Probabilistic forecasting is receiving growing attention nowadays in a variety of applied fields, including hydrology. Several machine learning concepts and methods are notably relevant toward addressing the major challenges formalizing optimizing probabilistic implementations, as well equally important challenge identifying most useful ones among these implementations. Nonetheless, practically...

In any hydrologic study, the most important parameter is runoff which necessary for designing hydraulic structure, and determining risk of flood. As there a scare in availability data many sites, hydrologists have developed indirect methods to determine accelerate program watershed management conserving developing water resources management. Many are used estimate runoff; Soil conservation curv...

In this reply to Thaler, we take the opportunity explore two main aspects of his piece continue discussion: (1) integration data from social and natural sciences, (2) importance transdisciplinary research. We agree, highlight that necessary learning, reflections participation processes are time-intensive for researchers, practitioners participants. believe these discussion pieces important info...

This work presents a comprehensive assessment of the suitability random forests, well-known machine learning technique, for statistical downscaling precipitation. Building on experimental and validation framework proposed in Experiment 1 COST action VALUE—the largest, most exhaustive intercomparison study methods to date—we introduce thoroughly analyze posteriori forests (AP-RFs), which use all...

Abstract Knowledge of hydraulic conductivity (K) is inevitable for sub-surface flow and aquifer studies. Hydrologists groundwater researchers are employing data-driven techniques to indirectly evaluate K using porous media characteristics as an alternative direct measurement. The study examines the ability Adaptive Neuro-Fuzzy Inference System (ANFIS) predict two membership functions (MFs), i.e...

Flash floods are a major weather-related risk, as they cause more than 5000 fatalities annually, according to the World Meteorological Organization. Quantitative Precipitation Estimation is method used approximate rainfall over locations where direct field observations not available. It represents one of most valuable information employed by meteorologists and hydrologists for issuing early war...

Preparedness against floods in a hazard management perspective plays major role the pre-event phase. Hence, assessing urban vulnerability and resilience towards for different risk scenarios is prerequisite planners decision makers. Therefore, main objective of this study to propose design implementation spatial support tool mapping flood metropolis Tehran under scenarios. Several factors reflec...

Solar radiation data are required for many applications and areas of research. In order to achieve this, several empirical models have been suggested predict the global solar in Turkey other countries. The different meteorological as radiation, sunshine duration, temperature, atmospheric pressure, wind speed relative humidity were measured by Eskisehir Osmangazi University during period between...

Current governance of regional scale water management systems in the United States has not placed them on a path toward sustainability, as conflict and gridlock characterize the social arena and ecosystem services continue to erode. Changing climate may continue this trajectory, but it also provides a catalyst for renewal of ecosystems and a window of opportunity for change in institutions. Res...

Popular concern over water quality has important implications for public water management because it can both empower water utilities to improve service but also limit their ability to make changes. In the desert city of Phoenix, Arizona, obtaining sufficient high-quality water resources for a growing urban population poses a major challenge. Decision makers and urban hydrologists are aware of ...