Change in Land Cover and Land Use (LCLU) influences the runoff characteristics of a drainage basin to a large extent, which in turn, affects the surface and groundwater availability of the area, and ...hence leads to further change in LCLU. This forms a vicious circle. Hence it becomes essential to assess the effect of change in LCLU on the runoff characteristics of a region in general and of small watershed levels (sub-basin levels) in particular. Such an analysis can effectively be carried out by using watershed simulation models with integrated GIS frame work. SWAT (Soil and Water Analysis Tool) model, being one of the versatile watershed simulation models, is found to be suitable for this purpose as many GIS integration modules are available for this model (e.g. ArcSWAT, MWSWAT). Watershed simulation using SWAT requires the land use and land cover data, soil data and many other features. With the availability of repository of satellite imageries, both from Indian and foreign sources, it becomes possible to use the concurrent local land use and land cover data, thereby enabling more accurate modelling of small watersheds. Such availability will also enable us to assess the effect of LCLU on runoff characteristics and their reverse impact. The current study assesses the effect of land use and land cover on the runoff characteristics of two watersheds in Kerala, India. It also assesses how the change in land use and land cover in the last few decades affected the runoff characteristics of these watersheds. It is seen that the reduction in the forest area amounts to 60% and 32% in the analysed watersheds. However, the changes in the surface runoff for these watersheds are not comparable with the changes in the forest area but are within 20%. Similarly the maximum (peak) value of runoff has increased by an amount of 15% only. The lesser (aforementioned) effect than expected might be due to the fact that forest has been converted to agricultural purpose with major portion as plantations which have comparatively similar characteristics of the forest except for evapo-transpiration. The double sided action (increase in evapo-transpiration owing to species like rubber and increase percolation due to its plantation method by using terracing) might be the reason for relatively smaller effect of the land use change, not commensurate with the changes in the forest area amounting to 60% and 32% for Manali and Kurumali watersheds respectively. Water harvesting methods like rain harvesting ditches can be made mandatory where species with high evapo-transpiration are grown. This action shall enhance the groundwater percolation and shall counter act the effect due to high evapo-transpiration.
•The transformation matrix analyses of the land use reveal an appreciable change in forest cover.•Paddy fields convertion was driven by prevailing economic condition in the state.•Effect of land use change on runoff does not commensurate with the change in land use.
The study presents a GIS-based morphometric analysis characterizing the watersheds in Bohol, Philippines. An IfSAR-derived DEM data were processed and used to delineate the watersheds and evaluate ...morphometric parameters in QGIS/QSWAT. The analysis revealed that Loboc Watershed (LW) and Wahig-Inabanga Watershed (WIW) were sixth-order watersheds. Covering 675 km
2
(LW) and 610 km
2
(WIW), the watersheds encompassed about 34% of the mainland area. The bifurcation ratios, 3.91 (WIW) and 4.06 (LW), suggested highly dissected watersheds with high flood peaks. LW has low permeability, and high runoff and erosion susceptibility compared to WIW, as indicated by higher values for the form factor, circulatory ratio, drainage density, and stream frequency. The ruggedness numbers of 1.653 (WIW) and 1.457 (LW) indicated steep slopes in WIW than in LW, associated with high erosion and environmental degradation. The hypsometric integral of 0.22 (WIW) and 0.37 (LW) implied lesser erosional areas in WIW than in LW. The study found that both watersheds were highly susceptible to erosional processes. The two watersheds performed critical environmental functions on Bohol Island; hence, the results of this study present a piece of baseline information for resource managers to conduct further investigations that would identify hotspot areas and enable targeted soil and water conservation initiatives.
Recent studies suggested that runoff of bedrock groundwater can influence shallow landslides. As a first step towards incorporating the effect of bedrock groundwater runoff into shallow landslide ...prediction models, we analyzed characteristics and developed models of bedrock spring runoff based on detailed observations of two bedrock springs in a small granitic mountainous catchment. Spring temperature and chemistry indicated that they originate from the same aquifer in deep bedrock. The increment in runoff in response to rainfall events was correlated with the total rainfall amount, and the lag time from the rainfall peak to the runoff peak was more than approximately 1 day. Runoff dynamics were reproduced by the functional models using antecedent precipitation indices with half lives of 156.0 and 211.9 h. These results imply that bedrock groundwater can influence shallow landslides through raising soil mantle groundwater level by its perennial runoff.
•Geological factors explain 27% to 56% of the variation in runoff characteristics.•Hydrogeological factors explain up to 30% of the variation in runoff characteristics.•Each geological factor not ...only directly but also indirectly affected the runoff characteristics.
Lithology, dissolution degree, and other geological factors are essential factors affecting karst environments. However, the complex effects of multiple geologic factors on runoff characteristics have not been well quantified in karst catchments. Thus, 30 catchments and four runoff characteristics (runoff coefficient, runoff modulus, annual runoff extremes ratio, and annual runoff variation coefficient) were selected in this study to evaluate the influence of geological factors on runoff characteristics in karst catchments. The linear mixed effect model was used to quantitatively evaluate the contribution rate of each factor to the runoff characteristics, and the structural equation model was used to analyze the quantitative relationship between each factor and the runoff characteristics. The results show that among the three aspects of geological factors, hydrogeological factors have the greatest influence on runoff characteristic values. In turn, the density of sinkhole is the most influential factor among the hydrogeological factors. Geological structure factors had both direct and indirect effects on runoff characteristics (path coefficient is 0.27). Among them, the density of faults is the most influential factor. Geochemical factors affected runoff characteristics more by influencing hydrogeological factors (path coefficient −0.51) or geological structure factors (path coefficient −0.43). In conclusion, data from several watersheds directly confirm that in karst watersheds, these geological factors such as hydrogeology, geochemistry, and geological structure have a very fundamental influence on karst watershed runoff characteristics. Our results can help us further understand karst hydrological processes and improve the accuracy of karst hydrological modeling.
•Runoff difference between volcanic and non-volcanic headwater catchments described.•Hydraulic conductivity and water table depth are key factors for these differences.•Difference in runoff among ...young volcanic headwater catchments (VHCs) is smaller.•Topography and water table depth differences affect runoff generation in youg VHCs.
Because volcanic rocks have high permeability, rainfall quickly infiltrates into the ground. Perennial rivers often do not exist in volcanic areas. However, available studies elucidating hydrologic characteristics and the mechanisms of stream formation in young volcanic areas are limited in number, extent, and coverage prohibiting a comprehensive understanding of runoff formation. By measuring river discharge for two years, we examined the characteristics of surface runoff in four adjacent headwater catchments within a young volcanic area of Mt.Fuji. The runoff coefficient R is small, rainfall thresholds for discharge are large, and the lag time Tlag and duration D of rainfall-runoff events are short. These characteristics can be explained by the groundwater flow as the dominant runoff mechanism with high hydraulic conductivity. Due to differences in topography and the depth of groundwater, some differences existed amongst the four adjacent catchments. In addition, a comparison of runoff characteristics between the young volcanic headwater catchments (VHCs) and non-volcanic headwater catchments (NVHCs) reported in other studies established that young VHCs have a smaller R, a shorter Tlag and D, and a larger runoff threshold for storm runoff than NVHCs. These differences are attributed to differences in the hydraulic conductivity of the underlying geology. These findings should help improve hydrological models and river structures for flood prevention.
•The variation characteristics of permafrost for 36 years has been identified.•The relationship between n in the Budyko framework and DDF is quantified.•Permafrost degradation contributes more than ...20% to runoff change.
To quantitatively investigate the permafrost degradation and its effects on hydrological processes in the upper reaches of Heihe River, a surface frost number model was firstly constructed to simulate the permafrost distribution and degradation from 1980 to 2015. The variation characteristics of the DDF, permafrost area, low limit of permafrost, and active layer thickness were then determined in the study area. Furthermore, the Budyko framework was applied to quantify the contribution of permafrost degradation to runoff. The results indicated that the permafrost degradation was significant in the past 36 years, with an average decreasing rate of 80.4 km2/a in the permafrost area, an average increasing rate of 13 m/a and 0.61 cm/a in the low limit elevation and in the active layer thickness, respectively. It is also found that basin characteristic parameter in the Budyko framework is closely related to permafrost degradation in cold regions, 40% of whose change is contributed by permafrost degradation. In addition, it is revealed that permafrost degradation contributed more than 20% to runoff change in study area. This investigation also indicated that the runoff response to permafrost degradation has a 3 months delayed effect. This study deepens the understanding of the impact of permafrost degradation on hydrological processes.
Short‐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.
Stream temperature shows varied responses to storms, including temperature increases and decreases. These increases may be gradual or consist of a rapid, short‐lived temperature increase at the start of the hydrograph rise. Stream temperature responses to storms are event‐specific and can be linked to event characteristics.
Clarifying the relationship between rainfall and runoff characteristics in mountainous areas is crucial to improving flood and sediment disaster prediction. This study investigates that relationship, ...focusing on meso‐scale catchments of 1–10 km2 in high‐relief mountainous regions where conventional observational data are limited. Such research requires observations in multiple adjoining watersheds due to the variability of runoff patterns in mountainous river systems. However, observations are challenging in meso‐scale catchments due to equipment loss in rivers. This study included seven observation sites with catchment areas of 0.16–9.01 km2 and relative elevations exceeding 1000 m within the Higashigochi River basin, a sub‐branch of the Oi River basin in Shizuoka Prefecture, Japan. Water level gauges were strategically installed at each of these locations to prevent loss. Peak lag time (the time difference between the rainfall and water level peaks), which is crucial to flood hydrograph definition and disaster preparedness, was assessed. The results indicate a general trend of increasing peak lag time with larger catchment area, although spatial heterogeneity was observed at small sites. This finding aligns with prior studies in meso‐scale catchments within mountainous regions with relative elevations of 450 m or less, suggesting that in such meso‐scale catchments, larger catchment area tends to result in longer peak lag times, regardless of topographic undulation. Overall, the impact of topographic undulations on peak lag time appears surprisingly modest, indicating that catchment area plays a more significant role in determining peak lag time. The observed heterogeneity of peak lag time could be attributable to the influence of bedrock groundwater discharge.
Rainfall–runoff data are notably scarce for meso‐scale (1–10 km2) catchments and high‐relief mountain areas.
Based on observations in seven high‐relief meso‐scale catchments, we found that peak runoff is delayed longer after the rainfall peak in larger catchments, while the peak lag time was more variable in smaller catchments.
Similar trends have been observed in low‐relief mountainous areas, suggesting that the peak lag time is primarily controlled by catchment size rather than undulation.
