Total evaporation estimation for accurate water accounting purposes: an appraisal of various available estimation methods

The estimation of total evaporation is fundamental for water accounting, considering its influence on water availability. Moreover, the current increase in water consumption (e.g. in sub-Saharan Africa and the world over), land cover/use changes, deteriorating water quality and the climate change projections in most regions of the world underscore the need to understand water loss. So far, different approaches have been developed and implemented in estimating the variations of total evaporation, with varying accuracies. The aim of this work was therefore, to provide a review of these different approaches for estimating total evaporation, as well as a detailed discussion of their strengths and weaknesses. Findings from this review have shown that total evaporation estimates derived, using ground-based meteorological and micro-meteorological methods are inadequate for representing its large-scale spatial variations. On the other hand, remote sensing technology, which acquires data at different resolutions (i.e. radiometric, spectral, spatial and temporal), provides timely, up-to-date and relatively accurate spatial estimates of total evaporation over large geographic coverage, for sustainable and effective water accounting, which is key for well-informed and improved management of water resources at both catchment and regional scales. In this regard, more details on the remote sensing-based methods of estimating total evaporation are provided, especially considering the robust technological advancements and its potential in characterizing earth features over time and space. This work has also managed to identify research gaps and challenges in the accurate estimation of total evaporation, using remote sensing, especially with the emergence of more advanced sensors and the characteristics of the landscape.     

Combined Digital Photogrammetry and Time-of-Flight Laser Scanning for Monitoring Cliff Evolution

Although cliffs form approximately 75% of the world's coastline, the understanding of the processes through which they evolve remains limited because of a lack of quantitative data on the morphological changes they undergo. In this paper the combination of terrestrial time-of-flight laser scanning with high-resolution digital photogrammetry is examined to generate high-quality data-sets pertaining to the geomorphic processes governing cliff development. The study was undertaken on a section of hard rock cliffs in North Yorkshire, UK, which has been monitored over a 12-month period. High-density, laser-scanned point clouds have been used to produce an accurate representation of these complex surfaces, free from the optical variations that degrade photographic data. These data-sets have been combined with high-resolution photographic monitoring, resampled with the fixed accuracies of the terrestrial laser survey, to generate a new approach to recording the volumetric changes in complex coastal cliffs. This has led to significant improvements in the understanding of the activity patterns of coastal cliffs.     

Spatially explicit models for exploring COVID‐19 lockdown strategies

This article describes two spatially explicit models created to allow experimentation with different societal responses to the COVID‐19 pandemic. We outline the work to date on modeling spatially explicit infective diseases and show that there are gaps that remain important to fill. We demonstrate how geographical regions, rather than a single, national approach, are likely to lead to better outcomes for the population. We provide a full account of how our models function, and how they can be used to explore many different aspects of contagion, including: experimenting with different lockdown measures, with connectivity between places, with the tracing of disease clusters, and the use of improved contact tracing and isolation. We provide comprehensive results showing the use of these models in given scenarios, and conclude that explicitly regionalized models for mitigation provide significant advantages over a “one‐size‐fits‐all” approach. We have made our models, and their data, publicly available for others to use in their own locales, with the hope of providing the tools needed for geographers to have a voice during this difficult time.     

Precipitation variability during the past 400?years in the Xiaolong Mountain (central China) inferred from tree rings

We developed the first tree-ring chronology, based on 73 cores from 29 Pinus tabulaeformis trees, for the Xiaolong Mountain area of central China, a region at the boundary of the Asian summer monsoon. This chronology exhibits significant (at 0.01 level) positive correlations with precipitation in May and June, and negative correlations with temperature in May, June and July. Highest linear correlation is observed between tree growth and the seasonalized (April–July) precipitation, suggesting that tree rings tend to integrate the monthly precipitation signals. Accordingly, the April–July total precipitation was reconstructed back to 1629 using these tree rings, explaining 44.7?% of the instrumental variance. A severe drought occurred in the area during the 1630s–1640s, which may be related to the weakened Asian summer monsoon caused by a low land-sea thermal gradient. The dry epoch during the 1920s–1930s and since the late 1970s may be explained by the strengthened Hadley circulation in a warmer climate. The dry (wet) epochs of the 1920s–1930s (the 1750s and 1950s) occurred during the warm (cold) phases of the El Ni?o-Southern Oscillation and the Pacific Decadal Oscillation that are often associated with weakened (strengthened) East Asian summer monsoon. These relationships indicate significant teleconnections operating over the past centuries in central China related to large-scale synoptic features.     

A Case Study on the Effects of Heterogeneous Soil Moisture on Mesoscale Boundary-Layer Structure in the Southern Great Plains, U.S.A. Part II: Mesoscale Modelling

The importance of soil moisture inputs and improved model physics in the prediction of the daytime boundary-layer structure during the Southern Great Plains Hydrology Experiment 1997 (SGP97) is investigated using the non-hydrostatic fifth-generation Pennsylvania State University/National Center for Atmospheric Research (PSU/NCAR) Mesoscale Model MM5. This is Part II of a two-part study examining the relationship of surface heterogeneity to observed boundary-layer structure. Part I focuses on observations and utilizes a simple model while Part II uses observations and MM5 modelling. Soil moisture inputs tested include a lookup table based on soil type and season, output from an offline land-surface model (LSM) forced by atmospheric observations, and high-resolution ( 800 m) airborne microwave remotely sensed data. Model physics improvements are investigated by comparing an LSM directly coupled with the MM5 to a simpler force-restore method at the surface. The scale of land surface heterogeneities is compared to the scale of their effects on boundary-layer structure.The use of more detailed soil moisture fields allowed the MM5 to better represent the large-scale (hundreds of km) and small-scale (tens of km) horizontal gradients in surface-layer weather and, to a lesser degree, the atmospheric boundary-layer (ABL) height, which was evaluated against observations measured by differential absorption lidar (DIAL). The benefits of coupling an LSM to the MM5 were not readily evident in this summertime case, with the model having particular difficulty simulating the timing of maximum surface fluxes while underestimating the depth of the mixed layer.     

Micrometeorological Observations of a Microburst in Southern Finland

On the afternoon of 3 July 2004 in Hyytiälä (Juupajoki, Finland), convective cells produced a strong downburst causing forest damage. The SMEAR II field station, situated near the damage site, enabled a unique micrometeorological analysis of a microburst with differences above and inside the canopy. At the time of the event, a squall line associated with a cold front was crossing Hyytiälä with a reflectivity maximum in the middle of the squall line. A bow echo, rear-inflow notch, and probable mesovortex were observed in radar data. The bow echo moved west-north-west, and its apex travelled just north of Hyytiälä. The turbulence data were analysed at two locations above the forest canopy and at one location at sub-canopy. At 1412 EET (Eastern European Time, UTC+2), the horizontal and vertical wind speed increased and the wind veered, reflecting the arrival of a gust front. At the same time, the carbon dioxide concentration increased due to turbulent mixing, the temperature decreased due to cold air flow from aloft and aerosol particle concentration decreased due to rain scavenging. An increase in the number concentration of ultra-fine particles (< 10 nm) was detected, supporting the new particle formation either from cloud outflow or due to rain. Five minutes after the gust front (1417 EET), strong horizontal and downward vertical wind speed gusts occurred with maxima of 22 and 15 m s^?1, respectively, reflecting the microburst. The turbulence spectra before, during and after the event were consistent with traditional turbulence spectral theory.     

Water level variations in the Neuse and Pamlico Estuaries,North Carolina due to local and remote forcing

Water level time series records from the Neuse and Pamlico River Estuaries were statistically compared to local and distant wind field data, water level records within the Pamlico Sound and also coastal ocean sites to determine the relative contribution of each time series to water levels in the Neuse and Pamlico Estuaries. The objectives of this study were to examine these time series data using various statistical methods (i.e. autoregressive, empirical orthogonal function analysis (EOF), exploratory data analysis (EDA)) to determine short- and long-time-scale variability, and to develop predictive statistical models that can be used to estimate past water level fluctuations in both the Neuse Estuary (NE) and Pamlico Estuary (PE). Short- and long-time-scale similarities were observed in all time series of estuarine, Pamlico Sound and subtidal coastal ocean water level and wind component data, due to events (nor'easters, fronts and tropical systems) and seasonality. Empirical orthogonal function analyses revealed a strong coastal ocean and wind field contribution to water level in the NE and PE. Approximately 95% of the variation was captured in the first two EOF components for water level data from the NE, sound and coastal ocean, and 70% for the PE, sound and coastal ocean. Spectral density plots revealed strong diurnal signals in both wind and water level data, and a strong cross correlation and coherency between the NE water level and the North/South wind component. There was good agreement between data and predictions using autoregressive statistical models for the NE (R² = 0.92) and PE (R² = 0.76). These methods also revealed significant autoregressive lags for the NE (days 1 and 3) and for the PE (days 1, 2 and 3). Significant departures from predictions are attributed to local meteorological and hydrological events. The autoregressive techniques showed significant predictive improvement over ordinary least squares methods. The results are considered within the context of providing long time-scale hindcast data for the two estuaries, and the importance of these data for multidisciplinary researchers and managers.