Flood risk mapping and modeling is important to prevent urban flood damage. In this study, a flood risk map was produced with limited hydrological and hydraulic data using two state-of-theart machine learning models: Genetic Algorithm Rule-Set Production (GARP) and Quick Unbiased Efficient Statistical Tree (QUEST). The flood conditioning factors used in modeling were: precipitation, slope, curve number, distance to river, distance to channel, depth to groundwater, land use, and elevation. Based on available reports and field surveys for Sari city (Iran), 113 points were identified as flooded areas (with each flooded zone assigned a value of 1). Different conditioning factors, including urban density, quality of buildings, age of buildings, population density, and socioeconomic conditions, were taken into account to analyze flood 2 vulnerability. In addition, the weight of these conditioning factors was determined based on expert knowledge and Fuzzy Analytical Network Process (FANP). An urban flood risk map was then produced using flood hazard and flood vulnerability maps. The area under the receiver-operator characteristic curve (AUC-ROC) and Kappa statistic were applied to evaluate model performance. The results demonstrated that the GARP model (AUC-ROC=93.5%, Kappa=0.86) had higher performance accuracy than the QUEST model (AUC-ROC=89.2%, Kappa=0.79). The results also indicated that distance to channel, land use, and elevation played major roles in flood hazard determination, whereas population density, quality of buildings, and urban density were the most important factors in terms of vulnerability. These findings demonstrate that machine learning models can help in flood risk mapping, especially in areas where detailed hydraulic and hydrological data are not available.

The natural flow regime of rivers has been strongly altered worldwide , resulting in ecosystem degradation and lakes drying up, especially in arid and semi-arid regions. Determining whether this is due mainly to climate change or to water withdrawal for direct human use (e.g. irrigation) is difficult, particularly for saline lake basins where hydrology data are scarce. In this study, we developed an approach for assessing climate and land use change impacts based on river flow records for headwater and lowland reaches of rivers, using the case of Lake Urmia basin, in north-westen Iran. Flow regimes at upstream and downstream stations were studied before and after major dam construction and irrigation projects. Data from 57 stations were used to establish five different time intervals representing 10 different land use development periods (scenarios) for upstream (not impacted) and downstream (impacted) systems. An existing river impact (RI) index was used to assess changes in three main characteristics of flow (magnitude, timing and, intra-annual variablity). The results showed that irrigation was by far the main driving force for river flow regime changes in the lake basin. All stations close to the lake and on adjacent plains showed significantly higher impacts of land use change than headwaters. As headwaters are relatively unaffected by agriculture, the non-significant changes observed in headwater flow regimes indicate a minor effect of climate change on river flows in the region. The benefit of the method developed is clear interpretatation of results based on river flow records, which is useful in communicating land use and climate change information to decision makers and lake restoration planners.

In terms of fuel resource, hydropower possesses a prominent advantage over any other large power plants which burn fossil fuels to generate electricity. Moreover, due to the abundance in resource availability (as a domestic source in small streams and rivers), small hydropower (SHP) plants are showing prominence all over the world. SHP plants have led to improved access to electricity usage in under-developed and developing nations, thereby contributing to sustainable development goals and social empowerment. SHP, as a technology, is regarded as the largest density renewable resource with high adaptability, and low investment costs. The primary objective of the paper is to study and analyze recent developments in SHP technologies with reporting statistical figures in terms of installed capacity and MW potential in several parts of the world. Methodologies adopted by researchers to conduct techno-economic analysis of SHP projects are reviewed. Various costs involved in conducting pre-feasibility studies—such as constructing, maintaining, and sustainably operating SHP projects—are studied. The results of the study indicate cost and regulatory issues are the major factors affecting the growth of the small hydropower sector in many nations. Major impediments to construction, development and deployment of SHP projects, mutually existing among the nations worldwide, are also reported. Technical hindrances include non-availability of the grid and very limited accessibility to SHP sites, emissions due to storage of water, disruptive technologies with limited manpower and non-technical hindrances include discouragement from local bodies and groups, lack of suitable and precise pathways to accomplish SHP goals of a nation, lack of incentives for encouraging private players to invest in SHP projects, complex approval processes, and many more.

Water is the most important resource for sustainable agriculture in arid and semi-arid regions, where agriculture is the mainstay for rural societies. By relating the water usage to renewable water resources, we define three stages from sustainable to unsustainable water resources: (1) sustainable, where water use is matched by renewable water capacity, ensuring sustainable water resources; (2) transitional, where water use occasionally exceeds renewable water capacity; and (3) unsustainable, with lack of water resources for agriculture, society, and the environment. Using available drought indicators (standardized precipitation index (SPI) and streamflow drought index (SDI)) and two new indices for agricultural drought (overall agricultural drought index (OADI) and agricultural drought index (ADI)), we evaluated these stages using the example of Fars province in southern Iran in the period 1977–2016. A hyper-arid climate prevailed for an average of 32% of the province’s spatio-temporal coverage during the study period. The area increased significantly from 30.6% in the first decade (1977–1986) to 44.4% in the last (2006–2015). The spatiotemporal distribution of meteorological drought showed no significant negative trends in annual precipitation during 1977–2016, but the occurrence of hydrological droughts increased significantly in the period 1997–2016. The expansion of irrigated area, with more than 60% of rainfed agriculture replaced by irrigated agriculture (especially between 1997 and 2006), exerted substantial pressure on surface water and groundwater resources. Together, climate change, reduced river flow, and significant declines in groundwater level in major aquifers led to unsustainable use of water resources, a considerable reduction in irrigated area, and unsustainability in agricultural production in the period 2006–2015. Analysis of causes and effects of meteorological, hydrological, and agricultural drought in the area identified three clear stages: before 1997 being sustainable, 1997–2006 being transitional, and after 2006 being unsustainable.

The Zayanderud Basin is an important agricultural area in central Iran. In the Basin, irrigation consumes more than 90 percent of the water used, which threatens both the downstream historical city of Isfahan and the Gavkhuni Wetland reserve—the final recipient of the river water. To analyze impacts of land use changes and the occurrence of metrological and hydrological drought, we used groundwater data from 30 wells, the standardized precipitation index (SPI) and the streamflow drought index (SDI). Changes in the wetland were analyzed using normalized difference water index (NDWI) values and water mass depletion in the Basin was also assessed with gravity recovery and climate experiment (GRACE)-derived data. The results show that in 45 out of studied 50 years, the climate can be considered as normal in respect to mean precipitation amount, but hydrological droughts exist in more than half of the recorded years. The hydrological drought occurrence increased after the 1970s when large irrigation schemes were introduced. In recent decades, the flow rate reached zero in the downstream part of the Zayanderud River. NDWI values confirmed the severe drying of the Gavkhuni Wetland on several occasions, when compared to in situ data. The water mass depletion rate in the Basin is estimated to be 30 (±5) mm annually; groundwater exploitation has reached an average of 365 Mm3 annually, with a constant annual drop of 1 to 2.5 meters in the groundwater level annually. The results demonstrate the connection between groundwater and surface water resources management and highlight that groundwater depletion and the repeated occurrence of the Zayanderud River hydrological drought are directly related to human activities. The results can be used to assess sustainability of water management in the Basin.