based joint probability approaches by incorporating seasonality using the hybrid causative events (HCE) approach. The HCE was chosen because it uses the true causative events of the floods of interest and is able to combine the accuracy of continuous simulation with the computational efficiency of event-based approaches. The incorporation of seasonality is evaluated using a virtual catchment approach at eight sites over a wide range of Australian climate zones, including tropical, temperature, Mediterranean and desert climates (virtual catchment data for the eight sites is freely available via digital repository). The seasonal HCE provided accurate predictions of the FFD at all sites. In contrast, the non-seasonal HCE significantly over-predicted the FFD at some sites. The need to include seasonality was influenced by the magnitude of the seasonal variation in soil moisture and its coherence with the seasonal variation in extreme rainfall. For sites with a low seasonal variation in soil moisture the non-seasonal HCE provided reliable estimates of the FFD. For the remaining sites, it was found difficult to predict a priori whether ignoring seasonality provided a reliable estimate of the FFD, hence it is recommended that the seasonal HCE always be used. The practical implications of this study are that the HCE approach with seasonality is an accurate and efficient event-based joint probability approach to derive the flood frequency distribution across a wide range of climatologies.