Journal of Hydrology-Regional Studies最新文献

Study region

Tropical watershed in the Colombian Andes, the Chico River (CR) watershed.

Study focus

Hydrological models are widely used to project the impacts of LULC (Land Use/Land Cover) change on water budget. However, their ability to produce reliable predictions depends on how accurately they represent the role of vegetation in the watershed’s water balance. We analyze how different representations of Leaf Area Index (LAI) affect streamflow responses to LULC change using the Soil and Water Assessment Tool (SWAT) model. We also examine streamflow response to 100 % pasture cover (PAS), 100 % forest cover (FOR), and a control scenario using the original SWAT model, SWAT-T, and a proposed new variant (SWAT-Tb), which improves LAI bimodal representation for tropical regions.

New hydrological insights for the region

SWAT-T and SWAT-Tb reproduce observed LAI and streamflow in the CR watershed. However, SWAT-T restricts LAI simulation to unimodal seasonality, while the original SWAT reproduces streamflow but not LAI seasonality. Results using SWAT-T (unimodal LAI) and SWAT-Tb (constant and bimodal LAI) show streamflow increases during the dry seasons for the FOR scenario and decreases for the PAS scenario. Conversely, the original SWAT, with its default LAI representation, tends to underestimate and overestimate streamflow changes in the FOR and PAS scenarios, respectively. Our results highlight that an unrealistic LAI representation can mislead LULC change impact assessments on streamflow in the tropical Andes.

Acacia mearnsii and Eucalyptus dunnii plantations play an important role in the South African economy as a source for a variety of wood products. However, these species are commonly associated with high evapotranspiration (ET) which may cause streamflow reduction, affecting downstream water users who are reliant on the stream for survival. The potential future increase in exotic plantations worldwide necessitates understanding the impact of these different species on the water balance, hence the streamflow. At the Two Streams research catchment in South Africa, intense hydrological observations (streamflow, ET and weather) have been conducted on A. mearnsii for almost two decades. In 2018, the catchment was clear-felled with subsequent replanting of E. dunnii and hydrological measurements continued. This provided an opportunity to present observations of the surface water balance of the catchment. However, gaps in the data at various times prevented a compilation of a continuous hydrological record. Therefore, three window periods, with complete records of streamflow, ET and precipitation, and with similar weather conditions, were compared. Only the interception loss (I_l) was estimated using the Von Hoyningen-Huene method. First window, A. mearnsii trees were three years old (Amear₃), second window, A. mearnsii trees were seven years old (Amear₇) and the third window, E. dunnii trees were three years old (Edun₃). Results indicated a negative catchment surface water balance for all window periods. During the Amear₇ window period, the I_l was highest compared to the young crops, which reduced effective precipitation, in turn contributing to the lowest measured streamflow. The negative surface water balance and high ET, suggests that trees were accessing water not quantified in the surface water balance. Crops of all three window periods were found to have the potential to significantly reduce the streamflow, which may in turn affect downstream water users. Further research using isotopes to trace the sources of water used by trees in the system is suggested.

Study region

South-east Mediterranean France

Study focus

Urbanisation and climate change are producing unprecedented flood risks. Urbanisation increases storm peak discharge and flooded area. Building in the flood plain exposes more people and infrastructure to floods. This study examines the impact of urbanisation over 3 decades (1988/90–2020) on flood risk in SE France. Building footprint layers were used to quantify urban growth, and peak discharge and flooded area were modeled for 3 12-hr rainfall events: 80 mm, 140 mm, and 200 mm. Building growth ranged from 28 % to 65 %. Total imperviousness grew at a rate that was equal to or greater than built area. The relative increase in peak discharge was greatest for the 80-mm event (+12.2 %) and diminished to its lowest value for the 200-mm event (+2.4 %).

New hydrological insights for the region

Flooded area increased proportionately to changes in peak discharge, but mean growth in flooded building footprint area was almost 43 times greater than growth in flooded area. New buildings within the flooded perimeter contributed more to flood risk than changes in peak discharge and flooded area. Planning legislation limited growth close to channels, but flood risk grew rapidly beyond in less restricted areas. Building footprint data provide an accurate approach to mapping changes in flood risk with urbanisation.

Study region

karst rocky desertification area, China

Study focus

The rocksoil interface, where exposed bedrock is in abrupt contact with the soil, is prevalent in rocky desertification areas. As a constraining boundary condition of soils, drying shrinkage cracks are easily developed at the rocksoil interface of outcrops with weak or un-weathered bedrock, but the shrinkage crack development under these conditions is still unknown, which seriously restricts a profound understanding of the hydrological processes on karst slopes with exposed bedrocks. This study aims to quantify the geometric morphological characteristics of these shrinkage cracks and the block areas cut by the crack network during the crack development, as well as to explore the development of drying shrinkage cracks at the rocksoil interface of outcrops.

New hydrological insights

When the soil moisture content was between 24.1 % and 28.6 %, shrinkage cracks at the rocksoil interface (CRSI) first formed along the border between rocks and soils and then at the soil surface perpendicular to the former, most of the cracks intersected vertically in shapes of "T" or "+". The geometric parameters of shrinkage cracks initially increased before stabilizing and reached a stabilization stage as soon as the moisture content decreased. However, all of them finally shrank slightly in the later stages of soil water loss in thicker soils. Soil thickness was not a crucial factor affecting the CRSI formation. The CRSI were 1.2 times wider than all other cracks, while being infrequent and making up just 40 % of the total length and area of all cracks. As a result, the CRSI may grow into a key pathway for the establishment of preferred flow at the rocksoil interface, which should be paid attention in the hydrological processes in the karst rocky desertification region.

Groundwater potential in Morocco’s Souss-Massa mountainous basin (SMMB) is being identified using geospatial tools and geological data. We deployed four mathematical models, namely Data-Driven Multi-index Overlay (DM_IO), Geometric Average (G_A), Support Vector Machine (SVM), and Logistic Regression (LR), to establish data-driven patterns among the nine influencing factors, primarily drainage density, permeability, slope, distance to rivers, elevation, lineament density, distance to lineaments, intersection node density, and rainfall. Based on the Concentration-Area (C-A) fractal approach, the findings of the four models were developed and classified into five levels of potentiality ranging from very low to very high. The regions designated as having high and very high potentialities for the DM_IO, G_A, SVM, and LR models, respectively, account for 22.44 %, 9.80 %, 19.36 %, and 26.77 % of the overall basin. We validated the models by calculating each model's area under the ROC curve (AUC). The estimated AUC values are more than 70 %, suggesting the model performs well. The four models' performance was compared, revealing that the SVM model outperforms the others. Gravimetric data shows that possible groundwater zones closely coincide with gravimetric lineaments. The findings of this study can provide valuable insights to decision-makers, allowing them to improve decision-making processes and develop holistic groundwater resource management in the Souss-Massa mountainous basin (SMMB).

Study area

The western and eastern flanks of Ethiopia's Awash and Abay Basins, respectively.

Study focus

Identifying recharge zones of the main aquifers in the Upper Awash Basin, which are water resources targeted for long-term sustainable use. In this work, lithohydrostratigraphic concepts with fracture density, hydrogeochemical and stable isotopic insights were applied using information from 94 water-supply wells, 188 geoelectrical resistivity, 124 hydrochemistry, and 81 stable isotopic data sets.

New hydrogeological insights of the area

The results illustrate that recharge of superficial deposits and Rift basalt aquifers is from modern precipitation and from nearby streams/rivers through fractures, which is exemplified by mixed CaHCO₃ or CaMgHCO₃ water types of low TDS (<200 mg/l), high Ca/Na ratio (>5), low RA (<2.0), enriched isotopic signature, and high deuterium excess (13.3). Seepage from the overlying aquifers, as well as direct precipitation in locations where the unit is exposed, form the mechanisms of recharge for fractured ignimbrite aquifer. The highland and transition areas are dominantly the recharge areas for the regional scoriaceous basalt aquifer. These areas have high fracture density (0.96<FD<3.0 km/km²), mineralized NaHCO₃ water type, high TDS (>468 mg/l), low Ca/Na ratio (<1), high RA (>2.0), highly depleted isotopic signals, and low deuterium excess (<11) relative to the Local Meteoric Water Line. The results also reveal groundwater flux from the adjacent eastern flank of Abay Basin.

Study region

Prahova river basin located in the central-southern region of Romania.

Study focus

This study aims to assess the susceptibility to flooding by using state-of-the-art machine learning and optimization procedures. To achieve this goal, we employed ten flood-related variables as independent variables in our machine learning models. These variables include slope angle, convergence index, distance from the river, elevation, plan curvature, hydrological soil group, lithology, topographic wetness index, rainfall, and land use. We used 158 flood locations as dependent variables in the training of four hybrid models: Deep Learning Neural Network-Statistical Index (DLNN-SI), Particle Swarm Optimization-Deep Learning Neural Network-Statistical Index (PSO-DLNN-SI), Support Vector Machine-Statistical Index (SVM-SI), and Particle Swarm Optimization-Support Vector Machine-Statistical Index (PSO-SVM-SI). Utilizing the Statistical Index method, we calculated coefficients for each flood predictor class or category.

New hydrological insights for the region

The PSO-DLNN-SI model demonstrated the best performance, achieving an AUC-ROC curve of 0.952. It's worth noting that the application of the PSO algorithm significantly enhanced the model's performance. Additionally, it's crucial to highlight that approximately 25 % of the study region exhibits a high to very high susceptibility to flood events. Taking into account the very precise results of the models applied in the present study, we can state that from a hydrological point of view, the current research contributes to a better understanding of the intensity with which floods can affect the different areas of the Prahova river basin.

Study region

The Huai River Basin, China.

Study focus

This study chooses the daily flow data of Huai River and its tributaries, Shi River and Hong River during 1959–2016. The co-occurrence of floods in different tributaries of the catchment is assessed by analyzing the flood peak and flood timing at three different gauging stations located in the river network. What’s more, the parameters(estimated from the 30-year scale time windows) of the marginal and joint distributions are assumed stationary and nonstationary respectively to explore how the trend of coincidence probability(CP) is effected by them.

New hydrological insights for the region

The results show that, over the period analyzed, the most probable time of flood co-occurrence over the gauge stations in the study area tends to move backwards from 10 July to about 20 July. The probability of flood co-occurrence at the Bantai and Jiangjiaji gauging stations, which singularly experience an increase in flood peak, increases from $9.25\times {10}^{-9}$(the 1st window) to $1.17\times {10}^{-5}$(the 25th window) when the return period of flood is 20 year, while in the same condition, the CP of Bantai and Wangjiaba decreased from $6.16\times {10}^{-6}$ to $2.48\times {10}^{-7}$.

Study region

China

Study focus

The Dryness/Wetness Index (DWI) data from China is widely utilized in palaeohydroclimate research. The initial part of this data, covering the years 1470–1979 (original DWI), is primarily generated from records of droughts/floods in historical documents. However, the extended data over 1980–2000 (precipitation-based DWI) is derived entirely from instrumental precipitation measurements. To date, there is no research on the regional differences in hydroclimatic representativeness of the original DWI. Moreover, when reconstructing precipitation using the combined 1470–2000 DWI data as a proxy and calibrating it with instrumental precipitation data post-1950, the overestimated reconstruction skill has not been evaluated. Therefore, utilizing data on crop yield reductions due to drought/flood disasters from 1978 to 2008, we establish the disaster-based DWI following the same method as the original DWI and explore its representativeness and reconstruction skill.

New hydrological insights for the region

Disaster-based DWI is more sensitive to precipitation in East Central China, with the seasonal window primarily lasting for five months and distributed between April and September. In contrast, it reflects soil water in the Northeastern, Southeast coastal, and Western regions in China. Additionally, by comparing the average predicted R-Squared of summer precipitation reconstruction using precipitation-based DWI and disaster-based DWI (58.6 % and 45.0 %, respectively), we identify an average overestimation of 13.6 %. Even after excluding this inflated R-Squared, the disaster-based DWI remains a highly reliable proxy for precipitation.

Study region

A gravel desert in the middle reaches of the Heihe River Basin, northwestern China.

Study focus

Lack of long-term monitoring of soil water and groundwater level (GL) limited accurately quantifying the interactions between soil water, groundwater, and the shrubs in the desert ecosystems. This study focused on clarifying the water movement in the groundwater-soil-plant-atmosphere continuum in the desert ecosystems. Hydrological processes of a shrub community were simulated by developing the HYDRUS-1D model based on the twelve-years monitoring in a gravel desert.

New hydrological insights for the region

Evapotranspiration of the shrub community was properly partitioned by the Penman-Monteith equation with the dual crop coefficient approach. Reaumuria songarica and Nitraria sphaerocarpa community relied on shallow soil water. Actual transpiration and evapotranspiration ranged from 33 mm and 80 mm in a dry year to 65 mm and 171 mm in a wet year, respectively. Only 39 % of evapotranspiration was used for shrub growth, and growing-season rainfall was more efficiently used in a dry year. Water rising from lower layers was dominant in the 0–10 m layer. The capillary fringe varied from 102 cm to 267 cm, averaging 205 cm above GL during the growing seasons. The rising groundwater is unavailable but promising for the shrubs’ utilization. The results of this study are valuable for developing sustainable management strategies for the similar gravel desert ecosystems.