775 Results Found

Understanding rainfall processes as the main driver of the hydrological cycle is important for formulating future water management strategies; however, rainfall data availability is challenging for countries such as Ethiopia. This study aims to evalu...

Small portable rainfall simulators are considered a useful tool to analyze soil erosion processes in cultivated lands. European research groups in Spain (Valencia, Málaga, Lleida, Madrid and La Rioja), France (Reims) and Germany (Trier) have used dif...

Near real-time precipitation is essential to many applications. In Africa, the lack of dense rain-gauge networks and ground weather radars makes the use of satellite precipitation products unavoidable. Despite major progresses in estimating precipita...

Climate change impacts have the potential to alter the design rainfall estimates around the world. Decreasing trends in the summer and winter rainfall in New South Wales (NSW), Australia have already been observed due to climate variability and chang...

In this paper, an experimental comparison between different rainfall harvesting devices through the study of the electrical rectifying circuit is proposed. In more detail, three harvesting structures are considered: the cantilever, the bridge and the...

Landslides can be triggered by intense or prolonged rainfall. Rain gauge measurements are commonly used to predict landslides even if satellite rainfall estimates are available. Recent research focuses on the comparison of satellite estimates and gau...

Accurate rainfall forecasting in watersheds is of indispensable importance for predicting streamflow and flash floods. This paper investigates the accuracy of several forecasting technologies based on Wavelet Packet Decomposition (WPD) in monthly rai...

Satellite derived rainfall products are useful for drought and flood early warning and overcome the problem of sparse, unevenly distributed and erratic rain gauge observations, provided their accuracy is well known. Mozambique is highly vulnerable to...

Accurate quantitative precipitation estimation (QPE) is fundamental for a large number of hydrometeorological applications, especially when addressing extreme rainfall phenomena. This paper presents a comprehensive comparison of various rainfall esti...

Accurate estimation of precipitation patterns is essential for the modeling of hydrological systems and for the planning and management of water resources. However, rainfall time series, as obtained from traditional rain gauges, are frequently corrup...

The spatial and temporal scale of rainfall datasets is crucial in modeling hydrological processes. Recently, open-access satellite precipitation products with improved resolution have evolved as a potential alternative to sparsely distributed ground-...

Rainfall infiltration is the primary factor that induces landslides. In this paper, discrete element software (PFC^3D) was used to establish a novel rainfall infiltration model, which integrates water transfer, intensity decay and seepage force into t...

To enable the accurate assessment of landslide susceptibility in the upper reaches of the Minjiang River Basin, this research intends to spatially compare landslide susceptibility maps obtained from unclassified landslides directly and the spatial su...

This research evaluates the applicability of different types of hydrological models to simulate discharge behavior scenarios in a northern Moroccan watershed, Oued Laou Watershed (OLW). In this context, an improved understanding of the runoff mechani...

The surface fine dead fuel moisture content (FFMC) is an important factor in predicting forest fire risk and is influenced by various meteorological factors. Many prediction methods rely on temperature and humidity as factors, resulting in poor model...

This paper presents a comparison between C-band and X-band radar data over an instrumented and regulated catchment of the Paris region. We study the benefits of polarimetry and the respective hydrological impacts with the help of rain gauge and flow...

Precipitation is one of the essential variables in rainfall-runoff modeling. For hydrological purposes, the most commonly used data sources of precipitation are rain gauges and weather radars. Recently, multi-satellite precipitation estimates have ga...

Monoculture forests formed by Fagus sylvatica L. belong to one of the most sensitive forest ecosystems, mainly at low altitudes. Cultivation of this species in mixed stands should reduce its sensitivity to drought in the vegetation period, which is w...

Several satellite precipitation estimates are becoming available globally, offering new possibilities for modeling water resources, especially in regions where data are scarce. This work provides the first validation of four satellite precipitation p...

This study analyzed the characteristics of, and locations prone to, extreme rainfall-induced landslides in three watersheds in Taiwan, as well as the long-term evolution of landslides in the Laonong River watershed (LRW), based on multiannual landsli...

This paper investigates the relationship between the Normalized Difference Vegetation Index (NDVI) and extracted rainfall in the Global Precipitation Climatology Project (GPCP) in Central Africa between latitudes 15°S and 20°N and longitudes 0°E a...

The Amazon Basin is the largest rainforest in the world, and studying the rainfall in this region is crucial for understanding the functioning of the entire rainforest ecosystem and its role in regulating the regional and global climate. This work is...

With the ultimate goal of developing models that involve the use of environmental variables, a GIS-based application is being developed that is circumscribed to the region of Galicia (Spain). Ten-minute data of six meteorological variables were colle...

Interactions between soil and rainfall plays a vital role in ecological, hydrological and biogeochemical cycles of land. Among those interactions, the phenomenon of rainfall induced soil erosion is crucial to the soil functions, as it affects the soi...

The spatial distribution of precipitation is an important aspect of water-related research. The use of different interpolation schemes in the same catchment may cause large differences and deviations from the actual spatial distribution of rainfall....

Despite the several sources of inaccuracy, commercial microwave links (CML) have been recently exploited to estimate the average rainfall intensity along the radio path from signal attenuation. Validating these measurements against “ground trut...

This study compares multi model ensemble (MME) projections of rainfall using general quantile mapping, gamma quantile mapping, Power Transformation and Linear Scaling bias correction (BC) methods for representative concentration pathways (RCPs) 4.5 a...

Different ways to estimate future return levels (RLs) for extreme rainfall, based on extreme value theory (EVT), are described and applied to the Iberian Peninsula (IP). The study was done for an ensemble of high quality rainfall time series observed...

Current research studies offer an investigation of machine learning methods used for forecasting rainfall in urban metropolitan cities. Time series data, distinguished by their temporal complexities, are exploited using a unique data segmentation app...

This study investigates the comparative performance of event-based and continuous simulation modelling of a stormwater management model (EPA-SWMM) in calculating total runoff hydrographs and direct runoff hydrographs. Myponga upstream and Scott Creek...

Precise rainfall measurement is essential for achieving reliable results in hydrologic applications. The technological advancement has brought numerous rainfall datasets that can be available to assess rainfall patterns. However, the suitability of a...

Climate change affects many meteorological parameters that could result in spatiotemporal variations of the hydrological cycle. These variations can affect local rainfall intensities or design storms; therefore, it is necessary to assess the local ef...

This study examines the changing rainfall patterns in the Vietnamese Mekong Delta (VMD) utilizing observational data spanning from 1978 to 2022. We employ the Mann–Kendall test, the sequential Mann–Kendall test, and innovative trend analy...

Rainfall–runoff models are crucial tools for managing water resources. The absence of reliable rainfall data in many regions of the world is a major limitation for these models, notably in many African countries, although some recent global rai...

Consistent time series rainfall datasets are important in performing climate trend analyses and agro-hydrological modeling. However, temporally consistent ground-based and long-term observed rainfall data are usually lacking for such analyses, especi...

Due to its location, its old sewage system, and the channelling of rivers, Oslo is highly exposed to urban flooding. Thus, it is crucial to provide relevant and reliable information on extreme precipitation in the planning and design of infrastructur...

This study delved into the analysis of hourly observed as well as future precipitation data in the towns of Willoughby and Buffalo on the Lake Erie Coast to examine the variations in IDF relationships over the 21st century. Several regional climate m...

Satellites offer a way of estimating rainfall away from rain gauges which can be utilised to overcome the limitations imposed by gauge density on traditional rain gauge analyses. In this study, Australian station data along with the Japan Aerospace E...

This study introduces a systematic methodology whereby different technologies were utilized to download, pre-process, and interactively compare the rainfall datasets from the Integrated Multi-Satellite Retrievals for Global Precipitation Mission (IME...

Due to the spatial variability of hydraulic properties, probabilistic slope seepage analysis becomes necessary. This study conducts a probabilistic analysis of slope seepage under rainfall, considering the spatial variability of saturated hydraulic c...

To better understand the effect and constraint of different data lengths on the data-driven model training for the rainfall-runoff simulation, the support vector regression (SVR) approach was applied to the data-driven model as the core algorithm in...

In this study, three model perturbation schemes, the stochastically perturbed parameter scheme (SPP), stochastically perturbed physics tendency (SPPT), and multi-physics process parameterization (MP), were used to represent the model errors in the re...

The objective of flood frequency analysis (FFA) is to associate flood intensity with a probability of exceedance. Many methods are currently employed for this, ranging from statistical distribution fitting to simulation approaches. In many cases the...

Precipitation is considered a crucial component in the hydrological cycle and changes in its spatial pattern directly influence the water resources. We compare different interpolation techniques in predicting the spatial distribution pattern of preci...

The isotopic composition of precipitation provides valuable information about its source and transportation. However, raindrops interact with vegetation before reaching the earth’s surface, leading to isotopic changes in the infiltrating water....

Rainfall is an indispensable link in the atmospheric water cycle, which plays a critical role in forest hydrology. Quercus acutissima and Cunninghamia lanceolata are two fast-growing and economically important tree species in the middle and lower rea...

Rainfall-runoff models can be classified into three types: physically based models, conceptual models, and empirical models. In this latter class of models, the catchment is considered as a black box, without any reference to the internal processes t...

Runoff information can be used for establishing watershed water management plans. However, hydrological models with complex parameters make it difficult to quickly estimate runoff. This study developed a one-parameter new exponential (ONE) model for...

This study compares the bias correction techniques of empirical quantile mapping (QM) and the Long Short-Term Memory (LSTM) machine learning model for summertime daily rainfall simulation focusing on precipitation-dependent bias and temporal variatio...

As a major component of the hydrologic cycle, rainfall runoff plays a key role in water resources management and sustainable development. Conceptual models of the rainfall-runoff process are governed by parameters that can rarely be directly determin...