ALBERT

Description: Structured diffuse auroras are often observed near magnetic local noon (MLN) but their generation mechanisms are poorly understood. We have found that two types of structured diffuse auroras with obviously different dynamical properties often coexist near MLN. One type usually drifts from low to high latitude with higher speed and shows pulsation. The other type is always adjacent to the discrete aurora oval and drifts together with nearby discrete aurora with much lower speed. Using coordinated observations from MMS and ground all-sky imagers, we found that the two types of diffuse auroras are well correlated with number density increase of O + (from the ionosphere) and of He 2+ (from magnetosheath) ions, respectively. These observations indicate that mangetosheath particles penetrated into the magnetosphere also can play important role for producing the dayside diffuse aurora. In addition, for the first time, electron cyclotron harmonic (ECH) waves are observed associated with dayside diffuse aurora.

Description: Water availability is one of the most important environmental controls on vegetation phenology, especially in semi-arid regions. It is often represented in terms of soil moisture in small-scale studies, whereas it tends to be represented by precipitation in large-scale (e.g., regional) studies. Clearly, soil moisture is the more appropriate indicator for root water uptake and vegetation growth/phenology. Its potential advantage and applicability needs to be demonstrated at regional scales. The paper presents a data-based regional study of the effectiveness of novel water and temperature-based indices to predict spring vegetation green-up dates based on the Normalized Difference Vegetation Index (NDVI) observations in the grasslands of Inner Mongolia, China. The macro-scale hydrological model, VIC (Variable Infiltration Capacity), is employed to generate a soil moisture database across the region. In addition to a standard index based on temperature, two potential hydrology-based indices for prediction of spring onset dates are defined, based on the simulated soil moisture data as well as on observed precipitation data. Results indicate that the correspondence between the NDVI-derived green-up onset date and the soil-moisture-derived potential onset date exhibits a significantly better correlation as a function of increasing aridity compared to that based on precipitation. In this way the soil-moisture-based index is demonstrated to be superior to the precipitation-based index in terms of capturing grassland spring phenology. The results also showed that both of the hydrological (water-based) indices were superior to the thermal (temperature-based) index in determining the patterns of grass green-up in the Inner Mongolia region, indicating water availability to be the dominant control on average. The understanding about the relative controls on grassland phenology and the effectiveness of alternative indices to capture these controls are important for future studies of vegetation phenology change under climate change.

Description: Hydrological modeling can exploit informative signatures extracted from long time sequences of observed streamflow for parameter calibration and model diagnosis. In this study we explore the diagnostic potential of hydrograph partitioning for model calibration in mountain areas, where meltwater from snow and glaciers is an important source for river runoff (in addition to rainwater). We propose an index-based method to partition the hydrograph according to dominant runoff water sources, and a diagnostic approach to calibrate a mountain hydrological model. First, by accounting for the seasonal variability of precipitation and the altitudinal variability of temperature and snow/glacier coverage, we develop a set of indices to indicate the daily status of runoff generation from each type of water source (i.e., glacier meltwater, snow meltwater, rainwater, and groundwater). Second, these indices are used to partition a hydrograph into four parts associated with four different combinations of dominant water sources (i.e., groundwater, groundwater + snow meltwater, groundwater + snow meltwater + glacier meltwater, and groundwater + snow meltwater + glacier meltwater + rainwater). Third, the hydrological model parameters are grouped by the associated runoff sources, and each group is calibrated to match the corresponding hydrograph partition in a stepwise and iterative manner. Similar to use of the regime curve to diagnose seasonality of streamflow, the hydrograph partitioning curve based on a dominant runoff water source (more briefly called the partitioning curve, not necessarily continuous) can serve as a diagnostic signature that helps relate model performance to model components. The proposed methods are demonstrated via application of a semi-distributed hydrological model (THREW, Tsinghua Representative Elementary Watershed) to the Tailan River basin (TRB) (1324 km2) in the Tianshan Mountains of China. Results show that the proposed calibration approach performed reasonably well. Cross-validation and comparison to an automatic calibration method indicated its robustness.

Description: Water availability is one of the most important environmental controls on vegetation phenology, especially in semi-arid regions, and is often represented in terms of soil moisture in small-scale studies whereas it tends to be represented by precipitation in large-scale (e.g. regional) studies. Clearly, soil moisture is the more appropriate indicator for root water uptake and vegetation growth/phenology and therefore its potential advantage and applicability needs to be demonstrated at regional scales. This paper represents a data-based regional study of the effectiveness of alternative indices based on water and energy availability on space-time patterns of spring vegetation green-up onset dates estimated from Normalized Difference Vegetation Index (NDVI) datasets in the grasslands of Inner Mongolia, China. The macro-scale hydrological model, VIC, is employed to generate a soil moisture database across the region. In addition to standard index based on temperature, two potential hydrology based indices for prediction of spring onset dates are defined based on the simulated soil moisture data as well as on observed precipitation data. Results indicate that the correspondence between the NDVI-derived green-up onset date and the soil moisture derived potential onset date exhibits a significantly better correlation as a function of increasing aridity, compared to that based on precipitation. In this way the soil moisture based index is demonstrated to be superior to the precipitation based index in terms of capturing grassland spring phenology. The results also showed that both of the hydrological (water based) indices were superior to the thermal (temperature based) index in determining the patterns of grass green-up in the Inner Mongolia region, indicating water availability to be the dominant control, on average. The understanding about the relative controls on grassland phenology, and the effectiveness of alternative indices to capture these controls, are important for future studies and predictions of vegetation phenology change under climate change.

Description: Hydrological modeling can exploit informative signatures extracted from long time sequences of observed streamflow for parameter calibration and model diagnosis. In this study we explore the diagnostic potential of hydrograph partitioning for model calibration in alpine areas, where meltwater from snow and glaciers are important sources for river runoff (in addition to rainwater). We propose an index-based method to partition the hydrograph according to dominant runoff water sources, and a diagnostic approach to calibrate an alpine hydrological model. First, by accounting for the seasonal variability of precipitation and the altitudinal variability of temperature and snow/glacier coverage, we develop a set of indices to indicate the daily status of runoff generation from each type of water source (i.e. glacier meltwater, snow meltwater, rainwater, and groundwater). Second, these indices are used to partition a hydrograph into four parts associated with four different combinations of dominant water sources (i.e. groundwater, groundwater + snow meltwater, groundwater + snow meltwater + glacier meltwater, groundwater + snow meltwater + glacier meltwater + rainwater). Third, the hydrological model parameters are grouped by the associated runoff generation mechanism, and each group is calibrated to match the corresponding hydrograph partition in a stepwise and iterative manner. Similar to use of the regime curve to diagnose seasonality of streamflow, the hydrograph partitioning curve based on a dominant runoff water source (more briefly called the partitioning curve, not necessarily continuous) can serve as a diagnostic signature that helps relate model performance to model components. The proposed methods are demonstrated via application of a semi-distributed hydrological model (THREW) to the Tailan River basin (1324 km2) in the Tianshan Mountain of China.

Description: Hydrological modeling depends on single- or multiple-objective strategies for parameter calibration using long time sequences of observed streamflow. Here, we demonstrate a diagnostic approach to the calibration of a hydrological model of an alpine area in which we partition the hydrograph based on the dominant runoff generation mechanism (groundwater baseflow, glacier melt, snowmelt, and direct runoff). The partitioning reflects the spatiotemporal variability in snowpack, glaciers, and temperature. Model parameters are grouped by runoff generation mechanism, and each group is calibrated separately via a stepwise approach. This strategy helps to reduce the problem of equifinality and, hence, model uncertainty. We demonstrate the method for the Tailan River basin (1324 km2) in the Tianshan Mountains of China with the help of a semi-distributed hydrological model (THREW).

Description: A multi-scale, multi-technique study was conducted to measure evapotranspiration and its components in a cotton field under mulched drip irrigation conditions in northwestern China. Three measurement techniques at different scales were used: photosynthesis system (leaf scale), sap flow (plant scale), and eddy covariance (field scale). The experiment was conducted from July to September 2012. To upscale the evapotranspiration from the leaf to the plant scale, an approach that incorporated the canopy structure and the relationships between sunlit and shaded leaves was proposed. To upscale the evapotranspiration from the plant to the field scale, an approach based on the transpiration per unit leaf area was adopted and modified to incorporate the temporal variability in the relationships between leaf area and stem diameter. At the plant scale, the estimate of the transpiration based on the photosynthesis system with upscaling was slightly higher (18%) than that obtained by sap flow. At the field scale, the estimates of transpiration derived from sap flow with upscaling and eddy covariance shown reasonable consistency during the cotton open boll growth stage when soil evaporation can be neglected. The results indicate that the upscaling approaches are reasonable and valid. Based on the measurements and upscaling approaches, evapotranspiration components were analyzed under mulched drip irrigation. During the two analysis sub-periods in July and August, evapotranspiration rates were 3.94 and 4.53 mm day−1, respectively. The fraction of transpiration to evapotranspiration reached 87.1% before drip irrigation and 82.3% after irrigation. The high fraction of transpiration over evapotranspiration was principally due to the mulched film above drip pipe, low soil water content in the inter-film zone, well-closed canopy, and high water requirement of the crop.