Supplemental Material: Landslide hypothesis for the origin of Haleakala volcano’s crater and great valleys, Hawaii

<div>Figure 1. Haleakala volcano location, geology, and rainfall map. Figure 1 is interactive. Use the buttons directly below the map to view the different layers. Layers may be viewed separately or in combination using the capabilities of the Acrobat (PDF) layering function (click “Layers” icon along vertical bar on left side of window for display of available layers; turn layers on or off by clicking the box to the left of the layer name).<br></div>

Supplemental Material: Landslide hypothesis for the origin of Haleakala volcano’s crater and great valleys, Hawaii

<div>Figure 1. Haleakala volcano location, geology, and rainfall map. Figure 1 is interactive. Use the buttons directly below the map to view the different layers. Layers may be viewed separately or in combination using the capabilities of the Acrobat (PDF) layering function (click “Layers” icon along vertical bar on left side of window for display of available layers; turn layers on or off by clicking the box to the left of the layer name).<br></div>

Supplemental Material: Landslide hypothesis for the origin of Haleakala volcano’s crater and great valleys, Hawaii

<div>Figure 1. Haleakala volcano location, geology, and rainfall map. Figure 1 is interactive. Use the buttons directly below the map to view the different layers. Layers may be viewed separately or in combination using the capabilities of the Acrobat (PDF) layering function (click “Layers” icon along vertical bar on left side of window for display of available layers; turn layers on or off by clicking the box to the left of the layer name).<br></div>

Spatial–temporal characterization of rainfall in Pakistan during the past half-century (1961–2020)

Spatial–temporal rainfall assessments are integral to climate/hydrological modeling, agricultural studies, and water resource planning and management. Herein, we evaluate spatial–temporal rainfall trends and patterns in Pakistan for 1961–2020 using nationwide data from 82 rainfall stations. To assess optimal spatial distribution and rainfall characterization, twenty-seven interpolation techniques from geo-statistical and deterministic categories were systematically compared, revealing that the empirical Bayesian kriging regression prediction (EBKRP) technique was best. Hence, EBKRP was used to produce and utilize the first normal annual rainfall map of Pakistan for evaluating spatial rainfall patterns. While the largest under-prediction was estimated for Hunza (− 51%), the highest and lowest rainfalls were estimated for Malam Jaba in Khyber Pakhtunkhwa province (~ 1700 mm), and Nok-kundi in Balochistan province (~ 50 mm), respectively. A gradual south-to-north increase in rainfall was spatially evident with an areal average of 455 mm, while long-term temporal rainfall evaluation showed a statistically significant (p = 0.05) downward trend for Sindh province. Additionally, downward inter-decadal regime shifts were detected for the Punjab and Sindh provinces (90% confidence). These results are expected to help inform environmental planning in Pakistan; moreover, the rainfall data produced using the optimal method has further implications in several aforementioned fields.

Recent Progresses of the Global Precipitation Measurement (GPM) Mission in Japan

&lt;p&gt;The Global Precipitation Measurement (GPM) mission is an international collaboration to achieve highly accurate and highly frequent global precipitation observations. The GPM mission consists of the GPM Core Observatory jointly developed by U.S. and Japan and Constellation Satellites that carry microwave radiometers and provided by the GPM partner agencies. The GPM Core Observatory, launched on February 2014, carries the Dual-frequency Precipitation Radar (DPR) by the Japan Aerospace Exploration Agency (JAXA) and the National Institute of Information and Communications Technology (NICT).&lt;/p&gt;&lt;p&gt;JAXA and NASA started to release the GPM/DPR Experimental product (Version 06X) in June 2020. This Version 06X is the first product to respond to the KaPR scan pattern changes implemented on May 21, 2018. This change in scan pattern allows for a more accurate precipitation estimation method based on two types of precipitation information, Ku-band Precipitation radar (KuPR) and KaPR, to be applied to the entire observation swath. A new version 07 of the GPM/DPR products will appear in 2021.&lt;/p&gt;&lt;p&gt;JAXA also develops the Global Satellite Mapping of Precipitation (GSMaP), to distribute hourly and 0.1-degree horizontal resolution rainfall map through the &amp;#8220;JAXA Global Rainfall Watch&amp;#8221; website (https://sharaku.eorc.jaxa.jp/GSMaP/index.htm). The GSMaP near-real-time version (GSMaP_NRT) product provides global rainfall map in 4-hour after observation, and an improved version of GSMaP near-real-time gauge-adjusted (GSMaP_Gauge_NRT) product has been published since Dec. 2018. Now the JAXA is developing the GPM-GSMaP V05 (algorithm version 8) which will be released in 2021.&lt;/p&gt;&lt;p&gt;In the GPM-GSMaP V05, the passive microwave (PMW) algorithm will be improved in terms of retrievals extended to the pole-to-pole, updates of databases for the PMW retrievals, and heavy Orographic Rainfall Retrievals. Normalization module for PMW retrievals (Yamamoto and Kubota 2020) will be implemented. A histogram matching method by Hirose et al. (2020) will be implemented in the PMW-IR Combined algorithm. In the Gauge-adjustment algorithm based upon Mega et al. (2019), artificial patterns appeared in V04 will be mitigated in V05.&lt;/p&gt;

Critical Continuous Rainfall Map for Forecasting Shallow Landslide Initiations in Busan, Korea

In recent years, precipitation patterns in Korea have shifted to be characterized as short and intense rainfalls. In consideration of shallow landslide initiations primarily governed by heavy rainfalls at short-time scales that diminish drainage effects, the concept of critical continuous rainfall is proposed as a single-rainfall-variable threshold for shallow landslide forecasting. To generate a critical continuous rainfall map for hillslope areas in a city of Korea (Busan), this study designed and applied a systematic modeling process. As a preparatory stage, input datasets of geo-hydraulic properties and geotechnical properties were assembled using estimation techniques based on experiment data of field samples. The inherent and fixed critical continuous rainfall values for hillslope areas in Busan were derived through one-dimensional infiltration analysis coupled with infinite slope stability calculations. As a result of a detailed analysis of historical rainfall records in a case study area over a period of 11 years, three false forecasting cases were recorded, whereas all landslide-triggering rainfall events were correctly captured with no missed forecasting cases. The results of the case study indicate that the proposed critical continuous rainfall may be useful as an effective and straightforward indicator for forecasting the initiation of shallow landslides.

Groundwater potential mapping in Ikorodu, Lagos State, Nigeria, using multi-criteria analysis and hydrogeophysics

The assessment of the potential groundwater recharge area is extremely important for water quality protection and proper management of ground water systems. The objective of this study was to evaluate systematic groundwater studies using the integration of remote sensing and geographic information systems (GIS) and hydrogeophysics as a tool to identify groundwater potential areas in Ikorodu, Lagos. In this study, various thematic maps (layers) derived from satellite image classification such as: Land use/ Land cover map, soil map, rainfall map, geological map, slope map derived from SRTM Digital Elevation Model, lineament density map obtained as a result if lineament analysis of the principal component of the image, were all integrated using the weighted overlay tool in the spatial analyst toolbox of ArcGIS 10.5. Ranks and weights of classes and sub-classes of the thematic layers were assigned based on their influences on groundwater occurrence. The vertical electrical sounding data obtained from the study area were used to validate the results of the groundwater potential map and also determine the areas with brackish water, saline water and freshwater and the most probable drillable depth for exploration. The results show that the groundwater potential zones of the study area could be classified into five zones with the following percentage for spatial distribution: “very high” potential zone (0.6%), “high” (4.2%), “moderate” (15.8%), “low” 71.7% and very low potential zone (7.7%). The South-Western region of Ikorodu, close to Oriwu has the highest concentration of groundwater. Imota is characterized with Moderate and Low ground water potentials. From the query results, the aquiferous layers were identified, their yield and potentials determined and the depths to which boreholes can be sunk for the drilling of fresh water were found to be between 20m and 120m respectively. Keywords: Groundwater, Remote sensing, GIS, Hydrogeophysics.

Recent status of the Dual-frequency Precipitation Radar (DPR) and the Global Satellite Mapping of Precipitation (GSMaP) in the Global Precipitation Measurement (GPM) mission

&lt;p&gt;The Global Precipitation Measurement (GPM) mission is an international collaboration to achieve highly accurate and highly frequent global precipitation observations. The GPM mission consists of the GPM Core Observatory jointly developed by U.S. and Japan and Constellation Satellites that carry microwave radiometers and provided by the GPM partner agencies. The GPM Core Observatory, launched on February 2014, carries the Dual-frequency Precipitation Radar (DPR) by the Japan Aerospace Exploration Agency (JAXA) and the National Institute of Information and Communications Technology (NICT).&lt;/p&gt;&lt;p&gt;JAXA is continuing DPR data monitoring to confirm that DPR function and performance are kept on orbit. A scan pattern of the DPR was changed in May 2018. The next product applying the new scan pattern will be released as an experimental product (V06X) in 2020. The DPR follow-on mission has been actively discussed in Japan.&lt;/p&gt;&lt;p&gt;JAXA also develops the Global Satellite Mapping of Precipitation (GSMaP), as national product to distribute hourly and 0.1-degree horizontal resolution rainfall map. GSMaP has been used for various research fields and JAXA keeps it developed and improved, in cooperation with domestic/international partner agencies.&lt;/p&gt;&lt;p&gt;The GSMaP near-real-time version (GSMaP_NRT) product provides global rainfall map in 4-hour after observation, and recently GSMaP near-real-time gauge-adjusted version (GSMaP_Gauge_NRT) product has been published. The higher priority to data latency time than accuracy leads to wider utilization by various users for various purposes, such as rainfall monitoring, flood alert and warning, drought monitoring, crop yield forecast, and agricultural insurance.&lt;/p&gt;&lt;p&gt;Improved GSMaP_Gauge_NRT product (v6) was open to the public in Dec. 2018. Correction coefficients are calculated using past 30 days based upon Mega et al. (2019)&amp;#8217;s method. We completed reprocessing of past 19yr data record (since Mar. 2000). Validations with reference to the JMA radar around Japan show smaller RMSEs in this new product than the current NRT (no gauge-correction).&lt;/p&gt;&lt;p&gt;JAXA started to provide the GSMaP real-time product called GSMaP_NOW by using the geostationary satellite Himawari-8 operated by the Japan Meteorological Agency (JMA) since November 2015. Recently, the domain of GSMaP_NOW was extended to the global region in June 2019. Furthermore, we developed the gauge-adjusted real-time version, GSMaP_Gauge_NOW, which was also released in June 2019. In the method, estimates from the GSMaP_NOW are adjusted using an optimization model (Mega et al. 2019) with parameters calculated from the GSMaP_Gauge (gauge-adjusted standard version) during the past 30 days.&lt;/p&gt;&lt;p&gt;GSMaP products can be seen via website and easy to monitor the global rainfall with good latency. GSMaP since March 2000 up to 4-hour after observation is available from the &amp;#8220;JAXA Global Rainfall Watch&amp;#8221; website (https://sharaku.eorc.jaxa.jp/GSMaP/index.htm); while GSMaP_NOW product is from the &quot;JAXA Realtime Rainfall Watch&quot; web site (https://sharaku.eorc.jaxa.jp/GSMaP_NOW/index.htm).&lt;/p&gt;

Pemetaan Curah Hujan Dalam Upaya Mengurangi Resiko Bencana Hidrometeorologi Dengan Sistem Informasi Geografis (SIG) Untuk Wilayah Kalimantan Utara

North Kalimantan is one of the regions in Indonesia which is prone to hydrometeorological disasters. The purpose of this study was to determine the rainfall analysis of the North Kalimantan Region as a basis in finding rainfall levels in areas that do not have climatological stations, knowing the rainfall maps of the North Kalimantan Region and knowing the conditions of high rainfall causing flood prone in the North Kalimantan region. Rainfall data collection locations are climatology stations Tanjung Harapan, Juwata, Tuvai Semaring, Kalimarau and R.A. Bessing. Rainfall data is taken from OGIMET for 10 years. The result of rainfall analysis is the average monthly rainfall, which is from January to December. The method used to determine the monthly rainfall value in the North Kalimantan region is the Spatial Analyst Interpolation -Kriging method. The results are in the form of monthly rainfall maps, from January to December. Monthly rainfall map is a source of information on the value of rainfall in the region in North Kalimantan. Maximum rainfall is found in the areas of Tanjung Selor and Tarakan, namely January 313,368 mm, May 366,238 mm, July 358,868 mm and December 324,513 mm. Map of monthly rainfall in January, May, July and December is a parameter to see the condition of high rainfall causing hydrometeorological disasters. Through this research it is expected to anticipate the risk of disasters caused by the weather.

Geo-Mapping of Areas Vulnerable to Ala-River Basin Flood Disaster Risk in Akure, Ondo State, Nigeria

Flood is identified as one of the major disasters in the world; it destroys both human and properties across the world, where lives are lost, properties, public infrastructure, farmlands and agricultural produce with farm crops carted away as a result of flood disaster. Studies revealed that the flood in itself is not the danger, but the level of human vulnerability to flooding disaster risk, which enhances its destructive capabilities. However, based on the challenges poses by flood disaster risk, this research identifies Ala river in Akure as a potential cause of flood, considering its location and other human activities around the river. Therefore, the research used Ala-river a case study to identify and mapped out areas susceptible to flood disaster risk. The research made use of both literature review and conducted goe-data gathering with the application GIS-computer database to retrieve georeferencing relevant data from the fieldwork in the study area of Ala-river basin to mapped out locations vulnerable to achieve the research aim. The research adopted a Geo-mapping of the vulnerable area to Ala-River basin using arc-GIS tool in combination with other software such as IKONAS and OLI (Operation Land Imager) for the production of the study area imagery, ER-ITERIM was used for the collection of rainfall data and FAO was applied for digital soil mapping. These applications produced; the land use/land cover map, digital elevation map, buffer map using 30 meters setback, annual rainfall map, soil types map, vulnerability map and soil textural table for the study area. Analysis of the produced and generated maps shows 316 buildings vulnerability to flood disaster risk; the soil texture and types, and alternative use to which the soil types can be useful. The research recommends that demolition of the identified 316 buildings prone to flood disaster and compliance of building construction to 30 meters setback by developers. Others are the conversion of the future land setback for urban agricultural purposes and preservation of water retention areas for agricultural activities during the dry season among others. The study concludes that relevant government agencies in the State and in particular in Akure South Local Government should ensure prompt compliance and implementation of the recommendations to avoid potential flood disaster risks.