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IntroductionThe world population has grown rapidly over the last 150 years and continues to do so, resulting in impacts on hydrologic resources at both a local and global scale (Yang et al., 2012). The competition for water between humans and ecosystems leads to complex interactions between hydrologic and social systems (liu et al., 2015). From the beginning of human history, it is located in floodplains. Floods can have large societal impacts, such as severe damage to urban areas, which are expected to grow around the world (Alfieriet al., 2018). In traditional hydrology, humans are either conceptualized as an external force to the system under study or taken into account as boundary conditions (Peel and Blöschl, 2011). Sivapalan et al. (2012) proposed a new model for investigating the interactions of the hydrological system and the social system. It explores the procedure coupled human-water system evolves and possible trajectories of its co-evolution, including the possibility of generating emergent, even unexpected, behaviors. Socio-hydrology must strive to be a quantitative science. There are several methods to control and mitigate flood risk, one of these methods is flood zoning (Jha et al., 2012). In last two decates, The Kalat city is flooded almost every year and many houses and historical sites in the city are damaged. Therefore, the main purpose of thisWe paper is to show investigated how changing human behavior with nature can affect the behavior of the natural system.Method and MaterialsKalat city located in 59° 43' 23" to 59° 47' 41" northern latitude and 36° 59' 35" to 37° 00' 05" eastern longitude. The city is divided into 11 sub-basins. The city has experienced fast and inappropriate urbanization over the past few years. To collect our data, the annual reports of the Regional Water Organization and the Environment Organization of Khorasan Province were used.SCS method was used to estimate the runoff peak discharge. Precipitation has been estimated for seven return periods: 2, 5, 10, 25, 50, 100, and 200 years. In this study, to analyze the sensitivity of runoff, we considered precipitation and curves number from 20% less to 20% more than the actual values in the study basin (at intervals of 5 %). We used the Cowan method to determine the roughness coefficient in this study. HEC-RAS model has been used for flood zoning. To determine the impact of various factors on the intensification of floods in Kalat city, we obtained questionnaires from relevant authorities. Likert scale was used to measure the results of the questionnaires. We prepared two questionnaires; first one is related to the inner city zone and includes the factors that intensify the occurrence of floods inside the city of Kalat, and it was classified into the following parts: 1) Local community 2) Managerial 3) Physical; and the second one includes the factors that intensify the flood in the upper part of Kalat city. We classified these factors into three parts: 1) Non-local community 2) Managerial 3) Environmental .Results and DiscussionResults of sensitivity analyzes demonstrated that land-use and land cover change had a further effect on peak discharge. In sub-basin 1, by 20% increase in the curve number, the level of peak dumping increased by more than 111%, with a return period of 2 year; while a 20% increase in precipitation, in the same return period, rises the peak discharge only 3%. The peak discharge time in some sub-basins was brief due to the presence of impermeable surfaces, so that in sub-basins 4, 6, 7, and 8, the peak discharge time was less than 30 minutes. These results highlight the dangers of these floods and the need for proper flood planning and management in these sub-basins. The results of the Manning coefficient demonstrated that we can reduce flood damage by applying management measures in the future, as well as paying attention to the feedback between urbanization and the flood zone. Roughness control by applying management programs can reduce the area of flood zones to 0.1 square kilometers. In this case, buildings should be removed from the river, and there should be no structure in the path of the river. According to the questionnaires in the inner city part, the most fundamental factor in intensifying the flood damage was related to “activities of local people” with the average of 3.59. In the upper part of the city, the most influential factors were ascribed to “managerial factors” with the average of 3.79.ConclusionIn a general conclusion, it can be concluded that the role of human factors in the occurrence and intensification of floods was much greater than rainfall. Therefore, in order to manage and control floods, it is necessary to prevent the change of land use and the reduction of permeability. And management programs should be aimed at increasing surface permeability. We suggest that more research be done on the role of economic and social factors in increasing flood risk in other climate zones.

The weighting factor of the sediment connectivity index (IC) is a challenging component of this index and must be properly explicated for different situations. The aim of this study is to develop a proper weighting factor for calculating IC based on experiments on three tilled soils from dry-farming fields in Kouheen, Sararud, and Gachsaran regions under a 111 mm/h rainfall simulation using a 5.8 m2 laboratory flume with a slope of 12%. For each soil sample, two rain events (R1 and R2) were simulated with an interval of 4 hours, and the soil losses were measured. In addition, a digital elevation model with a pixel size of 2 mm was prepared by accurate photography after each rain followed by calculating the IC based on roughness coefficient (RI) as the weighting factor. Measured soil losses of two rainfalls were 4796 and 3909 g for Gachsaran soil, 3465 and 2464 g for Kouheen soil, and 2679 and 2105 g for Sararud soil, respectively. The result shows that with increasing IC based-RI, soil loss was decreased which indicates the inadequacy of RI alone as a weighting factor. To develop a new weighting factor, several physical and chemical characteristics of soils were used in combination with RI. A comparison of the results showed that the IC based on a weighting factor obtained from the combination of mean weighted aggregate diameter, penetration resistance, and RI, has the highest coefficient of correlation with soil losses (0.92, P

Morphological changes in rivers lead to serious damages, including changes in the width of the waterways, changes in the drainage plan, erosion and sedimentation of the bed and banks, structural failure and loss of valuable land. A two-dimensional numerical model called CCHE2D was used to simulate the effect of the flow pattern on the river bed changes in the reach of the natural floodplain of the Kor River between the Abbas Abad Bridge and the Dorudzan Bridge, the Province of Fars. The topographical maps of the study area, the geometry of the model, and the computational grid with different dimensions were prepared. Based on the measured flow parameters, a two-dimensional hydrodynamic model of the mean depth, performance and results such as the changes in depth, flow velocity, secondary flow and shear stress were extracted. Finally, two data sets of the RMSE and MAPE were compared using the numerical model simulation versus the collected data. The results showed that this model had a good accuracy in predicting the flow parameter values, ​​and the simulated data were similar to those obtained from field measurements. The results of changes in the flow pattern as an effective indicator in predicting the hydraulic behavior and hydrodynamics showed that by correcting the path and removing the bends in the clay meadows of the Kor River by straightening the meanders, the heavy erosion of meander most agricultural land will be prevented. It must be emphasized that straightening the waterway entails its lining with erosion-resisting materials. It can be seen that using the computational fluid dynamics for modeling the stream bed variations brings researchers closer to a more general predictions for governing the processes in riverine plains. Also, the CCHE2D model has a good ability to predict changes in meandering rivers.