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The addition of crop straw is considered an important measure for sustainable agricultural production. Crop straw when incorporated into the soil affects crop growth and development by changing the hydrothermal conditions of the soil. However, quantitative studies that inform on the mechanisms by which added straw or straw biochar (SSB) affects hydrothermal response of soil and thereby crop productivity in lime concretion black soil (LCBS) are lacking. Moreover, the sustained effects during continuous cropping are less well understood. The impact of SSB on soil properties and crop yields in a typical LCBS area was systematically investigated through field experiments with maize and wheat rotations. Four treatments were set: straw (S), fertilizer (F), straw with fertilizer (SF) and straw biochar with fertilizer (BF). The results indicated that soil water‐holding capacity and rainfall storage efficiency were improved in BF and SF treatments. Compared with the F treatment, the soil water storage increased by 80%–98% and the response time of soil water to rainfall was advanced by approximately 4 h in the other three treatments during the maize season. BF and SF treatments only increased soil water storage by 6.8% due to the lack of rainfall during the wheat season. Soil inorganic nitrogen and available phosphorus were significantly increased in SF treatment by 101.1% and 32.9% compared with BF treatment in the wheat season. Considering crop plant height, leaf area index and yield, SF and BF treatments were beneficial to crop growth and improved water use efficiency. They did not increase maize yield significantly, with a maximum increase of 2.1% in BF treatment compared with F treatment. But, SF treatment significantly increased wheat yield by 11.8% and BF treatment increased wheat yield by 6.7%. Overall, this study illustrated the positive effects of SSB additions on the production of LCBS from multiple perspectives. This will provide reference for improving the soil hydrothermal conditions of LCBS and ensure food security. [ABSTRACT FROM AUTHOR]

The interaction between soil moisture (SM) and vegetation dynamics has been proven in previous studies. In situ measurements have provided reliable data to investigate and validate the time effect in different zones, which is important in the hydrology and agriculture fields. There were 845 SM in situ monitoring measurements utilized with the correlation between SM and vegetation across various soil depths and climate zones in China. The impact of climate and teleconnection factors on SM and the leaf area index (LAI) are also discussed. The results indicate that SM increases from northwest to southeast in China. The time lag responses of SM to temperature, precipitation, relative humidity, and sunshine duration are 0–3 days, 3–7 days, 1–3 days, and 3–15 days, respectively. The LAI is most strongly correlated with the climate of the current month. When the LAI leads SM, a negative correlation is observed, whereas a positive correlation is observed when SM leads the LAI. This proves that vegetation growth restricts the increase in SM, and soil drying further restricts the growth of vegetation. There was a response time of 2–4 months between the LAI and SM. The effect of vegetation and deeper SM was significant in the arid zone, while they were coupled with shallow SM in the humid zone. Additionally, the El Niño–Southern Oscillation (ENSO) showed a significant positive correlation with SM in 2015–2016 with signals of 9–14 months. The results provide support for balancing the contradiction between future vegetation restoration and water resource scarcity. [ABSTRACT FROM AUTHOR]

Global climate change has affected vegetation cover in alpine areas. In this paper, we analyzed the correlation between Leaf Area Index (LAI) and climate factors of the Yarlung Tsangpo River basin, and identified their contributions using the quantitative analysis method. The results show that the vegetation cover in the study area generally exhibited an increasing trend. Grassland in the middle- and high-altitude areas was the main contributing area. Temperature is the dominant climatic factor affecting the change, the effect of which increases with the rise in elevation. The influences of precipitation and radiation had obvious seasonality and regionality. The vegetation illustrated a lag response to climate drivers. With the change in the elevation band, the response time to precipitation was significantly less than that to air temperature in the low-elevation area, while the opposite trend was observed in the high-elevation area. In the future, the LAI of the watershed will show different characteristics at different time points, with the increases in the LAI in autumn and winter becoming the main factors for the future increase in the LAI. This provides a crucial basis upon which to explore hydrological and ecological processes as important components of the Third Pole region. [ABSTRACT FROM AUTHOR]

The distribution of terrestrial soil organic carbon changes with climate and substrate conditions. This study investigated the spatial and temporal distribution of soil organic carbon and its influencing elements in the Yarlung Tsangpo River Basin using meteorological, subsurface, and remotely sensed data over the past 39 years, combined with random forests and geodetector. The results of the study showed that soil organic carbon has been increasing in the study area over the past 39 years, and this change has been concentrated in the central part of the watershed. Among the environmental factors, precipitation, temperature, and leaf area index were the main contributors to the soil organic carbon changes, and the effects of the three factors were more significant at higher altitudes, with a 33 % increase in the significance level. Notably, the interactions among the factors exceeded their individual effects, and the combination of climate and leaf area index showed a significant two-factor enhancement effect, with q-value enhancements generally ranging from 0.15 to 0.3. The two-factor enhancement effect was more pronounced below 3000 m above sea level, where the topography of the study area concentrates soil organic carbon in the gently sloping areas of the catchment. [ABSTRACT FROM AUTHOR]

Evapotranspiration and soil moisture content (SMC) are key elements of the hydrological cycle. Accurate prediction of the dynamic processes of evapotranspiration and soil water is essential for irrigation and water management. Here, the boosted regression tree (BRT) method was employed to quantify environmental controls on actual evapotranspiration (ET a), potential evapotranspiration (ET 0), and SMC using monitoring data from the Wudaogou hydrological experimental station. The results indicated that: (1) the BRT algorithm was effective in predicting the relative control of different environmental factors on ET a , ET 0 , and SMC; and (2) vapor pressure deficit (VPD) was the most important factor affecting daily ET 0 , and sunshine duration (SSD) also played a nonnegligible role. The results further explained the phenomenon of the "evaporation paradox" in the study area. SSD could be a leading control on daily ET a , followed by VPD, leaf area index (LAI). (3) Among the underground factors, groundwater level (GL) and LAI played a dominant role in the relative contribution to SMC. Among the aboveground factors, relative humidity (RH) and soil temperature (TS) have a relatively large influence on SMC. (4) The differences in SMC at different depths were determined by multiple influencing factors, including LAI, VPD, and precipitation (P). This study also underscores the importance of vegetation variations to hydrological cycle processes. In general, climate warming and an increase in extreme rainfall events will increase the control of temperature on SMC and weaken the control of P on SMC in the future. • A boosted regression tree method is used to quantify controls on ET a and SMC by environmental factors. • The impact of SSD on ET a is substantial in the study sites, and the impact of VPD and LAI on ET a could not be ignored. • GL and LAI significantly affect the variation of SMC in the study sites. • SMC differences at different depths were determined by a combination of influencing factors. [ABSTRACT FROM AUTHOR]