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A reasonable assessment of the hydrological regime alteration is a prerequisite for river utilization, restoration, and protection. The hydrological alteration is quantified as changes in different indicators (IHAs) identified by Range of Variability Approach (RVA). However, RVA is unable to reveal the morphological characteristic which demonstrates the overall hydrological regime. This will lead to an incomplete assessment of the hydrological alteration. To supplement the current assessment, this work proposed a revised RVA method in three main steps: (1) to identify the morphological characteristics of each IHA; (2) to quantify the morphological alteration by comparing the Hasse matrices of different time series; (3) to combine the frequency alteration and morphological alteration of IHAs for reflecting overall hydrological alteration. A case study of the upper Yellow River shows that the revised RVA method outperforms RVA in the assessment of the hydrological regime not only because revised RVA captures the hydrological changes of certain IHAs that are not reflected by conventional RVA, but also the alteration identified by revised RVA shows more apparent differences at two stations upstream and downstream the dam than conventional RVA can provide. The revised RVA is more applicable to identify the hydrological alteration due to dam construction which could have negative impacts on river ecosystem since the morphological alteration of time series is considered. As a whole, the new method offers a better understanding of the alteration in hydrological regime, which gives beneficial guidance to river management.

Generalized likelihood uncertainty estimate (GLUE) approach is affected heavily by the choice of cut-off threshold (Tr) and likelihood measure. This work presents a research on investigating potential mechanisms behind the impacts of Tr and likelihood measure on 95% confidence interval estimated by GLUE (95 CI). Several typical likelihood measures are classified into five groups according to error models. Theoretical analysis reveals strict mathematical relationships between likelihood measures based on a same error model. Besides, a multiple attribute decision making (MADM) framework is proposed to assess overall quality of various geometrical features for 95 CI by integrating a range of interval indicators into a comprehensive score. Case studies indicate that (1) As Tr increases, 95 CI widens in low-level flow section, moves upward in recession phase of medium-level flow section and narrows in high-level flow section. The variations of interval indicators with Tr can be attributed to trade-off mechanism amongst the variations of geometrical features caused by widening, moving and narrowing trends of 95 CIs. (2) Much higher similarity in interval indicators and 95 CIs occurs for likelihood measures of a same group than those of different groups. (3) Formula of likelihood measure controls individuality of 95 CIs, error model of likelihood measure controls commonality of 95 CIs, and Tr acts as a regulator between individuality and commonality. (4) 95 CI shows similar responses to the choice of Tr and likelihood measure regardless of time span and climate variability. To summarize, this work offers further understanding and guidance in chose of Tr and likelihood measure for GLUE applications.

Commercial microwave link (CML) has become one of the most widely used opportunistic sensors for rainfall monitoring. The high density and coverage of CMLs enable us to monitor near‐ground rainfall in high spatial resolution. The empirical power‐law (PL) model proposed in 1978 is the leading approach in relating CML attenuation with rain rate. However, while giving good rain rate estimates for CMLs longer than 1 km, in short CMLs, large errors are observed when the PL approach is applied. In this paper, we studied a statistical approach to convert CML attenuation measurement to rainfall intensity. The proposed approach calculates the exceedance probability, p, of rain‐induced attenuation and derives the corresponding rainfall intensity based on the rain rate cumulative distribution curve. Data from two cities in two countries were used to validate the approach. The results of the proposed approach were compared with that of the PL model. Results show that the models derived using our approach outperform PL for short CMLs, while showing similar performance for long ones. Since in the next generation mobile networks short CMLs will become more and more dominant, our work provides a way to derive retrieval models for the future generation CML networks. Plain Language Summary Using commercial microwave link (CML) network for rainfall monitoring can provide us data in high spatial‐temporal resolution. However, the most widely used retrieval model for CML measurements may result in overestimation when applied to short links. To address this issue, this paper investigates an alternative approach to retrieve rainfall intensity from CML measurements, which also demonstrates favorable performance when applied to short links. As short links are expected to become increasingly prevalent in the next generation of mobile networks, their usage can greatly enhance the spatial resolution and accuracy of rainfall monitoring outcomes. Key Points Investigating a statistical approach to retrieve rainfall intensity from commercial microwave link (CML) data The statistical models show better performance for short CMLs Parameters of the statistical model can be transferred from other regions

As a water absorption material, superabsorbent polymer (SAP) has gained its popularity in agriculture and environmental remediations. This study conducted a comparative investigation on saturated water content of cinnamon soil mixed with SAP. Two SAPs, SAP1 and SAP2, with different behaviors were tested, where SAP1 is an organic superabsorbent polymer, and SAP2 is polyacrylic acid sodium salt polymer. The saturated water content of SAP composite cinnamon soil was investigated with the weighing method. The repeated water absorption capacity and dehydration behavior of SAP composite soil under different designed rainfall intensity were investigated with a soil column tester. The results showed that (1) cinnamon soil mixed with SAP increased the saturated soil water content, and SAP1 was more effective than SAP2; (2) SAP held strong water absorption ability and recycling efficiency with eight repeated absorption–dehydration tests; (3) the average dehydration time for SAP composite soil were 626 h and 1214 h under 5-year and 10-year design rainfall intensities.

The absence of aggregated uncertainty measures restricts the assessment of uncertainty in hydrological simulation. In this work, a new composite uncertainty measure is developed to evaluate the complex behaviors of uncertainty existing in hydrological simulation. The composite uncertainty measure is constructed based on a framework, which includes three steps: (1) identification of behavioral measures by analyzing the pairwise correlations among different measures and removing high correlations; (2) weight assignment by means of a new hierarchical weight assembly (HWA) approach incorporating the intra-class and inter-class weights; (3) construction of a composite uncertainty measure through incorporating multiple properties of the measure matrix. The framework and the composite uncertainty measure are demonstrated by case studies in uncertainty assessment for hydrological simulation. Results indicate that the framework is efficient to generate a composite uncertainty index (denoted as CUI) and the new measure CUI is competent for uncertainty evaluation. Besides, the HWA approach performs well in weighting, which can characterize subjective and objective properties of the information matrix. The achievement of this work provides promising insights into the performance comparison of uncertainty analysis approaches, the selection of proper cut-off threshold in the GLUE method, and the guidance of reasonable uncertainty assessment in a range of environmental modelling.

The partial runoff is complicated in semi-arid and some semi-humid zones in terms of what the runoff generates in partial vertical positions. The partial runoff is highlighted by horizontal soil heterogeneity as well. How to identify the partial runoff and develop a variable threshold for runoff generation is a great difficulty and challenge. In this work, the partial runoff is identified by using a variable active runoff layer structure, and a variable soil water storage capacity is proposed to act as a threshold for runoff generation. A variable layer-based runoff model (VLRM) for simulating the complex partial runoff was therefore developed, using dual distribution curves for variable soil water storage capacity over basin. The VLRM is distinct in that the threshold for runoff generation is denoted by variable soil water storage capacity instead of infiltration capacity or constant soil water storage capacity. A series of flood events in two typical basins of North China are simulated by the model, and also by the Xinanjiang model. Results demonstrate that the new threshold performs well and the new model outperforms the Xinanjiang model. The approach improves current hydrological modelling for complex runoff in regions with large deficiencies in soil water storage.

Auxin response factors (ARFs) encode transcriptional factors that function in the regulation of plant development processes. A tomato ARF gene, SlARF5 , was observed to be expressed at high levels in emasculated ovaries but maintained low expression levels in pollinated ovaries. The ami RNA SlARF5 lines exhibited ovary growth and formed seedless fruits following emasculation. These parthenocarpic fruits developed fewer locular tissues, and the fruit size and weight were decreased in transgenic lines compared to those of wild-type fruits. Gene expression analysis demonstrated that several genes involved in the auxin-signaling pathway were downregulated, whereas some genes involved in the gibberellin-signaling pathway were enhanced by the decreased SlARF5 mRNA levels in transgenic plants, indicating that SlARF5 may play an important role in regulating both the auxin- and gibberellin-signaling pathways during fruit set and development.

When coal and crude oil are associated, the immersion of crude oil affects the microstructure changes in coal oxidation process. In this work, thermogravimetric and in situ infrared spectroscopy experiments were used to study the oxidation characteristics and active functional groups evolution of oil-immersed coal. Results showed that the crude oil in coal slows down the oxidation process of coal and considerably affects weight gain phase due to O absorption. Considering crude oil O consumption and O attack on the active group methylene, the change law of methylene (2923 cm−1) with temperature can be used to represent the evolution of Aliphatic Functional Groups when the oil content is less than 10%. The characteristic demarcation point of the evolution rule of the active groups of coal with different oil ratios is 270 °C. The aromatic C = C of raw coal and 25% oil content coal samples satisfied the quadratic curve change relationship.

China’s natural gas demand is growing under the “dual carbon” goal. However, the peaking capacity of gas storage remains insufficient. Oil reservoir-based underground gas storage (UGS) has, thus, emerged as a critical research focus due to its potential for efficient capacity expansion. The complexity of seepage and phase change characteristics during the multi-cycle injection–production process has not been systematically elucidated. This study combines experimental and numerical simulations to examine the seepage and phase change characteristics. This study innovatively reveals the synergistic mechanism of permeability, pressure, and cycle. The control law of multi-factor coupling on the dynamic peaking capacity of UGS is first expounded. Oil–water mutual drive reduced oil displacement efficiency by 2.5–4.7%. Conversely, oil–gas mutual drive improved oil displacement efficiency by 3.0–4.5% and storage capacity by 4.7–6.5%. The fifth-cycle oil–gas mutual displacement in high-permeability cores (74 mD) under high pressure (22 MPa) exhibited reductions in irreducible water saturation (7.06 percentage points) and residual oil saturation (6.38 percentage points) compared with the first-cycle displacement in low-permeability cores (8.36 mD) under low pressure (16 MPa). Meanwhile, the gas storage capacity increased by 13.44 percentage points, and the displacement efficiency improved by 10.62 percentage points. Multi-cycle huff-and-puff experiments and numerical simulations revealed that post-depletion multi-cycle huff-and-puff operations can enhance the oil recovery factor by 2.74–4.22 percentage points compared to depletion. After five-cycle huff-and-puff, methane content in the produced gas increased from 80.2% to 87.3%, heavy components (C8+) in the remaining oil rose by 2.7%, and the viscosity of the remaining oil increased from 2.0 to 4.6 mPa·s. The deterioration of the physical properties of the remaining oil leads to a reduction in the recovery factor in the cycle stage. This study elucidates seepage mechanisms and phase evolution during multi-cycle injection–production, demonstrating the synergistic optimization of high-permeability reservoirs and high-pressure injection techniques for enhanced gas storage design and efficiency.