Spatial and temporal variation of soil moisture in dependence of multiple environmental parameters in semi-arid grasslands

2011 ◽  
Vol 340 (1-2) ◽  
pp. 73-88 ◽  
Author(s):  
Katrin Schneider ◽  
Ulrich Leopold ◽  
Friederike Gerschlauer ◽  
Frauke Barthold ◽  
Marcus Giese ◽  
...  
Author(s):  
Hao Han ◽  
Jingming Hou ◽  
Rengui Jiang ◽  
Jiahui Gong ◽  
Ganggang Bai ◽  
...  

Abstract Precipitation variations mostly affect the water resource planning in semi-arid regions of northwest China. The objective of this study is to quantitatively explore the spatial and temporal variations of precipitation in different time scales in Xi'an city area. The Mann–Kendall test and wavelet analysis methods were applied to analyze the precipitation variability. In terms of temporal variation of precipitation, the results indicated that the annual precipitation exhibited a significant decreasing trend during 1951–2018. Except for summer precipitation representing a slightly increasing trend, the other seasonal precipitations had a similar decreasing trend to annual precipitation throughout 1951–2018. The monthly precipitation had different change trends, showing the precipitation from June to September could account for 58.4% of the total annual precipitation. In addition, it was clear that annual precipitation had a significant periodic change, with the periods of 6, 13, 19, and 27 years. For the spatial variation of precipitation during 1961–2018, the results showed that annual and seasonal precipitation exhibited obvious spatial differences, indicating an increasing spatial trend from north to south. Thus, understanding the precipitation variation in Xi'an city can provide a theoretical foundation of future water resources management for other cities in semi-arid regions of northwest China.


2021 ◽  
Vol 13 (24) ◽  
pp. 5155
Author(s):  
Ester Carbó ◽  
Pablo Juan ◽  
Carlos Añó ◽  
Somnath Chaudhuri ◽  
Carlos Diaz-Avalos ◽  
...  

The prediction of spatial and temporal variation of soil water content brings numerous benefits in the studies of soil. However, it requires a considerable number of covariates to be included in the study, complicating the analysis. Integrated nested Laplace approximations (INLA) with stochastic partial differential equation (SPDE) methodology is a possible approach that allows the inclusion of covariates in an easy way. The current study has been conducted using INLA-SPDE to study soil moisture in the area of the Valencia Anchor Station (VAS), soil moisture validation site for the European Space Agency SMOS (Soil Moisture and Ocean Salinity). The data used were collected in a typical ecosystem of the semiarid Mediterranean conditions, subdivided into physio-hydrological units (SMOS units) which presents a certain degree of internal uniformity with respect to hydrological parameters and capture the spatial and temporal variation of soil moisture at the local fine scale. The paper advances the knowledge of the influence of hydrodynamic properties on VAS soil moisture (texture, porosity/bulk density and soil organic matter and land use). With the goal of understanding the factors that affect the variability of soil moisture in the SMOS pixel (50 km × 50 km), five states of soil moisture are proposed. We observed that the model with all covariates and spatial effect has the lowest DIC value. In addition, the correlation coefficient was close to 1 for the relationship between observed and predicted values. The methodology applied presents the possibility to analyze the significance of different covariates having spatial and temporal effects. This process is substantially faster and more effective than traditional kriging. The findings of this study demonstrate an advancement in that framework, demonstrating that it is faster than previous methodologies, provides significance of individual covariates, is reproducible, and is easy to compare with models.


2003 ◽  
Vol 11 ◽  
pp. 175-184
Author(s):  
C.C. Boswell ◽  
R.J. Lucas ◽  
M. Lonati ◽  
A. Fletcher ◽  
D.J. Moot

Four annual clovers have become adapted to the dry and semi-arid grasslands in New Zealand. In the absence of competition from perennial clovers, which are adapted to sub-humid and humid environments, further spread is likely to continue. Annuals rely on high numbers of small and hard seeds for survival. Their germination is dependent on a combination of adequate soil moisture and favourable temperatures, with no evidence of a prechilling treatment required. For striated clover, germination results highlight their adaptation to cool moist autumn conditions during germination. The benefits of adventive clovers for N fixation (0.2-100 kg N ha-1) are greatest where sulphur fertiliser has been applied, the clover population is dense, and soil moisture ideal over several months, but may be nil in drought conditions. Key words: annual clovers, germination, nitrogen fixation, semi-arid grassland, Trifolium arvense, T. dubium, T. glomeratum, T. striatum


CATENA ◽  
2014 ◽  
Vol 115 ◽  
pp. 123-133 ◽  
Author(s):  
Lei Yang ◽  
Wei Wei ◽  
Liding Chen ◽  
Wenlin Chen ◽  
Jinglan Wang

2018 ◽  
Vol 26 (8) ◽  
pp. 2811-2826 ◽  
Author(s):  
Martín Hernández-Marín ◽  
Lilia Guerrero-Martínez ◽  
Alfredo Zermeño-Villalobos ◽  
Lorena Rodríguez-González ◽  
Thomas J. Burbey ◽  
...  

2015 ◽  
Vol 30 (1) ◽  
pp. 10-19 ◽  
Author(s):  
Bradley J. Butterfield ◽  
John B. Bradford ◽  
Cristina Armas ◽  
Ivan Prieto ◽  
Francisco I. Pugnaire

1993 ◽  
Vol 3 (1) ◽  
pp. 167-174 ◽  
Author(s):  
R. J. Mitchell ◽  
B. R. Zutter ◽  
T. H. Green ◽  
M. A. Perry ◽  
D. H. Gjerstad

Water ◽  
2019 ◽  
Vol 11 (3) ◽  
pp. 435 ◽  
Author(s):  
Yun Li ◽  
Yuejian Wang ◽  
Jianghua Zheng ◽  
Mingxiang Yang

The performance of hydrological models in western China has been restricted due to the scarcity of meteorological observation stations in the region. In addition to improving the quality of atmospheric input data, the use hydrological models to analyze Hydrological Processes on a large scale in western China could prove to be of key importance. The Jing and Bortala River Basin (JBR) was selected as the study area in this research. The China Meteorological Assimilation Driving Datasets for the SWAT model (CMADS) is used to drive SWAT model, in order to greatly improve the accuracy of SWAT model input data. The SUFI-2 algorithm is also used to optimize 26 sensitive parameters within the SWAT-CUP. After the verification of two runoff observation and control stations (located at Jing and Hot Spring) in the study area, the temporal and spatial distribution of soil moisture, snowmelt, evaporation and precipitation were analyzed in detail. The results show that the CMADS can greatly improve the performance of SWAT model in western China, and minimize the uncertainty of the model. The NSE efficiency coefficients of calibration and validation are controlled between 0.659–0.942 on a monthly scale and between 0.526–0.815 on a daily scale. Soil moisture will reach its first peak level in March and April of each year in the JBR due to the snow melting process in spring in the basin. With the end of the snowmelt process, precipitation and air temperature increased sharply in the later period, which causes the soil moisture content to fluctuate up and down. In October, there was a large amount of precipitation in the basin due to the transit of cold air (mainly snowfall), causing soil moisture to remain constant and increase again until snowmelt in early spring the following year. This study effectively verifies the applicability of CMADS in western China and provides important scientific and technological support for the spatio-temporal variation of soil moisture and its driving factor analysis in western China.


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