Undoubtedly, the flood is known as a natural disaster. But in practice, the flood is considered the most terrible natural disaster in terms of mortality and financial losses. In this regard, a worrying trend is the increasing trend of mortality and flood damage in the world in recent decades. The increase in population and assets in the floodplain the changes in hydro systems and the destructive effects of human activities have been a major cause of this trend. In this chapter, due to the importance of this natural phenomenon in the ZayandehRud basin, the general study of flood and its effective factors in creating it, based on library studies and reports, and the collection of flood statistics in the basin during a 40-year period and the damage caused by this flood, has been attempted. With the causes and factors influencing the flooding and also the use of EXCEL software for various damages caused by these floods in high risk cities of this basin, has been identified. In general, the cause of many floods in the central parts of Iran, including ZayandehRud basin, is high rainfall. The causes of these rainfall are also related to the Elenino and Lenina phenomenon, as well as the passage of low pressure systems, which after affecting a large amount of steam from the Mediterranean, affect the western parts of the province that overlooks the Zagros mountains.
The solution of multipurpose tasks of ecological forecasting may depend to a great extent on the results of system analysis of nature-territorial structures, which are most sensitive to external effects including anthropogenic. The scientific search in this direction focuses more and more attention on the natural boundaries – both individual and complex, where the most significant natural or anthropogenic shifts in the structure and function of geo(eco)systems are observed. Considering one or another natural boundary as a vector (connection, cascade, para-dynamical, etc.) landscape system with a clearly defined spatial polarization of its different properties, we obtain a "fast-flowing" model of state response and resistance of geo(eco)systems to the action of certain ecological factors. The study of the structural-functional organization of natural ecosystems at the geographical ecotones is also of scientific and methodical importance, which is common with geo-ecology and, in addition, most important for regional and local landscape-ecological forecasts. Geographical ecotones are the most sensitive (and, in this sense, the least stable) fragments of natural-territorial mosaic. The boreal biogeographic ecotone of the Volga River basin is described as an example for considering the theoretical and scientific-methodical problems of geographical zonality: the fundamental ecological-geographical conception at the present-day stage of biosphere evolution associated with the global anthropogenic impact on the climate. A conception on regional bioclimatic system, characterizing climate-genic exo-dynamic characteristics of soil-vegetation "core" of natural com-plexes is presented. It can survey as a scientific-methodological base of paleogeographical reconstructions and landscape-ecological forecasts. Climate nishes of the phytocoenological and soil’ units are the elements of bioclimatic system and the forms of display of soil-vegatation cover’ hydrothermal stability during the changing climate. Zonal boundaries are considered as modern spatial analogs of the future landscape changes in time. The work dwells on the basic "trigger" mechanisms of zonal boundary formation at the interaction of background climatic signals and their refraction by local (mainly lithe-genic) factors.
Selecting a rainfall-runoff model for use in flood forecasting is not a direct decision and actually may contain the selection of more than one. There are a range of rainfall-runoff models for flow forecasting. They range in type from transfer function (empirical black box), through lumped conceptual to more physically-based distributed models. The rainfall-runoff models also are often accompanied by updating techniques for taking account of recent measurements of flow so as to improve the accuracy of model predictions in real-time. Against this variety of available modelling techniques, this study improved understanding of the most important and well known rainfall-runoff models for flood forecasting and highlighting their similarities and differences. Six models are selected in this study: the Probability Distributed Moisture (PDM) model, the Isolated Event Model (IEM), the US National Weather Service Sacramento model, the Grid Model, the Transfer Function (TF) model and the Physically Realisable Transfer Function (PRTF) model. The first three are conceptual soil moisture accounting models, with the Grid Model having a distributed formulation, whilst the TF and PRTF are “black box” time-series models. Also new model for the forecasting (e.g neural network (NN), fuzzy rule-based are reviewed. An important feature of the use of rainfall-runoff models in a real-time forecasting environment is the ability to integrate recent observations of flow in order to develop forecast performance. The available methods for forecast updating are reviewed with specific reference to state correction and error prediction techniques.