Hydrological Behaviour Research Articles

Comparison of methodologies for flow prediction through teleconnection indices. Case study: Paute river basin

The Paute river basin (southern Ecuador) suffers hydrological changes due to climate change and human activities. Hydrological changes cause extreme events and affect ecosystems, hydroelectric plants, and quality of life. It highlights the importance of understanding hydrological behavior to make appropriate decisions in extreme environments. This study seeks to predict discharges in the Paute river basin through global teleconnection indices. Multiple Linear Regression (MLR) was obtained using three different methodologies: multicollinearity analysis, Principal Component Analysis (PCA), and correlation with monthly delays. It was shown that the principal component analysis scenario obtained the best predictive fits, specifically by including 41 indices and 20 components. For the scenario using monthly delays, the best delay occurs within a single month for most seasons. Finally, with the multicollinearity analysis scenario, better results were obtained using 41 indices, although essentially the performance corresponds to the number and indices of each model. Teleconnection indices are not sufficient when used as the only input variable for download modeling and prediction, giving mostly unsatisfactory results. However, a clear trend links the behavior of flows and indices, and it is possible to improve the models based on more climatic variables or with other predictive methods.

Long-term hydrological behavior of an Alpine glacier

Alpine glaciers are shrinking at a relentless pace, as an effect of global warming. The impact of these changes in the European Alps is relevant, given the importance of this territory from both ecological and economic viewpoints. While the ubiquitous reduction of glaciers’ mass through the Alps has been reported in several studies, its effect on streamflow is less studied. In the present work, we analyzed the long streamflow time series, available since 1976, of the Careser Stream, a headwater stream emerging from the Careser Glacier, in northeastern Italy. A large amount of missing data characterizes the streamflow time series, which we filled with a high level of confidence by using a Feed Forward Deep Neural Network algorithm. We explored the influence of climatic drivers on streamflow at monthly and annual time scales. Our analysis highlighted significant changes in the timing of streamflow due to the combined effect of early snow melting and a progressive reduction of the glacier’s area. The hydrological regime changed significantly with glacier water contributing to streamflow proportionally less after a tipping point identified in 1996. Projections performed by using eight bias-corrected climate models of the EURO-CORDEX collections confirmed this tendency with the complete transition of the catchment from the glacial to the nival regime by 2045 at the latest. The Deep Neural Network algorithm was very effective in filling the missing streamflow data and this offers an encouraging premise for applications in other glaciers of the Alps suffering from the same transformation.

Impact of land-use change on karst spring response by integration of surface processes in karst hydrology: The ISPEEKH model

Karst groundwater represents a source of freshwater for a quarter of the world's population. Modeling the hydrological behavior of karst aquifers while accounting for the spatial variability of the recharge processes and the land-use change impacts on water availability remains a challenge for karst water resources management. Therefore, this study proposes a new semi-distributed hydrological model named Integration of Surface ProcEssEs in Karst Hydrology (ISPEEKH) for simulating the surface-underground water flows in karst-dominated catchments. ISPEEKH couples the restructured version of the Soil and Water Assessment Tool (SWAT+) with a non-linear three-reservoir groundwater model that represents the epikarst and matrix-conduit flow components in a karst aquifer. ISPEEKH was applied to the Baget karst catchment (13.25 km2) in the Pyrénées mountains of southwest France, characterized by a conduit-dominated spring flow and low surface runoff. The model simulated the catchment daily discharge satisfactorily, with NSE = 0.67 and R2 = 0.68 for the 2008–2013 calibration period, and NSE = 0.65 and R2 = 0.69 for the 2014–2018 validation period. The catchment evapotranspiration and discharge amounted to 33 % and 67 % of the average annual precipitation, respectively, and nearly 80 % of the discharge was attributed to spring flow. The matrix-to-conduit flow accounted for 4–7 % of the monthly spring flow during the high-flow period (December to June), and up to 22 % during the low-flow period (July to October). ISPEEKH was then used to assess the hydrological response of the Baget catchment to land-use change scenarios of afforestation and deforestation for wood production and pasture development. Afforestation of the full catchment area did not alter the catchment hydrology significantly. Deforestation for wood production reduced annual evapotranspiration by 12–18 % and increased annual recharge by 7–8 %, resulting in annual discharge rising by 6–9 %. These changes in the water balance components were most noticeable during the low-flow season and would augment freshwater availability. Conversely, deforestation for pasture development raised annual evapotranspiration by 13–17 % while reducing annual recharge by around 7 % and discharge by 5–7 %. These changes in the hydrological components were most remarkable during the high-flow season and affected discharge below 2.5 m3.s−1.

Model of Hydraulic Conductivity, Infiltration Rate, and Permeability at Gold Mine Waste Dump in North Sulawesi, Indonesia

The research area is a gold mine operating in North Sulawesi. The aim of the study was to analyze and calculate hydrological parameters, namely: hydraulic conductivity, infiltration rate, and permeability to find out how strong the soil cover is at one level of waste disposal. The method used is the Measurement of hydraulic conductivity, infiltration rate, and permeability in the field, analysis, and calculation of hydraulic conductivity, infiltration rate, and permeability based on field data. In the designated regions of the waste dump, specifically areas 1a, b, and c, we observed certain hydrological patterns that are worth noting. Firstly, the hydraulic conductivity in these areas, which is a crucial determinant of the rate at which water can move through the soil, consistently showcased low average values. This is further supported by the similarly slow infiltration rate identified in the same zones. The ability of the soil to transmit water, i.e., its permeability, also followed this trend, with values leaning towards the lower end of the scale, indicating very slow permeability. One major contributory factor to these patterns appears to be the soil's composition. Predominantly made up of sandy loam, the soil in these areas exhibits high water retention capabilities. Sandy loam, by its nature, binds and retains water effectively, which could potentially explain the observed hydrological behaviors in waste dump areas 1a, b, and c.

Biochemical, hydrological and mechanical behaviors of high food waste content MSW landfill: Numerical simulation analysis of a large-scale experiment

The complex process of thermal-hydro-mechanical-biochemical (THMBC) coupled degradation in high food waste content (HFWC) municipal solid waste (MSW) is the main cause of intense heat, gas, and leachate generation in the landfills, which could lead to environmental disasters. A large-scale indoor experiment on HFWC MSW has been done with operations of loading, heated mature leachate recharging to study the rules of degradation. A THMBC coupled degradation model is used to analyze the results in the first 400 days drawn from the experiments, to explain how recharge of heated mature leachate accelerated degradation process and how was the portion of settlement led by intraparticle water release. The numerical simulation also calculated the landfill gas that was not collected in the experiment due to operational defects. The results show that recharging the heated mature leachate allows the stabilization process to occur at least six months earlier and settlement due to intraparticle water release accounts for half of the settlement in the first 60 days. The research indicates highly coupled THMBC model can be used to analyze the complex process in MSW degradation, make up for the shortcomings of physical experiments, and provide theoretical support for the design, construction, and management of landfills.

A global streamflow indices time series dataset for large-sample hydrological analyses on streamflow regime (until 2022)

Abstract. With the booming big data techniques, large-sample hydrological analysis on streamflow regime is becoming feasible, which could derive robust conclusions on hydrological processes from a big-picture perspective. However, there is a lack of a comprehensive global large-sample dataset for components of the streamflow regime yet. This paper presents a new time series dataset on global streamflow indices calculated from daily streamflow records after data quality control. The dataset contains 79 indices over seven major components of streamflow regime (i.e., magnitude, frequency, duration, changing rate, timing, variability, and recession) of 41 263 river reaches globally on yearly and multiyear scales. Streamflow indices values until 2022 are covered in the dataset. Time span of the time series dataset is from 1806 to 2022 with an average length of 36 years. Compared to existing global datasets, this global dataset covers more stations and more indices, especially those characterizing the frequency, duration, changing rate, and recession of streamflow regime. With the dataset, research on streamflow regime will become easier without spending time handling raw streamflow records. This comprehensive dataset will be a valuable resource to the hydrology community to facilitate a wide range of studies, such as studies of hydrological behaviour of a catchment, streamflow regime prediction in data-scarce regions, as well as variations in streamflow regime from a global perspective. The dataset can be accessed at https://doi.org/10.57760/sciencedb.07227 (Chen et al., 2023a).

Comparing hydrological responses across catchments using a new soil water content metric

AbstractSoil water content (SWC) is a fundamental variable involved in several hydrological processes governing catchment functioning. Comparative analysis of hydrological processes in different catchments based on SWC data is therefore beneficial to infer driving factors of catchment response. Here, we explored the use of high‐temporal resolution SWC data in three forested catchments (2.4–60 ha) in different European climates to characterize hydrological responses during wet and dry conditions. The investigated systems include Ressi, Italy, with a humid temperate climate, Weierbach, Luxembourg, with a semi‐oceanic climate, and Can Vila, Spain, with a Mediterranean climate. We introduced a new SWC metric defined as the difference between seasonal mean SWC at a relatively shallow and a deep soil layer. The difference is classified in three distinct states: similar SWC between the two layers, higher SWC in the deeper layer, and higher SWC in the shallow layer. In the most humid site, Ressi, we frequently found similar SWC at the two soil depths which was associated with high runoff ratios. Despite similar precipitation amounts in Can Vila and Weierbach, SWC patterns were very different in both catchments. In Weierbach, SWC was similar across the entire soil profile during wet conditions, whereas evaporation of shallow water resulted in higher SWC in the deep soil layer during dry conditions. This led to high runoff ratios during wet conditions and low runoff ratios during dry conditions. In Can Vila, SWC was consistently higher in the deeper layer compared to the shallow layer, irrespective of the season, suggesting an important role of hydraulic redistribution and vertical water movement in this site. Our approach provides an easy and useful method to assess differences in hydrological behaviour solely based on SWC data. As similar datasets are increasingly collected and available, this opens the possibility for further analyses and comparisons in sites around the globe with contrasted physiographic and climate characteristics.

Drivers of δ18O Variability Preserved in Ice Cores From Earth's Highest Tropical Mountain

AbstractIn 2019, four ice cores were recovered from the world's highest tropical mountain, Nevado Huascarán (Cordillera Blanca, Peru; 9.11°S, 77.61°W). Composite hydroclimate records of the two Col cores (6,050 masl) and the two Summit cores (6,768 masl) are compared to gridded gauge‐analysis and reanalysis climate data for the most recent 60‐year. Spatiotemporal correlation analyses suggest that the ice core oxygen stable isotope (δ18O) record largely reflects tropical Pacific climate variability, particularly in the NINO3.4 region. By extension, the δ18O record is strongly related to rainfall over the Amazon Basin, as teleconnections between the El Niño Southern Oscillation and hydrological behavior are the main drivers of the fractionation of water isotopes. However, on a local scale, modulation of the stable water isotopes appears to be more closely governed by upper atmospheric temperatures than by rainfall amount. Over the last 60 years, the statistical significance of the climate/δ18O relationship has been increasing contemporaneously with the atmospheric and oceanic warming rates and shifts in the Walker circulation. Isotopic records from the Summit appear to be more sensitive to large‐scale temperature changes than the records from the Col. These results may have substantial implications for modeling studies of the behavior of water isotopes at high elevations in the tropical Andes.

Analysis of the Role of Precipitation and Land Use on the Size of the Source Area of Shallow Landslides

Rainfall-induced shallow landslides cause damage to human activities and infrastructureseach year, and although the size of a landslide correlates to the damage that it causes, very few studies have previously investigated the factors that influence the size of a shallow landslide. The aim of this work was to assess the role of precipitation and land use in controlling the size of the source area of rainfall-induced shallow landslides. After ruling out the impact of the slope angle and bedrock lithology in the two selected catchments, the role of land use was investigated: the statistical tests showed that woodlands and vineyards had statistically different source area size distributions, possibly due to the different hydrological behaviours between the two. A correlation was additionally found between the size of a source area and the amount of cumulated rainfall in the three days prior to each analysed event. In both cases, an increase in source area size was linked to an increase in pore pressure. This study aimed to fill the existing gap in the research to help implement policies aimed at reducing the size, and consequently the impact, of shallow landslides.

Impact of urbanization on baseflow characteristics in the central catchment of North China Plain, China

Study areaThe Dawenhe River and Xiaoqinghe River Basins (116°21′–118°41′E, 35°43′–37°15′N) in the center of the North China Plain (NCP), China. Study focusTo quantitatively assess the influence of urbanization (two indicators including Impervious Surface Percentage (ISP) and Average Night Light Index (ANLI)) on baseflow hydrological behavior (nine baseflow signatures), this study selects the typical urbanized catchment (nine sub-catchments) within the central NCP, where the baseflow was estimated from the total daily streamflow from 2006 to 2016. New hydrological insights for the regionFindings show that: (i) Baseflow signatures had a notable spatial variability, in which the magnitude baseflow signatures (Qb10, Qb25, Qb50, Qb90), Baseflow Index (BFI), Concavity Index (CI), and Slope of the baseflow duration curve (SBDC) demonstrated greater values in the north versus the south. (ii) Both ISP and ANLI exhibited an upward trend over time with some fluctuations (R2 > 0.65, p < 0.05). For ANLI, there were higher values in the northwest and northeast regions, and the higher ISP values were mainly located in the northern region. (iii) Overall, the effects of two urbanization indicators on baseflow signatures exhibited catchment-variability, and model performance between ISP and baseflow signatures is better than ANLI. This study provides a scientific reference to elucidate the water balance of the central NCP under the background of urbanization.

Predicting Hydrological Change in an Alpine Glacierized Basin and Its Sensitivity to Landscape Evolution and Meteorological Forcings

AbstractShifting precipitation patterns, a warming climate, changing snow dynamics and retreating glaciers are occurring simultaneously in glacierized mountain headwaters. To predict future hydrological behavior in an exemplar glacierized basin, a spatially distributed, physically based cold regions process hydrological model including on and off‐glacier process representations was applied to the Peyto Glacier Research Basin in the Canadian Rockies. The model was forced with bias‐corrected outputs from a high‐resolution Weather and Research Forecasting (WRF‐PGW) atmospheric simulation for 2000–2015, and under pseudo‐global warming for 2085–2100 under a business‐as‐usual climate change scenario. The simulations show that the end‐of‐century increase in precipitation nearly compensates for the decreased ice melt associated with almost complete deglaciation, resulting in a decrease in annual streamflow of 7%. However, the timing of streamflow advances drastically, with peak flow shifting from July to June, and August streamflow dropping by 68%. To examine the sensitivity of future hydrology to possible future drainage basin biophysical attributes, the end‐of‐century simulations were run under a range of initial conditions and parameters and showed the highest sensitivity to initial ice volume and surface water storage capacity. This comprehensive examination suggests that hydrological compensation between declining icemelt and increasing rainfall and snowmelt runoff as well as between deglaciation and increasing basin depressional storage capacity play important roles in determining future streamflow in a rapidly deglaciating high‐mountain environment. Conversely, afforestation and soil development had relatively smaller impacts on future hydrology.

Simulating the Hydrological Processes under Multiple Land Use/Land Cover and Climate Change Scenarios in the Mahanadi Reservoir Complex, Chhattisgarh, India

Land use/land cover (LULC) and climate are two crucial environmental factors that impact watershed hydrology worldwide. The current study seeks to comprehend how the evolving climate and LULC patterns are impacting the hydrology of the Mahanadi Reservoir catchment. A semi-distributed Soil and Water Assessment Tool (SWAT) model was utilized to simulate various water balance elements. Twelve distinct scenarios were developed by combining three different climatic data periods (1985–1996, 1997–2008, and 2009–2020) with four sets of land use maps (1985, 1995, 2005, and 2014). The SWAT model demonstrated strong performance in simulating monthly stream flows throughout the calibration and validation phases. The study reveals that changes in LULC have a distinct effect on the environment. Specifically, the changes in LULC lead to heightened streamflow and reduced evapotranspiration (ET). These changes are mainly attributed to amplified urbanization and the diminished presence of water bodies, forest cover, and barren land within the Mahanadi Reservoir catchment. The combined impact of climate change and LULC shifts reveals complex interactions. Therefore, the present study offers an understanding of how changes in climate and land use over the past few decades have influenced the hydrological behavior of the Mahanadi Reservoir catchment in Chhattisgarh. The findings of this study have the potential to offer advantages to governmental bodies, policymakers, water resource engineers, and planners seeking effective strategies for water resource management. These strategies would be particularly relevant in the context of climate change and land use/land cover changes in ecological regions similar to those of the Mahanadi Reservoir catchment. In addition, a rational regulatory framework for land use patterns is essential for assisting stakeholders in managing water resources and appropriately developing the entire catchment.

Control of climate and physiography on runoff response behavior through use of catchment classification and machine learning

Understanding of runoff response changes (RRC) is essential for water resource management decisions. However, there is a limited understanding of the effects of climate and landscape properties on RRC behavior. This study explored RRC behavior across controls and predictability in 1003 catchments in the contiguous United States (CONUS) using catchment classification and machine learning. Over 1000+ catchments are grouped into ten classes with similar hydrological behavior across CONUS. Indices quantifying RRC were constructed and then predicted within each class of the 10 classes and over the entire1000+ catchments using two machine learning models (random forest and CUBIST) based on 56 indicators of catchment attributes (CA) and 16 flow signatures (FS). This enabled the ranking of the important influential factors on RRC. We found that (i) CA/FS-based clusters followed the ecoregions over CONUS, and the impact of climate on RRC seemed to overlap with physiographic attributes; (ii) CUBIST outperforms the random forest model both within the cluster and over the whole domain, with a mean improvement of 39 % (depending on clusters) within clusters. Runoff sensitivity was better predicted than runoff changes; (iii) FS related to runoff ratio, average, and high flow are the most important for RRC, whereas climate (evaporation and aridity) is a secondary factor; and (iv) RRC patterns are substantial in the dominant factor space. High total changes and catchment characteristic-induced changes occurred mainly at 100°west longitude. The elasticity of climate and catchment characteristics was found to be high in spaces with high evaporation and low runoff ratios and low in spaces with low evaporation and high runoff ratios. Uncertainties existed in the number of catchments between clusters which was verified using a fuzzy clustering algorithm. We recommend that future research that clarifies the impact of uncertainty on hydrological or catchment behavior should be conducted.

A universal multifractal-based method to model pore size distribution, water retention and hydraulic conductivity of granular green roof substrates

Hydrological behaviour of granular substrates is of critical interest in Nature-based solutions (NBS) like green roofs. To simulate this behaviour in a physically realistic manner it is indispensable to model the substrate’s hydraulic conductivity (HC) as it determines infiltration rate at various degrees of saturation. Since HC is directly dependent on water content retained by the substrate, it is necessary to physically model this water retention (WR) behaviour too. Capillary water is stored or retained in pore spaces and this water content that can be retained by a substrate under different suction pressures is therefore dependent upon its pore size distribution (PSD). Since pores in any granular media are spaces where grains are absent, their size distribution too is intrinsically related to the substrate’s grain size distribution (GSD) which provides the probability of finding grains smaller than some threshold diameter dg,t. Although earlier studies have attempted to model PSD, WR and HC, they frequently use simplifying mono-fractal approximations, whereas this study proposes a more generalized multifractal-based approach. Furthermore, while it is quite usual to incorporate pore tortuosity through some indirect parameter l in the HC model, a related ink-bottle effect which even though capable of affecting WR behaviour is commonly ignored. Therefore, this paper attempts to address the aforementioned research gaps in modelling GSD, PSD, WR and HC by i) investigating the somewhat overlooked question of similarity in multifractal behaviour between grain size fields and substrate density fields, and consequently suggesting an improved method for estimating universal multifractal (UM) parameters of grain size fields in a more reliable manner from just conventional GSD measurements in order to be directly used in the multifractal GSD model, ii) proposing a new UM-based PSD model, and subsequently using it to obtain a new UM-based WR model with a parameter to directly represent ink-bottle effect - a consequence of the substrate’s pore configuration or arrangement, iii) using this UM-based WR model to suggest a new UM-based HC model without the necessity for a separate pore tortuosity parameter. Finally, the proposed models have been validated by using experimental measurements from 4 different commercially used green roof substrates.

Estimation and attribution of water storage changes in regulated lakes based on Budyko’s supply–demand framework

Study regionLake Dianchi, southwest China Study focusUnderstanding changes in lake water storage (LWS) and its attribution to climate change and human activities is essential for adaptive management of water resources in regulated lakes. Although altimetric measurements, whether ground- or satellite-based, can reproduce LWS dynamics, they do not provide sufficient information on why LWS is changing. Neither the water balance method nor detailed hydrological modeling can capture exactly LWS change in most regulated lakes largely because of the scarcity of water output observations. Here, a simple water balance model, following Budyko’s supply–demand framework, was proposed to estimate LWS change in regulated lakes without the need for water output information. The elasticity of LWS was theoretically derived from the Budyko-type model to attribute LWS change to its main driving factors. New hydrological insights for the regionApplication of the proposed model to the Lake Dianchi for the period 1964–2022 indicated that the model accurately captured the variations of annual LWS in Lake Dianchi with a relative root mean square error of 4.23%, and correlation coefficient of 0.77. The attribution results suggested that lake regulation strategies were the chief determinant of LWS change in Lake Dianchi, while water transfer had a limited contribution. This study suggests that complex hydrological behavior in regulated lakes can be explored using Budyko's supply–demand framework with a low requirement for data.

Increased nonstationarity of stormflow threshold behaviors in a forested watershed due to abrupt earthquake disturbance

Abstract. Extreme earthquake disturbances to the vegetation of local and regional landscapes could swiftly impair the former hydrologic function, significantly increasing the challenge of predicting threshold behaviors of rainfall–runoff processes as well as the hydrologic system's complexity over time. It is still unclear how alternating catchment hydrologic behaviors under an ongoing large earthquake disruption are mediated by long-term interactions between landslides and vegetation evolution. In a well-known watershed affected by the Wenchuan earthquake, the nonlinear hydrologic behavior is examined using two thresholds with intervening linear segments. A lower rising threshold (THr) value (210.48 mm) observed in post-earthquake local landslide regions exhibited a faster stormflow response rate than that in undisturbed forest and grassland–shrubland regions, easily triggering huge flash-flood disasters. Additionally, an integrated response metric pair (integrated watershed average generation threshold THg−IWA and rising threshold THr−IWA) with areas of disparate land use, ecology, and physiography was proposed and efficiently applied to identify emergent catchment hydrologic behaviors. The interannual variation in the two integrated hydrologic thresholds before and following the earthquake was assessed to detect the temporal nonstationarity in hydrologic extremes and nonlinear runoff response. The year 2011 was an important turning point along the hydrologic disturbance–recovery timescale following the earthquake, as post-earthquake landslide evolution reached a state of extreme heterogeneity in space. At that time, the THr−IWA value decreased by ∼ 9 mm compared with the pre-earthquake level. This is closely related to the fast expansion of landslides, leading to a larger extension of variable source area from the channel to neighboring hillslopes, and faster subsurface stormflow, contributing to flash floods. Finally, we present a conceptual model interpreting how the short- and long-term interactions between earthquake-induced landslides and vegetation affect flood hydrographs at event timescale that generated an increased nonstationary hydrologic behavior. This study expands our current knowledge of threshold-based hydrologic and nonstationary stormflow behaviors in response to abrupt earthquake disturbance for the prediction of future flood regimes.

Assessment of the shift in the precipitation–streamflow relationship influenced by multiyear drought, Yellow River basin, China

Climate change intensification (e.g., long-term drought) dramatically triggers catchment property changes, which introduces larger uncertainties for describing catchment hydrological behavior. In this study, hydrological behavior responses to multiyear drought were explored, and then causes were explained. The hydrological response to multiyear drought was explored using a magnitude of shift (M) in describing the relationship between precipitation (P) and streamflow (Q) in different catchment states, and a novel method, the trigonometric function decomposition method within the Budyko framework (the TFD method), was applied to assess the causes of Q changes. Several conclusions can be drawn: (i) multiyear drought mainly caused insignificant and significant upward (p < 0.05) changes in the P–Q relationship among 95.45 % of the studied catchments (p < 0.05); (ii) more server drying, lower leaf area index (LAI) and slope can induce a higher M via multiyear drought. In particular, catchment water storage, indicated by the deep soil layer in the Loess Plateau, can effectively mitigate the Q reduction and resulted in a 77.27 % (17/22) upward shift compared with the expected Q reduction; (iii) an asymmetric effect was caused by a multiyear P deficit, that is, (P-Q)/P increase and catchment property parameter (n) decrease were induced by the increases in ratio between potential evapotranspiration and P (Ep/P), suggesting that the catchment properties can mitigate the Q reduction; and (iv) catchment properties had negative effects on the Q reduction (7.76 mm a−1), and partially offset Q reduction (−21.32 mm a−1) resulted from climate change during the multiyear drought period. All of these results indicated that multiyear drought triggered Q reduction, while catchment behavior in the changeable induction mechanism induced a nonlinear Q response to P reduction, which is important for accurate Q projections and appropriate adaptation strategies for droughts.

Contrasting hydrological responses to climate change in two adjacent catchments dominated by karst and nonkarst

Karst systems are well-known for their special features, such as epikarst zone and quick flow, compared to other hydrological systems. However, few studies explored the difference in hydrological responses to climate change between karst and nonkarst catchments. In this paper, two adjacent catchments dominated by karst and nonkarst in Southwest China (subtropical monsoon climate) were selected to investigate their different hydrological behaviors under future climates. To account for potential model structure uncertainties, three different karst hydrological models and three traditional catchment models were used to simulate these two catchments. The results demonstrate that different models yield comparable streamflow simulations within each catchment, allowing for the focus to be on the impact of climate change and catchment hydrological characteristics. The karst-dominated catchment is modeled to have larger actual evapotranspiration (AET) than the nonkarst-dominated catchment under similar climate conditions, with the AET of the former being more sensitive to changes in precipitation and potential evapotranspiration. These differences are primarily due to the presence of the epikarst in the unsaturated zone of the karst system, which can store more infiltration rainwater for evapotranspiration. Both catchments are expected to experience a wetter projection in the wet season and a drier projection in the dry season in the future. However, the karst-dominated catchment will face a drier climate with a significant increase in precipitation in just two months (July and August). Additionally, because of a higher sensitivity of monthly AET to climate change, the karst-dominated catchment will experience a greater monthly discharge reduction in the first two wet months (April and May), a relatively lower discharge increase in other wet months, and a lower monthly discharge in dry months, while the monthly discharge of the nonkarst-dominated catchment increases in the wet season and decrease in the dry season. Furthermore, the karst-dominated catchment will have a much lower annual discharge than the nonkarst-dominated catchment, particularly during extremely dry years in the future period due to its larger AET consumption. These all suggest that the karst-dominated catchment will be more vulnerable to droughts. Overall, due to the drier climate and the different hydrological backgrounds of the karst-dominated catchment, it is expected to have much drier hydrological conditions in the future compared to the nonkarst-dominated catchment.

Spatial pattern of hydrological and erosion behaviour along a dolomite hillslope in Southwest China

Dolomite hillslopes are highly vulnerable to rocky desertification, but the linkages among soil type, runoff mechanisms, and soil erosion remain unclear. During four hydrological years (2018–2021), soil type, plot-scale hydrological and erosion behavior at the upper, middle, and lower slopes along the dolomite hillslope in karst regions of Southwest China were investigated. The results indicated that along the downward slope direction, the degree of soil development gradually increased, forming a typical soil catena pattern. The soil types along the downward direction on the dolomite hillslope gradually transitioned from Entisol to Inceptisol and to Semi-Alfisol. The Entisol was thin and gravelly, with the highest volume ratio of gravel of 75 %. In contrast, Semi-Alfisol was thick and clayey, with the highest volume ratio of fine soil of 97 %. The surface runoff coefficient of the upper slope was only 2.3 % because of the high water infiltration capacity of shallow and rocky soil, and the runoff generation mode was dominated by discontinuous infiltration–excess runoff occurring on rock outcrop patches. Due to the higher soil water content (mean value of 37 %) and frequently occurring lateral flow, the lower slope exhibited the highest surface runoff coefficient of 21 %, mainly as saturation-excess runoff. Catenary soils and their correspondingly divergent hydrological regimes led to average annual soil losses of 0.4, 0.8, and 2.8 t·ha−1·yr−1 at the upper, middle, and lower slopes, respectively. These results advance the understanding of the relationship between hydrology and erosion on karst hillslopes and provide theoretical support for further rocky desertification control.

Flow signatures and catchment’s attributes for HCA clustering in a hydrologic similarity assessment (Tunisian case)

Partitioning methods such as cluster analysis are advantageous in pooling catchments into hydrometric similar regions. They help overcome data shortage in ungauged catchments, which is a common problem in Sud Mediterranean zones. Without accurate forecasts, it is difficult to assess and manage water resources efficiently this situation won't be of any assistance to hydrology decision-makers. This paper illustrates a Tunisian application case, that aims to pool catchments with a hierarchical clustering algorithm (HCA) based on distances calculated in multidimensional physiographical and hydrometric space. The homogeneity of generated clusters is checked by the silhouette index. Then the distances efficiencies are compared. Nineteen semi-arid Tunisian catchments monitored since 1992 are studied. Twelve physiographical attributes, nine rainfall and streamflow signatures are considered in the HCA with two clusters. Correlation distance provides the most homogeneous clusters. Statistically the: percentage of area affected by anti-erosive practices, percentage of forest cover and catchment area are the most discriminating attributes. However, hydrometrical signatures appear to be irrelevant. These partitions highlight two different hydrological behaviors that must support forecasting. Results are promising in the Sud-Mediterranean case, where the shortage of hydrometrical data is an ongoing problem. They have the advantage of enabling hydrologic forecasting without requiring heavy information.