The complex interactions and feedbacks between humans and water are critically important issues but remain poorly understood in the newly proposed discipline of sociohydrology (Sivapalan et al., 2012). An exploratory model with the appropriate level of simplification can be valuable for improving our understanding of the co-evolution and self-organization of socio-hydrological systems driven by...

The phase of precipitation when it reaches the ground is a first-order driver of hydrologic processes in a watershed. The presence of snow, rain, or mixed-phase precipitation affects the initial and boundary conditions that drive hydrological models. Despite their foundational importance to terrestrial hydrology, typical phase partitioning methods (PPMs) specify the phase based on near-surface ...

underground dams have recently been considered as hydrological structures for the development of water resources, especially in the dry regions of iran. in this investigation along with the basic studies and the aquifer flow modeling, the probable hydrogeological effects of an underground dam are investigated. the proposed place for the ganjeh underground dam is chehel-khaneh aquifer located in...

prediction of hydrological variables is a highly effective tool in water resource management. One of the important tools for modeling hydrological processes is the use of time series modeling and analysis. River series production series can be used by time series models in various studies such as drought, flood, reservoir systems design and many other purposes For this purpose, monthly flow dat...

Computer models, especially conceptual models, are frequently used for catchment hydrology studies. Teaching hydrological modeling, however, is challenging, since students have to both understand general model concepts and be able to use particular computer programs when learning to apply computer models. Here we present a new version of the HBV (Hydrologiska Byråns Vattenavdelning) model. This...

There has been increasing interest in algae-based bioassessment, particularly, trait-based approaches are increasingly suggested. However, the main drivers, especially the contribution of hydrological variables, of species composition, trait composition, and beta diversity of algae communities are less studied. To link species and trait composition to multiple factors (i.e., hydrological variab...

An artificial neural network (ANN) was used to evaluate the hydrological responses of two streams in the northeastern U.S. having different hydroclimatologies (rainfall and snow+rain) to hypothetical changes in precipitation and thermal regimes associated with climate change. For each stream, historic precipitation and temperature data were used as input to an ANN, which generated a synthetic d...