Hydrological Processes最新文献

Stream sediment transport results from a convolution of climate, weather, geology, topography, biology, and human influence. In addition to providing water and food security for rural dryland communities, sand dams—small weirs designed to trap only the coarse fractions of transported sediments in seasonal and ephemeral streams—highlight many complexities of geomorphological dynamics. Sand dams store water in interstitial riverbed pores and the size of deposited sediment particles largely determines the recoverability of stored water: Fine materials limit transmission and provide lower volumetric yield. In this study, we seek to identify a practical method for evaluating the theoretical effect of staged sand dam crest construction on key sediment-trapping processes for a proposed dam site. We argue that the Rouse number provides a useful criterion for identifying regimes where the target material grades are trapped. These ideas were tested using sediment data collected in Kenya and US Army Corps of Engineers River Analysis System numerical simulations to evaluate the sensitivity of sedimentation processes to crest height. We show that constructing sand dams in stages results in more targeted trapping of coarse material. Sedimentation is shown to be more sensitive to variation in crest height than the flood hydrograph, especially when a dam's crest height is small. By introducing a method to assess the necessity and inform design of staged crest construction based on local flow dynamics, this study offers a framework for optimising sand dam performance in data-scarce environments. This approach provides a means to balance construction costs with expected benefits, enhancing the sustainability and functionality of sand dams in arid and semi-arid regions.

Land surface models (LSMs) are used to simulate the terrestrial component of water, energy, and biogeochemical cycles. These simulations are useful for water resources management, drought and flood prediction, and numerical climate/weather prediction. However, the usefulness of LSMs are dependent by their ability to reproduce states and fluxes realistically. Accurate measurements of water storage are useful to calibrate and validate LSMs outputs. Geological weighing lysimeters (GWLs) are instruments that can provide field-scale estimates of integrated total water storage within a soil profile. We use field estimates of total water storage and subsurface storage to critically evaluate two different land surface models: the Modélisation Environnementale communautaire—Surface Hydrology (MESH) which uses the Canadian Land Surface Scheme (CLASS), and the Structure for Unifying Multiple Modeling Alternatives: (SUMMA). These models have differences in how the processes and properties of the land surface are represented. We attempted to parameterize each model in an equivalent manner, to minimize model differences. Both models were able to reproduce observations of total water storage and subsurface storage reasonably well. However, there were inconsistencies in the simulated timing of snowmelt; depth of soil freezing; total evapotranspiration; partitioning of evaporation between soil evaporation and evaporation of intercepted water; and soil drainage. No one model emerged as better overall, though each model had specific strengths and weaknesses that we describe. Insights from this study can be used to improve model physics and performance.

Soil water is a crucial factor for the growth of vegetation and sustainable development in water-limited areas. After large-scale vegetation restoration on the Chinese Loess Plateau, understanding the relationship between vegetation and deep soil moisture has become a crucial focus in current research. In this study, artificial forest (Pinus tabulaeformis [PT], Robinia pseudoacacia [RP] and Platycladus orientalis [PO]), apple orchard (AO), secondary forest (SF) and farmland (FL) were selected as the research objects, and grassland (GL) as the control, using soil-drilling techniques. We systematically monitored the soil water content of 0–10 m soil layer over two hydrological years, and explored the effects of different vegetation types on soil water deficiency. The results showed that: (1) The deep soil water various significantly among different vegetation types. Compared with GL, the soil water content in all forest land was generally lower, and this difference became more pronounced in deeper soil layer (>7 m), which indicating the depth of the influence of vegetation on soil water has reached 10 m. (2) The mean soil water deficit size (SWDS) values of PT (0.14), RP (0.17), PO (0.07), AO (0.15), SF (0.10) and FL (0.27) in 0–1 m were all positive, indicating that surface soil water had accumulated during more than half of the sampling periods. In the 2–10 m soil layer, mean SWDS was negative in all vegetation types except in FL, leading to soil desiccation. SWDS was found to fluctuate with soil depth. (3) SWDS was affected by a combination of soil properties and vegetation growth. Our results indicate that the current afforestation model could lead to the deficiency of deep soil water. Therefore, it is imperative to make reasonable vegetation structure according to the available local soil and water resources in future vegetation allocation and management.

Seawater intrusion (SWI) is threatening coastal aquifers and farmland productivity worldwide. Although this phenomenon naturally occurs in coastal areas, it is intensified by anthropogenic activities such as groundwater pumping and land reclamation that cause a lowering of the hydraulic head and land subsidence. Moreover, the consequences of climate change such as sea level rise, increase of the mean temperature and the shifting of rainfall events to tropical regimes, have strong negative effects on groundwater quality and agriculture. Countermeasures against SWI are needed to maintain agricultural productivity and protect the freshwater resources in coastal areas. In the low-lying farmlands surrounding the southern Venice Lagoon, in northern Italy, SWI is exacerbated by land subsidence, the presence of sandy paleochannels connected to the lagoon subsurface, seawater encroachment into the river estuaries, the presence of fossil brine waters and peat deposits. This study provides a detailed hydrogeological and geochemical characterisation of an experimental agricultural field affected by SWI located in this area using a large dataset collected over the 4 years between 2019 and 2022. Furthermore, it presents the results of novel intervention established across the farmland in 2021 to mitigate saltwater contamination. This intervention involved a controlled discharge of freshwater supplied by a reclamation channel through a 200 m-long drainpipe buried 1.5 m below the field surface along a well-preserved sandy paleochannel. The interpretation of the collected data demonstrates that the freshwater recharge carried out in 2021 and 2022 effectively reduced the groundwater salinity along the paleochannel. Moreover, statistical analyses highlighted that a certain lateral spread of freshwater occurred too, although the variability of the monitored parameters in the sites located outside the sandy body was only partially explained by the drain activity.

Understanding plant-water relations is essential for effective regional water management and promoting ecologically sustainable development on the Loess Plateau, especially in the context of the Grain for Green project initiated in 1999. This study evaluated the variations in vegetation variables (leaf area index, enhanced vegetation index, solar-induced chlorophyll fluorescence and gross primary production) and hydroclimatic variables (precipitation, total water storage, aridity index and standardized precipitation evapotranspiration index) from 2003 to 2020, along with their interactions across the Loess Plateau. Our analysis revealed a general increase in vegetation variables, with the largest increase observed in the forest expansion areas. Precipitation and the aridity index exhibited significant upwards trends, while total water storage showed a significant decline, particularly in the forest expansion areas. Vegetation variables were more sensitive to changes in total water storage across the Loess Plateau. In the northwest region, where large-scale croplands and grasslands expansion occurred, vegetation variables also showed sensitivity to precipitation. Lag effect analysis revealed short time lags (1–3 months) between vegetation and hydroclimatic variables, expect for total water storage (6 months). Overall, human activities and climate factors contributed 58.4% and 41.6% to the increase in leaf area index, and 52.2% and 47.8% to the increase in gross primary production, respectively. In relatively arid environments, precipitation contributed over 50% to the observed vegetation greening. This study underscores the increasingly significant role of human activities in driving vegetation greening on the Loess Plateau, particularly in large-scale afforestation areas.

Distributed, coupled surface-groundwater hydrologic models are high-dimensional, given the necessity to reflect the spatially diverse nature of complex hydrologic processes. Furthermore, inverse/inference problems involving these high-dimensional models are naturally ill-posed, given the limited information content of state observations that are typically assimilated. Many inversion/inference algorithms do not cope well with high dimensionality, leaving the practitioner to make subjective choices related to uncertain model inputs. The objective of this study is to evaluate the impact of these subjective calibration choices within a formal sensitivity analysis, uncertainty analysis, and parameters estimation (SA-UA-PE) framework on model testing for a surface-subsurface hydrologic model. In doing so, we address the concepts of ‘over-parameterisation’ and ‘under-parameterisation’. We completed a series of numerical experiments, testing several otherwise subjective aspects of the calibration process: (1) the number (5, 10, 15, 20) and type (soil, aquifer, land surface, channel) of calibration parameters selected); (2) the type of state observations assimilated (streamflow, groundwater head); and (3) the length of testing period (1 to 14 years), using monthly streamflow and groundwater head as testing data. The experiments were completed for models of the Winnebago River watershed (Minnesota, Iowa), (significant tile drainage) and the Nanticoke River watershed (Delaware, Maryland (significant groundwater-channel interactions). The selected hydrologic model is SWAT+, using the gwflow module for physically based groundwater storage and flow modelling, and simulations are run for the 2000–2015 period. Through this process, we found that increasing the number of parameters from 5 to 15 improves the representation of streamflow, principally through an improvement of groundwater storage representation and baseflow generation, but minimal improvement when increasing to 20 parameters. Therefore, the SA-UA-PE process can be optimised based on an ideal number of parameters that yield adequate results while maintaining a lower computational burden. The method presented here can be used for any watershed, using integrated surface-subsurface hydrologic models.