Underlying Surface Characteristics Research Articles

Incorporating canopy radiation enhances the explanation of maize yield change and increases model accuracy under film mulching

Plastic film mulching (PM) has been extensively used to increase crop yields in dryland regions in China. However, the impact of differently colored PM on crop radiation utilization due to the optical properties of the underlying PM surfaces remains unclear. We conducted a two-year field experiment in northwest China to evaluate the dynamics of photosynthetically active radiation interception and absorption (fIPAR and fAPAR), as well as the radiation use efficiency for intercepted and absorbed radiation (RUEi and RUEa) during spring maize (Zea mays L.) growth periods. Two fertilization levels (high and low) and 3 PM treatments (transparent film, black film, and no film) were considered in this study. We also developed empirical regression functions to calculate canopy fAPAR, accounting for both canopy and underlying surface characteristics. Furthermore, we used canopy absorption radiation to drive the Soil-Plant-Atmosphere Continuum System (SPACSYS) model to simulate maize biomass and yield. We found that transparent film mulching (TM) exhibited higher fIPAR and fAPAR than black film mulching and no mulching (CK). TM had an increase of RUEi and RUEa by 10.6% and 9.7%, respectively, relative to CK, resulting in a 9.3–19.2% increase in maize yield and a 25.8–30.2% increase in the partial factor productivity of nitrogen. These increases were mainly attributed to the increased relative chlorophyll content, net photosynthesis rate, and extended grain-filling period under TM. We found that the modified radiation input increased the accuracy of the SPACSYS model in simulating maize biomass and yield. We underscore the importance of using TM in dryland areas to increase crop yields and advocate for incorporating canopy radiation data into crop models, especially in agricultural regions where plastic film mulching is used, to enhance the accuracy of yield simulations.

Development of an Integrated Urban Flood Model and Its Application in a Concave-Down Overpass Area

Urban floods caused by extreme rainstorm events have increased in recent decades, particularly in concave-down bridge zones. To simulate urban flooding processes accurately, an integrated urban flood model (IUFM) was constructed by coupling a distributed urban surface runoff model based on the cellular automata framework (CA-DUSRM), a widely used pipe convergence module in the storm water management model (SWMM), with an inundation module that describes the overflow expansion process associated with terrain and land-cover. The IUFM was used in a case study of the Anhua Bridge (a typical concave-down overpass) study area in Beijing, China. The spatial-temporal variations in flood depth modeled by the IUFM were verified to be reliable by comparison with actual measurements and other simulations. The validated IUFM was used to obtain temporal variations in flood range, depth, and volume under four rainstorm scenarios (return periods of 3-year, 10-year, 50-year, and 100-year). The results showed that the surface runoff process, overflow from drainage networks, and overflow expansion process could affect the flooding status by changing the composition and spatial configuration of pervious or impervious patches, drainage capacity, and underlying surface characteristics (such as terrain and land-cover). Overall, although the simulation results from the IUFM contain uncertainties from the model structures and inputs, the IUFM is an effective tool that can provide accurate and timely information to prevent and control urban flood disasters and provide decision-making support for long-term storm water management and sponge city construction.

Accelerated integrated watershed management enhances agricultural carbon sequestration and water use efficiency in an endorheic basin

With the continuous promotion of integrated river basin management (IRBM) in endorheic watersheds, the oasis surface processes have undergone significant changes. However, these underlying surface characteristics have not been well integrated into models for simulating carbon-water flux thus far. In this work, a regional SWAT-TECO model was constructed by coupling the modified TECO simulator with irrigation, film mulching, and soil hydraulic redistribution processes within the SWAT framework. The results indicated that the carbon sequestration and water use efficiency (WUE) showed an increasing trend after IRBM implementation in Heihe endorheic basin. WUE was projected to improve under future climate change and can be further enhanced by a maximum of 6.37 % through improving irrigation water use efficiency by 20 %, maintaining existing planting scale, increasing film mulching by 20 %, and reducing fertilizer application by 10 %. These findings can guide the formulation of high-water efficiency agricultural management strategies in global endorheic basins.

Droplet impacting on pillared hydrophobic surfaces with different solid fractions

HypothesisThe solid fraction of the substrate is expected to influence the bouncing behavior of an impinging droplet, thereby affecting spreading and contact time. Hence, it should be possible to alter the velocity and pressure distribution of impacting droplet, and also affect the impact velocity for droplet penetration right upon impact. SimulationsWe systematically investigate the impact dynamics of water droplets on pillared hydrophobic surfaces with different solid fractions using phase-field simulations. The velocity and pressure distributions of impacting droplets on pillared hydrophobic surfaces with varied Weber numbers and solid fractions are studied. In addition, the influences of the solid fraction on the bouncing behaviors of the impinging droplet, such as the maximum wetting spreading, the maximum impacting depth, and the contact time, are also investigated to further understand the impact event. FindingsWe show that a three-peak pressure profile appears on the top of the pillared hydrophobic surface during droplet impact by varying the solid fraction of the surface. The first peak is generated by the impact of the droplet itself, while the second peak arises from the droplet recoil impact associated with the dynamic properties of the jet. Moreover, we identify a hitherto unknown third pressure peak related to the hydrodynamic singularity that emerges due to the convergence of the fluid during the droplet rebound. This solid fraction-dependent impacting behavior reveals the intricate interplay between droplet dynamics and the underlying surface characteristics, providing valuable insights into the design and optimization of micro/nano structured hydrophobic surfaces for various applications.

High Resolution WRF Modelling of Extreme Heat Events and Mapping of the Urban Heat Island Characteristics in Athens, Greece

In recent decades, large-scale urbanisation has developed rapidly, resulting in significant changes in the local and regional environment and climate. Large metropolitan areas worldwide induce significant changes in local atmospheric circulation and boundary layer meteorology by modifying the underlying surface characteristics and through the emission of anthropogenic heat and pollutants into the atmosphere. We investigate the urban heat island (UHI) characteristics in the city of Athens, Greece, which is one of Europe’s largest metropolitan complexes with a population of approximately 3.7 million inhabitants. The UHI effect is intense due to the city’s size, dense construction, high incident solar radiation, and almost complete lack of natural vegetation, with previous studies suggesting a temperature rise of 4 °C on average in the city centre compared to summer background conditions. We used high-resolution WRF simulations (1-km horizontal grid) driven with ERA5 reanalysis data to produce surface temperature maps in the city of Athens and the surrounding areas (Region of Attiki) during the summer period of 1 July–20 August 2021. Different model parameterizations were tested, both with respect to urban characteristics and physical parameters. The daily minimum and maximum temperatures (Tmin and Tmax) derived from the model were validated against observational data from a dense network of weather stations covering metropolitan Athens and surrounding locations. We further investigate the influence of different meteorological conditions on the UHI gradients as produced by the model and the observational dataset, including the extreme heat wave of 28 July–5 August 2021, during which persistent maximum temperatures of >40 °C were recorded for nine consecutive days. The results indicate a strong correlation between WRF output and recorded minimum and maximum temperatures throughout the test period (R ranges from 0.80 to 0.93), with an average mean absolute bias (MAB) of 1.5 °C, and reveal the intensity and spatiotemporal variability of the UHI phenomenon in the city of Athens, with UHI magnitude reaching 8–9 °C at times. Our work aims to maximise the potential of using high-resolution WRF modelling for simulating extreme heat events and mapping the UHI effect in large metropolitan complexes.

Exploring two-decadal risk variability of drought-flood abrupt alternation in a high-plateau basin

The escalating intensity and frequency of drought-flood abrupt alternation (DFAA) events, intensified by climate change, pose a significant threat to both the eco-environment and human life. Despite their evident impacts, the risk associated with DFAA events has received limited attention. In this study, we present a comprehensive risk assessment model incorporating multifold natural and anthropogenic indicators to analyze the spatiotemporal variations of DFAA risk. Utilizing a DFAA index (DFAAI) based on river flow data from seven monitoring stations spanning 1999 to 2019, we investigate DFAA events in the Dianchi Basin, the largest lake in the Yunnan-Guizhou Plateau, China. Our analysis reveals that 56% of total DFAA events occurred between June and August, with drought-to-flood (DTF) events accounting for 62.5% of DFAA occurrences in the Dianchi Basin. Notably, the intensity and frequency of DFAA events exhibit significant spatial variations across the basin. The hazard, vulnerability, exposure, and disaster defense indices further exhibit substantial spatial discrepancies, with hazard indicators being the most influential, notably the DFAA rate accounting for 72.4% of the overall impact. Spatial correlations in DFAA risk among monitoring stations were found to be low, primarily influenced by variations in meteorological conditions, underlying surface characteristics, and human activities. The findings of this study can offer valuable insights for effective water resource management in an ever-changing environment.

Development of a cellular automata-based distributed hydrological model for simulating urban surface runoff

The present study developed a distributed urban surface runoff model based on the cellular automata framework (CA-DUSRM) to simulate two-dimensional urban surface runoff processes. CA-DUSRM uses an improved nonlinear reservoir algorithm to simulate the generation of surface runoff outflow at grid cell scale and flow interactions among cells. The CA-DUSRM simulation results (total surface runoff and peak discharge) for an asphalt road sub-catchment during different rainfall events were in good agreement with actual measurements of both surface runoff and rainfall processes. The performance of CA-DUSRM was comprehensively and systematically analyzed under different rainfall–terrain scenarios. The results showed that increasing the temporal grain resulted in uncertain simulation results in relation to the rainfall intensity, slope, and terrain undulation employed; and significant spatial grain effects were mainly caused by large terrain undulation changes. Compared with the storm water management model (SWMM), CA-DUSRM performed better overall and was more sensitive to variation in terrain undulation and fluctuations in rainfall. Based on model structure and simulation mechanism perspectives, CA-DUSRM can present the influence of spatially heterogeneous underlying surface characteristics on the runoff processes and describe the lateral water exchanges, which makes the simulated processes closer to the actual processes when compared with SWMM. CA-DUSRM is potentially suitable for application in urban areas that have complex underlying surfaces.

Effect of land surface parameters on meteorology and ozone air quality simulations in the Great Bay Area, China

Land surface parameters play a crucial role in simulations of weather and air quality. This study investigated the impact of underlying surface parameters on meteorological fields and pollutant concentrations in the Greater Bay Area (GBA), China, during warm and cold season. Updated land surface parameters, namely land use type, leaf area index, vegetation fraction, albedo, and roughness length, were incorporated to improve simulations. The model showed 7%–14% improvements (in terms of the index of agreement) in wind speed simulations, whereas temperature and relative humidity were not sensitive to the adoption of updated parameters. Moreover, compared with the model with default parameters, the model with updated natural underlying surface parameters showed a 2–3 m/s reduction in cross-border wind speed during cold season in the GBA. The model also showed a 1–2 m/s increase in the wind speed in urban areas, owing to thermal contrast. During periods in which clean air came from the north, the reduced wind speed hindered ozone removal in the GBA. The use of updated underlying surface parameters enhanced the urban heat island effect by ∼2 K and increased the wind speed over urban areas by ∼2 m/s. The intensified urban heat island circulation generated strong updrafts and intensified sea breezes, promoting the penetration of sea breezes inland. Additionally, the intensified sea breeze and urban heat island circulation contributed to a ∼10-ppb reduction in ozone concentrations. Hence, incorporating the latest land surface parameters improved the simulation of meteorological fields and influenced cross-border pollutant transportation. This study highlights the importance of considering underlying surface characteristics in regional modelling and provides insights for air pollutant management.

Influence of Grain on Green Patterns and Their Underlying Surface Characteristics on Water Conservation: A Case Study in a Semiarid Area

Water-conservation enhancement is a crucial objective of regional ecological restoration projects in arid and semiarid areas, and it is significantly influenced by land use/cover change (LUCC). The Grain for Green Project (GFGP) is a common strategy for ecological restoration. However, insufficient attention has been paid to the impact of reforestation patterns and the underlying surface characteristics on the effectiveness of GFGP in enhancing water conservation. In this study, a Soil and Water Assessment Tool (SWAT) scenario-based simulation was conducted to assess changes in water-conservation depth (WCD) in the Zhangjiakou section of the Guanting Reservoir basin. Redundancy analysis (RDA) and a mixed linear model were employed to determine the effects of different reforestation patterns and their underlying slope gradient and soil-type characteristics on WCD variation. The results showed that there were differences in the effect characteristics of reforestation patterns and different vegetation types on WCD changes; the effectiveness of increased water conservation is associated with the adaptation of reforestation plants to underlying characteristics. Returning farmland to evergreen forests was the most effective approach, leading to a relative increase in WCD that was 2.6 times greater than the relative increase in total WCD. WCD decreased with the slope gradient, with WCD decreasing by 0.2 mm for every 1° increase in slope. Converting grassland to evergreen forests on slopes greater than 16.19° and converting deciduous forests to grassland on slopes less than 16.19° would further increase WCD, promoting the synergistic development of ecosystem services. This study provides insights into the development of more efficient reforestation strategies to enhance water conservation in a complex terrain area.

Analysis of the Changes and Influencing Factors of Evapotranspiration in Fuping County based on Meteorological Data

Using meteorological station data, this paper analyzes the annual evapotranspiration and influencing factors in Fuping County from 1998 to 2017, and explores the dominant meteorological factors that affect the changes in evapotranspiration. The results show that from 1998 to 2017, the annual evapotranspiration in Fuping County showed a significant upward trend, with a growth rate of 9.9mm/a; The correlation between evapotranspiration and meteorological factors on a daily scale shows temperature>pressure>relative humidity>wind speed. There is a positive correlation between NDVI and evapotranspiration, with a correlation coefficient of 0.6693, indicating that surface evapotranspiration in the region is significantly influenced by underlying surface characteristics. Overall, temperature and vegetation are the main factors affecting evapotranspiration changes in Fuping County.

Runoff–Sediment Simulation of Typical Small Watershed in Loess Plateau of China

The implementation of measures such as check dams and terraces in the Loess Plateau of China has had a groundbreaking impact on water and sediment conditions. The question of how to accurately simulate the runoff–sediment process under complex underlying surface conditions has become key to clarifying the water cycle law. This study focused on the Chenggou River basin, a small watershed located in the Loess Plateau, to examine the effect of the underlying surface characteristics on the runoff production process, and the spatial distribution of the dominant runoff process in the runoff generation mechanism was determined according to the land application, slope and vegetation coverage of the watershed. A runoff–sediment model was constructed that was combined with the traditional hydrological physical mechanism and a deep learning algorithm. Different parameters were calibrated depending on the spatial distribution of the dominant runoff process and we then ran the runoff–sediment simulation model to very its serviceability in the typical watershed of the Loess Plateau. Different parameters were calibrated for each type of hydrological response unit (HRU), according to the division of each HRU and the actual flood process, to calculate the runoff yield of each HRU. An LSTM algorithm was used for flow routing and a CSLE algorithm was used to simulate soil erosion. The results show that there were 29 flood events in the Chenggou River basin from 2013 to 2017. The average runoff depth had an 8.86% margin of error, while the peak flow had a slightly higher 9.44% deviation. The Nash efficiency coefficient was 0.84, and the relative error of soil erosion was 14.45%. The model simulation effect is good and can be applied to the typical watershed of the Loess Plateau. The model can provide a scientific basis for the highly efficient and sustainable utilization of water resources, ecological environment construction and the sustainable development of agriculture.

Dependence of Ice Crystal Size Distributions in High Ice Water Content Conditions on Environmental Conditions: Results from the HAIC-HIWC Cayenne Campaign

Abstract A new method that automatically determines the modality of an observed particle size distribution (PSD) and the representation of each mode as a gamma function was used to characterize data obtained during the High Altitude Ice Crystals and High Ice Water Content (HAIC-HIWC) project based out of Cayenne, French Guiana, in 2015. PSDs measured by a 2D stereo probe and a precipitation imaging probe for particles with maximum dimension (Dmax) > 55 μm were used to show how the gamma parameters varied with environmental conditions, including temperature (T) and convective properties such as cloud type, mesoscale convective system (MCS) age, distance away from the nearest convective peak, and underlying surface characteristics. Four kinds of modality PSDs were observed: unimodal PSDs and three types of multimodal PSDs (Bimodal1 with breakpoints 100 ± 20 μm between modes, Bimodal2 with breakpoints 1000 ± 300 μm, and Trimodal PSDs with two breakpoints). The T and ice water content (IWC) are the most important factors influencing the modality of PSDs, with the frequency of multimodal PSDs increasing with increasing T and IWC. An ellipsoid of equally plausible solutions in (No–λ–μ) phase space is defined for each mode of the observed PSDs for different environmental conditions. The percentage overlap between ellipsoids was used to quantify the differences between overlapping ellipsoids for varying conditions. The volumes of the ellipsoid decrease with increasing IWC for most cases, and (No–λ–μ) vary with environmental conditions related to distribution of IWC. HIWC regions are dominated by small irregular ice crystals and columns. The parameters (No–λ–μ) in each mode exhibit mutual dependence.

Estimating the Routing Parameter of the Xin’anjiang Hydrological Model Based on Remote Sensing Data and Machine Learning

The parameters of hydrological models should be determined before applying those models to estimate or predict hydrological processes. The Xin’anjiang (XAJ) hydrological model is widely used throughout China. Since the prediction in ungauged basins (PUB) era, the regionalization of the XAJ model parameters has been a subject of intense focus; nevertheless, while many efforts have targeted parameters related to runoff yield using in-site data sets, classic regression has predominantly been applied. In this paper, we employed remotely sensed underlying surface data and a machine learning approach to establish models for estimating the runoff routing parameter, namely, CS, of the XAJ model. The study was conducted on 114 catchments from the Catchment Attributes and MEteorology for Large-sample Studies (CAMELS) data set, and the relationships between CS and various underlying surface characteristics were explored by a gradient-boosted regression tree (GBRT). The results showed that the drainage density, stream source density and area of the catchment were the three major factors with the most significant impact on CS. The best correlation coefficient (r), root mean square error (RMSE) and mean absolute error (MAE) between the GBRT-estimated and calibrated CS were 0.96, 0.06 and 0.04, respectively, verifying the good performance of GBRT in estimating CS. Although bias was noted between the GBRT-estimated and calibrated CS, runoff simulations using the GBRT-estimated CS could still achieve results comparable to those using the calibrated CS. Further validations based on two catchments in China confirmed the overall robustness and accuracy of simulating runoff processes using the GBRT-estimated CS. Our results confirm the following hypotheses: (1) with the help of large sample of catchments and associated remote sensing data, the ML-based approach can capture the nonstationary and nonlinear relationships between CS and the underlying surface characteristics and (2) CS estimated by ML from large samples has a robustness that can guarantee the overall performance of the XAJ mode. This study advances the methodology for quantitatively estimating the XAJ model parameters and can be extended to other parameters or other models.

Timely Plastic-Mulched Cropland Extraction Method from Complex Mixed Surfaces in Arid Regions

Plastic mulch is extensively applied in agricultural production in arid regions. It significantly influences the interactions between land and atmosphere by altering underlying surface characteristics. An accurate and timely extraction method for Plastic-Mulched Cropland (PMC) is required to understand land surface energy transfer processes, eco-hydrological cycle, the climate effect of PMC, and in the management of water resources. In this study, we proposed a Timely Plastic-mulched cropland Extraction Method (TPEM) from complex mixed surfaces with multi-source remote sensing data in the Shiyanghe River Basin (SRB), a typical representation of a complex and inhomogeneous arid region in the northwest of China. We defined TPEM in three phases; in the first phase, the spectral characteristic curves were drawn from ground object points labeled by visual interpretation with multi-source remote sensing data. In the second phase, a spectral characteristic analysis of the modified index was proposed to amplify the difference between PMC and non-PMC ground objects. Finally, the Classification and Regression Tree (CART) classifier was used to generate thresholds of indices as PMC extraction rules. The results showed that it can extract the boundary of PMC in large-scale farmland, distinguish PMC from ground objects in complex mixed surfaces, and separate the PMC from desert land that shares same spectral characteristics with PMC. The TPEM is verified to be efficient and robust, with an overall accuracy of 0.9234, quantity disagreement of 0.0541, and allocation disagreement of 0.0224, and outperformed two extensively used PMC extraction methods, especially for timely PMC extraction when satellite data only during the period that ground surface incomplete covered by plastic mulch is available. This study will provide us with an accurate and timely method to extract PMC, especially in the widely distributed complex mixed surfaces.

Analysis on the Variation of Hydro-Meteorological Variables in the Yongding River Mountain Area Driven by Multiple Factors

In recent decades, strong human activities have not only brought about climate change including both global warming and shifts in the weather patterns but have also caused anomalous variations of hydrological elements in different basins all around the world. Studying the mechanisms and causes of these hydrological variations scientifically is the basis for the management of water resources and the implementation of ecological protection. Therefore, taking the Yongding River mountain area as a representative watershed in China, the changes of different observed and simulated hydro-meteorological variables and their possible causes are analyzed on an inter-annual scale based on ground based observations and remotely sensed data of hydrology, meteorology and underlying surface characteristics from 1956 to 2016. The results show that the annual natural runoff of Guanting hydrological station in the main stream of the Yongding River, Cetian hydrological station and Xiangshuibao hydrological station in the tributary of the Yongding River all have a significant decreasing trend and abrupt changes, and all the abrupt change points of the annual natural runoff series of the three hydrological stations appear in the early 1980s. On the inter-annual scale, the water balance model with double parameters is unable to effectively simulate the natural surface runoff after the abrupt change points. The annual average precipitation after the abrupt change points decreases by no more than 10%, compared with that before the abrupt change points. However, the precipitation from July to August, which is the main runoff-production period, decreases by more than 25%, besides the intra-annual temporal distribution of precipitation becoming uniform and a significant decrease in effective rainfall, which is the source of the runoff. Meanwhile, the NDVI in the basin show an increasing trend, while the groundwater level and land water storage decrease significantly. These factors do not lead only to the continuous reduction of the annual natural runoff in the Yongding River mountain area from 1956 to 2016, but also result in significant changes of the hydro-meteorological relationship in the basin.

Research on Outdoor Thermal Environment of Campus in Cold Area in Winter with Different Underlying Surfaces

Thermal environment has many influences on people who use outdoor space. The thermal environment of university campus is an important part of educational living space. In campus planning and design, the impact of landscape design on the thermal environment should be considered. This paper measures the thermal environment of the campus of Xi’an Eurasia University and conducts questionnaire survey to obtain the Library and Nanshan Road, East Gate Square and Parking lot 4 different underlying surface characteristics of the impact on the thermal environment. The results show that the SET* correlation of different underlying surfaces: Library> East Gate Square> Nanshan Road > Parking lot. Shade, grassland, and water bodies can effectively reduce the average radiant temperature. Among them, the humidification and cooling effects of the shade are the best, and the cooling ability of the grass is second only to the shade. In the process of campus environment design, reasonable adjustment of the relationship between the shade of the grass and other underlying surfaces can effectively improve the outdoor thermal comfort of the campus in winter and create a comfortable outdoor activity place on the campus.

Flash flood modeling in the data-poor basin: A case study in Matina River Basin

Forecasting flooding hazards is a very effective non-engineering measure for flood control. Presently, the commonly used forecasting method in simulating flash flood events is through a watershed hydrological model. Many Asia-Pacific countries like the Philippines are prone to frequent hydrometeorological hazards such as tropical cyclones, resulting in frequent heavy rainfall events. However, most rivers in the many basins lack water flow observation data, which makes it challenging to use lumped and data-driven models for flash flood forecasting. With the continuous progress of remote sensing (RS) and geographic information system (GIS) techniques, the physically-based distributed hydrological model (PBDHMs) has rapidly advanced. PBDHMs can directly determine the model parameters according to the underlying surface characteristics from remotely-sensed data, which makes it possible for flood forecasting in areas with little to virtually no data. In this study, the Matina River basin in Davao City was selected as a case study in simulating a small data-poor basin in the region. The Liuxihe model was used to formulate a forecasting scheme and simulated the past flash flood events. The results show that there is a good correspondence between the past heavy rainfall events and their corresponding simulated river discharges. The results conform to the hydrological regularities, which can be used for flood forecasting and can serve as a baseline for the development of a flood forecasting system in the rivers of Davao City and elsewhere.

Application of HEC-HMS Parameter Regionalization in Small Watershed of Hilly Area

To explore the applicability of HEC-HMS and its parameter regionalization in small ungauged watersheds in hilly areas, this paper takes hydrological divisions III and IV of Henan Province as the research area. The HEC-HMS model is applied to three typical small watersheds in Luanchuan, Gaocheng and Xiahecun. On the basis of verifying the validity of the model, the regression relationships between model parameters and underlying surface characteristics are established and verified in the Zhongtang small watershed. The results show that the qualified rates of runoff depth, flood peak flow, peak occurrence time and NSE in flood simulation are higher than 75%, and the accuracy reaches the grade B level regardless of the HEC-HMS model test or the parameter regionalization method verification. In summary, the HEC-HMS model can be applied to simulate the rainfall-runoff process of small watersheds in hilly areas, and the parameter regionalization method can effectively deduce the model parameters of HEC-HMS for small ungauged watersheds in hilly areas.

Study on relationship between underlying surface of typical warping dam and erosion and sediment yield

Under the condition of rainstorm, the underlying surface is an important factor of erosion and sediment yield, and an important embodiment of the process of soil erosion and the law of sediment deposition. This paper analyzes the soil erosion of warping dams with different underlying surface characteristics based on the data of typical warping dams, such as sedimentation amount, sediment retention modulus and underlying surface. The results show that: (1) the average slope of dam55, dam97 and dam011 is 27.55°, 30.79° and 34.68° respectively, and the erosion modulus is 11020t/km2, 15204 t/km2 and 22579 t/km2 respectively; the average slope of dam55, dam97 and dam011 is positively correlated with the erosion modulus, and the correlation coefficient is 0.9889. (2) The sedimentation depth and erosion modulus of dam011 are significantly higher than those of dam55 and dam97. Under the condition of rainstorm, the average slope of watershed is an important factor of soil erosion, which can better reflect and predict the comprehensive intensity of soil erosion.

Uncertainty analysis of eleven multisource soil moisture products in the third pole environment based on the three-corned hat method

Soil moisture (SM) is a fundamental environmental variable for characterizing climate, land surface and atmosphere. In recent years, several SM products have been developed based on remote sensing (RS), land surface model (LSM) or land data assimilation system (LDAS). However, little knowledge is available in understanding spatial patterns of the uncertainty of different SM products and potential regional drivers over the Qinghai-Tibet Plateau (QTP), a complex environment for accurate SM estimation. This paper investigates the sensitivity of the SM uncertainties based on the three-cornered hat (TCH) method and a generalized additive model (GAM) in terms of underlying surface characteristics (sand fraction, soil organic matter, vegetation, land surface temperature, and topography) and near-ground meteorology (precipitation and air temperature) in the third pole environment over the 2015–2018 period. Eleven SM products are involved in this work, including Soil Moisture Active Passive (SMAP), Soil Moisture Ocean Salinity INRA-CESBIO (SMOS-IC), Japan Aerospace Exploration Agency (JAXA), Land Surface Parameter Model (LPRM), Climate Change Initiative - Active/Combined (CCI_A/CCI_C), Global Land Data Assimilation System (GLDAS), European Centre for Medium-Range Weather Forecasts Interim reanalysis (ERA-Interim), Global Land Evaporation Amsterdam Model product a/b (GLEAM_a/GLEAM_b), and Random Forest Soil Moisture (RFSM). Results show that most of the SM products perform well across QTP, while SMOS-IC is strongly affected by radio-frequency interference in this region, JAXA has a relatively higher noise level over QTP, and LPRM has larger relative uncertainties (RUs) in the southeast of QTP. Nonlinear regression analysis demonstrates that variations of RUs in SMOS-IC and JAXA are driven by topography, while LPRM's are mainly controlled by vegetation. In addition, two groups of opposite (positive/negative) effects from topography and vegetation, topography and precipitation, and precipitation and land surface temperature affect the spatial variations of RUs in CCI_A, RFSM, and ERA-Interim, respectively. Meanwhile, more complex relationships are found between multiple surface factors and RUs of different products. In general, the underlying surface factors explain on average 39.41% and 28.34% of the variations in RS and LSM/LDAS SM RUs, respectively. Comparatively, the near-ground meteorology factors have a slightly larger effect on LSM/LDAS products than that on RS products.