Search

Background and Objectives: The complex knowledge of local communities on the full cycle of disaster risk management has been proven valuable in various researches. However, the scientific literature still lacks studies that examine how to use Local Knowledge (LK) and the local people's capabilities for crowdsourcing in Flash Flood Early Warning Systems (FFEWS) studies. Hence the main target of this research is the investigation of the capacity of crowdsourcing for FFEWS and the identification of Flash Flood Hotspots (FFHs) by LK across a flood-prone area in northeast of Iran. Materials and Methods: In this study, a questionnaire with three different themes was designed. The first theme was related to the individual characteristics as independent variables, and the second theme addressed the residents' LK in determining the FFHs, the type and the predominant time of the flood occurrence in the region, by asking open-ended questions with short answers. The last theme addressed the assessment of people's capacity in Flash Flood Crowdsourcing (FFC), through asking questions with a Likert scale of 0-5. The face-to-face questionnaire administration mode was used for public surveys through conducting oral interviews and live discussions. Results: The results showed that there was no significant correlation between the individuals' characteristics and their willingness and motivation to participate in FFC. Comparing residents' LK with the 31- year flood report and literature review showed that the residents' LK about the flood occurrence location, time and type on a local scale was very promising. The research results indicated that the respondents showed the highest level of willingness to participate in the release of flood warning messages with an average score of 4.23 and the most important motivating factor for their willingness to participate was introducing saving relatives, fellow villagers, and human being from flood hazards with an average score of 4.84. Conclusion: In the most of the previous studies that have focused on the development of FFEWS, very little attention has been paid to understanding the needs of citizens and promoting their participation. There is a research gap regarding the method of citizen's participation and their potential support for FFEWS. Hence in this research, an attempt was made to take a small step towards filling this gap by investigating LK, motivation and willingness of local residents to participate in various aspects and steps of FFEWS. Our findings indicate that involving local people in FFEWS has various unknown aspects that should be explored through more extensive and detailed studies. [ABSTRACT FROM AUTHOR]

Analyzing land use/land cover change is a fundamental tool for evaluating the environmental consequences of human activities. This research was conducted to detect and predict likely land use changes in the Gorganrud River basin, Iran, and to estimate past and future population growth as a driving force in land use change and degradation. First, land use maps for 1999, 2009, and 2017 were prepared. Then, the likely land use changes for 2030 and 2040 were predicted using the Land Change Modeler (LCM) in TERRSET software. Results indicate that the percentage of changes in agricultural and residential areas, bare lands, and semi‐dense forests from 1999 to 2017 were +4.2, +0.62, +1.76, and +3.15, respectively, while the percentage of changes in rangelands, dense forests, and water bodies were −8.7, −0.37, and −0.63. Analysis of changes from 2017 to 2040 indicates that the percentage of changes in croplands, dense forests, and bare lands may reach −4.42, −2.35, and −2.74, respectively. Conversely, the area of rangelands, semi‐dense forests, water bodies, and residential areas would likely increase by +7.78%, +1.02%, +0.04%, and + 0.7%, respectively. The population density in 2011 and 2016 was 94 and 97 persons/km2, respectively, whereas the 5‐year population growth rate was 3.5%. Better conservation practices to prevent deforestation and inappropriate growth of residential areas, in line with forest replantation to prevent the conversion of semi‐dense forests into rangelands, are some of the management strategies required in the study area. Population control and redistribution are other prescribed actions based on the research findings. [ABSTRACT FROM AUTHOR]

The KINEROS2 model was utilized for runoff simulation in the Dehgin catchment situated in the Hormozgan province of Iran. A parameter allocation procedure was used in lieu of parameter optimization. After parameter allocation, the model was able to adequately simulate hydrographs associated with high‐magnitude peak discharge events with the efficiency values between 0.011–0.83 for Nash–Sutcliffe and 0.36–0.98 for Kling–Gupta, but the model did not accurately simulate hydrographs corresponding to low‐magnitude peak discharge events. Although calibration after parameter allocation improved model performance with respect to the simulation of low‐magnitude discharge events, numerical values of the hydraulic conductivity and net capillary pressure as the most sensitive model parameters did not agree with parameters known to be reasonable in the region. So that the value of hydraulic conductivity was decreased from 61 to 55 mm/h in channels and from 3.7 to 1.7 mm/h in planes. The new values are physically reasonable but are not approximately the same as physical values associated with the regional and environmental context of the Dehgin catchment. In this case, the values of the evaluation criteria were obtained between −2.5 and 0.78 for Nash–Sutcliffe and 0.17 and 0.98 for Kling–Gupta. The results of using the HydroPSO package in R to automated calibration of the model, with the value of Nash–Sutcliffe between −0.63 and 0.43, indicated that autocalibration without intelligent and deliberate selection of parameters cannot accurately represent hydrological processes, and therefore should be avoided. Also, the results show that an understanding of the catchment environmental conditions and appropriate allocation of parameters is initially more effective as a first step of the modeling process and thereby contributes to a first‐order characterization of environmental conditions in the catchment. Recommendations for Resource Managers: A better understanding of the catchment and model behavior helps the resource managers to have a better simulation of the hydrologic system and to achieve a better water resources management of the study area.Although parameter calibration is often unavoidable while working with some models, it should be minimized, and only conducted after parameter allocation. Some minimal calibration or adjustments after parameter allocation may lead to a better simulation of the hydrologic system, which will be beneficial for management purposes. [ABSTRACT FROM AUTHOR]

Hydrologic models are simplified representations of natural hydrologic systems. Since these models rely on assumptions and simplifications to capture some aspects of hydrological processes, calibration of parameters is unavoidable. However, utilizing the philosophy of a recent modelling framework proposed by Bahremand (2016), we show how calibration of most model parameters can be avoided by allocating or presetting these parameters utilizing knowledge gained from sensitivity analyses, field observations and a priori specifications as a part of a parameter allocation procedure. This paper details the simulation of daily river flow of the Shemshak‐Roudak watershed performed using the Python version of the WetSpa model. The WetSpa‐Python model is a distributed model of hydrological processes applied at the watershed scale. The model was applied to the Shemshak‐Roudak watershed of Iran with parameter allocation. Model calibration involved only two parameters. Straightforward methods were proposed for allocating model parameters, including three baseflow‐related parameters and the determination of maximum active groundwater storage using a mass curve technique. Also, the Budyko curve was used to constrain a correction factor for potential evapotranspiration. The WetSpa‐Python model was extended to include the influence of snowmelt. A failure to include snow in the hydrological processes of the WetSpa‐Python model creates a significant discrepancy between the observed and simulated hydrographs during the spring. The results of daily simulations for 12 years (2002–2014) are in good agreement with observations of discharge (Kling‐Gupta Efficiency = 0.84). These results demonstrate that it is feasible to simulate hydrographs with limited calibration given a knowledge of hydrological processes and an understanding of relationships between catchment characteristics and model parameters. [ABSTRACT FROM AUTHOR]

The main objective of this study is to assess the relative contribution of the state-of-the-art topo-hydrological factor, known as height above the nearest drainage (HAND), to landslide susceptibility modellling using three novel statistical models: weights-of-evidence (WofE), index of entropy and certainty factor. In total, 12 landslide conditioning factors that affect the landslide incidence were used as input to the models in the Ziarat Watershed, Golestan Province, Iran. Landslide inventory was randomly divided into a ratio of 70:30 for training and validating the results of the models. The optimum combination of conditioning factors was identified using the principal components analysis (PCA) method. The results demonstrated that HAND is the defining factor among hydrological and topographical factors in the study area. Additionally, the WofE model had the highest prediction capability (AUPRC = 74.31%). Therefore, HAND was found to be a promising factor for landslide susceptibility mapping. [ABSTRACT FROM AUTHOR]