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Purpose: Water retention capacity (WRC) is crucial for assessing the hydro-physical behavior of unsaturated soils. Dispersive soil, erodible and found mainly in arid regions, lacks sufficient WRC knowledge, hindering its stability evaluation in unsaturated state. This study aimed to explore the WRC of dispersive soil by measuring its matric suction (ψ) under coupling effects of dry density (ρd) and soluble salt content (η). Materials and method: Compacted specimens with different ρd and η were prepared. For each ρd-η case, six levels of soil mass water content were considered and the ψ was measured via filter paper method. Soil water characteristic curves (SWCCs) were fitted by van Genuchten model. Results and discussion: The WRC of dispersive soil enhances as ρd increases. Increasing η first weakens then strengthens the WRC, showing suction dependence. The air-entry value and residual state suction range within 0.95–17.8 kPa and 15.7–98.4 MPa, respectively. As for the air-entry value, increasing η from 0.3% to 2.0% decreases it from 36.0% to 58.7% when ρd increases, and its average growth rate changes from 174.5% to 265.3% when ρd exceeds 1.53 g/cm3. Increasing ρd reduces the average water loss rate of SWCC transition stage, while the impact of η is nonmonotonic, with an inflection point at 1.0%. Conclusions: The ρd and η influenced the WRC of dispersive soil individually and interactively. The effect of ρd links to the water release sequence from pores of different sizes, whereas that of η, rather complex and non-monotonic, relates to clay electrochemistry and salt phase. [ABSTRACT FROM AUTHOR]

In environmentally sensitive areas, especially the arid and semi-arid regions, the greening stability process and its influencing factors can directly affect the sustainable development of the ecological environment. In this study, multi-source remote sensing data such as land use/cover data, MODIS NDVI, and soil moisture, methods such as stability index, vegetation quantitative remote sensing, and Geodetector were employed to analyze the sustainability of the greening process in the Mu Us Sandy in 2000–2020, which were viewed from three aspects: changes in stability of land use types and function, soil moisture change and influencing factors on greening stability. The results showed that, (1) From the stability of land use types, continuous stable ecological land accounted for more than 50%, showing that decreased from northwest toward southeast. (2) From the functional stability, NDVI showed a fluctuated growth (0.035/a), with an increasing distribution pattern from northwest to southeast. Additionally, Vegetation changes were unstable and concentrated in the western part of the study area (OtogBanner and Otog Front Banner), while the eastern part was stable, in which vegetation improvement took the main position. Moreover, mobile dunes almost disappeared, and semi-fixed dunes decreased and gradually shrank to the west of the sandy area, while fixed dunes soared and were concentrated in the middle of the sandy land. (3) From the soil moisture change, soil moisture at different underground depths showed an overall increasing trend, but the deep soil moisture was higher than the shallow, and spatial distribution varied greatly. (4) From the influencing factors, natural factors significantly influence greening stability, among which precipitation had a particularly profound impact, and interactions with other natural and social factors were higher explanatory. The paper aims to explore whether the ecological environment is developing in a good and orderly direction in the Mu Us Sandy Land, and the potential factors that cause its changes, to provide a theoretical basis for scientific governance in the Mu Us Sandy Land and other arid and semi-arid areas in the future. [ABSTRACT FROM AUTHOR]

Atriplex canescens is widely cultivated as drought and salt-tolerant fodder in arid regions of Northwest China, which is used for photoremediation of degraded land and soil and water conservation. To explore the growth performance of A. canescens when exposed to drought and salt stress, seedlings were treated with a range of drought stress (WC1: 75 ± 3.6%, WC2: 49 ± 2.9% and WC3: 27 ± 2.5% of soil water content) and the corresponding drought stress with additional sodium salt supplementation (NaCl:Na2SO4 = 1:1 with the total concentration of Na+ set to 150 mM). The findings of this paper indicated that moderate sodium salt could stimulate the growth of A. canescens and effectively alleviate the deleterious impact of drought stress by increasing the turgor potential (ψt) and relative water content (RWC) and decreasing the leaf water osmotic potential (ψs). Furthermore, the photosynthetic capacity was improved and the negative effects of drought stress on photosystem II (PSII) were mitigated. The extra 150 mM sodium salt also markedly increased the contribution of Na+ to ψs and the contribution of betaine to ψs. In summary, these results indicate that A. canescens can adapt to drought stress by accumulating enough Na+ for osmotic adjustment (OA). Additionally, this paper is aimed to provide a fundamental basis for the utilization and cultivation of A. canescens as a favored pasture crop in the Qaidam basin, thus increasing the ecological and environmental benefits for arid regions worldwide. [ABSTRACT FROM AUTHOR]

Satellite-derived soil moisture fields received attention due to their large spatial coverage and spatial resolution that suits many applications. The sensors used vary from passive (e.g., LANDSAT-8) to active (e.g., SENTINEL-1) with varying accuracy problems. Passive sensing can only determine relative indices between pixels within a vegetation class and not the real value of moisture. Active sensing suffers from the sensitivity of its detecting behaviour to the level of moisture (anomalous backscatter). The above problems impose limitations on the application without frequent ground-based calibration. The paper investigates possible models to improve the estimation of soil moisture using the powers of the two sensors. In addition, a Hydrologic Surface Moisture indicator (HSM) is included as a third source of information. The paper tests modeling combinations of the three soil moisture predictors (Landsat-8, Sentinel-1, and HSM). The models are validated using in-situ measurements. The results showed that Landsat-8 data can be rescaled using HSM to provide the actual soil moisture in the soil. On the other side, it is possible to remove the anomaly from the Sentinel-1 backscatter using either Landsat-8 or HSM. The elimination of the above problems explained a significant portion of the differences between the two sensors. [ABSTRACT FROM AUTHOR]

Irrigation water use represents the primary source of freshwater consumption by humans. The amount of water withdrawals for agricultural purposes is expected to further increase in the upcoming years to face the rising world population and higher living standards. Hence, effective plans for enacting a rational management of agricultural water use are urgent, but they are limited by knowledge gaps about irrigation. Detailed information on irrigation dynamics (i.e., extents, timing, and amounts) is generally lacking worldwide, but satellite observations can be used to fill this gap. This paper describes the first regional-scale and high-resolution (1 and 6 km) irrigation water data sets obtained from satellite observations. The products are developed over three major river basins characterized by varying irrigation extents and methodologies, as well as by different climatic conditions. The data sets are an outcome of the European Space Agency (ESA) Irrigation+ project. The irrigation amounts have been estimated through the SM-based (soil-moisture-based) inversion approach over the Ebro river basin (northeastern Spain), the Po valley (northern Italy), and the Murray–Darling basin (southeastern Australia). The satellite-derived irrigation products referring to the case studies in Europe have a spatial resolution of 1 km, and they are retrieved by exploiting Sentinel-1 soil moisture data obtained through the RT1 (first-order Radiative Transfer) model. A spatial sampling of 6 km is instead used for the Australian pilot area, since in this case the soil moisture information comes from CYGNSS (Cyclone Global Navigation Satellite System) observations. All the irrigation products are delivered with a weekly temporal aggregation. The 1 km data sets over the two European regions cover a period ranging from January 2016 to July 2020, while the irrigation estimates over the Murray–Darling basin are available for the time span April 2017–July 2020. The retrieved irrigation amounts have been compared with benchmark rates collected over selected agricultural districts. Results highlight satisfactory performances over the major part of the pilot sites falling within the two regions characterized by a semiarid climate, namely, the Ebro and the Murray–Darling basins, quantified by median values of RMSE, Pearson correlation r , and bias equal to 12.4 mm/14 d, 0.66, and - 4.62 mm/14 d, respectively, for the Ebro basin and to 10.54 mm/month, 0.77, and - 3.07 mm/month, respectively, for the Murray–Darling basin. The assessment of the performances over the Po valley is affected by the limited availability of in situ reference data for irrigation. The developed products are made available to the scientific community for use and further validation at 10.5281/zenodo.7341284 (Dari et al., 2022a). [ABSTRACT FROM AUTHOR]

Copyright of Journal of Irrigation & Drainage is the property of Journal of Irrigation & Drainage Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The accurate estimation of global evapotranspiration (ET) is essential to understanding the water cycle and land–atmosphere feedbacks in the Earth system. This study focused on the Inner Mongolia Reach of the Yellow River Basin, a typical arid and semi-arid region. Although there are many remote sensing ET datasets, many of the ET algorithms have not considered the impact of soil moisture, especially in water-limited areas. In this paper, the new PT-JPL model, which incorporates soil moisture into ET simulation, is used to improve the accuracy of ET simulation in water-limited areas. The simulation value is evaluated using two Hobq Desert eddy-covariance towers and the Penman–Monteith–Leuning version 2 (PML-V2) dataset. The new PT-JPL model shows the most significant improvements in water-limited regions; the coefficient of determination can reach 0.826, and the RMSE can reduce to 9.645 W/m2. Soil evaporation is central to the actual ET increase in the study area. Implementing ecological restoration projects reduced the exposed area of land in the study area and reduced the rate of total ET effectively. Furthermore, the most advanced machine learning local interpretation algorithm—the TreeExplainer-based Shapley additive explanation (SHAP) method—was used to identify the driving factors of ET capacity under different land use types. Temperature, NDVI, and root zone soil moisture were the main environmental factors causing ET changes in different plants. Meanwhile, temperature and root zone soil moisture had a noticeable coupling effect, except for grassland. Furthermore, a threshold effect of temperature to ET was found, and the value is 25, 30, and 30 °C in the forest, grassland, and cropland, respectively. This study provides an essential reference for accurately describing the ET characteristics of arid and semi-arid regions to achieve the efficient management of water resources. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Irrigation & Drainage is the property of Journal of Irrigation & Drainage Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Introduced in Tanzania by the World Agroforestry (ICRAF), chololo pits is a technology that help conserve moisture in the soil and improve soil fertility, hence increasing crop production and mitigating drought effects. However, socio-economic factors are increasingly affecting farmers' practising chololo pits in the semi-arid Dodoma Region, hence the need to understand these factors that affect the sustainability of this technology. Therefore, the aim of this paper is to investigate the socio-economic factors affecting the sustainability of the technology of chololo pits in the semi-arid Chamwino district, Dodoma region, in Tanzania. Data were collected through a documentary review, household interviews, focus group discussions, key informant interviews and field observation. The findings indicate that the cost of labour for the construction of pits (92.1%, n=337), and land ownership (92.1%, n=337), were the major factors affecting the sustainability of the practice in the study area. Other minor economic factors scoring less than two digits were capital and household income; and social factors including group membership, sources of labour and education level. To enhance the sustainability of the practice, four strategies were suggested by stakeholders: use of improved seeds (75.7%), use of user-friendly pitting tools (65.5%), farmers' capacity building (47.1%), and up-scaling the practice (24.8%). [ABSTRACT FROM AUTHOR]

Evaluation and modeling of soil water infiltration are essential to all aspects of water resources management and the design of hydraulic structures. Nonetheless, research focused on experimental studies of infiltration rates in arid and semi-arid regions under unknown boundary conditions remains minimal. This paper investigates the characteristics of the spatial variability of infiltration over a semi-arid rural basin of Algeria. The experiments were conducted using a portable double-ring infiltrometer filled at an equal volume of approximately 100 L of water for each of the 25 catchment locations. Soil moisture contents at the proximity of each test location were evaluated in the laboratory as per the standard NF P94–050 protocol. The experimental results are used to produce the catchment infiltration curves using three statistically fitted infiltration models, namely Horton, Kostiakov, and Philip models. The reliability of the models was assessed using four performance criteria. The statistical regressions of the fitted models suggest that the Horton model is the most suitable to assess the infiltration rate over the catchment with mean coefficients of Nash = 0.963, CC = 0.985, RMSE = 1.839 (cm/h), and Bias = 0.241. The superiority of the Horton model suggests that the initial and final infiltration rates, primarily affected by soil type, initial soil moistures, and land cover, are important predictors of the modeling process over the Madjez Ressoul catchment. The results also infer that the applicability of other models to the different types of undeveloped soils in the study area requires advanced field investigations. This finding will support the understanding of the hydrologic processes over semi-arid basins, especially in advising crop irrigation schemes and methods and managing the recurring flood and drought over the country. [ABSTRACT FROM AUTHOR]

Aeolian desertification, a serious degradation of soil and vegetation, is one of the most important issues in arid and semi-arid regions in terms of society/economy and environment. However, there still remains problematic on the study of climate change and its impact on aeolian desertification in the such region. To reverse aeolian desertified land (ADL), it is necessary to identify the causes of ADL. The paper uses meteorological data to characterize climate change and its impact on ADL during 1970–2015 with the method of geostatistics, and the results showed that the climate tended to be warmer and drier. The linear trend rates of annual mean temperature for the whole year (WY), winter half year (WHY), and summer half year (SHY) were 0.24 °C (10 a)−1, 0.25 °C (10 a)−1, and 0.18 °C (10 a)−1, respectively. The linear trend rates of average precipitation were − 8.29 mm (10 a)−1, 2.69 mm (10 a)−1, and − 8.27 mm (10 a)−1, respectively. Rising temperatures in WY, WHY, and SHY lead to increase topsoil evaporation and may trigger ADL development. However, the decreasing precipitation in SHY weakened soil erosion, and the increasing precipitation with a rate of 0.26 mm a−1 in WHY improved the soil moisture content. Therefore, our results show that climatic change has a relatively high sensitivity, especially in WHY, to the expansion or reversal of ADL in semi-arid regions. [ABSTRACT FROM AUTHOR]

The association of hydrological models with remote sensing data allows the estimation of parameters that cannot be easily measured in situ, especially in regions with poor monitoring networks. In this paper, a distributed hydrological energy water balance model (FEST-EWB) was calibrated and validated in a basin located in a climate transition zone between a semi-arid region and the humid Atlantic Forest, in Brazil. Land surface temperature (LST) data from the Moderate Resolution Imaging Spectroradiometer (MODIS) were used to calibrate the model, that solves the system of energy and mass balance equations as a function of the representative equilibrium temperature. For validation, soil moisture and LST data collected in situ were used. The model presented good performance for the simulation of the variables studied in the basin, even with reduced availability of MODIS data due to cloud coverage, allowing the use of FEST-EWB in areas with these characteristics, which are common in many regions of the world. [ABSTRACT FROM AUTHOR]

Variability in soil moisture has implications for regional terrestrial environments under a warming climate. This paper focuses on the spatiotemporal variability in the intra-annual persistence of soil moisture in China using the fifthgeneration reanalysis dataset by the European Centre for Medium-Range Weather Forecasts for the period 1979-2018. The results show that in China, the mean intra-annual persistence in the humid to arid zones increased from 60 to 115 days in the lower layer but decreased from 19 to 13 days and from 25 to 14 days in the upper and root layers, respectively. However, these changes were strongly attenuated in extremely dry and wet regions due to the scarcity of soil moisture anomalies. Large changes in persistence occurred in the lower soil layer in dryland areas, with a mean difference of up to 40 days between the 2010s and the 1980s. Overall increasing trends dominated the large-scale spatial features, despite regional decreases in the eastern arid zone and the North and Northeast China plains. In the root layer, the two plains experienced an expanded decrease while on the Tibetan Plateau it was dominated by decadal variability. These contrasting changes between the lower and root layers along the periphery of the transition zone was a reflection of the enhanced soil hydrological cycle in the root layer. The enhanced persistence in drylands lower layer is an indication of the intensified impacts of soil moisture anomalies (e.g., droughts) on terrestrial water cycle. These findings may help the understanding of climate change impacts on terrestrial environments. [ABSTRACT FROM AUTHOR]

Irrigated areas, mainly in arid regions, are threatened by salinization processes. Climate change inducing temperature rise and rainfall depletion are expected to enhance these processes. Numerical models are often used to predict salinization in the root zone as well as water and solute fluxes reaching groundwater. Climatic data, mainly rainfall, have an important influence on the estimation of those fluxes. The present paper studies the impact of rainfall structure and climate change on soil and groundwater salinization. Soil samples were collected in three drip-irrigated plots in Korba semi-arid coastal plain in Tunisia during dry and wet seasons. Collected field data (water contents and soil salinities) are used to define the initial solute and flow conditions and to estimate the soil hydraulic parameters for numerical modeling. Daily rainfall structure and annual rainfall transition under both Markov Chain and climate change (RCP4.5 and RCP8.5) are assessed. Different climatic scenarios are then introduced as boundary conditions in HYDRUS-1D, to test the influence of rainfall on the salinity evolution in the soil profile and groundwater. Results show that both annual rainfall amounts and daily structure have an impact on soil concentrations and solute fluxes quantities reaching groundwater. The influence of rainfall paths is more important for larger unsaturated zone thickness when considering the dry and median rainfall conditions. Climate change scenarios show significant accumulation of salts in the root zone implying the imperative use of adequate irrigation practices. [ABSTRACT FROM AUTHOR]

This paper investigates the extreme wet‐bulb temperatures (TWs) in China, with a focus on understanding the relative contributions of temperature and moisture to the extremes. Analysis of station observations shows that daily extreme temperatures (T), specific humidity (q), and TWs generally co‐occur in Southeastern China, while extreme TW and T rarely overlap in the arid and semiarid North and Northwest China. Overall, q contributes more than T to extreme TWs, especially in North and Northwest China. Based on the relative contributions of q and T, regional extreme TW events are classified as q dominated and T dominated, respectively, to study their large‐scale environment. Cluster analysis of global reanalysis data shows that extreme TWs are generally accompanied by increased surface air temperature and humidity, concomitant with anomalous high pressure and notable water vapor flux convergence. However, important differences are also seen in the large‐scale environment during q‐dominated and T‐dominated extreme TWs. During q‐dominated extreme TWs, the large‐scale environment favors convection, as indicated by ascending motions, decreased downward solar radiation as well as increased precipitable water and near‐surface relative humidity. In contrast, during T‐dominated extreme TWs, convection is inhibited by the large‐scale environment that features descending motion and increased downward solar radiation, decreased precipitable water, and decreased relative humidity. Consistent with the contrasting environments, we demonstrate that T‐dominated extreme TWs tend to last longer than q‐dominated extremes. Given the significant role of moisture in extreme TWs, more research is needed to understand its impacts on heat stress now and in the future. Key Points: Extreme wet‐bulb temperatures in China are investigated using observations, considering both the role of temperatures and moistureMoisture contributes more to extreme wet‐bulb temperatures than temperature in most regions of ChinaThe environment during moisture‐/temperature‐dominated extreme wet‐bulb temperatures tends to be convection favored/convection inhibited. [ABSTRACT FROM AUTHOR]

• A MGWR-based SMAP soil moisture product downscaling method is proposed. • The method considers the scale differences in the impact of surface variables on soil moisture. • Field validation shows higher accuracy from the downscaled SM than the SMAP SM itself. • This proposed downscaling method performs better than the traditional GWR and MW methods in the semiarid area. Passive microwave remote sensing missions such as Soil Moisture Active Passive (SMAP) are widely used for global soil moisture (SM) estimation. But the low spatial resolution of passive microwave SM products limits their applications at regional and local scales (normally 1–10 km). Using high-resolution auxiliary data to downscale passive microwave SM products is the primary way to obtain high-resolution SM data. However, the existing SM downscaling methods do not entirely account for the scale differences in the impact of various variables on the distribution of SM. To solve this problem, this paper introduced MGWR (Multiscale Geographically Weighted Regression) as a novel way to analyze the scale differences of normalized difference vegetation index (NDVI) and land surface temperature (LST) on the spatial pattern of SM. Accordingly, a new spatial downscaling algorithm for SMAP SM products is proposed and compared with the geographically weighted regression (GWR) algorithm and moving window algorithm (MW). The algorithm was applied to data taken during the SMAP Validation Experiment 2016 (SMAPVEX16), and the downscaled SM evaluated with in situ SM and aircraft observations. These results show that: 1) the SM downscaling conversion function, based on the MGWR, effectively reveals how different surface parameters relate to SM, with LST influencing SM globally and NDVI affecting it locally, 2) compared with GWR and MW, the 1 km SM obtained by the MGWR-based downscaling method showed better spatial agreement with airborne SM in the semiarid region with the ubRMSE decreasing by 0.023 m3/m3 and 0.026 m3/m3 for GWR and MW respectively, 3) when evaluating the 1 km SM with in situ SM in the semiarid region, the SM obtained through MGWR exhibited lower ubRMSE values as compared to both GWR and MW. Specifically, the median ubRMSE values for MGWR, GWR, and MW were 0.043 m3/m3, 0.053 m3/m3, and 0.094 m3/m3, respectively. In conclusion, this study demonstrates that MGWR can effectively improve the accuracy of downscaled SM in semiarid regions. [ABSTRACT FROM AUTHOR]

Surface emissivity (ε) is used to characterize surfaces and to determine surface temperature from thermal radiation data. While in many applications it is treated as a constant, it is known to change with surface water content. Several ASTER/SEVERI based studies have speculated that diurnal changes in ε over deserts are linked to diurnal soil water content cycles resulting from water vapor adsorption during the night and subsequent evaporation during the day. This paper aims, for the first time, to validate the relationship between diurnal changes in surface ε and the changes in soil water content due to water vapor adsorption and evaporation under natural conditions. Measurements were conducted with a 6-band infrared radiometer, designed to validate ASTER bands 10–14, with study-specific recalibration for improved accuracy of ε. The evaluation included two different approaches to determine ε : using a single reference band (1B) and using the temperature/emissivity separation algorithm (TES). water content. While the TES has proven itself in many applications, it was found that for the soils studied (sand and loess) the use of 1B approach gave more consistent results for ε changes with soil water content than TES. Emissivity could be a powerful tool to characterize little studied soil water content changes in arid regions, but will require better characterization of surface properties to quantify the relationship between ε and soil water content for various soil types. Additional challenges to upscale this method include properly accounting for air irradiance and spatial heterogeneity. Meeting these main challenges will lead the way to detect small changes in soil water content under dry conditions at larger scales. Whether these are a result of water vapor adsorption or other processes, detecting such small changes in soil water content will provide new insights into desert hydrology. • On-ground validation of an infrared radiometer with ASTER bands. • Calibration and measuring protocol for minute changes in emissivity. • Observed emissivity changes of 0.2–0.6 due to water vapor adsorption. • Main challenges: air radiance, surface heterogeneity, and soil spectral properties. • Potential for new insights into desert hydrology. [ABSTRACT FROM AUTHOR]

Soil moisture (SM) is a critical element of the hydrological cycle, land surface processes, and surface energy balance. However, the low spatial resolution of commonly used SM products limits the application of SM in agriculture and eco‐hydrology in cold and arid regions. In this study, the normalized difference soil index (NDSI) and bare soil index (BSI) were added to traditional downscaling factors including land surface temperature, normalized difference vegetation index, digital elevation mode, apparent thermal inertia, Albedo, and temperature vegetation dryness index, as they are more strongly correlated with surface SM in the bare soil‐vegetation alternation zone of such region. Using the random forest algorithm, a downscaling model of SM was constructed for such region. The accuracy of the downscaled SM estimates was validated by comparing them with the original SM data collected from May to September 2021, which is the non‐freezing period of the soil. The findings indicate that the newly added NDSI and BSI have good correlation with SM. Incorporating NDSI and BSI to construct the downscaled model enhances the accuracy by over 19% compared to excluding them, while also providing a more comprehensive representation of SM information. NDSI and BSI can be well applied to the downscaled research of SM in the bare soil‐vegetation alternation zone, which is of great value for the study of eco‐hydrology and agricultural drought monitoring in cold and arid regions. Core Ideas: Adding soil factors improves the downscaling of soil moisture in cold and arid regions.Compared with the traditional model, the improved model showed a significant increase in accuracy.This improved model better characterized soil moisture spatial and temporal variability. [ABSTRACT FROM AUTHOR]

Soil moisture is an important component of natural water cycles and plays a crucial role for the healthy development of ecological environment in arid and semiarid areas. Microwave remote sensing techniques are promising to rapidly monitor regional soil moisture. However, major difficulties associated with retrieving soil moisture via microwave remote sensing are attributed to effects of surface roughness and vegetation cover. The objective of this paper is to investigate the potentials of combined roughness parameters and develop a model that mostly relies on the satellite data and requires minimum a priori information for soil moisture inversion over sparse vegetation covered areas through combing Radarsat-2 synthetic aperture radar (SAR) and GF-1 data. For the purpose, the impacts of vegetation on the radar backscattering coefficient were removed by the water-cloud model (WCM) and a new roughness parameter $Zs$ ($Zs = S^{3}/L$ is defined as a combined roughness parameter) was proposed by simulating relationships between surface roughness parameters, soil moisture, and backscattering coefficients using advanced integral equation model (AIEM). On the basis, a coupling model of soil moisture inversion for blown-wind areas of the Uxin Banner in Inner Mongolia, China, was in turn developed with Radarsat-2 HH and VV polarization data, and the soil moisture content (SMC) values for sparse vegetation covered surfaces were retrieved with limited use of in situ roughness parameters. The in situ measurements and satellite data set were used to validate the reliability of the developed model. The results showed that the retrieved soil moisture levels fell below in situ soil moisture levels before the vegetation effect was removed, and the precision of retrieved soil moisture was effectively improved when the vegetation effect was corrected by the WCM, with the root-mean-square error and mean absolute error decreasing from 7.45% and 6.24% to 5.12% and 3.44%, respectively. According to the map of retrieved soil moisture levels generated for the study area, most of SMCs were below 35% in accordance with field observations. These study results can serve as a foundation for monitoring soil moisture and water environments in arid and semiarid regions. [ABSTRACT FROM AUTHOR]

This paper analyzed the impact of treated wastewater irrigation on long-term soil water retention. Irrigation with treated wastewater (TWW) constitutes a strategic opportunity for development of agriculture in semi-arid regions. For the sustainable management one of the challenges is evaluating its effect on the soil. The results of the current study indicated that TWW-irrigation leads to increased soil salinity at a depth of 0-0.20 m. In terms of the soil's ability to retain water, at the mid-period use (8 y), the TWW retention was reduced by 33% capacity at a depth of 0.10 m compared to soil irrigated by freshwater. The decrease was less significant (24% of retention) in the long term. The surface layer of the soil (0-0.10 m) irrigated by TWW retained less water than when irrigated by fresh water. Regarding the soil water retention curve, the impact of TWW becomes important at very high suction pressures (i.e., VHP > 1,000 cm) compared to lower suction pressures (i.e., HP: 10-1,000 cm). The results suggested that the use of TWW decreased the water retention at field capacity and wilting point values. [ABSTRACT FROM AUTHOR]

Soil available water capacity (AWC) is an important factor affecting soil productivity in semiarid and subhumid environments and is mainly determined by the soil textural composition. As the soils of these environments usually present fairly uniform textures across depth, we hypothesized that it would be possible to accurately estimate the whole-profile AWC using surface information. Our objective was to test this hypothesis in the Argentine Semiarid Pampas. Information was collected from 152 sites where AWC was measured in 20 cm layers up to a depth of 140 cm or up to the upper limit of the petrocalcic horizon, when present. In each case, whole profile AWC was estimated using a one-step and a two-step approach, comparing multiple regression and artificial neural networks as modeling techniques. Both modeling methods were effective (R2 > 0.76,P < 0.05), however the former was chosen as no special software is required to run it, thus favoring simplicity. Models showed a strong interaction between surface AWC and soil depth and a simple nomogram was developed to estimate whole-profile AWC. Sampling and laboratory efforts should be significantly reduced using the model proposed in this paper. [ABSTRACT FROM AUTHOR]

Ultisol dry land is characterized by significantly low organic carbon content, an important factor influencing soil water content and physicochemical dynamics. The addition of N fertilizer dissolved in seaweed liquid extract as an enrichment solution can change the character of biochar. Therefore, this study aimed to analyze the characteristics of cogongrass biochar enriched with dissolved N fertilizer in seaweed extract of different species and assess its impact on soil water content in Ultisol. Urea was used as a nitrogen source, and biochar enriched with N fertilizer dissolved in seaweed liquid extract from Kappapychus alvarezii, Sargassum sp., and Ulva lactuca was tested. Biochar dose used was 20% of soil weight with a 10% extract concentration for each type. Furthermore, five-level treatments were tested in a pot experiment, namely (i) without biochar, (ii) biochar unenriched, (iii) enriched with N fertilizer dissolved in K. alvarezii extract, (iv) enriched with N fertilizer dissolved in Sargassum sp. extract, and (v) biochar enriched with N fertilizer dissolved in U. lactuca extract. Each treatment was repeated three times, following a randomized block design. The results showed that cogongrass biochar enriched with N fertilizer dissolved in seaweed extract had a more amorphous surface morphology structure. The proportion of elements and functional groups in cogongrass biochar changed. Enriched biochar increased Ultisol moisture levels, but water holding capacity and retention were lower than the unenriched sample. [ABSTRACT FROM AUTHOR]

Water vapor adsorption on soil, a crucial non-rainfall water resource in arid regions, warrants further experimental investigation, particularly on two typical land surfaces: bare soil and gravel. This study examined the formation characteristics and influencing factors of vapor adsorption in an arid region of Northwestern China. Observations and analyses were conducted on adsorption and evaporation measurements taken by two small weighing lysimeters (SLSs); soil temperature at a depth of 5 cm; surface temperature; relative humidity; and air temperature at a height of 30 cm above the ground from 2019 to 2020. The adsorbed water in this area was more abundant at night and less abundant during the day, with a stable nightly adsorption rate of 0.013 mm/h. Adsorption was more frequent in spring and winter (from January to June and November to December), accounting for about 90% of the total annual adsorption. In 2019 and 2020, the ratio values of adsorption to evaporation were 0.16 and 0.10 for bare soil, and 0.10 and 0.12 for gravel, respectively. Adsorption was more likely to occur when the soil moisture content was less than 13%; the highest adsorption frequency was close to 20% when the RH was between 75 and 95%; low soil temperatures were more conducive to the occurrence of adsorption. The effect of temperature differences (Ta−Ts) on adsorption was stronger than that of relative humidity. The adsorption frequency generally showed a bimodal change with increasing temperature difference, but the effect of temperature differences was less effective for gravel than bare soil. When the relative humidity was high and the temperature difference was weakly positive, the maximum adsorption intensity could reach 0.18 mm/h. [ABSTRACT FROM AUTHOR]

Soil water availability is an essential prerequisite for vegetation functioning. Vegetation takes up water from varying soil depths depending on the characteristics of its rooting system and soil moisture availability across depth. The depth of vegetation water uptake is largely unknown across large spatial scales as a consequence of sparse ground measurements. At the same time, emerging satellite-derived observations of vegetation functioning, surface soil moisture, and terrestrial water storage present an opportunity to assess the depth of vegetation water uptake globally. In this study, we characterize vegetation functioning through the near-infrared reflectance of vegetation (NIRv) and compare its relation to (i) near-surface soil moisture from the ESA's Climate Change Initiative (CCI) and (ii) total water storage from the Gravity Recovery and Climate Experiment (GRACE) mission at a monthly timescale during the growing season. The relationships are quantified through partial correlations to mitigate the influence of confounding factors such as energy- and other water-related variables. We find that vegetation functioning is generally more strongly related to near-surface soil moisture, particularly in semi-arid regions and areas with low tree cover. In contrast, in regions with high tree cover and in arid regions, the correlation with terrestrial water storage is comparable to or even higher than that of near-surface soil moisture, indicating that trees can and do make use of their deeper rooting systems to access deeper soil moisture, similar to vegetation in arid regions. At the same time, we note that this comparison is hampered by different noise levels in these satellite data streams. In line with this, an attribution analysis that examines the relative importance of soil water storage for vegetation reveals that they are controlled by (i) water availability influenced by the climate and (ii) vegetation type reflecting adaptation of the ecosystems to local water resources. Next to variations in space, the vegetation water uptake depth also varies in time. During dry periods, the relative importance of terrestrial water storage increases, highlighting the relevance of deeper water resources during rain-scarce periods. Overall, the synergistic exploitation of state-of-the-art satellite data products to disentangle the relevance of near-surface vs. terrestrial water storage for vegetation functioning can inform the representation of vegetation–water interactions in land surface models to support more accurate climate change projections. [ABSTRACT FROM AUTHOR]

Significant temporal and spatial variability in soil moisture (SM) is observed during the warm season in China and its surrounding regions. Because of the existence of two different evapotranspiration regimes, i.e., soil moisture-limited and energy-limited, averaging the land–atmosphere (L–A) coupling strength for all soil wetness scenarios may result in the loss of coupling signals. This study examines the daytime-only L–A interactions under different soil moisture conditions, by using two-legged metrics in the warm season from May to September 1981–2020, partitioning the interactions between SM and latent heat flux (SM–LH, the land leg) from the interactions between latent heat flux and the lifting condensation level (LH–LCL, the atmospheric leg). The statistical results reveal large regional differences in warm-season daytime L–A feedback in China and its surrounding areas. As the soil becomes wetter, the positive SM–LH coupling strength increases in arid regions (e.g., northwest China, Hetao, and the Great Indian Desert) and the positive feedback shifts to the negative one in semi-arid/semi-humid regions (northeast and northern China). The negative LH–LCL coupling is most pronounced in wet soil months in arid regions, while the opposite is true for the Tibetan Plateau. In terms of intraseasonal variation, the large variability of SM in north China, the Tibetan Plateau, and India due to the influence of the summer monsoon leads to the sign change in the land segment coupling index, comparing pre- and post-monsoon periods. To further examine the impact of SM anomalies on L–A coupling and to explore evapotranspiration regimes in the North China Plain, four sets of sensitivity experiments with different soil moisture levels over a period of 10 years were conducted. Under relatively dry soil conditions, evapotranspiration is dominated by the soil moisture-limited regime with positive L–A coupling, regardless of external moisture inflow. The critical soil moisture value separating a soil moisture-limited and an energy-limited regime lies between 0.24 m3/m3 and 0.29 m3/m3. Stronger positive feedback under negative soil moisture anomalies may increase the risk of drought in the North China Plain. [ABSTRACT FROM AUTHOR]

Earth Observation (EO) technologies have played an increasingly important role in monitoring the Sustainable Development Goals (SDG). These technologies often combined with Machine Learning (ML) models provide efficient means for achieving the SDGs. The great progress of this combination is also demonstrated by the large number of software, web tools and packages that have been made available for free use. In this paper, we introduce a software architecture to facilitate the generation of EO information targeted towards soil moisture that derive several challenges regarding the facilitation of satellite data processing. Thus, this paper presents a web-based tool for Soil Moisture Estimation (SMETool), designed for the soil moisture estimation using Sentinel-1A and Sentinel-2A data based on Eo-learn library. SMETool implements several ML techniques such as (Artificial Neural Network (ANN), Random Forest (RF), Convolutional Neural Network (CNN), etc.). The SMETool could be very useful for decision makers in the region in assessing the effects of drought and desertification events. Experiments were carried out on two sites in Tunisia during the period from 2016 to 2017. Although the performance of the used models is very close, it is clear that CNN and RF outperformed other ML models. The achieved results reveal that the soil moisture, was highly correlated to the in-situ measurements with high Pearson's correlation coefficient r ( r RF = 0. 86 , r ANN = 0. 75 , r XGBoost = 0. 79 , r CNN = 0. 87) and low Root Mean Square Error (RMSE) (RMSE RF = 1.09%, RMSE ANN = 1.49%, RMSE XGBoost = 1.39%, RMSE CNN = 1.12%), respectively. • A new web-based tool for soil moisture estimation at the scale of arid regions. • Simple implementation using Eo-learn framework and machine learning methods. • A case study on arid region in southern Tunisia using Sentinel 1-A and Sentinel 2-A products. [ABSTRACT FROM AUTHOR]

Soils that contain rock fragments (particles > 2 mm in diameter) are distributed all over the world. The presence of these small rock fragments can have a great impact on soil water retention properties, as well as on the soil-water infiltration and vegetation restoration in semi-arid regions. To quantitatively describe the transport of water in stony soils, repacked soil cores were used to determine the infiltration rates for different rock fragment contents (0%, 10%, 20%, 30%, and 40%) and rock fragment sizes (2-5, 5-8, 8-11, and 2-11 mm). The results showed that both the content and size of the rock fragments and their interaction significantly affected the infiltration process. The infiltration rates over time and the saturated hydraulic conductivity (Ks) decreased with an increasing rock fragment content to an observed minimum value for a 40% rock fragment content. The soil-water infiltration processes were accurately described by the Kostiakov model. The measured and calculated Ks values decreased with an increasing rock fragment content, which was in accordance with the published data and in accordance with the Ks obtained by five empirical methods. The variations in the measured Ks were likely due to the variations in the soil properties caused by the soil sample repacking. The results of this study may improve the understanding of the effects of the rock fragment content and size on the infiltration processes in arid and semi-arid desert steppes. [ABSTRACT FROM AUTHOR]

Understanding the differences and controlling factors of stable water isotopes in the soil-plant-atmosphere continuum of different vegetation zones has important guiding significance for revealing the hydrological processes and regional water cycle mechanisms.This study selected three different vegetation zones (alpine meadows, forests, and arid piedmont zones) in the Shiyang River Basin for study. This paper's analysis results show that: (1) In SPAC, precipitation isotope has the main controlling effect. From alpine meadows to arid foothills, as the altitude decreases, the temperature effect of precipitation isotopes increases. (2) From the alpine meadow to the arid foothills, the soil water isotope is gradually enriched, indicating that the evaporation is gradually increasing. (3) Alpine meadow plants are mainly supplied by precipitation in the rainy season; forest plants mainly utilize soil water in the dry season and precipitation in the rainy season. The soil water in the arid mountain foothills is mainly recharged by groundwater, and the evaporation and fractionation of plant isotopes are very strong.This research will help understand the SPAC system's water cycle at different altitudes and climates on high mountains. [ABSTRACT FROM AUTHOR]

Water resource management scenarios have become more crucial for arid to semi-arid regions. Their application prerequisites rigorous hydrological modelling approaches since data are usually exposed to uncertainties and inaccuracies. In this work, Soil Water Assessment Tool (SWAT), an open source semi-distributed, continuous-time, process-based physical hydrological model is used to model hydrological processes and eventually calculate groundwater recharge estimations in Seybouse basin, Northeast Algeria. The model uses estimated rainfall to calibrate the model with observed discharge from hydrometric stations. Model calibration and validation are performed over four hydrometric stations located in the basin. Uncertainty analysis and sensitivity analysis supported the calibration period. SUFI-2 algorithm is used for uncertainty estimations along with a global sensitivity analysis prior to calibration simulations. Simulated flood hydrographs showed generally good accuracy with few misfits on the peaks. The model obtained satisfactory and consistent calibration and validation results for which the Nash score varied from 0.5 to 0.7 for calibration and from −0.1 to 0.6 for validation and R2 from 0.6 to 0.7 for calibration and 0.03 to 0.8 for validation. Moreover, estimated water budget values show strong similarities with the observed values found in the literature. The present work shows that the rigorously calibrated and validated SWAT model can simulate hydrological processes as well as major high and low flows using estimated rainfall data. [ABSTRACT FROM AUTHOR]

Soil erosion is a key factor in soil quality degradation and carbon balance in arid ecosystems. However, many models ignore the soil erosion process in arid regions, which may lead to limits in our understanding of ecosystem processes in arid regions. In this study, we added the soil erosion process according to field observed data of soil hydrothermal regimes and carbon flux. We validated this coupling version of IBIS (Integrated Biosphere Simulator) and RUSLE (RU–IBIS) by examining four different vegetation types and the carbon budget in the arid region on the Loess Plateau (LP). Our results indicated that the coupling model (RU–IBIS) produced more reliable simulations of the soil water content (with the r from 0.23–0.90 to 0.71–0.97) and evaporation (ET) (the average r was 0.76) and significantly improved the simulation of the leaf area index (LAI) (the average r was 0.95) and net primary production (NPP) (the average r was 0.95). We also conducted sensitivity experiments to determine how soil texture and aerodynamic roughness (Z0m) affect the soil water content. Moreover, it was revealed that specific leaf area (SLA) plays a key role in the simulation of NPP and NEE. Our study suggests that the coupled soil erosion process and parameterization can effectively improve the performance of IBIS in arid regions. These results need to be considered in future Earth system models. [ABSTRACT FROM AUTHOR]

Lack of water is the main problem facing agriculture and crop production in arid and semi-arid regions. Deficit irrigation is widely used to optimize water application efficiency under drought conditions in arid areas. The purpose of the work is to estimate the efficiency of SALTMAD model for simulating soil moisture dynamics, water application efficiency, and seed yield under three Deficit Irrigation Strategies (DIS) [DIS1 (100% Full Irrigation (FI)), DIS2 (80% FI), and DIS3 (60% FI)] with six treatments of Integrated Nitrogen-Fertilization (INF) including [INF1 (100% MN + 0% ON), INF2 (80% MN + 20% ON), INF3 (60% MN + 40% ON), INF4 (40% MN+ 60% ON), INF5 (20% MN + 80% ON) and INF6 (0% MN + 100% ON), (MN: Mineral Nitrogen, and ON: Organic Nitrogen)]. Moreover, the best strategy of deficit irrigation with the best treatment of integrated nitrogen fertilizer will be selected for improving soil hydro-physical properties, water productivity, and seed yield in semi-arid soil regions without any water stress. Field experiment was conducted during 2020/2021 and 2021/2022 at the Research Farm of National Research Center (NRC) at Nubaryia Region, Al Buhayrah Governorate, Egypt. Soil hydro-physical properties including infiltration rate (IR), and soil moisture dynamics were measured in the field. In addition, soil moisture dynamics, water application efficiency, seed yield, and water productivity of bean were simulated using the SALTMAD model and compared with thatmeasured in the field under the above conditions. The results observed that the best treatment that led to increased water application efficiency and seed yield was at DIS2 (80% FI) with INF4 (40% MN+ 60% ON) compared to DIS1 (100% FI), and DIS3 (60% FI). In this strategy, seed yield productivity increased by 43.4% in the first season, and 34.7% in the second season as well as saving irrigation water by up to 20% for cultivated faba bean in sandy soil without any water stress. The usage of balance a combination of mineral and organic fertilizers can be used to compensate for deficit irrigation by improving infiltration rate, water holding capacity, water application efficiency, and seed yield. The SALTMAD model can be used to simulate soil moisture dynamics, water application efficiency, seed yield, and water productivity with little calculation error under different deficit irrigation strategies and integrated nitrogen fertilization in arid and semi-arid areas with sandy soil. [ABSTRACT FROM AUTHOR]

Satellite observations have provided global and regional soil-moisture estimates in the last four decades. However, the accuracy of these observations largely depends on reducing uncertainties in the retrieval algorithms. In this study, we address two challenges affecting the quality of soil-moisture estimates from a widely used soil-moisture-retrieval model, the land parameter retrieval model (LPRM). We studied two improvement schemes that were aimed at reducing uncertainties in open water signals (the LPRMv6_OWF) and vegetation signals (the LPRMv6_Veg), as well as a scheme to reduce their combined impacts (the LPRMv6_OWFVeg) on LPRM-retrieved soil moisture using the FengYun-3B (FY-3B) satellite observations. To assess the impacts of the improvement schemes, we utilized in situ soil moisture from the Jiangsu and Jiangxi provinces in China. We found that the retrievals (Rs) of the LPRMv6_Veg and the LPRMv6_OWFVeg were mainly in the range of 0.2 to 0.5 in Jiangsu and Jiangxi, with increases of 0.1 compared to those of the LPRMv6. The standard deviation (SD) of the LPRMv6_OWFVeg increased in Jiangsu, while the R of the LPRMv6_OWF increased in Jiangsu by 0.05–0.1 compared to that of the LPRMv6, but the SD tended to become worse. In Jiangxi, there was an increase of 0.1 in R. The results show that each of these algorithms improved the accuracy of soil-moisture inversion to some extent, compared to the original algorithm, with the LPRMv6_OWFVeg showing the greatest improvement, followed by the LPRMv6_Veg. The accuracy of both the LPRMv6_OWF and the LPRMv6_OWFVeg decreased to some extent when the open-water fraction (OWF) was greater than 0.2. Full areal extent analyses based on triple collocation showed significant improvements in correlations and minimized errors across different vegetation scenarios over the entire region of China in both the LPRMv6_OWF and the LPRMv6_Veg. However, reduced qualities were found in arid regions in northern China because of the nonlinear relationships between land-surface temperature, vegetation, and soil moisture in the LPRM. These results highlight important lessons for developing comprehensive improvement schemes for soil-moisture retrievals from passive microwave satellite observations. [ABSTRACT FROM AUTHOR]

This paper examines determinants of adoption of rainwater harvesting and conservation techniques in semi-arid Tharaka sub-county, Eastern Kenya. Given the erratic rainfall that characterises Tharaka, rainwater harvesting and conservation is critical for the improvement of agricultural production. The study was conducted in two agro-ecological zones, and 196 respondents were interviewed. The majority of the farmers were practising between 1-3 and 4-6 rainwater harvesting and conservation techniques-an indication of the awareness of the benefits. In situ technologies were more frequently practised than micro-catchment and macro-catchment technologies. There were institutional efforts supporting adoption of micro-catchment and macro-catchment techniques in the recent past. Correlation results showed that the number of techniques practised was influenced by the number of years spent in school, arable land size, labour availability and number of livelihood options. Soil quality is an unlikely determinant of rainwater harvesting because a majority of the farmers rated it as good and fair. Chi-squared results suggest that choice of rainwater techniques is primarily informed by a desire to harvest and conserve soil moisture than to improve soil quality. Although adoption of these technologies is encouraging, assessment of their efficiency in the context of physical attributes such as soil characteristics, slope and rainfall amount of the area would add value. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Crop water stress significantly reduces crop yield. Several studies have employed optical and remote-sensing methods to obtain nondamage monitoring crop water content to understand the agriculture drought process. In this paper, the spectral information (i.e., the canopy absorption feature at the 350–2500 nm band range) from the field experiments was used to estimate and identify the canopy water stress. Five different levels of water treatments exist in the spring wheat field in the semiarid regions of Loess Plateau, Northwest China. The hyperspectral reflectance, soil moisture content, soil water potential, canopy water content, amount of chlorophyll, leaf area index, and environmental parameters were measured. The relationship between canopy reflectance and canopy water content was analyzed at different water stress levels. In addition, various spectral indices were tested by measurements. Results showed that a high correlation exists in semiarid water index-1, semiarid water index-2, and red-edge normalized difference vegetation index, thus denoting that these indices can indicate water stress effectively. We can conclude that canopy reflectance can identify crop water stress and can be used to develop a certain index for monitoring agriculture drought. [ABSTRACT FROM PUBLISHER]

In semiarid montane regions, spatial patterns of shallow soil moisture (0-5 cm) are expected to depend on vegetation patterns and topographic attributes. In some cases, the vegetation patterns themselves depend on the topography, which makes the interaction of soil moisture, vegetation and topography especially complex. Such is the case in portions of the Colorado Front Range where many south-facing and north-facing slopes are primarily vegetated by mountain mahogany ( Cercocarpus montanus) shrubs and ponderosa pine ( Pinus ponderosa) trees, respectively. The objectives of this paper are the following: (1) to determine how the presence of a shrub or tree affects the shallow soil moisture on these distinct hillslopes and (2) to understand the main mechanisms through which the vegetation affects the shallow soil moisture. On opposing hillslopes in the Cache la Poudre catchment, soil moisture was monitored for intercanopy, shrub canopy and tree canopy locations. Throughfall, insolation, soil texture and hydrophobicity were also measured to understand the reasons for any soil moisture differences. The results suggest that the shallow soil moisture is more distinct between the canopy and intercanopy locations on the south-facing slope than the north-facing slope. On the south-facing slope, intercanopy locations are less shaded by the nearby canopy because of the shorter stature of the shrubs and the orientation of this hillslope towards the sun. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Arid and semi-arid ecosystems are characterized by patchy vegetation and variable resource availability. The interplant spaces of these ecosystems are very often covered by cyanobacteria-dominated biocrusts, which are the primary colonizers of terrestrial ecosystems and key in facilitating the succession of other biocrust organisms and plants. Cyanobacterial biocrusts regulate the horizontal and vertical fluxes of water, carbon and nutrients into and from the soil and play crucial hydrological, geomorphological and ecological roles in these ecosystems. In this paper, we analyze the influence of cyanobacterial biocrusts on water balance components (infiltration-runoff, evaporation, soil moisture and non-rainfall water inputs (NRWIs)) in representative semiarid ecosystems in southeastern Spain. The influence of cyanobacterial biocrusts, in two stages of their development, on runoff-infiltration was studied by rainfall simulation and in field plots under natural rainfall at different spatial scales. Results showed that cover, exopolysaccharide content, roughness, organic carbon, total nitrogen, available water holding capacity, aggregate stability, and other properties increased with the development of the cyanobacterial biocrust. Due to the effects on these soil properties, runoff generation was lower in well-developed than in incipient-cyanobacterial biocrusts under both simulated and natural rainfall and on different spatial scales. Runoff yield decreased at coarser spatial scales due to re-infiltration along the hillslope, thus decreasing hydrological connectivity. Soil moisture monitoring at 0.03 m depth revealed higher moisture content and slower soil water loss in plots covered by cyanobacterial biocrusts compared to bare soils. Non-rainfall water inputs were also higher under well-developed cyanobacterial biocrusts than in bare soils. Disturbance of cyanobacterial biocrusts seriously affected the water balance by increasing runoff, decreasing soil moisture and accelerating soil water loss, at the same time that led to a very significant increase in sediment yield. The recovery of biocrust cover after disturbance can be relatively fast, but its growth rate is strongly conditioned by microclimate. The results of this paper show the important influence of cyanobacterial biocrust in modulating the different processes supporting the capacity of these ecosystems to provide key services such as water regulation or erosion control, and also the important impacts of their anthropic disturbance. [ABSTRACT FROM AUTHOR]

The success of reforestation of degraded areas in semiarid environments is constrained by low soil water content and fertility. In order to overcome these limitations, several site preparation techniques previous to plantation have been developed. Organic amendments have been used to improve physical soil properties in order to increase water availability for plants. However, the role of improvement in nutrient availability produced by organic amendment could have been neglected in semiarid vegetation restoration. In this paper, we analyze the effect of two site preparation treatments on soil moisture dynamics of an experimental reforestation with Pinus halepensis Mill. in a semiarid Mediterranean ecosystem. In one treatment (S) only lineal subsoiling (60–80 cm deep) was applied, in the other (SFF) a fresh urban refuse was added at a dose of 10 kg m−1 into the subsoiled furrow. During the first 5 years the growth of pines was significantly higher in SFF. At this time, we studied soil moisture dynamics at 0–20 cm in transects (for 8 months) and in soil profiles at 5, 15, 25 and 45–55 cm depth (for 23 months). Measurements made in two adjacent off-lines unaffected by site preparation were used as covariates. We also measured soil physical properties, macronutrients (N,P,K) and total organic carbon (TOC) content. No significant differences in soil physical properties were found between the amended versus not amended treatment except for hydraulic conductivity and sand fraction content. SFF treatment showed higher hydraulic conductivity, especially in top soil layers (0–10 cm), and lower content of sand fraction. Phosphorus availability was significantly higher in soil amended with organic refuse while no effect was detected in the content of the rest of macronutrients measured. In the transects, a reduction of 30% of the mean soil water content was observed in planting lines (0.14 cm 3 cm−3) in contrast with adjacent off-lines (0.20 cm 3 cm−3); no statistically significant differences between site preparation techniques were found. Soil profiles observations revealed that soil water content was significantly higher in S than in SFF treatment. This suggests that improvement in soil moisture associated to improvement in the physical structure of the soil cannot explain differences in growth. We argue instead this is mostly attributable to improved nutrient availability and microbiological activity associated with the organic amendment. These results stress the importance of a better understanding of the role of nutrients in the restoration of water-stressed ecosystems. • Addition of organic amendment to subsoiled furrows increased growth of planted seedlings. • Soil water content was significantly higher in subsoiled than in subsoiled and amended furrows. • Difference in growth is attributable to fertilizing effects of organic amendment. • The role of nutrients in restoration of water-stressed ecosystems needs to be emphasized. [ABSTRACT FROM AUTHOR]

Field survey, focus group discussions and key informants' interview were conducted to collect data on the effects of degraded hillsides allocation to landless youth groups. Data on vegetation recovery, and status of physical soil and water conservation structures were collected from 3 allocated and 3 adjacently non-allocated hillsides. Our findings indicated that hillside allocation improved the length of physical soil and water conservation structures by 58% (from 1310 meters ha-1 on communal hillsides to 2067 meters ha-1 on allocated hillsides). Hillside allocation to landless youth also improved tree survival rate, number of woody species and species diversity by 25%, 14% and up-to 62%, respectively. It can be concluded that allocation of communal hillsides to landless youth resulted in improved land management and vegetation cover on top of their economic benefits. This implies that the strategy can be taken as a potential option to overcome the challenges of land degradation. [ABSTRACT FROM AUTHOR]

In the context of climate warming, flash drought has become increasingly frequent, posing significant threats to agriculture, ecosystems, and the environment. Xinjiang, located in an arid and semi-arid region, necessitates a thorough investigation into the distinctions between flash drought and traditional drought, as well as an exploration of the driving forces behind both types of drought. In this study, soil moisture data from ERA5-Land were utilized to construct a framework for the identification of flash drought and traditional drought based on historical events. The Geodetector was employed to explore the factors that influence the spatial heterogeneity of these two drought forms. The findings illuminate that (1) in terms of spatial distribution, traditional drought predominated in southern Xinjiang, while flash drought exhibited greater prominence in northern Xinjiang. (2) Regarding changes in trends, both flash drought and traditional drought exhibited an increasing trend in frequency since the 1990s, with the frequency trend of flash drought passing the significance test (α ≤ 0.05). Additionally, the severity of both flash drought and traditional drought displayed a noteworthy and statistically significant increase within sliding windows ranging from 46 to 62 years. (3) Concerning the driving forces, precipitation emerged as the principal driving force behind both flash drought and traditional drought. Furthermore, human activities exerted a more substantial influence on traditional drought, and the interactions involving human activities had the potential to significantly amplify the explanatory power of the spatial heterogeneity for both drought types. (4) In terms of the drought risk, a notable variation in the risk of flash drought was observed across various ecological zones, with the highest risk occurring in mildly fragile ecological zones. Furthermore, when comparing the results from 1995 to 2019, the flash drought risk exhibited a marked increase in severely fragile ecological zones. This study enriches the understanding of the dynamics of flash drought and traditional drought in Xinjiang and carries important implications for enhancing the precision of drought monitoring and early warning systems. [ABSTRACT FROM AUTHOR]

As vegetation plays a critical role in terrestrial ecosystems, understanding its status and variation is vital for preserving the stability of an ecosystem. Central Asia serves as a representative example of an arid and semi-arid region characterized by sparse vegetation and poor soils, making its vegetation particularly fragile and sensitive. To investigate the vegetation condition in the region, this study examined the spatial and temporal characteristics of vegetation variation from 2001 to 2020, utilizing the normalized difference vegetation index (NDVI) as an indicator. Meanwhile, trend analysis, Mann–Kendall abrupt change point test, geodetector, and correlation analysis were used to quantitatively analyze the natural and anthropogenic drivers of these variations over the past two decades. The results suggest that vegetation coverage in Central Asia was relatively low, with an annual average NDVI of 0.16 over the past 20 years. Moreover, the spatial distribution of NDVI in Central Asia exhibited significant spatial heterogeneity, with vegetation coverage declining from north to south and from east to west. Furthermore, the NDVI exhibited a slightly increasing trend during the period of 2001 to 2020 with an increased rate of 0.00025/yr. However, we detected an abrupt change point in vegetation dynamics in Central Asia around 2010, which indicated a significant shift in vegetation variation in the region. Land-use type has a great influence on the spatial heterogeneity of NDVI in Central Asia, which can explain 46% of the vegetation distribution in this region. Moisture factors such as precipitation and soil water content followed with 35% and 32% contributions, respectively. Regarding the temporal variation of NDVI, it is mainly driven by the fluctuation in precipitation, with the degree of influence of precipitation on NDVI varying for different regions in various geographical conditions. This study offers a more comprehensive insight into the spatial and temporal dynamics of NDVI in Central Asia and indicates that precipitation plays a significant role in driving the spatial heterogeneity and temporal variation of NDVI. These findings are essential for predicting vegetation changes in arid regions under future environmental conditions and formulating effective strategies to prevent and alleviate vegetation degradation. [ABSTRACT FROM AUTHOR]

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This study aims to analyze the potential of different drought indices for identifying drought periods and predicting cereal yield in two semi-arid regions, Lleida in Catalonia and Kairouan in Tunisia, which have similar Mediterranean climates but different agricultural practices. Four drought indices, namely the Soil Moisture Anomaly Index (SMAI), the Vegetation Anomaly Index (VAI), the Evapotranspiration Anomaly Index (EAI), and the Inverse Temperature Anomaly Index (ITAI), were calculated from remote sensing data. Drought periods were identified from 2010/2011 to 2021/2022 based on the aforementioned indices. A correlation study between drought indices and wheat and barley yields was performed in order to select the most informative index and month for yield prediction. In the rainfed cereal area of Lleida, the strongest correlation was found between the EAI and VAI with barley yield (0.91 and 0.83, respectively) at the time of cereal maturity in June. For wheat, the strongest correlation was found between the EAI and VAI (0.75 and 0.72, respectively) at the time of cereal maturity in July. However, the VAI, EAI, and SMAI showed the best performance as an earlier indicator in March with a correlation with barley yield of 0.72, 0.67, and 0.64, respectively; the lowest standard deviation was for the SMAI. For wheat yield, the best earlier indicator was the SMAI in March, showing the highest correlation (0.6) and the lowest standard deviation. For the irrigated cereal zone of Kairouan, the strongest correlation (0.9) and the lowest standard deviation are found between the EAI and cereal yield in April. In terms of advanced prediction, the VAI shows a high correlation in March (0.79) while the SMAI shows a slightly lower correlation in February (0.67) and a lower standard deviation. The results highlight the importance of the EAI and SMAI as key indicators for the estimation and early estimation (respectively) of cereal yield. [ABSTRACT FROM AUTHOR]

Despite the mounting attention being paid to vegetation growth and their driving forces for water-limited ecosystems, the relative contributions of atmospheric and soil moisture dryness stress on vegetation growth are an ongoing debate. Here we comprehensively compare the impacts of high vapor pressure deficit (VPD) and low soil water content (SWC) on vegetation growth in Eurasian drylands during 1982–2014. The analysis indicates a gradual decoupling between atmospheric dryness and soil dryness over this period, as the former has expanded faster than the latter. Moreover, the VPD–SWC relation and VPD–greenness relation are both non-linear, while the SWC–greenness relation is near-linear. The loosened coupling between VPD and SWC, the non-linear correlations among VPD–SWC-greenness and the expanded area extent in which SWC acts as the dominant stress factor all provide compelling evidence that SWC is a more influential stressor than VPD on vegetation growth in Eurasian drylands. In addition, a set of 11 Earth system models projected a continuously growing constraint of SWC stress on vegetation growth towards 2100. Our results are vital to dryland ecosystems management and drought mitigation in Eurasia. [ABSTRACT FROM AUTHOR]

Desert vegetation in the outer transition zone of an arid oasis serves as a protective barrier against wind and sand, safeguarding the oasis ecosystem. However, intensive agricultural water usage within the oasis has led to water depletion, posing a threat to the survival and growth of desert vegetation, as well as the associated increase in wind and sand phenomena. To ensure the sustainable distribution of water resources and maintain the stability of the oasis peripheral ecosystem, this study aimed to investigate the relationship between the ecological water demand of desert vegetation and its effectiveness in preventing wind erosion. Through a combination of field sample tests, field pit tests, and data analysis, this research focused on Haloxlon ammodendron, the most prevalent species on the oasis periphery, to explore the intricate relationship between its ecological water demand and resistance to wind erosion. The results showed that medium-vegetation-coverage soils exhibited a higher soil moisture content (7.02%) compared to high-vegetation-coverage soils (1.57%) and low-vegetation-coverage soils (3.41%). As the soil water content decreased, the growth rate of H. ammodendron's plant height, new branches, and crown width decelerated. The ecological water requirement of H. ammodendron during its growth period was 70.95 mm under medium-vegetation-coverage conditions, exhibiting a significant increase of 14.6% and 12.3% compared to high- and low-vegetation-coverage conditions, respectively. Meanwhile, H. ammodendron exhibits remarkable wind erosion prevention effects in moderate coverage conditions, resulting in a significant reduction in surface sand collection and sand transport by 53.15% and 51.29%, respectively, compared to low vegetation coverage; however, no significant difference was observed when compared to high vegetation coverage. The SEM model results revealed that soil water content had an indirect effect on sand transport (R2 = 0.90) and sand collection (R2 = 0.96) through three pathways of action, namely: volatile water content–crown growth rate–wind speed–sediment discharge; volatile water content–plant height growth rate–vegetation coverage–wind speed–sediment discharge; and volatile water content–plant height growth rate–vegetation coverage–sediment accumulation. This study provides valuable insights for the scientific formulation and implementation of strategies aimed at protecting desert vegetation. [ABSTRACT FROM AUTHOR]

Dual use of water for fish and crop production could be a promising approach to improve irrigation under arid conditions. A watercress pot study was carried out to assess the effects of irrigation by catfish and tilapia aquaculture water on the sandy soil properties as well as the growth parameters of watercress with various combinations of artificial NPK fertilizers at El-Minia Governorate of Egypt (28°18′16″ N latitude and 30°34′38″ E longitude). Catfish aquaculture water had the greatest phytoplankton abundance at 83,762 units (×104/L), while the minimum number of phytoplankton existed in tilapia aquaculture water, recorded at 14,873 units (×104/L). There were significant average changes that varied from 120 to 237 (×104 cfu/mL−1) in total bacterial counts in tilapia and catfish waters. Watercress growth quality parameters closely paralleled at all NPK application rates, indicating that the highest quality plants were produced in pots receiving 25% of the recommended levels and irrigated with catfish aquaculture water. Nitrate concentrations of watercress plants were determined under pollution levels established by the European Commission for leafy and tuber vegetables. In conclusion, the use of microbial and phytoplankton-rich aquaculture water to irrigate vegetables and as fertilizer can maintain a balanced soil ecosystem. [ABSTRACT FROM AUTHOR]

In this paper, we analyze the paleoclimatic and paleoenvironmental evolution of Laguna Yema in semi-arid Chaco region of Argentina over the past six hundred years. High resolution multiproxy studies of lake sediments utilize analyses of lithology, mineralogy, geochemistry, palynology, and are constrained by radiocarbon and gamma spectrometry dating. Laguna Yema sediments were mainly composed of well stratified fine sediments (silts and clays), with variable proportions of quartz, clays (illite) and feldspar (microcline and albite). Twelve light and heavy geochemical elements were registered. Most elements (Al, Si, K, Ti, Fe, Rb, Ba, and Br) are associated with illite and albite. Different material transport processes related to the changes in aridity and humidity of the basin were identified using the main mineralogical origins of geochemical elements. Palynological records indicate cycles of contraction and expansion of the lake, with an increase in concentration of Alternanthera aquatica during wet periods (expansion of lake), and an increase in Ambrosia , Poaceae and fern spores during dry periods (contraction of lake). These changes are linked to fluctuations in moisture conditions in the Subandean Mountains and semi-arid Chaco regions, in response to interactions between the South American Monsoon System (SAMS) and the South American Low Level Jet (SALLJ), which send warm and humid air to northern Argentina. In a regional context, the Laguna Yema records are in accordance with the analyses of the temporal and spatial pattern of moisture distribution for the last six centuries. • High-resolution variations of moisture conditions were registered by multiproxy lake sediments studies for the last 553 years. • Dissimilar material transport processes, related to the precipitation, were identified through mineralogy and geochemistry. • The palynological analyses allowed us to complement the paleohydrologic reconstruction in the basin. • The climatic model responds to the interconnection between the South American Monsoon System and South American Low Level Jet. [ABSTRACT FROM AUTHOR]

Soil moisture plays an important role in various applications such as hydrology, agronomy, climatology and ecology. Over the past few decades, images acquired by PolSAR (Polarimetric Synthetic Aperture Radar) systems have raised much interest in the remote sensing community. However, only a few studies have analysed the potential use of polarimetric parameters for the estimation of soil moisture. Taking Juyanze as the study area, two feature extraction methods, the simple polarimetric intensity and phase processing, and the polarimetric decomposition were used to extract different polarimetric parameters. The response of single, multiple, and combined polarimetric parameters to bare surface soil moisture was investigated based on linear and non-linear regression strategies in using fully polarimetric RADARSAT-2 SAR (Synthetic Aperture Radar) imagery and field measurements. The results indicate that each individual polarimetric parameter at C-band is not very sensitive to surface soil moisture under this investigation. However, with the increasing number of polarimetric parameters, the correlation between soil moisture and polarimetric parameters improves steadily and the root mean square error (RMSE) and mean absolute error (MAE) decreased gradually. Combined polarimetric parameters have little improvement on the correlation between soil moisture and polarimetric parameters. The non-linear regression method can improve the correlation to some extent. However, the preliminary results so far still do not satisfy the accuracy of using the polarimetric parameters to inverse soil moisture. Further investigations are required in the direction of a better characterization and exploitation of polarimetric SAR data for the retrieval of soil moisture in arid regions. [ABSTRACT FROM AUTHOR]

Drought is a meteorological phenomenon that negatively impacts agricultural production. In recent years, southwest China has frequently experienced agricultural droughts; these have significantly impacted the economy and the ecological environment. Although several studies have been conducted on agricultural droughts, few have examined the factors driving agricultural droughts from the perspective of water and energy balance. This study aimed to address this gap by utilizing the Standardized Soil Moisture Index (SSMI) and the Budyko model to investigate agricultural drought in southwest China. The study identified four areas in Southwest China with a high incidence of agricultural drought from 2000 to 2020. Yunnan and the Sichuan-Chongqing border regions experienced drought in 10% of the months during the study period, while Guangxi and Guizhou had around 8% of months with drought. The droughts in these regions exhibited distinct seasonal characteristics, with Yunnan experiencing significantly higher drought frequency than other periods from January to June, while Guizhou and other areas were prone to severe droughts in summer and autumn. The Budyko model is widely used as the mainstream international framework for studying regional water and energy balance. In this research, the Budyko model was applied to analyze the water and energy balance characteristics in several arid regions of southwest China using drought monitoring data. Results indicate that the water and energy balances in Yunnan and Sichuan-Chongqing are more moisture-constrained, whereas those in Guizhou and Guangxi are relatively stable, suggesting lower susceptibility to extreme droughts. Furthermore, during severe drought periods, evapotranspiration becomes a dominant component of the water cycle, while available water resources such as soil moisture decrease. After comparing the causes of drought and non-drought years, it was found that the average rainfall in southwest China is approximately 30% below normal during drought years, and the temperature is 1–2% higher than normal. These phenomena are most noticeable during the spring and winter months. Additionally, vegetation transpiration is about 10% greater than normal during dry years in Southwest China, and soil evaporation increases by about 5% during the summer and autumn months compared to normal conditions. [ABSTRACT FROM AUTHOR]