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Arid area is very sensitive to global warming and are extremely vulnerable to climate change. Moreover, the water resources system in the arid area is fragile and will undergo tremendous changes with climate change. Therefore, the interaction of climate and hydrology in arid area has an important impact on the formation of regional microclimate and hydrological changes. Daihai Lake is a typical closed inland lake in arid area of China, and a key area for ecological protection in North China. In this paper, WRF-Hydro model is used to simulate the climate hydrological coupling situation of Daihai Basin from 1980 to 2020, and the coupling results are verified and calibrated by meteorological statistics, runoff calculation and remote sensing analysis. Based on the synopsis of climate and hydrology in the past 40 years, the causes and future trends of the hydrological elements in Daihai Basin are analyzed. Through the analysis, it is found that the interannual variation of precipitation in Daihai Basin is sharp, with 401.75 mm as the average from 1980 to 1994; and drastic fluctuations from 1995 to 2011, with a difference of nearly 400 mm between the interannual maximum and minimum; From 2012 to 2020, the fluctuation is small. Although the interannual variation of evaporation fluctuated, it showed an upward trend with a slope of 8.855 mm/year. The annual average temperature showed an obvious upward trend with a slope of 0.040 °C/year. From 1980 to 2020, the inflow of Daihai Lake shows a downward trend; Since 2013, the runoff into the lake has tended to be flat. Climate change and human activities are the decisive factors leading to the change of water quantity in Daihai, among which human activities play a greater role. Cultivated land irrigation and industrial water use are highly correlated with the lake discharge, and these two factors have a great influence on the lake discharge. If the current agricultural and industrial water consumption does not increase, Daihai still has a lifespan of nearly 120 years. If human activities do not change and any protective measures are not taken in time, under the background of global climate change, the flow of the Daihai Lake into the lake will be reduced to zero in 2025, and the Daihai Lake will completely dry up in 2031–2033. The study of climate hydrological coupling of long time series in Daihai Basin can not only make up for the lack of runoff data, but also provide the basis for water resources management, disaster prevention and mitigation. [ABSTRACT FROM AUTHOR]

Densely populated coastal urban areas are often exposed to multiple hazards, in particular floods and storms. Flood defenses and other engineering measures contribute to the mitigation of flood hazards, but a holistic approach to flood risk management should consider other interventions from the human side, including warning information, adaptive behavior, people/property evacuation, and the multilateral relief in local communities. There are few simulation approaches to consider these factors, and these typically focus on collective human actions. This paper presents an agent-based model that simulates flood response preferences and actions taken within individual households to reduce flood losses. The model implements a human response framework in which agents assess different flood scenarios according to warning information and decide whether and how much they invest in response measures to reduce potential inundation damages. A case study has been carried out in the Ng Tung River basin, an urbanized watershed in northern Hong Kong. Adopting a digital elevation model (DEM) as the modeling environment and a building map of household locations in the case area, the model considers the characteristics of households and the flood response behavior of their occupants. We found that property value, warning information, and storm conditions all influence household losses, with downstream and high density areas being particularly vulnerable. Results further indicate (i) that a flood warning system, which provides timely, accurate, and broad coverage rainstorm warning, can reduce flood losses by 30-40%; and (ii) to reduce losses, it is more effective and cheaper to invest early in response measures than late actions. This dynamic agent-based modeling approach is an innovative attempt to quantify and model the role of human responses in flood loss assessments. The model is demonstrated being useful for analyzing household scale flood losses and responses and it has the potential to contribute to flood emergency planning resource allocation in pluvial flood incidents. [ABSTRACT FROM AUTHOR]

As the potential for and scope of some types of disasters increases, so too does the need to build greater disaster resilience across the globe. Communities ideally begin building resilience prior to experiencing a disaster in order to reduce negative impacts and ease recovery processes; however, numerous environmental and sociopolitical factors can impede such efforts until a disaster occurs. While the disaster recovery period offers opportunities for communities to build resilience as they replace infrastructure and restore services, a host of new issues arise during this time that can further complicate or delay resilience building. In this study, we highlight the opportunities and challenges inherent at the intersection of disaster recovery and resilience building, which we term the "recovery–resilience nexus." To study this nexus, we analyze a first-of-its-kind disaster recovery program in Colorado, United States, that promotes resilience-building activities in disaster-affected communities by supporting the efforts of place-based watershed coalitions. Although the program faced numerous and interrelated technical, political, and fiscal hurdles, we argue that it provides an opportunity for drawing important lessons about how communities can navigate the recovery–resilience nexus via cross-boundary collaboration and creatively leveraging traditional disaster recovery funding sources to achieve resilience goals. [ABSTRACT FROM AUTHOR]

NALCO – the largest exporter of aluminium in India has a power plant of 720 MW capacity in Nandira watershed in Angul district of Orissa. The power plant utilises local coal to generate thermal power and disposes of large amount of ash which accumulates in slurry form at nearby two ash ponds. These ash ponds were breached on 31 December 2000, causing ash accumulation for entire regime of the Nandira river. An attempt has been made towards preparation of recovery and rehabilitation plan for NALCO using temporal Remote Sensing data and GIS. Indian remote sensing satellite data for pre-breach condition 12 December 2000, during breach event 31 December 2000 and post-breach condition 4 and 6 January 2001 has been digitally analysed for Nandira watershed. The satellite data of coarse spatial resolution provides the absence and presence of fresh sediment deposition along Nandira watershed and Brahmani river pertaining to pre-breach and post-breach conditions respectively on regional scales. The temporal comparison of fine resolution has clearly highlighted the aerial extent of damage caused by the disaster for entire watershed on local scales. The GIS has helped in demarcation of freshly accumulated ash at interval of 500 m along the river length as well as in delineation of maximum ash accumulation across the river width. The study has clearly demonstrated the use of temporal Remote Sensing data in conjunction with GIS for disaster management in terms of recovery and rehabilitation plan preparation of the Nandira watershed. [ABSTRACT FROM AUTHOR]