Rooting Depth and Extreme Precipitation Regulate Groundwater Recharge in the Thick Unsaturated Zone: A Case Study

Many modeling efforts have been made for shallow soil, but little has been done in deep-rooted ecosystems, especially on the long-term impact of deep-rooted vegetation to understand the impact of vegetation type on hydrological processes. In this study, we used the Community Land Model (CLM) version 4.0 to simulate the soil water dynamics and groundwater recharge with shallow-rooted and deep-rooted vegetation cover in the critical soil zone of 100 m thickness. We selected winter wheat and summer maize to represent shallow-rooted vegetation and apple trees as deep-rooted vegetation growing in the semi-humid Loess Plateau of China over the period of 1901–2015. Our results show that the rooting depth and precipitation dictate the occurrence of disconnected recharge. This occurred in soil depths that were below 75 m in wet years with annual precipitation of over 650, 730, and 1000 mm for the winter wheat field, summer maize field, and apple orchard, respectively. Connected recharge was the major component of groundwater recharge for all three crop fields. The transit time of precipitation ranged from several to hundreds of years via the disconnected recharge that is caused by extreme precipitation and the connected recharge that is generated by other precipitation. Therefore, both rooting depth and growth period of vegetation affect the groundwater recharge and transit time, as well as precipitation

Effects of Severe Water Stress on Maize Growth Processes in the Field

In this study, we investigated the effects of water stress on the growth and yield of summer maize (Zea mays L.) over four phenological stages: Seedling, jointing, heading, and grain-filling. Water stress treatments were applied during each of these four stages in a water-controlled field in the Guanzhong Plain, China between 2013 and 2016. We found that severe water stress during the seedling stage had a greater effect on the growth and development of maize than stress applied during the other three stages. Water stress led to lower leaf area index (LAI) and biomass owing to reduced intercepted photosynthetically active radiation (IPAR) and radiation-use efficiency (RUE). These effects extended to the reproductive stage and eventually reduced the unit kernel weight and yield. In addition, the chlorophyll content in the leaf remained lower, even though irrigation was applied partially or fully after the seedling stage. Severe and prolonged water stress in maize plants during the seedling stage may damage the structure of the photosynthetic membrane, resulting in lower chlorophyll content, and therefore RUE, than those in the plants that did not experience water stress at the seedling stage. Maize plants with such damage did not show a meaningful recovery even when irrigation levels during the rest of the growth period were the same as those applied to the plants not subjected to water stress. The results of our field experiments suggest that an unrecoverable yield loss could occur if summer maize were exposed to severe and extended water stress events during the seedling stage

Agent-Based Load Balancing on Homogeneous Minigrids: Macroscopic Modeling and Characterization

Abstract—In this paper, we present a macroscopic characterization of agent-based load balancing in homogeneous minigrid environments. The agent-based load balancing is regarded as agent distribution from a macroscopic point of view. We study two quantities on minigrids: the number and size of teams where agents (tasks) queue. In macroscopic modeling, the load balancing mechanism is characterized using differential equations. We show that the load balancing we concern always converges to a steady state. Furthermore, we show that load balancing with different initial distributions converges to the same steady state gradually. Also, we prove that the steady state becomes an even distribution if and only if agents have complete knowledge about agent teams on minigrids. Utility gains and efficiency are introduced to measure the quality of load balancing. Through numerical simulations, we discuss the utility gains and efficiency of load balancing in different cases and give a series of analysis. In order to maximize the utility gain and the efficiency, we theoretically discuss the optimization of agents ’ strategies. Finally, in order to validate our proposed agentbased load balancing mechanism, we develop a computing platform, called Simulation System for Grid Task Distribution (SSGTD). Through experimentation, we note that our experimental results in general confirm our theoretical proofs and numerical simulation results on the proposed equation system. In addition, we find a very interesting phenomenon, that is, our agent-based load balancing mechanism is topology-independent

Development and evaluation of a physically based multiscalar drought index: The Standardized Moisture Anomaly Index

In this study, a new physically based multiscalar drought index, the Standardized Moisture Anomaly Index (SZI), was developed and evaluated, which combines the advantages of the Palmer Drought Severity Index (PDSI) and the Standardized Precipitation Evapotranspiration Index (SPEI). The SZI is based on the water budget simulations produced with a sophisticated hydrological model, and it also includes a multiscalar feature to quantify drought events at different temporal scales taken from SPEI. The Chinese Loess Plateau was selected to evaluate the performance of the SZI. Our evaluation indicates that the SZI accurately captures the onset, duration, and ending of a multiyear drought event through its multiscalar feature, while the PDSI, which lacks this feature, is often unable to describe the evolution of a multiyear drought event. In addition, the variability of the SZI is more consistent with observed streamflow and the satellite normalized difference vegetation index than that of the Standardized Precipitation Index and the SPEI. Although the SPEI includes potential evapotranspiration (PE) as water demand, water demand is often unrealistically estimated based solely on PE, especially over arid and semiarid regions. The improved drought quantification with the SZI is the result of a more reasonable estimation of water demand by including evapotranspiration, runoff, and any change in soil moisture storage. In general, our newly developed SZI is physically based and includes a multiscalar feature, which enables it to provide better information for drought monitoring and identification at different temporal scales. © 2015. American Geophysical Union. All Rights Reserved

Quantifying the Impact of Climate Change and Human Activities on Streamflow in a Semi-Arid Watershed with the Budyko Equation Incorporating Dynamic Vegetation Information

Understanding hydrological responses to climate change and land use and land cover change (LULCC) is important for water resource planning and management, especially for water-limited areas. The annual streamflow of the Wuding River Watershed (WRW), the largest sediment source of the Yellow River in China, has decreased significantly over the past 50 years at a rate of 5.2 mm/decade. Using the Budyko equation, this study investigated this decrease with the contributions from climate change and LULCC caused by human activities, which have intensified since 1999 due to China’s Grain for Green Project (GFGP). The Budyko parameter that represents watershed characteristics was more reasonably configured and derived to improve the performance of the Budyko equation. Vegetation changes were included in the Budyko equation to further improve its simulations, and these changes showed a significant upward trend due to the GFGP based on satellite data. An improved decomposition method based on the Budyko equation was used to quantitatively separate the impact of climate change from that of LULCC on the streamflow in the WRW. Our results show that climate change generated a dominant effect on the streamflow and decreased it by 72.4% in the WRW. This climatic effect can be further explained with the drying trend of the Palmer Severity Drought Index, which was calculated based only on climate change information for the WRW. In the meantime, although human activities in this watershed have been very intense, especially since 1999, vegetation cover increase contributed a 27.6% decline to the streamflow, which played a secondary role in affecting hydrological processes in the WRW

Assessment of the Effects of Climate Change on Evapotranspiration with an Improved Elasticity Method in a Nonhumid Area

Climatic elasticity is a crucial metric to assess the hydrological influence of climate change. Based on the Budyko equation, this study performed an analytical derivation of the climatic elasticity of evapotranspiration (ET). With this derived elasticity, it is possible to quantitatively separate the impacts of precipitation, air temperature, net radiation, relative humidity, and wind speed on ET in a watershed. This method was applied in the Wuding River Watershed (WRW), located in the center of the Yellow River Watershed of China. The estimated rate of change in ET caused by climatic variables is −10.69 mm/decade, which is close to the rate of change inET (−8.06 mm/decade) derived from observable data. The accurate estimation with the elasticity method demonstrates its reliability. Our analysis shows that ET in the WRW had a significant downward trend, but the ET ratio in the WRW has increased continually over the past 52 years. Decreasing precipitation is the first-order cause for the reduction of ET, and decreasing net radiation is the secondary cause. Weakening wind speed also contributed to this reduction. In contrast, regional warming led to an increase in ET that partly offset the negative contributions from other climatic variables. Moreover, reforestation can affect the energy budget of a watershed by decreasing albedo, compensating for the negative influence of global dimming. The integrated effect from precipitation and temperature can affect the energy budget of a watershed by causing a large fluctuation in winter albedo

Assessment of the Effects of Climate Change on Evapotranspiration with an Improved Elasticity Method in a Nonhumid Area

Climatic elasticity is a crucial metric to assess the hydrological influence of climate change. Based on the Budyko equation, this study performed an analytical derivation of the climatic elasticity of evapotranspiration (ET). With this derived elasticity, it is possible to quantitatively separate the impacts of precipitation, air temperature, net radiation, relative humidity, and wind speed on ET in a watershed. This method was applied in the Wuding River Watershed (WRW), located in the center of the Yellow River Watershed of China. The estimated rate of change in ET caused by climatic variables is −10.69 mm/decade, which is close to the rate of change inET (−8.06 mm/decade) derived from observable data. The accurate estimation with the elasticity method demonstrates its reliability. Our analysis shows that ET in the WRW had a significant downward trend, but the ET ratio in the WRW has increased continually over the past 52 years. Decreasing precipitation is the first-order cause for the reduction of ET, and decreasing net radiation is the secondary cause. Weakening wind speed also contributed to this reduction. In contrast, regional warming led to an increase in ET that partly offset the negative contributions from other climatic variables. Moreover, reforestation can affect the energy budget of a watershed by decreasing albedo, compensating for the negative influence of global dimming. The integrated effect from precipitation and temperature can affect the energy budget of a watershed by causing a large fluctuation in winter albedo

Online Time-Optimal Trajectory Generation for Two Quadrotors with Multi-Waypoints Constraints

The autonomous quadrotor's flying speed has kept increasing in the past 5 years, especially in the field of autonomous drone racing. However, the majority of the research mainly focuses on the aggressive flight of a single quadrotor. In this letter, we propose a novel method called Pairwise Model Predictive Control (PMPC) that can guide two quadrotors online to fly through the waypoints with minimum time without collisions. The flight task is first modeled as a nonlinear optimization problem and then an efficient two-step mass point velocity search method is used to provide initial values and references to improve the solving efficiency so that the method can run online with a frequency of 50 Hz and can handle dynamic waypoints. The simulation and real-world experiments validate the feasibility of the proposed method and in the real-world experiments, the two quadrotors can achieve a top speed of 8.1m/s in a 6-waypoint racing track in a compact flying arena of 6m*4m*2m