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Monitoring changes in natural ecosystems is considered essential to natural resource management. Despite the global importance of the lakes' quality monitoring, there is currently a research gap in the simultaneous predictive modeling of lakes' land-use changes and ecosystem measurements. In the present study for projecting the water bodies of lakes and their surrounding ecosystems, the land-use changes and the landscape analysis of different periods, i.e., 1987, 2002, 2018, and 2030, are studied using remote sensing data and various metrics. The trend of land-use and landscape changes is projected for 2030. The results indicate significant degradation of rangelands and forests due to the conversion to agriculture and construction and the declining trend of lakes' water body and their transformation to salt lake and salt lands. The increase of agricultural lands and the overuse of groundwater wells upstream of the lakes could be one of the reasons for this decline. Decreasing the lakes' water body and subsequently increasing salt lands are considered a severe threat to human health and the ecosystem services of the lakes. Besides, the dust generated by salt lands could also decrease crop yield in the study area.

Floods are among the most frequently occurring natural disasters and the costliest in terms of human life and ecosystem disturbance. Identifying areas susceptible to flooding is important for devel...

With the growth of cities, urban flooding has increasingly become an issue for regional and national governments. The destructive effects of floods are magnified in cities. Accurate models of urban flood susceptibility are required to mitigate this hazard mitigation and build resilience in cities. In this paper, we evaluate flood riskin Jiroft city, Iran, using a combination of machine learning and decision-making methods. Flood hazard maps were created using three state-of-the-art machine learning methods (support vector machine, random forest, and boosted regression tree). The metadata supporting our analysis comprises 218 flood inundation points and a variety of derived factors: slope aspect, elevation, slope angle, rainfall, distance to streets, distance to rivers, land use/land cover, distance to urban drainages, urban drainage density, and curve number. We then employed the TOPSIS decision-making tool for urban flood vulnerability analysis, which is based on socio-economic factors such as building density, population density, building history, and socio-economic conditions. Finally, we derived an urban flood risk map for Jiroft based on flood hazard and vulnerability maps. Of the three models tested, the random forest model yielded the most accurate map. The results indicate that urban drainage density and distance to urban drainages are the most important factors in urban flood hazard modeling. As might be expected, areas with a high or very high population density are most vulnerable to flooding. These results show that flood risk mapping provide insights for priority planning in flood risk management, especially in areas with limited hydrological data.

© 2019 China University of Geosciences (Beijing) and Peking University The sub-watershed prioritization is the ranking of different areas of a river basin according to their need to proper planning and management of soil and water resources. Decision makers should optimally allocate the investments to critical sub-watersheds in an economically effective and technically efficient manner. Hence, this study aimed at developing a user-friendly geographic information system (GIS) tool, Sub-Watershed Prioritization Tool (SWPT), using the Python programming language to decrease any possible uncertainty. It used geospatial–statistical techniques for analyzing morphometric and topo-hydrological factors and automatically identifying critical and priority sub-watersheds. In order to assess the capability and reliability of the SWPT tool, it was successfully applied in a watershed in the Golestan Province, Northern Iran. Historical records of flood and landslide events indicated that the SWPT correctly recognized critical sub-watersheds. It provided a cost-effective approach for prioritization of sub-watersheds. Therefore, the SWPT is practically applicable and replicable to other regions where gauge data is not available for each sub-watershed.

In recent decades, population growth and development of agriculture, indiscriminate increase and exacerbate the decline in the quality of groundwater resources in most parts of the country. Thus, given the importance of this research to study the spatial and temporal changes in parameters of calcium, magnesium, pH, chloride, sodium sulfate and water in Jiroft discussed. The data from 40 wells in the region of Kerman province in 2002 - 2012 water harvesting and qualitative analysis had been done on it was used. In this regard, after normalizing the data to evaluate the accuracy of different geostatistical methods including the kriging and inverse distance weighted, and then map the spatial zoning in the software quality parameters ArcGIS9.3 was prepared using the best method of interpolation. The results showed that the amount of calcium, pH and chlorine in the water and magnesium, and sodium sulfate also has declined. But the quality of groundwater resources Jiroft in general in 2012 compared to 2002, decreased and the process of change if they do go to the South and West Water quality is reduced. Keyword: Modeling, Jiroft plains, groundwater, spatial changes, interpolation.