Ground, Proximal, and Satellite Remote Sensing of Soil Moisture

Soil moisture (SM) is a key hydrologic state variable that is of significant importance for numerous Earth and environmental science applications that directly impact the global environment and human society. Potential applications include, but are not limited to, forecasting of weather and climate variability; prediction and monitoring of drought conditions; management and allocation of water resources; agricultural plant production and alleviation of famine; prevention of natural disasters such as wild fires, landslides, floods, and dust storms; or monitoring of ecosystem response to climate change. Because of the importance and wide‐ranging applicability of highly variable spatial and temporal SM information that links the water, energy, and carbon cycles, significant efforts and resources have been devoted in recent years to advance SM measurement and monitoring capabilities from the point to the global scales. This review encompasses recent advances and the state‐of‐the‐art of ground, proximal, and novel SM remote sensing techniques at various spatial and temporal scales and identifies critical future research needs and directions to further advance and optimize technology, analysis and retrieval methods, and the application of SM information to improve the understanding of critical zone moisture dynamics. Despite the impressive progress over the last decade, there are still many opportunities and needs to, for example, improve SM retrieval from remotely sensed optical, thermal, and microwave data and opportunities for novel applications of SM information for water resources management, sustainable environmental development, and food security

Using Cosmic-Ray Neutron Probes to Monitor Landscape Scale Soil Water Content in Mixed Land Use Agricultural Systems

With an ever-increasing demand for natural resources and the societal need to understand and predict natural disasters, soil water content (SWC) observations remain a critical variable to monitor in order to optimally allocate resources, establish early warning systems, and improve weather forecasts.However, routine agricultural production practices of soil cultivation, planting, and harvest make the operation andmaintenance of direct contact point sensors for long-termmonitoring challenging. In this work, we explore the use of the newly established Cosmic-Ray Neutron Probe (CRNP) and method to monitor landscape average SWC in a mixed agricultural land use systemin northeastAustria.Thecalibrated CRNP landscape SWC values compare well against an independent in situ SWC probe network (MAE = 0.0286m3/m3) given the challenge of continuous in situ monitoring from probes across a heterogeneous agricultural landscape. The ability of the CRNP to provide real-time and accurate landscape SWC measurements makes it an ideal method for establishing long-term monitoring sites in agricultural ecosystems to aid in agricultural water and nutrient management decisions at the small tract of land scale as well as aiding in management decisions at larger scales

Multi-product characterization of surface soil moisture drydowns in the UK

The persistence or memory of soil moisture (θ) after rainfall has substantial environmental implications. Much work has been done to study soil moisture drydown for in-situ and satellite data separately. In this work, we present a comparison of drydown characteristics across multiple UK soil moisture products, including satellite-merged (i.e. TCM), in-situ (i.e. COSMOS-UK), hydrological model (i.e. G2G), statistical model (i.e. SMUK) and land surface model (LSM) (i.e. CHESS) data. The drydown decay time scale (τ) for all gridded products are computed at an unprecedented resolution of 1-2 km, a scale relevant to weather and climate models. While their range of τ differ (except SMUK and CHESS are similar) due to differences such as sensing depths, their spatial patterns are correlated to land cover and soil types. We further analyse the occurrence of drydown events at COSMOS-UK sites. We show that soil moisture drydown regimes exhibit strong seasonal dependencies, whereby the soil dries out quicker in summer than winter. These seasonal dependencies are important to consider during model benchmarking and evaluation. We show that fitted τ based on COSMOS and LSM are well correlated, with a bias of lower τ for COSMOS. Our findings contribute to a growing body of literature to characterize τ, with the aim of developing a method to systematically validate model soil moisture products at a range of scales

Investigation of tempospatial variability of soil moisture in Ås, Norway

Accurate measurements of soil moisture are necessary for predicting weather patterns, mitigating floods and droughts, estimating precipitation and evapotranspiration, and calculating energy fluxes between the biosphere and the atmosphere. However, soil moisture variability is influenced by environmental conditions such as precipitation, soil properties, topography, temperature and vegetation cover. As part of the Hydrometeorology to Operations (H2O) project by the Norwegian Meteorological Institute, this study aims to investigate the temporal and spatial variability of soil moisture at Søråsfeltet in Ås, and to compare the effectiveness of satellite measurements to ground-based sensors. Both ground-based and remote sensing methods were used to measure soil moisture, including the GroPoint Profile (SMIoT), SoilVUE10, COsmic-ray Soil Moisture Observing System (COSMOS), ThetaProbe ML2 (ADR), in addition to manual samples using the volumetric method, as well as data from the Sentinel-1 satellite. The data was collected from January to December 2022 at three locations in Ås with Søråsjordet as the main focus area. The results showed significant temporal and vertical spatial variability of soil moisture. While ground-based sensors responded well to precipitation and provided reasonable soil moisture ranges, measurements from the Sentinel-1 satellite did not capture the same variability and its usage is not recommended. The ground truth data lies between the measurements of COSMOS and SoilVUE sensors, suggesting they provide a more accurate representation of surface soil moisture than the SMIoT sensors. However, the SoilVUE sensor experienced a malfunction or data transfer issue, resulting in incorrect data for soil moisture at depths of 10 and 50 cm. The shallow soil moisture layers of the SMIoT and SoilVUE sensors exhibited more significant fluctuations than the deeper layers, consistent with the faster response of shallow soil layers to meteorological events. The overall trend suggests lower vertical and horizontal spatial variability when the soil is close to or at its saturation point. The SoilVUE sensor consistently reported lower values than other in-situ sensors, but it showed an overestimation during heavy precipitation. A likely reason is poor contact with the soil due to the hysteresis effect of the soil's expansion/contraction characteristics, which resulted in air gaps after several wetting and drying cycles. This led to preferential flow during precipitation and poor soil contact during dry periods. This study made several specific contributions to the understanding of soil moisture measurement in Ås: first, it compared various soil moisture sensors; second, it identified malfunctions in the SoilVUE sensor at Søråsfeltet; third, it contributed to the verification process for relocating a SMIoT sensor by discovering a drainage pipe that was affecting measurements in its original location; and fourth, it determined that satellite measurements are not appropriate for this region

A global atmospheric electricity monitoring network for climate and geophysical research

The Global atmospheric Electric Circuit (GEC) is a fundamental coupling network of the climate system connecting electrically disturbed weather regions with fair weather regions across the planet. The GEC sustains the fair weather electric field (or potential gradient, PG) which is present globally and can be measured routinely at the surface using durable instrumentation such as modern electric field mills, which are now widely deployed internationally. In contrast to lightning or magnetic fields, fair weather PG cannot be measured remotely. Despite the existence of many PG datasets (both contemporary and historical), few attempts have been made to coordinate and integrate these fragmented surface measurements within a global framework. Such a synthesis is important elvinin order to fully study major influences on the GEC such as climate variations and space weather effects, as well as more local atmospheric electrical processes such as cloud electrification, lightning initiation, and dust and aerosol charging. The GloCAEM (Global Coordination of Atmospheric Electricity Measurements) project has brought together experts in atmospheric electricity to make the first steps towards an effective global network for atmospheric electricity monitoring, which will provide data in near real time. Data from all sites are available in identically-formatted files, at both one second and one minute temporal resolution, along with meteorological data (wherever available) for ease of interpretation of electrical measurements. This work describes the details of the GloCAEM database and presents what is likely to be the largest single analysis of PG data performed from multiple datasets at geographically distinct locations. Analysis of the diurnal variation in PG from all 17 GloCAEM sites demonstrates that the majority of sites show two daily maxima, characteristic of local influences on the PG, such as the sunrise effect. Data analysis methods to minimise such effects are presented and recommendations provided on the most suitable GloCAEM sites for the study of various scientific phenomena. The use of the dataset for a further understanding of the GEC is also demonstrated, in particular for more detailed characterization of day-to-day global circuit variability. Such coordinated effort enables deeper insight into PG phenomenology which goes beyond single-location PG measurements, providing a simple measurement of global thunderstorm variability on a day-to-day timescale. The creation of the GloCAEM database is likely to enable much more effective study of atmospheric electricity variables than has ever been possible before, which will improve our understanding of the role of atmospheric electricity in the complex processes underlying weather and climate

Neutron monitors and muon detectors for solar modulation studies: Interstellar flux, yield function, and assessment of critical parameters in count rate calculations

Particles count rates at given Earth location and altitude result from the convolution of (i) the interstellar (IS) cosmic-ray fluxes outside the solar cavity, (ii) the time-dependent modulation of IS into Top-of-Atmosphere (TOA) fluxes, (iii) the rigidity cut-off (or geomagnetic transmission function) and grammage at the counter location, (iv) the atmosphere response to incoming TOA cosmic rays (shower development), and (v) the counter response to the various particles/energies in the shower. Count rates from neutron monitors or muon counters are therefore a proxy to solar activity. In this paper, we review all ingredients, discuss how their uncertainties impact count rate calculations, and how they translate into variation/uncertainties on the level of solar modulation $\varphi$ (in the simple Force-Field approximation). The main uncertainty for neutron monitors is related to the yield function. However, many other effects have a significant impact, at the 5-10\% level on $\varphi$ values. We find no clear ranking of the dominant effects, as some depend on the station position and/or the weather and/or the season. An abacus to translate any variation of count rates (for neutron and $\mu$ detectors) to a variation of the solar modulation $\varphi$ is provided.Comment: 28 pages, 16 figures, 9 tables, match accepted version in AdSR (minor corrections, Dorman (1974,2004,2009) reference textbooks added