Structural basis of the protochromic green/red photocycle of the chromatic acclimation sensor RcaE

Cyanobacteriochromes (CBCRs) are bilin-binding photosensors of the phytochrome superfamily that show remarkable spectral diversity. The green/red CBCR subfamily is important for regulating chromatic acclimation of photosynthetic antenna in cyanobacteria and is applied for optogenetic control of gene expression in synthetic biology. It is suggested that the absorption change of this subfamily is caused by the bilin C15-Z/C15-E photoisomerization and a subsequent change in the bilin protonation state. However, structural information and direct evidence of the bilin protonation state are lacking. Here, we report a high-resolution (1.63Å) crystal structure of the bilin-binding domain of the chromatic acclimation sensor RcaE in the red-absorbing photoproduct state. The bilin is buried within a “bucket” consisting of hydrophobic residues, in which the bilin configuration/conformation is C5-Z,syn/C10-Z,syn/C15-E,syn with the A- through C-rings coplanar and the D-ring tilted. Three pyrrole nitrogens of the A- through C-rings are covered in the α-face with a hydrophobic lid of Leu249 influencing the bilin pKa, whereas they are directly hydrogen bonded in the β-face with the carboxyl group of Glu217. Glu217 is further connected to a cluster of waters forming a hole in the bucket, which are in exchange with solvent waters in molecular dynamics simulation. We propose that the “leaky bucket” structure functions as a proton exit/influx pathway upon photoconversion. NMR analysis demonstrated that the four pyrrole nitrogen atoms are indeed fully protonated in the red-absorbing state, but one of them, most likely the B-ring nitrogen, is deprotonated in the green-absorbing state. These findings deepen our understanding of the diverse spectral tuning mechanisms present in CBCRs.

Implementation of Snowpack Treatment in the CPC Water Balance Model and Its Impact on Drought Assessment

Droughts are a worldwide concern, thus assessment efforts are conducted by many centers around the world, mainly through simple drought indices which usually neglect important hydrometeorological processes or require variables available only from complex Land Surface Models (LSMs). The U.S. Climate Prediction Center (CPC) uses the Leaky Bucket (LB) water-balance model to post-process temperature and precipitation, providing soil moisture (SM) anomalies to assess drought conditions. However, despite its crucial role in the water cycle, snowpack has been neglected by LB and most drought indices.Taking advantage of the high-quality snow water equivalent (SWE) data from the University of Arizona (UA), a single-layer snow scheme, forced by daily temperature and precipitation only, is developed for LB implementation and tested with two independent forcing datasets. Compared against the UA and SNOTEL SWE data over CONUS, LB outperforms a sophisticated LSM (Noah/NLDAS-2), with the median LB vs SNOTEL correlation (RMSE) about 40% (26%) higher (lower) than that from Noah/NLDAS-2, with only slight differences due to different forcing datasets.The changes in the temporal variability of SM due to the snowpack treatment lead to improved temporal and spatial distribution of drought conditions in the LB simulations compared to the reference U.S. Drought Monitor maps, highlighting the importance of snowpack inclusion in drought assessment. The simplicity but reasonable reliability of the LB with snowpack treatment makes it suitable for drought monitoring and forecasting in both snow-covered and snow-free areas, while only requiring precipitation and temperature data (markedly less than other water-balance-based indices).

Early detection of the flash drought: a preliminary study by the National Water Model

<p>As one key innovation in the NOAA hydrological modeling, the National Water Model (NWM) was recently upgraded to v2.0 in June 2019. The NWM could provide not only the streamflow prediction for hydrological guidance, but also the real-time high-resolution land state analysis and assimilation.  Based on the NWM v2.0 retrospective analysis from 1993 to 2018, we evaluated NWM soil moisture (SM) and evapotranspiration(ET) for the drought monitor application.  The Soil Moisture Percentile (SMP) from NWM is compared with the official US drought monitor (USDM) map in major drought events. The drought categories (D0-D4) based on NWM, is quantitively compared with similar drought monitor from the NLDAS2 multi-model ensemble.  A long time-series soil moisture monitor from CPC leaky bucket model is also compared against NWM, to distinguish the importance of the long temporal record vs high spatial resolution for drought monitor. The rapid intensification or rapid onset drought, i.e. flush drought, is also investigated by the temporal change of the SMP. The preliminary results indicated the NWM could well capture the major droughts during 2000 to 2018. In particular, the flash droughts indicated by the NWM could provide one to three weeks early warning than the USDM map, show great potential in the future application for flash drought detection, monitor and prediction.</p><p> </p>

Multiple measures of water storage in monsoon Asia

<p>Temporal water storage is a fundamental component of the terrestrial water cycle. Almost all precipitation falling on land is transferred via a series of short- to long-term storage locations, e.g. groundwater, to rivers, and eventually ends in the oceans or, through evapotranspiration, back in the atmosphere. The intermediate storage compartments are recharged during precipitation events and subsequently purge during phases of very little precipitation input. Methods to estimate water storage variations are often limited to specific, well-monitored locations and the findings from there are often difficult to generalize or to upscale. At the same time large scale monitoring represents an average of the entire system with very little prediction power for small areas. Thus, measures of storage from small systems can be difficult to compare to large systems and vice versa. In this recently published study (Schmidt et al., 2020) we compare three independent methods of estimating water storage variations for systems spanning over three orders of magnitude in basin area: 1) GRACE, 2) hydrograph recession curve analysis, and 3) quantifying precipitation-discharge hysteresis loops. We measured storage using all three methods for 242 watersheds in Asia spanning a size range from 10<sup>3</sup> to 10<sup>6</sup> km<sup>2</sup> and find that GRACE- derived storage correlates well with the quantification of hysteresis terms but recession curve derived dynamic storage does not correlate with hysteresis terms or GRACE-derived storage. Thus, we argue that precipitation-discharge hysteresis may be able to be scaled to GRACE-derived storage as an  independent estimate of storage to systems much smaller than the typical resolution of GRACE. Hysteresis-derived storage correlates well with mean monsoon rainfall in the upstream watershed while recession-derived dynamic storage does not. This suggests that hysteresis- and GRACE-derived storage may be input limited. In contrast, recession-derived dynamic storage does not correlate with topographic, climatic, or land cover metrics, suggesting that it may be limited by the rate at which water infiltrates into deep groundwater and then enters the river system. In addition, we find that recession-derived dynamic storage is a factor of seven lower than hysteresis-derived or GRACE derived storage. Recession-derived dynamic storage represents the annual variability in deep and saturated groundwater storage, a “leaky bucket” that is recharged from the top and “leaks” into rivers from deeper storage. The GRACE and hysteresis derived storage in turn integrates groundwater variations in addition to other storage units at or close to the Earth surface, such as snowpack, lakes, and soil moisture. These data may be able to be used to better quantify storage terms in hydrologic modeling and might help to improve GRACE data products.</p> <p>Schmidt, A. H., Lüdtke, S., & Andermann, C. (2020). Multiple measures of monsoon-controlled water storage in Asia. Earth and Planetary Science Letters, https://doi.org/10.1016/j.epsl.2020.116415</p>

SIR approach in modeling data packets forwarding at a leaky bucket

When network users are intensively interacting during rush hour, avoiding data loss and latency is a concern in guaranteeing segment reliability. Implementing a leaky bucket could be needed to achieve flows effective monitoring by generating network of queues at given output link. Packets associated with different sessions and originated from different hosts may be mixed up and queuing delay may become longer, depending on network segment state, buffering strategy, users’ behavior among other factors. It is interesting to assimilate these stages of packets traveling through network segment to the concept of epidemic control. This paper proposes a SIR (Susceptible–Infected–Recovered) approach in modeling data packets transmission at a leaky bucket at peak hour. We focused our analysis on packets buffering and recovery strategy impact on segment forwarding performance in heavy load situation. Numerical results suggested adapting buffering strategy and packets recovery to enhance transmission and network overall performance.

“Leaky Bucket” of Kazakhstan’s Power Grid: Losses and Inefficient Distribution of Electric Power

This paper aims to determine and explain the main factors for power losses (the so-called “leaky bucket” effect) in Kazakhstan and the reasons for inefficient energy distribution within the country. Energy efficiency in Kazakhstan is much lower compared to more economically developed countries. The differences between energy efficiency in various regions of Kazakhstan are also significant. This article explores the impact of administrative monopoly tariffs on the regional energy efficiency, based on a national study conducted in Kazakhstan in 2017. The purpose of the study was to identify the administrative barriers and their impact on the sustainability of enterprise development. What hinders the distribution of energy resources among different regions is artificial barriers in the energy market and the administrative tariff monopoly for electric power. This leads to the inefficient distribution of resources throughout the country. In addition, it is difficult to leverage low distribution efficiency in the absence of a market. The authors attempt to prove that the magnitude of administrative barriers directly affects the efficiency and competitiveness of business, as well as the final prices of goods and services for the end consumer.

Analysis of the State-Dependent Queueing Model and Its Application to Battery Swapping and Charging Stations

This study analyzes the performance of a queue length-dependent overload control policy using a leaky bucket (LB) scheme. This queueing model is applied to the operation of a battery swapping and charging station for electric vehicles (EVs). In addition to the LB scheme, we propose two congestion control policies based on EV queue length thresholds. With these policies, the model determines both EV-arrival and battery-supply intervals, and these depend on the number of EVs waiting in the queue. The queue length distributions, including those at arbitrary epochs, are derived using embedded Markov chain and supplementary variable methods. Performance measures such as blocking probability and mean waiting time are investigated using numerical examples. We study the characteristics of the system using numerical examples and use a cost analysis to investigate situations in which the application of each congestion control policy is advantageous.