Runoff Response Research Articles

Hydrological responses of pine needle litter to rainfall erosional processes on Chinese karst hillslopes

Native vegetation restoration, such as pines, is an effective measure for mitigating soil erosion. However, the impact of pine needle litter on runoff, soil erosion, and hydrological responses on karst hillslopes remains unclear. This study investigated these factors during the rainy season from June to August 2021 under six distinct treatments (flat, gentle, and steep slopes with and without pine needle coverings). The results showed that pine needle litter significantly increased the soil water content, particularly on steeper slopes, by improving the water-holding capacity. It also substantially reduced runoff (by 23.8%) and soil erosion (by 92.5%). The critical rainfall threshold for generating runoff did not occur in the pine needle covering treatment, whereas it was 19.3 ± 8.8 mm in the bare soil treatment under wet conditions. These findings highlight the efficacy of pine needle cover in mitigating runoff and soil erosion in karst areas, suggesting it as a sustainable alternative against erosion, and underscoring the importance of pine plantations in degraded soil restoration efforts.

Modulation of evapotranspiration and stream runoff by weathered bedrock in arid and semi-arid mountains

Earth's Critical Zone exhibits remarkable heterogeneity and complexity. Hence, further investigation is required to examine the composition of Earth's Critical Zone as well as the diverse eco-hydrological patterns they exhibit under varying climatic and geological circumstances. This exploration should primarily be conducted through the investigation and experiments of the hillslope unit, where the topography and weathered bedrock are representative, with particular emphasis on semi-arid regions where water resources serve as the primary limiting factor. Here, we have determined that the structure of the weathering profile displays systematic variation across the topography and heterogeneous landscape on uninterrupted slopes. Differences in the structure of the subsurface critical zone led to differences in its water storage capacity at the same time. Runoff in alpine shrubs and forests was dominated by subsurface runoff, and grassland was dominated by surface runoff. In the alpine shrub immediately adjacent to the watershed, an estimated quantity of 129 mm of water is stored within the unsaturated zone of the soil, serving as exchange water to replenish moisture in the underlying bedrock. In contrast to alpine shrubs, an estimated quantity of 62.7 mm of water originates from the unsaturated zone of soil and weathered bedrock in the forest. However, approximately 21.1 mm of moisture is unavailable to plants. The soil water storage in grasslands exhibits a decline throughout the growing season, with a subsequent augmentation occurring solely after substantial precipitation events exceeding 20 mm. In wet years, dynamic storage predominantly manifests as groundwater saturation throughout the entire ground and high subsurface runoff. In dry years, the limited runoff response indicates that the catchment's dynamic water storage primarily comprises “indirect” water storage, which predominantly resides within the soil, saprolite, and weathered rock below the “field capacity”, subsequently being released into the atmosphere through evapotranspiration.

Hydrological responses to permafrost degradation on Tibetan Plateau under changing climate

The Tibetan Plateau (TP) has undergone significant warming and humidification in recent years, resulting in rapid permafrost degradation and spatiotemporal variations in hydrological processes, such as subsurface water transport, hydrothermal conversion, and runoff generation. Understanding the mechanisms of hydrological processes in permafrost areas under changing climate is crucial for accurately evaluating hydrological responses on the TP. This study comprehensively discusses the permafrost hydrological processes of the TP under changing climate. Topics include climate conditions and permafrost states, subsurface water transport under freeze–thaw conditions, development of thermokarst lakes and hydrothermal processes, and runoff response during permafrost degradation. This study offers a comprehensive understanding of permafrost changes and their hydrological responses, contributing significantly to water security and sustainable development on the TP.

Rainfall–runoff modeling using an Adaptive Neuro-Fuzzy Inference System considering soil moisture for the Damanganga basin

ABSTRACT Rainfall is the major component of the hydrologic cycle and it is the primary source of runoff. The main purpose of this study was to estimate daily discharge by employing an Adaptive Neuro-Fuzzy Inference System (ANFIS) model using rainfall and soil moisture data at three different depths (5 cm, 100 cm and bedrock) for the Damanganga basin. The length of the data for the study period 1983–2022 is 39 years. The model employed nine membership functions for each variable of soil moisture, rainfall, discharge and 30 rules were optimized. The results were compared considering a range of model performance indicators as correlation coefficient (R2) and Nash–Sutcliffe efficiency (NSE) coefficient. The model application results shows that soil moisture at bedrock gives more precise value of daily discharge with (R2) and NSE value as 0.9936 and 0.9981, respectively, as compared to the soil moisture at depths of 5 and 100 cm. The better results obtained for the measurement of soil moisture in the deeper soil layer are consistent with the hydrological behavior anticipated for the analyzed catchment, where the root-zone soil layer is the driver of the runoff response rather than the surface observations. This study can be helpful to hydrologists in selecting appropriate rainfall–runoff models.

Runoff Simulation of the Upstream Watershed of the Feiling Hydrological Station in the Qinhe River Based on the SWAT Model

This study examined the impacts of climate change and human activities on runoff within the Feiling Hydrological Station watershed in the Qinhe River basin, utilizing the SWAT (Soil and Water Assessment Tool) model. Several climate change and extreme land-use scenarios were evaluated for their effects on runoff. Results demonstrated the SWAT model’s suitability for runoff simulation in the watershed, revealing a negative correlation between runoff and temperature changes, and a positive correlation with precipitation changes. Significantly, runoff responses to precipitation variations of ±10% and ±20% were more marked than those to temperature changes of ±1 °C and ±2 °C. In scenarios of extreme woodland and fallow land, runoff decreased, whereas in scenarios of extreme cropland and grassland, it increased, particularly in the extreme farmland scenario. The study’s findings are important for the sensible management of soil and water resources and the enhancement of the natural environment in the studied area.

Groundwater Recharge and Surface Runoff Modeling Response to Land Use and Land Cover Dynamics in a Mae Wong Watershed of Thailand

This study aims to develop efficient management strategies and assess the spatiotemporal dynamics of land use and land cover (LULC) on surface runoff modeling response dynamics for the long-term sustainability of watersheds. The soil and water assessment tool (SWAT) model was used to evaluate the LULC dynamics on GRSR in the Mae Wong Watershed (MWW) of Thailand. Using Landsat images, three different LULC maps (2011, 2021, and 2031) were created using the cellular automata markov chain (CA-Markov) model, and TerrSet 2020 geospatial monitoring and modeling software. In the overall MWW, the forestland has undergone deforestation and decreased by 2.10% of the total area and 2.72% of the total area has been transformed into agricultural lands due to human activity and population growth. The soil, LULC, weather, and the digital elevation model (DEM) were all used in the SWAT simulation procedure. To understand the groundwater recharge and surface runoff (GRSR) responses of each hydrologic response units (HRUs), the SWAT model was calibrated and verified using streamflow and the sequential uncertainty fitting (SUFI-2) technique from the SWAT calibration and uncertainty program (SWAT-CUP). The results indicate that there is a good agreement for both the calibration and validation phases of all LULC simulations. The study indicated that groundwater recharge has decreased over the last two decades while surface runoff has increased due to the forest area being converted to agricultural land. Thus, the study can support maximizing water management and strategies for systematically attaining sustainability.

Uncertainty quantization of meteorological input and model parameters for hydrological modelling using a Bayesian‐based integrated approach

AbstractThe traditional treatment of uncertainty in hydrological modelling primarily attributes it to model parameters, but rarely systematically considers meteorological input errors, especially in quantifying the impact of meteorological input errors on parameter uncertainty. This study developed a Bayesian‐based integrated approach to quantitatively investigate uncertainties in meteorological inputs (precipitation and temperature) and model parameters as well as the variation in parameter uncertainty due to meteorological input errors. Additionally, we analysed the propagation from these uncertainties to runoff response in snowmelt and non‐snowmelt periods. The applicability and advantages of this approach were presented by applying of the Soil and Water Assessment Tool to the Shitoukoumen Reservoir Catchment. Differential Evolution Adaptive Metropolis‐Markov Chain Monte Carlo was applied for the straightforward Bayesian inference the uncertainties of meteorological inputs and model parameters. On this basis, multilevel factorial analysis technology was used to quantitatively investigate the specific impact of the model parameters' individual and interactive effects due to meteorological input errors. Finally, the impact of meteorological input errors and model parameter uncertainty on the model performance were analysed and quantified systematically. The results showed that the meteorological input errors could affect the random characteristics of multiple model parameters. Moreover, meteorological input errors could further affect the model parameters' effects on annual average runoff. Overall, the above results have significant implications in enhancing hydrological model to simulate/predict runoff and understanding hydrological processes during different periods.

Runoff response to multiple land‐use changes and climate perturbations

AbstractRunoff response to multiple land‐use changes and climate perturbations is distinct, and the main influencing factors vary significantly in different regions. However, few have simultaneously considered the effects of multiple land use changes (vegetation cover changes, terraces and check‐dams construction, and urban expansion) and climatic perturbations (precipitation, potential evapotranspiration, and temperature) on runoff and constructed separate expressions for distinct study areas. This article attempted to determine the main influencing factors of runoff according to the fitting function in the eight subregions of the middle Yellow River (MYR), construct the expressions between the controlling parameter in the Budyko framework and the main factors, and quantify the contribution of climate factors and land use changes to runoff by combining the elasticity coefficient in each subregion. The results indicated that climate factors and land use changes could significantly impact controlling parameters, and there were differences between regions. Climate change promoted an increase in runoff, while land use change promoted its reduction, and the reduction value outweighed its increase. In terms of land use changes, increasing vegetation coverage could suppress runoff reduction, while constructing terraces and check‐dams could promote its reduction. The urban expansion benefited runoff collection and, therefore, could suppress runoff reduction. Its absolute contribution rate exceeded 200% in apparent urban expansion areas. In addition, the contribution rates of land use to runoff changes in the northern arid and semi‐arid regions were significantly higher than those in the southern, and they were more sensitive to land use changes. The research results can provide a reference for analysing the runoff response to different land‐use changes and can further advance people's understanding of the water cycle.

The response of forested upland micro-watersheds to extreme precipitation in a precipitation abundant year

We performed a comparative paired catchment study of three headwater upland forest micro-catchments with different forest types in the precipitation-abundant year 2020. The analysis was based on baseflow separation and resulting baseflow index (BFI). The year 2020 was intentionally chosen as a way to reflect the expected effects of climate change in the region where more extreme hydroclimatic events are expected. Our team demonstrated that in case of hydroclimatic extremes, there are significant differences in the runoff response from these catchments, depending especially on the tree species composition in the forest stands. Three forest types with the predominance of European beech (Fagus sylvatica), Norway spruce (Picea abies), and mixed forest were analyzed. The observed different values of BFI were interpreted in relation to the ability of forest stands to retain water and slow runoff in extreme runoff events determined by the stormflow component as an indication of their flood control efficiency. A significantly worse flood control efficiency and an overreaction of runoff response to precipitation events were observed in the spruce catchment. This also suggests that the spruce catchment is more prone to suffer from drought since twice as much water was lost from the system during extreme hydroclimatic events as opposed to the other two with less spruce in the stands and less water is thus available for groundwater recharge.

Effect of Slope and Runoff Trends on the Hydrological Response of River Kaduna

A monotonic upward/downward trends of hydrological variables was used to test the null hypothesis that slope and runoff trends have a significant impact on land use and land. The Mann-Kendall (M-K) and P- values statistical measurement were used to validate the null hypothesis against the observed data Relationships between gradients and climatic parameters for the hydrological response of Kaduna River was developed using geographic information tools (GIS). GIS maps of runoff, Digital Elevation Model (DEM), Land Use and Land were established Mann-Kendall (M-K) trend analysis was used to identify trends in climate parameters. The data used are precipitation, evapotranspiration, runoff, and temperature over a 30-year period from 1992 to 2021 obtained from the Kaduna State Water Authority and the Nigerian Meteorological Service. Results of the trend analysis of annual runoff and rainfall indicates the same M-K and P-values of 0.094 and 0.475which are all greeter than 0.05 significant level but the magnitude of Seen slope for rainfall and runoff are 5.130 and 0.016 demonstrating that rainfall is the major driving variable foe runoff generation. The annual evapotranspiration has M-K and P-values of 0.126 and 0.335 while the values for average annual temperature are 0.138 and 0.292. Land use in parts of the study area exhibits unstable ecosystems and vulnerable hilly terrain, suggesting that seasonal runoff and corresponding hydrological responses of rivers are dominated by changes in precipitation.

Repeating patterns in runoff time series: A basis for exploring hydrologic similarity of precipitation and catchment wetness conditions

Runoff responses to precipitation at the catchment scale exhibit a high variability in space and time due to a complex interaction of numerous factors, e.g., topography, land use, soil properties, geology, and climatic conditions. To find similar patterns in the runoff response and examine the effects of these factors on runoff variability, previous studies have either compared and classified catchments in space or focused on grouping extreme events. Here, we analyzed runoff processes in three highly instrumented catchments in Germany and Austria individually and compared them to themselves in time. To this end, we used long-term time series of 10 to 13 years and classified runoff events as similar by performing a cluster analysis based on calculated goodness-of-fit criteria between each possible pair of runoff events. For each cluster, we examined the degree to which precipitation and catchment wetness conditions were similar to themselves at the respective times when similar runoff events occurred by calculating Spearman rank correlation coefficients (ρ) as well as their descriptive statistics. The similarities assessed varied among the three catchments, with the two catchments in western Germany with maritime climates showing a stronger correlation for soil moisture conditions (ρ = 0.76 and ρ = 0.74) for classified similar runoff events rather than precipitation (ρ = 0.26 and ρ = 0.36). The Austrian catchment with a predominantly continental climate showed an overall higher correlation for precipitation (ρ = 0.57) and a lower one for soil moisture (ρ = 0.53) for similar runoff events compared to the other two catchments. The proposed method assesses similarity of precipitation and wetness conditions under similar runoff responses, and gives an indication of possible influencing factors controlling runoff generation in the three catchments in relation to their respective wetness and precipitation patterns. The similarities investigated help identify similar catchment functioning and can be used, for instance, to develop enhanced catchment similarity indices.

Runoff response to the uncertainty from key water-budget variables in a seasonally snow-covered mountain basin

Study regionThe American River Basin, a seasonally snow-covered mountain basin in the northern Sierra Nevada of California, USA. Study focusPrecipitation phase (rain, snow, and mixed rain-snow) partitioning in snowy basins is important for runoff forecasting. This study focuses on how predicted runoff response is affected by uncertainty in rain-snow-transition elevation and other water-budget variables. Using a distributed hydrologic model, we examined predicted runoff differences across 33 extreme-precipitation events and dry seasons during 1982–2020, through a set of modeling experiments with different sources of transition elevation and values of water-budget variables. New hydrological insights for the regionDifferent transition elevations can result in noticeable differences in predictions of peak snow water equivalent (SWE) and dry-season runoff. Transition elevation modulates runoff response in a nonlinear way, with runoff uncertainty increasing during larger precipitation events. In terms of the relative impacts of water-budget variables on runoff response, precipitation has the greatest impact, followed by antecedent soil moisture, transition elevation, and antecedent SWE. A 2 °C warming would push the rain-snow-transition elevation ∼300-m higher, increasing the number and severity of extreme events. Compared to the historical period, the same transition-elevation uncertainty in climate warming conditions nearly triples its impacts on runoff uncertainty, posing additional challenges to flood control. This study provides implications for addressing uncertainty in flood-control and water-supply decisions confronted with hydrologic extremes and climate warming.

Lateral flow in bedrock dominates baseflow and flood flow in a catchment underlain with permeable sedimentary rock in the high‐relief Chichibu Mountains

AbstractDetermining the mechanisms of runoff generation is essential to land and water resource conservation, but lateral flow processes in high‐relief mountain areas remain unclear due to the difficulty to observe and measure these processes. This study demonstrates that lateral flow in bedrock dominates both high and low flows in a catchment underlain with permeable sedimentary bedrock in the high‐relief Chichibu Mountains. Through measurement of precipitation, discharge, soil, and stream temperatures and tracers (SiO2 and δ18O) in the first‐order stream Bakemonozawa (0.51 km2) and comparison of its water balance with the nested Kawamata catchment (93.58 km2) i, we showed that 831–1012 mm/year or 47%–53% of annual precipitation leaked from Bakemonozawa. The streamflow was discharged from an average depth of 2.3 m or deeper, which were deeper than the measured deepest soil near the gauge. Furthermore, stream temperature decreased significantly during a large summer storm, demonstrating that the relative contribution of the deep bedrock flowpath increased. Large isotopic variation in precipitation was dampened in the stream, suggesting that most baseflow and some higher flows arose from groundwater storage with a constant isotopic ratio due to dispersion and mixing. The discharge–SiO2 relationship suggested at least two groundwater sources, namely, shallow and deep bedrock groundwater, with different runoff responses. Discharge increased dramatically when the catchment became wet, coinciding with the deep bedrock groundwater contribution. Further research is needed to clarify the hydrological characteristics of bedrock.

The heat is on: Predicting urban stream temperature responses to summer storms

AbstractShort‐term increases in stream temperature in response to storm events have frequently been observed in urban areas, highlighting the need for improved understanding of the factors influencing urban stream temperature. Urban land cover complexity and infrastructure designed for rapid water routing to the sewer system create a direct link between storm events and water release processes, influencing urban stream temperature responses. This study aims to identify predictors of diverse stream temperature response patterns to summer storms. We analysed 403 storm events from six urban and semi‐urban catchments along the US East Coast using dynamic time warping to identify archetype patterns of stream temperature responses. We further disentangled observed stream temperature increase patterns to reveal the drivers associated with ‘heat pulses’, which are characterized by a rapid but high‐magnitude temperature increase followed by a sharp temperature drop at the start of the hydrograph increase. Our results show that stream temperature patterns were event‐specific and linked to pre‐event conditions and rainfall–runoff characteristics, with the shape of the hydrograph and rainfall–runoff response identified as the most important determinators of the observed temperature response patterns. Ponded surface waters and storm drains, as well as cooler water from the shallow subsurface, were identified as potential sources contributing to temperature patterns. These findings have important implications for understanding urban hydrology and the contributions of different source zones in urban catchments. Specifically, our results suggest that stream temperature may serve as a cost‐effective tracer providing information about urban water sources and pathways, thus aiding in the understanding of complex urban hydrology.

Runoff Threshold Responses in Continental Boreal Catchments: Nexus of Subhumid Climate, Low‐Relief, Surficial Geology, and Land Cover

AbstractWe examined annual runoff from 20 meso‐scale catchments over 25 years, to elucidate how interactions between physiography and long‐term weather patterns influence the magnitude of spatial–temporal thresholds in annual runoff responses in water‐limited, low‐relief, glaciated continental Boreal landscapes. Annual runoff ranged over 2 orders of magnitude (<3 to >300 mm) among catchments receiving similar annual precipitation. Threshold relationships were observed with cumulative regional moisture deficits that reflected spatial–temporal differences in effective storage and antecedent moisture among catchments with differing portions of glacial‐deposit and land‐cover types. The importance of the glacial‐deposit texture and forest‐peatland cover on runoff behavior among catchments varied with weather patterns and catchment antecedent moisture states. Dry states yielded low annual runoff that ranged by 2 orders of magnitude (0–80 mm), with higher values in catchments with predominantly coarse‐textured deposits. During near normal antecedent moisture, annual runoff remained low (<10 mm) in catchments associated with fine‐textured, hummocky landforms and deciduous forests. Annual runoff >10 mm was observed only in catchments with extensive peatlands. Infrequent wet states resulted in increased runoff in all catchments; however, ranges in maximum runoff were associated with heterogeneity in catchment landforms and land covers. Integrating cumulative precipitation with the proportion of glacial‐deposit and land‐cover types within catchments can (a) represent water cycling and regional sink‐source dynamics controlling runoff and (b) provide an effective management framework for predicting climate and land use impacts on regional runoff in water‐limited, low‐relief, glaciated landscapes such as the Boreal Plain.

Can land use/land cover optimization improve the environmental flow guarantee in regulated basins?

Land use/land cover (LULC) change is an important driver of changes in hydrologic processes in watersheds. Many studies have focused on the disruptive effects of human activity-induced urban sprawl and increased impervious surfaces on river runoff and environmental flow (e-flow), and little has been reported on whether LULC changes can improve e-flow security. Therefore, we proposed a hypothesis on whether LULC optimization can improve the e-flow guarantee using the Shayinghe River watershed as an example. To test the hypothesis, we evaluated the runoff response and e-flow security status of seven LULC scenarios (four historical scenarios and three possible optimization scenarios) by constructing the Soil and Water Assessment Tool (SWAT) model to establish the statistical relationship between a single LULC type and the e-flow guarantee rate (EGR) and e-flow deviation rate (EDR) and screened the best land optimization scenario for the Shayinghe River watershed. The results showed that: (1) forest land and grassland have positive effects on EGR, and LULC optimization can counteract the risk of dry season e-flow security caused by urban expansion and increased construction land to a certain extent; (2) construction land was the most active LULC type and inhibited the dry season flow and EGR of rivers, leading to moderate changes in the hydrological process of Shayinghe River; (3) the Grain for Green Project was the best LULC optimization scenario for the Shayinghe River basin, which converts 1342 km2 of cultivated land in the western part of the basin to forest land, resulting in the highest dry season EGR increases of 3.23 % and 2.26 % in Zhoukou and Fuyang, respectively. Our study proposes a relatively simple and easily replicable approach in other watersheds, providing a new reference for rational LULC planning and environmental flow protection in highly regulated watersheds.

SWAT model calibration for hydrological modeling using concurrent methods, a case of the Nile Nyabarongo River basin in Rwanda

The Nile Nyabarongo, which is Rwanda's largest river, is facing stress from both human activities and climate change. These factors have a substantial contribution to the water processes, making it difficult to effectively manage water resources. To address this issue, it is important to find out the most accurate techniques for simulating hydrological processes. This study aimed to calibrate the SWAT model employing various algorithms such as GLUE, ParaSol, and SUFI-2 for the simulation of hydrology in the basin of the Nile Nyabarongo River. Different data sources, such as DEM, Landsat images, soil data, and daily meteorological data, were utilized to input information into the SWAT modeling process. To divide the basin area effectively, 25 sub-basins were created, with due consideration of soil characteristics and the diverse land cover. The outcomes point out that SUFI-2 outperformed the other algorithms for SWAT calibration, requiring fewer computing model runs and producing the best results. ParaSol established residing the least effective algorithm. After calibration with SUFI-2, the most sensitive parameters for modeling were revealed to be (1) the Effective Channel Hydraulic Conductivity (CH K2) measuring how well water can flow through a channel, with higher values indicating better conductivity, (2) Manning's n value (CH N2) representing the roughness or resistance to flow within the channel, with smaller values suggesting a smoother channel, (3) Surface Runoff Lag Time (SURLAG) quantifying the delay between rainfall and the occurrence of surface runoff, with shorter values indicating faster runoff response, (4) the Universal Soil-Loss Equation (USLE P) estimating the amount of soil loss. The average evapotranspiration within the basin was calculated to be 559.5 mma-1. These calibration results are important for decision-making and updating policies related to water balance management in the basin.

Nonlinear control of climate, hydrology, and topography on streamflow response through the use of interpretable machine learning across the contiguous United States

Abstract Runoff has been greatly affected by climate change and human activities. Studying nonlinear controls on runoff response is of great significance for water resource management decision-making and ecological protection. However, there is limited understanding of what physical mechanisms dominate the runoff response and of their predictability over space. This study analyzed the spatial patterns of runoff response including runoff changes and its sensitivity to climate–landscape variations in 1,003 catchments of the contiguous United States (CONUS). Then, an interpretable machine learning method was used to investigate the nonlinear relationship between watershed attributes and runoff response, which enables the importance of influencing factors. Finally, the random forest model was employed to predict runoff response according to the predictors of catchment attributes. The results show that alteration of runoff is up to 56%/10 years due to climate change and human activities. Catchment attributes substantially altered runoff over CONUS (−60% to 56%/10 years). Climate, topography, and hydrology are the top three key factors which nonlinearly control runoff response patterns which cannot be captured by the linear correlation method. The random forest can predict runoff response well with the highest R2 of 0.96 over CONUS.

Evolution Characteristics of Landscape Patterns and the Response of Surface Runoff in a Rapid Urbanization Area: Focus on the Chang–Zhu–Tan Metropolitan Area of China

With the acceleration of urbanization, the disturbance to urban landscape patterns causes changes to urban surface runoff and increases the risk of urban waterlogging. We studied the response relationship between landscape pattern change and surface runoff in the Chang–Zhu–Tan metropolitan area for the period from 2000 to 2020, analyzing the driving factors that affected surface runoff. The influence of landscape pattern evolution on surface runoff was studied using the SCS-CN flow generation model, the moving window method, and Pearson’s analysis. The analysis showed that between 2000 and 2020, the forest area decreased, while the impermeable land area increased substantially. At the same time, the landscape spread degree (CONTAG) decreased, whereas the landscape fragmentation degree (DIVISION) increased, and the Shannon diversity index (SHDI) and landscape shape index (LSI) increased. The surface runoff in the main urban areas of Chang–Zhu–Tan increased substantially. The results showed that surface runoff is negatively correlated with SHDI, LSI, and DIVISION but displays a positive relationship to CONTAG. Soil texture and precipitation had the greatest impact on surface runoff. This study emphasizes the importance of landscape pattern evolution to surface runoff in rapidly developing metropolitan areas in terms of reducing surface runoff, alleviating urban waterlogging and preventing regional floods. Our research additionally seeks to optimize the landscape pattern of the Chang–Zhu–Tan metropolitan area.

Local‐ and network‐scale influence of peatlands on boreal catchment response to rainfall events

AbstractBoreal catchments are composed of different land covers, such as forests, peatlands and lakes, which differ in their runoff response to rainfall events. Understanding the individual and combined responses to rainfall events of these different land cover types is crucial for predicting potential impacts of future climate conditions on boreal water cycling. A common assumption is that peatlands attenuate peak flows, which is used as a motivation to restore drained boreal wetlands. However, it remains unclear how and to what extent peatlands can affect peak flow response. Only a few previous studies have looked at the hydrologic dynamics of peatlands in response to specific rainfall events across a wide range of nested sub‐catchments with varying peatland cover. In this study, we use nine years of hourly hydrometric data from 14 catchments within the Krycklan Catchment Study in northern Sweden to examine how peatlands contribute to flood attenuation at both local and stream network scales. Our analysis at the local scale demonstrated that during large events with low antecedent wetness conditions, peatland‐dominated catchment exhibited more muted responses compared to the similar‐sized forest‐dominated catchment. However, during events with high antecedent wetness conditions, the peatland‐dominated catchment exhibited flood magnitudes similar to the forest‐dominated catchment, although the elevated flow condition at the peatland‐dominated catchment persisted for longer periods. Finally, our analysis revealed no significant influence of peatlands on the attenuation or amplification of floods at the stream network scale.