Soil Moisture Distribution Research Articles

Research on Underground Drip Irrigation and Soil Redistribution - Take Heshan District of Yiyang City as an Example

Abstract: The drip flow and the buried depth of drip irrigation zone are not only important parameters of subsurface irrigation design and operation management, but also important factors affecting the migration and redistribution of soil water and fertilizer. Crop growth is closely related to soil water and nitrogen leaching, water and fertilizer transport patterns and redistribution characteristics. It is of great significance to study the migration and redistribution of soil water and fertilizer under subsurface drip irrigation for improving the utilization efficiency of water and fertilizer and improving the system of subsurface drip irrigation. In this paper, the migration mode and redistribution characteristics of water and nitrogen in subsurface drip irrigation were studied and analyzed by means of laboratory soil box experiment, considering the two factors of drip flow and the buried depth of drip irrigation belt. The main research conclusions are as follows: Ⅰ. Different drip flows had effects on soil moisture front, soil moisture content and soil water redistribution. If other conditions remain unchanged, increasing the drip flow can increase the moist body area of soil and increase the moisture content of soil. The distance between vertical and horizontal directions increased with the large drip flow, and the soil water content decreased with the increase of distance. Large drip flow can promote the redistribution of soil water after drip irrigation. Ⅱ. Different drip depth had effects on soil moisture content and soil water redistribution. When the drip depth was 0cm, the surface shape of the wet body was a "horizontal" semi-ellipse after drip irrigation. When the drip depth was 10cm and 20cm, the surface of the wet body was an "upright" semi-ellipse after drip irrigation. The larger the buried depth of the drip can make the distribution of soil moisture more uniform, and the larger the buried depth of the drip can promote the migration of water in the soil. Ⅲ. Different drip discharge had an effect on soil nitrogen redistribution, and large drip discharge promoted soil nitrogen redistribution after drip irrigation. The Nitrate Nitrogen (NO3--N) content in the moist body is lower than that near the edge of the wetting front. The content of Ammonium Nitrogen (NH4+-N) near the edge of the wetting peak is higher than that inside the wetting body. Ⅳ. The redistribution of soil nitrogen was affected by different buried depth of drip head, and the greater buried depth of drip head could promote the redistribution of soil nitrogen. In terms of vertical and horizontal migration of ammonium nitrogen and nitrate nitrogen, on the day after drip irrigation, the cumulative effect of Nitrate Nitrogen (NO3--N) buried at a depth of 20cm was more significant near the wetting front edge at a larger vertical downward distance, and the cumulative effect of Nitrate Nitrogen (NO3--N) buried at a depth of 20cm was more significant inside the wetting body at a larger vertical downward distance. At the same time, the drip buried depth of 20cm can spread the cumulative effect inside the wet body and near the edge of the wet front to a longer horizontal distance.

Modeling the weight moisture content of soils in Anabar tundra using ground-based research and remote sensing data of the earth

Presently, the climate is warming, with average annual temperatures rising every year, and the Arctic remaining one of the most vulnerable regions. This has a noticeable effect on the northern forests, which leads to the displacement of the tundra zone. Assessing the consequences of a projected increase in air temperature under climate change conditions requires spatial and instant monitoring of hard-to-reach areas. In the last few years, the use of remote sensing techniques and combinations of satellite imagery to calculate vegetation indices has generated great interest in obtaining high-definition ground data. The article presents the results of modeling soil moisture in Anabar tundra, which is located in the north-west of Yakutia. The study was conducted on the border of tundra and forest tundra in three reference areas (tundra, tundra young forest, tundra indigenous forest). The simulation is presented by comparing the field data and the normalized difference index of humidity NDMI. The NDMI index uses the NIR and SWIR channels, calculates a multi-channel raster object and creates a raster image with index values from -1 to 1, which show the humidity level with a spatial resolution of 10 meters. The data showed that the value of humidity pixels according to NDMI in the tundra zone is 0.04, in the tundra young forest is 0.09 and, in the tundra, native forest is 0.15. It was found that the index data correlated with field humidity data obtained from a depth of 0.2 m. A comparison of remote sensing decryption data with field data made it possible to simulate the spatial distribution of soil moisture over the vast study area by extrapolation.

Water productivity of barley crop under laser land leveling technique and minimum tillage

ABSTRACTLaser land leveling is an important method that helps to improve the spatial distribution of irrigation water and fertilizers applications, subsequently reduce water, nutrient, and energy inputs to agriculture and contributes to increasing productivity. Thus, the aim of the study was to improve the productivity of the barley crop grown in sandy lands under conditions of water scarcity and the negative impact of climate change in Egypt by using laser leveling and the minimum tillage method. Two experiments were conducted during the 2020/2021 and 2021/2022 seasons at the Nubariya farm, Buhaira Governorate, Egypt to study the effects of laser leveling and minimum tillage (zero – tillage, 10 cm, 20 cm, and 30 cm) affecting the distribution of soil moisture, water stress, effectiveness of water application, yield characteristics, water productivity, and some quality parameters of the barley crop. The statistical analysis’ findings revealed a considerable influence of both laser soil leveling and minimum depth of plowing on productivity, water productivity and quality properties of barley crop. Laser leveling with a plowing depth of 10 cm gave the most favorable values of the soil moisture content at the root-zone as well as better grain yield and water productivity in addition to improve the quality properties of barley. The grain yield has improved by 12.65% and 10.41%, while water productivity has increased by 12.75% and 10.06% during the seasons 2020/2021 and 2021/2022, respectively. This increase is likely the result of improving soil moisture distribution and increasing irrigation application efficiency, which resulted in less water stress in the root zone and subsequently increased yield, water productivity and quality properties of barley during the two growing seasons. Generally, the application of laser land leveling as eco-friendly practice will help in sustaining barley productivity in Egypt particularly in the sandy soil regions. According to this study, laser-assisted precision field leveling has the potential to improve grain yield and crop establishment, water productivity and barley quality properties in addition to achievement of the highest net income for farmers.

Soil Moisture Monitoring in Banjarnegara Regency Using SMAP imagery

One of the places in Indonesia where landslides occur relatively frequently, is Banjarnegara Regency. Landslides with significant losses are observed in the study area almost annually. The preceding soil wetness is one of the elements that trigger landslides. In this study, we determine high and low soil wetness by classifying soil moisture and observing how it relates between soil moisture and the occurrence of landslides. Temporary and spatial processing was done on historical soil moisture imaging data from the Soil Moisture Active Passive (SMAP) satellite. The soil moisture variability in each of the 20 grids in the study area was compared. The highest and lowest soil moisture distribution is noticeable using the high-frequency approach. The findings demonstrate that the historical soil water content trend often follows a similar pattern. When divided by the number of samples (n), the Very High-Frequency method has a minimum value of 0 and a maximum value of 25.4mm. In this value range, there are five different classes of soil moisture: very low (0–5mm), low (5.1–10mm), medium (10.1–15mm), high (15.1–20mm), and very high (20.1-25.4mm). Despite not being the highest value from very high-frequency computations, the Banjarnegara Regency is in the high class, ranging from 16.12mm to 20.03mm. The elements causing the frequent landslides in Banjarnegara Regency are excessive and antecedent soil moisture. From 894 historical data records, entire grids with very-high and high classes cumulatively have between 51% and 85% incidences of soil moisture value.

Assimilation of Sentinel-1 Backscatter into a Land Surface Model with River Routing and Its Impact on Streamflow Simulations in Two Belgian Catchments

Abstract Accurate streamflow simulations rely on good estimates of the catchment-scale soil moisture distribution. Here, we evaluated the potential of Sentinel-1 backscatter data assimilation (DA) to improve soil moisture and streamflow estimates. Our DA system consisted of the Noah-MP land surface model coupled to the HyMAP river routing model and the water cloud model as a backscatter observation operator. The DA system was set up at 0.01° resolution for two contrasting catchments in Belgium: (i) the Demer catchment dominated by agriculture and (ii) the Ourthe catchment dominated by mixed forests. We present the results of two experiments with an ensemble Kalman filter updating either soil moisture only or soil moisture and leaf area index (LAI). The DA experiments covered the period from January 2015 through August 2021 and were evaluated with independent rainfall error estimates based on station data, LAI from optical remote sensing, soil moisture retrievals from passive microwave observations, and streamflow measurements. Our results indicate that the assimilation of Sentinel-1 backscatter observations can partly correct errors in surface soil moisture due to rainfall errors and overall improve surface soil moisture estimates. However, updating soil moisture and LAI simultaneously did not bring any benefit over updating soil moisture only. Our results further indicate that streamflow estimates can be improved through Sentinel-1 DA in a catchment with strong soil moisture–runoff coupling, as observed for the Ourthe catchment, suggesting that there is potential for Sentinel-1 DA even for forested catchments. Significance Statement The purpose of this study is to improve streamflow estimation by integrating soil moisture information from satellite observations into a hydrological modeling framework. This is important preparatory work for operational centers that are responsible for producing the most accurate flood forecasts for the society. Our results provide new insights into how and where streamflow forecasting could benefit from high-spatial-resolution Sentinel-1 radar backscatter observations.

The ecohydrological response to soil moisture based on the distributed hydrological assimilation model in the mountain region

AbstractIn the mountain region, there is high spatial variability of soil moisture, which limited soil moisture sites may not express. Data assimilation methods can combine the advantages of model simulation and data observation. This study constructs the distribution of soil moisture based on the distributed hydrological assimilation model and explores the ecohydrological response to soil moisture in the mountain region. The relationship between the coefficient of variation and mean soil moisture shows a hysteresis pattern. The terrain conditions where high soil moisture occurs in the study area are an altitude of about 3500 m, a gentle slope, and a shady slope. The low value of soil moisture is characterized by banded aggregation distribution. There is an initial threshold for the contribution of soil moisture to watershed runoff, and the threshold value in the study area of this paper is 0.28 cm3/cm3. The regions with dense vegetation exhibit higher spatial variability in soil moisture. Vegetation plays a heterogeneous role in the spatial variability of soil moisture when precipitation events occur. The study contributes to a deeper understanding of ecohydrological processes by providing regional‐scale data and uncovering the relationships between soil moisture and various ecohydrological factors.

A copula-based parametric composite drought index for drought monitoring and applicability in arid Central Asia

Due to the complexity of meteorological and hydrological conditions in a changing environment, previous drought indices for monitoring a specific drought type do not reflect the overall regional situation of water scarcity. Therefore, in order to obtain accurate and reliable drought monitoring, a more integrated drought index should be developed to identify drought events comprehensively. In this paper, a non-linear trivariate drought index (NTDI) was constructed based on the joint probability distribution of parametric copulas, combining precipitation (P), potential evapotranspiration (PET), and root zone soil moisture (SM) variables. Subsequently, it was respectively compared with four drought indices, SPEI, SSMI, SC-PDSI and TVDI, and cross-validated with actual recorded drought events and annual crop yield to evaluate its applicability in arid Central Asia (ACA). The results indicated that: (1) Frank copula (1-,3-month scale) and Gumbel copula (6-,12-month scale) were considered to be the best-fitted copula functions for constructing joint probability distributions in the ACA. (2) The NTDI integrated the P-PET and SM drought signals to sensitively capture drought onset and duration, reflecting the combined characteristics of meteorological and agricultural drought. (3) The drought information expressed by NTDI was generally consistent with recorded drought events, and the monitoring results are accurate. (4)The NTDI performed better in agricultural drought monitoring than other drought indices. This study provides a reliable multivariate composite indicator which is significant for drought monitoring, prevention and risk assessment in ACA.

Envisioning urban environments resilient to vector-borne diseases: a protocol to study dengue in Vietnam

Transmitted primarily by Aedes aegypti (Ae. aegypti) and Aedes albopictus (Ae. albopictus), arboviral diseases pose a major global public health threat. Dengue, chikungunya, and Zika are increasingly prevalent in Southeast Asia. Among other arboviruses, dengue and Zika are becoming more common in Central and South America. Given human encroachment into previously uninhabited, often deforested areas, to provide new housing in regions of population expansion, conceptualizing built urban environments in a novel way is urgently needed to safeguard against the growing climate change-driven threat of vector-borne diseases. By understanding the spread from a One Health perspective, enhanced control and prevention can be achieved. This is particularly important considering that climate change is likely to significantly impact the persistence of ponded water where mosquitoes breed due to increasing temperature and shifting rainfall patterns with regard to magnitude, duration, frequency, and season. Models can incorporate aquatic mosquito stages and adult spatial dynamics when habitats are heterogeneously available, thereby including dispersal and susceptible-exposed-infected-recovered (SEIR) epidemiology. Coupled with human population distribution (density, locations), atmospheric conditions (air temperature, precipitation), and hydrological conditions (soil moisture distribution, ponding persistence in topographic depressions), modeling has improved predictive ability for infection rates. However, it has not informed interventional approaches from an urban environment perspective which considers the role of ponds/lakes that support green spaces, the density of population that enables rapid spread of disease, and varying micro-habitats for various mosquito stages under climate change. Here, for an example of dengue in Vietnam, a preventive and predictive approach to design resilient urban environments is proposed, which uses data from rapidly expanding metropolitan communities to learn continually. This protocol deploys computational approaches including simulation and machine learning/artificial intelligence, underpinned by surveillance and medical data for validation and adaptive learning. Its application may best inform urban planning in low-middle income countries in tropical zones where arboviral pathogens are prevalent.

Soil Moisture, Nutrients, Root Distribution, and Crop Combination Benefits at Different Water and Fertilizer Levels during the Crop Replacement Period in an Apple Intercropping System

Uneven soil moisture and nutrient distribution before and after intercropping limits apple cropping system productivity in the western Shanxi–Loess Plateau area. To address this issue, a field trial was conducted between 2020 and 2021 to study the effects of different water and fertilizer management practices on soil moisture, nutrients, and root distribution, as well as the overall effectiveness of the apple–maize and apple–soybean intercropping systems during crop replacement. The experiment involved two irrigation methods: drip (D) and flood (M) irrigation. Three irrigation levels included rain-fed without irrigation (W0), and 50% (W1) and 80% (W2) of field capacity (Fc). Three fertilizer treatments included no additional fertilizer application (F0), 375 kg∙hm−2 (F1), and 750 kg∙hm−2 (F2), in addition to a control (CK) without irrigation or fertilization. The soil water content (SWC) decreased after the crop replacement. Additionally, nitrate nitrogen (NN), ammonium nitrogen (AN), and organic matter (OM) content levels in all treatments increased, whereas total phosphorus (TP) content decreased. The soil layer with crop roots moved downward after crop replacement, and partial fertilizer productivity (PFP), irrigation water use efficiency (IWUE), and water use efficiency (WUE) were decreased under both irrigation treatments. Principal component analysis showed that the W2F2 treatment had the highest benefit from crop combination across both irrigation treatments during the crop replacement period. According to our results, to optimize the benefits of apple-crop intercropping, drip irrigation with complete water supply and flood irrigation with incomplete water supply are recommended during crop replacement. In addition, an upper irrigation limit of 80% Fc with 750 kg∙hm−2 fertilization is recommended for optimal water and fertilizer regulation.

A Review of Earth’s Surface Soil Moisture Retrieval Models via Remote Sensing

Soil moisture is essential parameter in the Earth’s surface. The information provided by soil moisture plays a vital role in agricultural production, eco-environmental protection, water and land resources management, etc. Meanwhile, the accurate monitoring of the spatial and temporal distribution of soil moisture is of great significance for the engineering geological assessment and geological disaster prevention. Monitoring and retrieving soil moisture via remote sensing data and mathematical models are the main research methods at present and the crucial issue is how to eliminate the influence of other surface and soil parameters like roughness and soil bulk density, and the interference of vegetated areas to electromagnetic waves. Nowadays, many branches of retrieval methods have been developed, and researchers are integrating multiple models to improve the retrieval accuracy. This paper summarizes the present research status and progress of soil moisture retrieval via remote sensing based on four kinds of models: empirical model, semi-empirical model, physical model, and machine learning. The soil moisture products are summarized and listed at the same time. The difficulties and issues in the present research are discussed and the future outlook is explored.

Effect of Partial Drip Irrigation Methods on Soil Moisture and Water Potential Distribution, Growth Characteristics and Yield of Maize

A field experiment was conducted during the autumn of 2021 at the Agricultural Research Department station / Abu Ghraib to evaluate the soil moisture, water potential distribution, and growth factors of maize crops under alternating and constant partial drip irrigation methods. In the experiment, two irrigation systems were used, surface drip irrigation (DI) and subsurface irrigation (SD); under each irrigation system, five irrigation methods were: conventional irrigation (CI), and 75 and 50% of the amount of water of CI of each of the alternating partial irrigation APRI75 and APRI50 and the constant partial irrigation FPRI75 and FPRI50 respectively. The results showed that the water depth for conventional irrigation (C1) was 658.3 and 579.4 mm for the DI and SD irrigation systems, respectively, and the irrigation depth was reduced to 18% when applied APRI75 and FPRI75 and 37% when applied APRI50 and FPRI50 respectively. The moisture distribution differed according to the irrigation method, and the SD provided a higher moisture content and lower water potential due to the lower evaporation rate from the soil surface. Also, the growth traits of maize varied according to the irrigation system and its methods. The SD system was significantly superior in the grain yield of maize with an increase of 5.4% compared with DI, and the alternating partial irrigation treatments were significantly superior to the constant partial irrigation. Keywords: Matric suction, Zea mays L., irrigation system, irrigation depth.

Soil Moisture Distribution and Time Stability of Aerially Sown Shrubland in the Northeastern Margin of Tengger Desert (China)

Considering the importance of soil moisture in hydrological processes, it is crucial to understand the water distribution and time stability of different aerial shrub soils. There are few studies on the soil moisture of aerial vegetation in the northeastern margin of the Tengger Desert. Based on long-term monitoring data from the aerial seeding area in the northeastern margin of the Tengger Desert, the distribution characteristics of soil moisture and the temporal stability of soil moisture were studied. From June to October 2022, the soil moisture monitoring instrument WatchDog was used to monitor the long-term soil moisture changes (0–200 cm) in the four aerial afforestation plots of Hedysarum scoparium, mixed forest land (Hedysarum scoparium dominant species), mixed forest land (Calligonum mongolicum dominant species), and Calligonum mongolicum. The Spearman rank correlation coefficient was used to study the temporal stability of soil moisture in the four plots. Rainfall data were collected through small weather stations. The results show that the average soil water storage of four kinds of aerial shrub land in the study area was the highest in August, and the average soil water storage of different forest lands was different. The soil water content of the surface layer (0–30 cm) fluctuated the most in different months. The variation in soil water content in the shallow layer (30–100 cm) was smaller than that in the surface layer. The fluctuation of soil water content in the middle layer (100–150 cm) and deep layer (150–200 cm) was relatively stable. There was no strong variability in soil moisture content, and the temporal variation coefficient of surface soil moisture was the highest (31.44–39.8%), which showed moderate variability. The temporal variation coefficient of soil moisture in the shallow, middle and deep layers of all kinds of plots was significantly reduced, and the soil moisture stability of different aerial shrub land was the same. Spearman rank correlation analysis showed that the spatial pattern of soil water content in the surface layer (0–30 cm) and deep layer (150–200 cm) was more stable over time, that is, the temporal stability of soil water content was higher, and the temporal stability of soil water content in the middle and shallow layers of different types of shrub land was different. The research results help us to understand the soil hydrological process in the aerial seeding afforestation area in the northeastern margin of Tengger Desert, rationally arrange soil moisture monitoring points, efficiently manage and utilize water resources in the aerial seeding area, and provide a theoretical basis for local vegetation restoration and the optimization of the ecological environment.

The analysis of fire hotspot distribution in Kalimantan and its relation- ship with ENSO phases

Kalimantan experiences fire hazards almost every year, which threaten the largest tropical forest in South- east Asia. Climatic conditions, such as increasing surface temperature and decreasing rainfall, become important es- pecially when El Nino Southern Oscillation (ENSO) occurs. Studies on fire are commonly conducted based on the climatic condition such as the dry or wet season, but those which focused on analysis of fire occurrences with the specific ENSO phases are still limited. This study aims to identify the spatial and temporal distribution of rainfall, land surface temperature, and soil moisture and analyses the distribution of hotspots in Kalimantan from 2014 to 2020 dur- ing different ENSO phases. The data used are Moderate Resolution Imaging Spectroradiometer (MODIS) for hotspot analysis, Global Precipitation Measurement (GPM) for rainfall analysis, MODIS Land Surface Temperature (LST) for surface temperature analysis and Soil Moisture Active Passive (SMAP) for soil moisture analysis. The methods used were descriptive and spatial analyses based on each ENSO phase, which were then combined to analyse the temporal and spatial distribution of fire, rainfall, LST and soil moisture. The temporal distribution shows a positive relationship between ENSO, rainfall, LST, soil moisture and hotspots with a confidence level of 90% in the dry months of August– October. Fire occurred in most parts of West and Central Kalimantan, associated with low elevation, organic soil types and agricultural peatland. The average trend of increasing hotspots is 17.4% in the El Nino phase and decreasing hot- spots by 84.7% in the La Nina phase during August–October in Kalimantan.

Spatial and Temporal Variations in Soil Moisture for a Tamarisk Stand under Groundwater Control in a Hyper-Arid Region

In hyper-arid regions, soil moisture’s role in ecohydrological processes can differ significantly from that in arid or semi-arid ecosystems. We investigated the spatial–temporal dynamics of soil moisture and its relationship with groundwater depths in a 200 m × 300 m phreatophytic tamarisk stand in the lower basin of the Tarim River, a hyper-arid zone in China. Soil moisture profiles, from the surface to the water table, were derived using drilling and oven-drying techniques. Over a three-year period, the soil moisture at multiple depths was continuously monitored in a specific plot using nine frequency domain reflectometry (FDR) sensors. Our results indicate a correlation between horizontal variations in soil moisture and groundwater depths (GWDs). Nevertheless, anomalies in this correlation were observed. Variations in horizontal soil moisture were strongly influenced by the clay content in the soil, with finer soils retaining more moisture. Despite varying GWDs, soil moisture profiles remained consistent, with no distinct correlation between them. Soil moisture exhibited stability across layers, with noticeable changes only adjacent to the water table. These results imply that in hyper-arid environments, soil texture primarily governs soil moisture distribution. However, the limited spatial and temporal scopes in our dataset, constrained by the region’s inhospitable conditions, necessitate further investigation. Future work should prioritize amalgamating diverse data sources to devise a region-specific soil moisture model for in-depth analysis of hyper-arid regions.

Response of NPK Fertilization and Irrigation in Nutrient and Soil Moisture Distribution Under High-Density Apple Plantation in the NW Himalayan Region

ABSTRACT Drip fertigation provides enormous opportunities for the effective utilization and distribution of water and nutrients in sustainable management of orchard. Under various drip irrigation and fertigation schedules, the analysis of NO3 −-N and NH4 +-N distribution within the soil has been found to be efficacious to enhance the crop growth. Over the 2-year period of study (2019 and 2020), the response of NPK fertilization and irrigation in nutrient and soil moisture distribution under high-density apple plantation in the NW Himalayan region was investigated. In the present study, under drip irrigation, the wetting front extended up to 45 cm horizontally from the emitter; however, the maximum increase in soil moisture content remained confined near the emitting point. The soil moisture content decreased consistently with the increasing horizontal distance from the emitter. Drip irrigation recorded a higher soil moisture content at the surface soil depth of 0–15 cm compared to conventional surface irrigation, where the sub-surface soil depths of 15–30 cm registered a higher moisture content. The distribution of NO3 −-N and NH4 +-N content under drip fertigation nearly followed the soil moisture distribution pattern. The NO3 −-N and NH4 +-N content was maximum below the emitter and decreased thereafter with the increasing lateral distance from the emitter as nutrient mobility in soil is primarily governed by water movement. The decreasing trend of NO3 −-N and NH4 +-N with the increasing lateral distances is in accordance with the water distribution pattern under drip irrigation. The nutrient mobility is proved to be well pronounced under the drip fertigation system, and nutrients carried along with the water movement get concentrated near the outer periphery of the wetting zone.

Prediction of the Soil–Water Retention Curve of Loess Using the Pore Data from the Mercury Intrusion Technique

The soil–water characteristic curve (SWCC) is a crucial input parameter for describing the distribution of soil moisture and water movement in various environmental and geotechnical challenges. It is widely recognized that the SWCC is controlled by the soil’s pore structure. Attempts to estimate the SWCC using pore data obtained through the mercury intrusion porosity (MIP) technique have been conducted. However, the performance of MIP estimation remains uncertain and requires further validation with experimental data. In this study, the accuracy of MIP estimation is validated using intact and compacted loess samples prepared at different water contents, specifically dry of optimum (8%), optimum (17%), and wet of optimum (19%). The results reveal that intact and dry of optimum specimens exhibit relatively good pore connectivity, with more point-to-point contacts between particles. Conversely, specimens compacted under optimum and wet of optimum conditions exhibit poor pore connectivity, with more isolated pores, particularly in the wet-of-optimum specimen. The SWCC predictions based on MIP data are accurate for intact and dry-of-optimum compacted specimens, but significant errors occur for the optimum and wet-of-optimum specimens. Prediction accuracy using MIP data is closely linked to the soil’s pore connectivity. Despite a tenuous theoretical basis in the high suction range where adsorption forces dominate, a strong consistency between predictions and measured data across a wide suction range (e.g., 10–104 kPa) instills a high level of confidence in using MIP data to predict the wetting SWCC. The contact angle required for the prediction is suggested as a fitting parameter.

Coupling effects of soil organic carbon and moisture under different land use types, seasons and slope positions in the Loess Plateau

Understanding the response of soil organic carbon (SOC) and moisture to different land-use types, slope positions, seasonal variations, and their interactions has great significance for land use and management. However, the coupling effects of SOC and soil moisture in typical hilly and gully regions are still elusive. Therefore, in this study, five different land-use types, including cropland, abandoned land, grassland, shrubland, and forestland were selected in a typical Chinese loess hilly-gully region, and soil samples were collected from 0 to 200 cm profiles at the upper, middle, and lower slope positions in four seasons. The results demonstrated that the distributions of SOC and soil moisture were jointly significantly affected by land-use types, seasons, and slope positions (P < 0.01). Average SOC content was found to be highest in the shrubland, followed by grassland, abandoned land, forestland, and cropland. SOC storage at the lower slope position was 10.97% higher than that at the upper slope position. SOC storage in winter was 45.47% higher than that in summer. SOC storages of abandoned land, grassland, shrubland, and forestland were 17.38%, 33.08%, 52.52% and 1.26% more than that of cropland, respectively. Soil moisture fluctuated greatly in 0–100 cm layers and was stable beneath the 100 cm layers, which was highest in autumn, and lowest in summer. Whereas, under different land-use types, the soil moisture of cropland was the highest, especially significantly higher than all revegetated treatments in the 60–200 cm soil layers. Compared with cropland, soil water storage at other land-use types was averagely 36.45 % lower in the entire 200 cm soil profile. SOC was positively correlated with soil moisture under different factors. Thus, we recommend planting shrub and grass in watersheds with serious soil erosion in the semi-arid hilly and gully region, because they can sequestrate more SOC and retain more soil water.

Modeling of soil moisture movement and wetting behavior under point-source trickle irrigation

The design and selection of ideal emitter discharge rates can be aided by accurate information regarding the wetted soil pattern under surface drip irrigation. The current field investigation was conducted in an apple orchard in SKUAST- Kashmir, Jammu and Kashmir, a Union Territory of India, during 2017–2019. The objective of the experiment was to examine the movement of moisture over time and assess the extent of wetting in both horizontal and vertical directions under point source drip irrigation with discharge rates of 2, 4, and 8 L h−1. At 30, 60, and 120 min since the beginning of irrigation, a soil pit was dug across the length of the wetted area on the surface in order to measure the wetting pattern. For measuring the soil moisture movement and wetted soil width and depth, three replicas of soil samples were collected according to the treatment and the average value were considered. As a result, 54 different experiments were conducted, resulting in the digging of pits [3 emitter discharge rates × 3 application times × 3 replications × 2 (after application and 24 after application)]. This study utilized the Drip-Irriwater model to evaluate and validate the accuracy of predictions of wetting fronts and soil moisture dynamics in both orientations. Results showed that the modeled values were very close to the actual field values, with a mean absolute error of 0.018, a mean bias error of 0.0005, a mean absolute percentage error of 7.3, a root mean square error of 0.023, a Pearson coefficient of 0.951, a coefficient of correlation of 0.918, and a Nash–Sutcliffe model efficiency coefficient of 0.887. The wetted width just after irrigation was measured at 14.65, 16.65, and 20.62 cm; 16.20, 20.25, and 23.90 cm; and 20.00, 24.50, and 28.81 cm in 2, 4, and 8 L h−1, at 30, 60, and 120 min, respectively, while the wetted depth was observed 13.10, 16.20, and 20.44 cm; 15.10, 21.50, and 26.00 cm; 19.40, 25.00, and 31.00 cm, respectively. As the flow rate from the emitter increased, the amount of moisture dissemination grew (both immediately and 24 h after irrigation). The soil moisture contents were observed 0.4300, 0.3808, 0.2298, 0.1604, and 0.1600 cm3 cm−3 just after irrigation in 2 L h−1 while 0.4300, 0.3841, 0.2385, 0.1607, and 0.1600 cm3 cm−3 were in 4 L h−1 and 0.4300, 0.3852, 0.2417, 0.1608, and 0.1600 cm3 cm−3 were in 8 L h−1 at 5, 10, 15, 20, and 25 cm soil depth in 30 min of application time. Similar distinct increments were found in 60, and 120 min of irrigation. The findings suggest that this simple model, which only requires soil, irrigation, and simulation parameters, is a valuable and practical tool for irrigation design. It provides information on soil wetting patterns and soil moisture distribution under a single emitter, which is important for effectively planning and designing a drip irrigation system. Investigating soil wetting patterns and moisture redistribution in the soil profile under point source drip irrigation helps promote efficient planning and design of a drip irrigation system.

Long-Term Characteristics of Surface Soil Moisture over the Tibetan Plateau and Its Response to Climate Change

Soil moisture over the Tibetan Plateau (TP) can affect hydrological cycles on local and remote scales through land–atmosphere interactions. However, TP long-term surface soil moisture characteristics and their response to climate change are still unclear. In this study, we firstly evaluate two satellite-based products—SSM/I (the Special Sensor Microwave Imagers) and ECV COMBINED (the Essential Climate Variable combined)—and three reanalysis products—ERA5-Land (the fifth generation of the land component of the European Centre for Medium-Range Weather Forecasts atmospheric reanalysis), MERRA2 (the second version of Modern-Era Retrospective Analysis for Research and Applications), and GLDAS Noah (the Noah land surface model driven by Global Land Data Assimilation System)—against two in situ observation networks. SSM/I and GLDAS Noah outperform the other soil moisture products, followed by MERRA2 and ECV COMBINED, and ERA5-Land has a certain degree of uncertainty in evaluating TP surface soil moisture. Analysis of long-term soil moisture characteristics during 1988–2008 shows that annual and seasonal mean soil moisture have similar spatial distributions of soil moisture decreasing from southeast to northwest. Additionally, a significant increasing trend of soil moisture is found in most of the TP region. With a non-linear machine learning method, we quantify the contribution of each climatic variable to warm-season soil moisture. It indicates that precipitation dominates soil moisture changes rather than air temperature. Pixel-wise partial correlation coefficients further show that there are significant positive correlations between precipitation and soil moisture over most of the TP region. The results of this study will help to understand the role of TP soil moisture in land–atmosphere coupling and hydrological cycles under climate change.

Improved understanding of vegetation dynamics and wetland ecohydrology via monthly UAV‐based classification

AbstractVegetation classification is an essential prerequisite for understanding vegetation‐water relations at a range of spatial scales. However, in site‐specific applications, such classifications were mostly based on a single Unmanned Aerial Vehicle (UAV) flight, which can be challenging in grasslands and/or herbaceous‐dominated systems, as those communities are small in size and highly mixed. Here, we conducted monthly UAV flights for two years in a riparian wetland in Germany, with acquired imagery used for vegetation classification on a monthly basis under different strategies (with or without auxiliary information from other flights) to increase understanding in ecohydrology. The results show that multi‐flight‐based classification outperformed single‐flight‐based classification due to the higher classification accuracy. Moreover, improved sensitivity of temporal changes in community distribution highlights the benefits of multi‐flight‐based classification ‐ providing a more comprehensive picture of community evolution. From reference to the monthly community distribution, we argue that a combination of two or three flights in early‐ and late‐summer is enough to achieve comparable results to monthly flights, while mid‐summer would be a better timing in case only one flight is scheduled. With such detailed vegetation mapping, we further interpreted the complex spatio‐temporal heterogeneity in NDVI and explored the dominant areas and developmental progress of each community. Impacts from management (mowing events) were also evaluated based on the different responses between communities in two years. Finally, we explored how such vegetation mapping could help understand landscape ecohydrology, and found that the spatio‐temporal distribution of minimal soil moisture was related to NDVI peaks of local community, while grass distribution was explained by both topography and low moisture conditions. Such bi‐directional relationships proved that apart from contributing to an evidence base for wetland management, multi‐flight UAV vegetation mapping could also provide fundamental insights into the ecohydrology of wetlands.