Provided is an exponential model-based method for predicting a two-dimensional flow velocity field in a river channel with emergent vegetation. The method comprises the following steps: (1) with a center of an upstream boundary of an emergent vegetation patch as an origin, dividing the river channel into a vegetated region and a bare channel in a direction perpendicular to a streamwise direction namely, an x direction; (2) determining a model for predicting flow velocity distribution of a two-dimensional flow velocity field in the vegetated region and the bare channel and (3) determining the flow velocity U.sub.y=b at the side edge of the vegetation patch and the mean flow velocity U.sub.bare over transverse profiles in a streamwise direction of the bare channel.

Described herein are methods and systems for real-time swiftwater risk category distributed mapping. A mobile computing device generates a request for swiftwater risk information, the request including a location. A server computing device receives the request for swiftwater risk information from the mobile computing device. The server computing device models hydrologic conditions for a plurality of segments of one or more bodies of water at or near the location. The server computing device classifies each segment of the bodies of water according to a level of potential risk of hazards associated with the hydrologic conditions. The server computing device generates a visual representation of the bodies of water that includes a classification indicator for one or more of the plurality of segments for display on the mobile computing device, and transmits the visual representation to the mobile computing device.

Methods, systems, and computer programs are presented for estimating downtime and recovery time after a disaster. One method includes an operation for calculating component fragility functions for components of a facility that are vulnerable to damage after a disaster. Further, the method includes calculating component recovery functions for the components of the facility. The component recovery functions indicate a probability of recovery after a disaster over time. The method further includes operations for calculating a facility fragility function and a facility recovery function based on the component fragility functions and the component recovery functions, and for determining a downtime for the facility for a given intensity associated with the disaster. Further, the method includes an operation for causing presentation of the downtime for the facility on a user interface (UI).

A system, apparatus, computer program product, and method use a convolutional neural network to auto-determine a first floor height (FFH) and a FFH elevation (FFE) of a building. The FFH, and FFE of the building are determined with respect to the terrain or surface of the parcel of land on which the building is located. In turn, by knowing the FFH and/or FFE of the building on the parcel, it is possible to use that information while performing a flood risk assessment to a property without requiring a personal inspection of the parcel by a human.

A system, methodology, and programming logic for active stormwater controls to optimize sizing and design of Hydromodification Management (HM) structural Best Management Practices (BMPs) to achieve optimal flow duration control. Control logic enables the controlled release of stormwater from a BMP in a manner most akin to pre-development flow duration curves. Inputs to this logic include: flow duration curves based on continuous hydrologic simulation for pre- and post-development conditions; real-time measurement of water level within the BMP; and real-time measurement of discharge entering the BMP. This control logic can interact with control logic for other stormwater management objectives, such as harvest and reuse, infiltration, and combined sewer overflow prevention, and respective inputs, such as real-time weather forecast data, precipitation gage data, downstream flow gauge data, and water quality data, to meet those design objectives as well. New HM BMPs can be optimized to be smaller and, thus, more feasible to implement. Existing stormwater facilities designed for flood control or other management objectives can be retrofitted to provide hydromodification control as well. When utilized with real-time flow and water level monitoring equipment and data, the flow release logic can be adaptively adjusted without physical retrofit of the BMP's outlet.

A method includes displaying a user interface on a screen of a computing device of a homeowner, and receiving an input of an address for a property of the homeowner. The method also includes receiving global positioning system (GPS) data from the computing device, and verifying the address for the property based on the GPS data. The method also includes calculating probabilities for the property to have a flood event at hypothetical high water heights based on GPS located and mapped floodplain data relating to the property, flood zone map data relating to the property, and historical flood data for a region in which the property is located. The method also includes calculating fixed-value payout amounts based on an estimated elevation of the property, the probabilities for the property to have the flood event at the hypothetical high water heights, and estimated flood water depths in the property.

The method for preventing and controlling glacial lake outbreak flood and related debris flows by the present invention is mainly controlling the scale of the floods by separating water and rocks and dispersing its energy step by step. The cascading amplification effects of floods can be reduced by controlling the initiation of source material with energy dissipation by using ground sills, groups of piles, and placed large stones and prefabricated artificial structures. The diversion dam built in the downstream area discharge floods in different layers, which can quickly guide water to the main river. The preconstructed engineering system can be used in a timely manner to prevent and control floods and debris flows induced by a sudden outburst of glacial lakes in areas with important facilities and inhabitants enduring the risk of natural hazards. Prevention and control systems can separate floods and debris flows and dissipate their energy. The groups of ground sills and check dams gradually dissipate the energy of floods, prevent high-energy boulders, and control the initiation of source materials in the channel and bank. Moreover, the systems can also separate the water and rocks in dilute debris flows or debris flows with high bulk densities but low viscosities. The diversion dams also enhance the separation function and keep the flood and debris flow discharge in the lower and upper channel to the main river.

A prediction device 100 of the present invention includes a detection means 121 for, on the basis of a river image that is an image obtained by capturing a river and associated with capturing position information representing a position where the river is captured, detecting river condition information representing a condition of the river at the position where the river image is captured; and a prediction means 122 for, on the basis of the capturing position information, the river condition information, and topography information representing the topography of the river, predicting a river condition representing a condition of the river at a given point of the river. The given point is different from the position represented by the capturing position information.

An information providing apparatus includes an acquisition section that acquires position information from a terminal device, a specifying section that specifies a target publication from plural publications on which maps have been posted, by performing processing with the position information, and a providing section that provides the terminal device with information indicating a correspondence relationship between a map posted on the target publication and a position indicated by the position information.

The present invention provides a method for calibrating monthly precipitation forecast by using a Gamma-Gaussian distribution, including the following steps: acquiring forecast data of monthly average precipitation in a watershed area and corresponding observed values of the average precipitation in the watershed area as input data; performing fitting on the input data by means of a Gamma distribution function; calculating a cumulative distribution function value of each input data in a corresponding Gamma distribution; transforming the cumulative distribution function values into variables obeying a standard normal distribution; constructing a joint normal distribution according to the variables obeying the standard normal distribution to characterize a correlation between the forecast data and the observed values in the input data; and randomly sampling the observed values according to the correlation, and inversely transforming acquired samples to obtain a calibrated forecast result.