Abstract. Prediction of mean annual runoff is great interest but still poses a challenge in ungauged basins. The present work diagnoses the prediction affected by uncertainty estimated distribution soil water storage capacity. Based on function, balance model for estimating developed, which effects climate variability and capacity are explicitly represented. As such, two parameters have explici...

Abstract Groundwater availability is one of the key anxieties in most semi-arid regions Ethiopia. The purpose this study was to investigate groundwater potential zone map alluvial plain Gambela. applied analytic hierarchy process (AHP) models with four different machine learning algorithms: random forest classifier (RFC), gradient boosting (GBC), decision tree (DTC), and K-neighbor (KNC). featu...

The success rate in landslide susceptibility mapping efforts increased with the advancements machine learning algorithms and availability of geospatial data high spatial temporal resolutions. Existing data-driven models are not globally applicable due to variability conditioning parameters limitations up-to-date accurate data. Among numerous applications, maps essential for site selection healt...

Land-use change has an impact on growing physical flood vulnerability. Geographic Information System (GIS) and Analytic Hierarchy Process (AHP) approaches are increasingly being used for vulnerability assessments. However, none time-series land cover data evaluation rainfall over various return periods prediction simultaneously, especially in Indonesia. Therefore, this study aims to evaluate pr...

Protected areas (PA) play an important role in minimizing the effects of soil erosion watersheds. This study evaluated performance machine learning models, specifically support vector with linear kernel (SVMLinear), polynomial (SVMPoly), and random forest (RF), on identifying indicators 761 sub-watersheds PA northern Portugal, by using water Europe, according to revised universal loss equation ...

Digital elevation models (dems) provide the basic information required to characterise the topographic attributes of terrain. The primary derived topographic parameters associated with DEMs are slope and aspect. Slope and aspect can be used to calculate other significant topographic parameters such as upslope area and topographic index. The topographic index, in turn, can be used by distributed...

Groundwater occurrence in semi-arid regions is variable space and time due to climate patterns, terrain features, aquifer properties. Thus, accurate delineation of Potential Zones (GWPZs) essential for sustainable water resources management these environments. The present research aims delineate assess GWPZs a basin San Luis Potosi (SLP), Mexico, through the integration Remote Sensing (RS), Geo...

Many biochemical processes and dynamics are strongly controlled by terrain topography, making digital elevation models (DEM) a fundamental dataset for range of applications. This study investigates the quality four pan-Arctic DEMs (Arctic DEM, ASTER ALOS DEM Copernicus DEM) within Kalix River watershed in northern Sweden, with aim informing users about when comparing these DEMs. The assessment ...

Cold sensations are suggested as the primary inducer of the perception of skin wetness. However, limited data are available on the effects of skin cooling. Hence, we investigated the role of peripheral cold afferents in the perception of wetness. Six cold-dry stimuli (producing skin cooling rates in a range of 0.02-0.41°C/s) were applied on the forearm of 9 female participants. Skin temperature...

A wetness duration experiment was carried out within a lily field situated adjacent to coastal dunes in the Netherlands. A within-canopy model was applied to simulate leaf wetness in three layers, with equal leaf area indices, within the canopy. This simulation model is an extension of an existing model. It appeared that in most cases leaf wetness started in the uppermost layer followed by the ...