Water use efficiency in China is impacted by climate change and land use and land cover.

A crucial physiological indicator known as water use efficiency (WUE) (Foley et al.) assesses the trade-off between water loss and carbon uptake. The carbon and water coupling mechanisms, energy balance, and hydrological cycle processes in the ecosystem are impacted by climate change, vegetation dynamics, and land use change. In this study, we employed Sen trend analysis, the Mann-Kendall test, the land-use transfer matrix, and multiple linear regression analysis to investigate the regional and temporal dynamics of WUE and its reaction to climate change and land-use transfer changes in China. According to the findings, the annual average WUE in China was 0.998 gC/mm·m2 from 2000 to 2017. Of the nine major river basins, the Continental Basin had the lowest WUE (0.529 gC/mm·m2), and the Southwest River Basin had the highest WUE (0.691 gC/mm·m2), while the Pearl River Basin and the Southeast River Basin had the highest WUEs (1.184 gC/mm·m2). The Haihe River Basin and the Yellow River Basin were the key regions with elevated WUE. Forest had the greatest WUE (1.134 gC/mm·m2; out of the nine major river basins), followed by shrub (1.109 gC/mm·m2). Vegetation dynamics changes had a higher impact on WUE than climate change and land use changes, when the contributions of climate change, vegetation dynamics changes, and land use changes to WUE were separated. The largest climatic factor influencing variations in WUE was VPD (28.04% ± 3.98%), whereas among the vegetation dynamics factors, NDVI (33.75% ± 6.90%) and LAI (22.21% ± 2.11%) contributed the most. The transition from high to low vegetation cover led to a relative decrease in WUE, and vice versa, according to data on land use change in China from 2000 to 2017. Land use change made a positive impact to WUE change. The findings of this study may be helpful in China for choosing a suitable regional plant cover and managing local water resources sustainably.

Synergies and trade-offs of ecosystem services affected by land use structures of small watershed in the Loess Plateau.

The Chinese government has implemented a series of ecological restoration projects in the Loess Plateau (LP), and the surface cover changed dramatically, impacting the ecosystem services (ESs) greatly. In this study, we used K-means clustering to classify the land use structures (LUSs) of the LP from 1990 to 2015 at the small watershed scale, and investigated the effects of LUS on water supply (WS), soil conservation (SC), and carbon sequestration (CS, expressed as NPP) with constraint lines. The values of WS and SC were obtained from the InVEST simulation, validated by the hydrographic station data. The results showed that the LUSs in LP were cropland structure (CLS, distinguished with CS), forest structure (FS), grassland structure (GS), crop-grassland structure (CGS), crop-forest-grassland structure (CFGS) and a very few areas of barren structure (BS). The proportion of dominant land use in those LUSs with a balance of WS, SC, and CS was 0.6-0.7 (cropland in CLS), 0.5 (forest in FS), 0.45/0.4 (cropland/grassland in CGS), 0.75 to 0.85 (grassland in GS), and 0.15/0.4/0.25 to 0.35 (cropland/forest/grassland in CFGS), respectively. The types of constraint curves of ESs for those LUSs involves hump-shaped curve, negative convex, half-concave-waved curve and concave-waved curve. This study proposed a method to objectively delineate LUS and improved the constraint line method to make it suitable for cases with less data, innovatively presenting the variation of ESs inside LUSs, which may provide a reference for optimal land planning and sustainable development of social-ecological systems.

BK-SWMM flood simulation framework is being proposed for urban storm flood modeling based on uncertainty parameter crowdsourcing data from a single functional region.

In recent years, urban flood disasters caused by sudden heavy rains have become increasingly severe, posing a serious threat to urban public infrastructure and the life and property safety of residents. Rapid simulation and prediction of urban rain-flood events can provide timely decision-making reference for urban flood control and disaster reduction. The complex and arduous calibration process of urban rain-flood models has been identified as a major obstacle affecting the efficiency and accuracy of simulation and prediction. This study proposes a multi-scale urban rain-flood model rapid construction method framework, BK-SWMM, focusing on urban rain-flood model parameters and based on the basic architecture of Storm Water Management Model (SWMM). The framework comprises two main components: 1) constructing a SWMM uncertainty parameter sample crowdsourcing dataset and coupling Bayesian Information Criterion (BIC) and K-means clustering machine learning algorithm to discover clustering patterns of SWMM model uncertainty parameters in urban functional areas; 2) coupling BIC and K-means with SWMM model to form BK-SWMM flood simulation framework. The applicability of the proposed framework is validated by modeling three different spatial scales in the study regions based on observed rainfall-runoff data. The research findings indicate that the distribution pattern of uncertainty parameters, such as depression storage, surface Manning coefficient, infiltration rate, and attenuation coefficient. The distribution patterns of these seven parameters in urban functional zones indicate that the values are highest in the Industrial and Commercial Areas (ICA), followed by Residential Areas (RA), and lowest in Public Areas (PA). All three spatial scales' REQ, NSEQ, and RD2 indices were superior to the SWMM and less than 10%, greater than 0.80, and greater than 0.85, respectively. However, when the study area's geographical scale expands, the simulation's accuracy will decline. Further research is required on the scale dependency of urban storm flood models.

[Distribution of fine root biomass of main planting tree species in Loess Plateau, China].

The distribution of fine roots of Pinus tabuliformis, Populus tomentosa, Prunus armeniaca, Robinia pseudoacacia, Hippophae rhamnoides, and Caragana korshinskii was investigated by using soil core method and the fine root was defined as root with diameter less than 2 mm. The soil moisture and soil properties were measured. The results showed that in the horizontal direction, the distribution of fine root biomass of P. tabuliformis presented a conic curve, and the fine root biomass of the other species expressed logarithm correlation. Radial roots developed, the fine root biomass were concentrated within the scope of the 2-3 times crown, indicating that trees extended their roots laterally to seek water farther from the tree. In the vertical direction, the fine root biomass decreased with the increasing soil depth. Fine root biomass had significant negative correlation with soil water content and bulk density, while significant positive correlation with organic matter and total N contents.

[Canopy interception of Pinus tabulaeformis plantation on Longzhong Loess Plateau, Northwest China: characteristics and simulation].

Taking the Pinus tabulaeformis plantation in the Anjiagou catchment on Longzhong Loess Plateau as test object, an observation was made on the characteristics of throughfall, stemflow, interception, and canopy structure of P. tabulaeformi during its growth season (from May to September) in 2011. Based on the observed data, the revised Gash analytical model was adopted to simulate the canopy interception, aimed to understand the ecological hydrological processes of Pinus tabulaeformis plantation and related mechanisms. In the observation period, a total of 19 precipitation events were observed, with a total precipitation of 215.80 mm. The throughfall, stemflow, and canopy interception were 165.24 mm, 2.29 mm, and 48.27 mm, occupying 76.7%, 1.1%, and 22.4% of the total precipitation, respectively. The simulated canopy interception was 41.24 mm, being 7.13 mm lower than the observed value and with a relative error of 14.7%. There were 33.8% and 60.0% of interception were evaporated from the canopy during and after precipitation, respectively. The revised Gash analytical model was highly sensitive to the canopy storage capacity, forest coverage, rainfall intensity, and evaporation, but less sensitive to the stemflow rate and stem water holding capacity.

[Characteristics of rainfall interception by Caragana korshinskii and Hippophae rhamnoides in Loess Plateau of Northwest China].

From May to October 2011, an investigation was conducted on the effects of rainfall and its intensity on the canopy interception, throughfall, and stemflow of Caragana korshinskii and Hippophae rhamnoides, the main shrub species commonly planted to stabilize soil and water in the Anjiagou catchment of Loess Plateau. A total of 47 rainfall events were observed, most of which were featured with low intensity, and the total amount and average intensity of the rainfalls were 208.9 mm and 2.82 mm x h(-1), respectively. As a whole, the rainfall events of 2-10 mm and 0.1-2 mm x h(-1) had the highest frequency. The canopy interception, throughfall, and stemflow of C. korshinski were 58.5 mm (28%), 124.7 mm (59.7%), and 25.7 mm (12.3%), while those of H. rhamnoides were 17.6 mm (8.4%), 153. 1 mm (73.3%), and 38.2 mm (18.3%), respectively. Regression analysis showed that the canopy interception, throughfall, and stemflow of the two shrub species all had significant positive correlations with the rainfall amount, and had exponent or power correlations with the rainfall amount and the maximum rainfall intensity in 10 minutes.