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Supporting climate adaptation for rural Mekong River Basin communities in Thailand

Climate change impacts on large river basins, such as the Mekong River Basin (MRB), are complex due to shared governance and interconnected socioeconomic areas, making them highly vulnerable to change. The MRB, spanning six countries including Thailand, is crucial for the food and economic security of > 60 million people. However, in 2021, Thailand was ranked as the 9th highest risk country affected by climate change. To integrate climate adaptation in Thailand's MRB, we examined the effects of climate change on rapidly developing farmer and fisher communities in northeastern Thailand and explored feasible adaptation options. Using an interdisciplinary approach that included literature review, participatory action methods, and the resist-accept-direct (RAD) framework, we found that climate change is projected to increase temperatures, precipitation, extreme events, erosion, and water clarity, while decreasing heavy sediment transport. These changes negatively impact agriculture, fisheries, human health, and tourism. We identified several adaptation strategies across environmental, ecological, and human health categories to accommodate local needs, such as preventing habitat degradation (e.g., from dams and deforestation), providing fish refuge and passage, and supporting technical capacity. Community-driven adaptation planning and implementation are essential for supporting global sustainable development in a changing climate.

Mitigation and Adaptation Strategies for Global Ch

Mapping cropland extent of Southeast and Northeast Asia using multi-year time-series Landsat 30-m data using Random Forest classifier on Google Earth Engine

Cropland extent maps are useful components for assessing food security. Ideally, such products are a useful addition to countrywide agricultural statistics since they are not politically biased and can be used to calculate cropland area for any spatial unit from an individual farm to various administrative unites (e.g., state, county, district) within and across nations, which in turn can be used to estimate agricultural productivity as well as degree of disturbance on food security from natural disasters and political conflict. However, existing cropland extent maps over large areas (e.g., Country, region, continent, world) are derived from coarse resolution imagery (250 m to 1 km pixels) and have many limitations such as missing fragmented and\or small farms with mixed signatures from different crop types and\or farming practices that can be, confused with other land cover. As a result, the coarse resolution maps have limited useflness in areas where fields are small (<1 ha), such as in Southeast Asia. Furthermore, coarse resolution cropland maps have known uncertainties in both geo-precision of cropland location as well as accuracies of the product. To overcome these limitations, this research was conducted using multi-date, multi-year 30-m Landsat time-series data for 3 years chosen from 2013 to 2016 for all Southeast and Northeast Asian Countries (SNACs), which included 7 refined agro-ecological zones (RAEZ) and 12 countries (Indonesia, Thailand, Myanmar, Vietnam, Malaysia, Philippines, Cambodia, Japan, North Korea, Laos, South Korea, and Brunei). The 30-m (1 pixel = 0.09 ha) data from Landsat 8 Operational Land Imager (OLI) and Landsat 7 Enhanced Thematic Mapper (ETM+) were used in the study. Ten Landsat bands were used in the analysis (blue, green, red, NIR, SWIR1, SWIR2, Thermal, NDVI, NDWI, LSWI) along with additional layers of standard deviation of these 10 bands across 1 year, and global digital elevation model (GDEM)-derived slope and elevation bands. To reduce the impact of clouds, the Landsat imagery was time-composited over four time-periods (Period 1: January- April, Period 2: May-August, and Period 3: September-December) over 3-years. Period 4 was the standard deviation of all 10 bands taken over all images acquired during the 2015 calendar year. These four period composites, totaling 42 band data-cube, were generated for each of the 7 RAEZs. The reference training data (N = 7849) generated for the 7 RAEZ using sub-meter to 5-m very high spatial resolution imagery (VHRI) helped generate the knowledge-base to separate croplands from non-croplands. This knowledge-base was used to code and run a pixel-based random forest (RF) supervised machine learning algorithm on the Google Earth Engine (GEE) cloud computing environment to separate croplands from non-croplands. The resulting cropland extent products were evaluated using an independent reference validation dataset (N = 1750) in each of the 7 RAEZs as well as for the entire SNAC area. For the entire SNAC area, the overall accuracy was 88.1% with a producer’s accuracy of 81.6% (errors of omissions = 18.4%) and user’s accuracy of 76.7% (errors of commissions = 23.3%). For each of the 7 RAEZs overall accuracies varied from 83.2 to 96.4%. Cropland areas calculated for the 12 countries were compared with country areas reported by the United Nations Food and Agriculture Organization and other national cropland statistics resulting in an R 2 value of 0.93. The cropland areas of provinces were compared with the province statistics that showed an R 2 = 0.95 for South Korea and R 2 = 0.94 for Thailand. The cropland products are made available on an interactive viewer at www.croplands.org and for download at National Aeronautics and Space Administration’s (NASA) Land Processes Distributed Active Archive Center (LP DAAC): https://lpdaac.usgs.gov/node/1281 .

International Journal of Applied Earth Observation

Geospatial assessment of agrivoltaic opportunities and land use requirements in Nigeria

Agrivoltaics, the co-location of agriculture and solar photovoltaic (PV) infrastructure, can deliver co-benefits like reduced plant drought stress and improved yields of shade-tolerant crops, particularly in water-scarce regions. Despite growing global interest, the technical potential and opportunities for agrivoltaics remain poorly understood in many regions facing both food and energy insecurity, such as sub-Saharan Africa. Here we provide a spatial assessment of agrivoltaic opportunities in Nigeria by integrating cropland distribution, solar resources, and water stress. We find that northern states—where cropland is abundant and water-stressed, solar irradiance is high, and electricity access remains low—offer the greatest potential for agrivoltaic systems to generate co-benefits. In contrast, the humid forest regions of southern Nigeria exhibit lower suitability, with sparse cropland and weaker solar potential. We also estimate that northern states could fully meet their projected 2050 solar energy targets by allocating less than 1% of existing cropland to agrivoltaics, whereas southern states would require much larger fractions (5.9–18.9%). Notably, in the northern state of Kano, the country’s most populous, allocating 0.6–1.8% of cropland would be sufficient to meet mid-century solar energy projections. Collectively, our findings highlight priority regions where agrivoltaics could most effectively strengthen food-energy security linkages and support equitable energy transition in Nigeria.

Scientific Reports

Conserving migratory land birds in the New World: Do we know enough?

Migratory bird needs must be met during four phases of the year: breeding season, fall migration, wintering, and spring migration; thus, management may be needed during all four phases. The bulk of research and management has focused on the breeding season, although several issues remain unsettled, including the spatial extent of habitat influences on fitness and the importance of habitat on the breeding grounds used after breeding. Although detailed investigations have shed light on the ecology and population dynamics of a few avian species, knowledge is sketchy for most species. Replication of comprehensive studies is needed for multiple species across a range of areas. Information deficiencies are even greater during the wintering season, when birds require sites that provide security and food resources needed for survival and developing nutrient reserves for spring migration and, possibly, reproduction. Research is needed on many species simply to identify geographic distributions, wintering sites, habitat use, and basic ecology. Studies are complicated, however, by the mobility of birds and by sexual segregation during winter. Stable-isotope methodology has offered an opportunity to identify linkages between breeding and wintering sites, which facilitates understanding the complete annual cycle of birds. The twice-annual migrations are the poorest-understood events in a bird's life. Migration has always been a risky undertaking, with such anthropogenic features as tall buildings, towers, and wind generators adding to the risk, Species such as woodland specialists migrating through eastern North America have numerous options for pausing during migration to replenish nutrients, but some species depend on limited stopover locations. Research needs for migration include identifying pathways and timetables of migration, quality and distribution of habitats, threats posed by towers and other tall structures, and any bottlenecks for migration. Issues such as human population growth, acid deposition, climate change, and exotic diseases are global concerns with uncertain consequences to migratory birds and even lesscertain remedies. Despite enormous gaps in our understanding of these birds, research, much of it occurring in the past 30 years, has provided sufficient information to make intelligent conservation efforts but needs to expand to handle future challenges. ?? 2010 by the Ecological Society of America.

Ecological Applications

Dynamics of green and blue water supply stress index across major global cropland basins

Global food and water insecurity could be serious problems in the upcoming decades with growing demands from the increasing global population and more frequent effect of climatic extremes. As the available water resources are diminishing and facing continuous stress, it is crucial to monitor water demand and water availability to understand the associated water stresses. This study assessed the water stress by applying the water supply stress index (WaSSI) in relation to green (WaSSI G ) and blue (WaSSI B ) water resources across six major cropland basins including the Mississippi (North America), San Francisco (South America), Nile (Africa), Danube (Europe), Ganges-Brahmaputra (Asia), and Murray-Darling (Australia) for the past 17-years (2003–2019). The WaSSI G and WaSSI B results indicated that the Murray-Darling Basin experienced the most severe (maximum WaSSI G and WaSSI B anomalies) green and blue water stresses and the Mississippi Basin had the least. All basins had both green and blue water stresses for at least 35% (6 out of 17 years) of the study period. The interannual variations in green water stress were driven by both crop water demand and green water supply, whereas the blue water stress variations were primarily driven by blue water supply. The WaSSI G and WaSSI B provided a better understanding of water stress (blue or green) and their drivers (demand or supply driven) across cropland basins. This information can be useful for basin-specific resource mobilization and interventions to ensure food and water security.

Frontiers in Climate

Crop water productivity from cloud-Based landsat helps assess California’s water savings

Demand for food and water are increasing while the extent of arable land and accessible fresh water are decreasing. This poses global challenges as economies continue to develop and the population grows. With agriculture as the leading consumer of water, better understanding how water is used to produce food may help support the increase of Crop Water Productivity (CWP; kg/m 3 ), the ratio of crop output per unit of water input (or crop per drop). Previous large-scale CWP studies have been useful for broad water use modeling at coarser resolutions. However, obtaining more precise CWP, especially for specific crop types in a particular area and growing season as outlined here are important for informing farm-scale water management decision making. Therefore, this study focused on California’s Central Valley utilizing high-spatial resolution satellite imagery of 30 m (0.09 hectares per pixel) to generate more precise CWP for commonly grown and water-intensive irrigated crops. First, two products were modeled and mapped. 1. Landsat based Actual Evapotranspiration (ET a ; mm/d) to determine Crop Water Use (CWU; m 3 /m 2 ), and 2. Crop Productivity (CP; kg/m 2 ) to estimate crop yield per growing season. Then, CWP was calculated by dividing CP by CWU and mapped. The amount of water that can be saved by increasing CWP of each crop was further calculated. For example, in the 434 million m 2 study area, a 10% increase in CWP across the 9 crops analyzed had a potential water savings of 31.5 million m 3 of water. An increase in CWP is widely considered the best approach for saving maximum quantities of water. This paper proposed, developed, and implemented a workflow of combined methods utilizing cloud computing based remote sensing data. The environmental implications of this work in assessing water savings for food and water security in the 21st century are expected to be significant.

California

Enhancing the application of Earth observations for improved environmental decision-making using the Early Warning eXplorer (EWX)

The mitigation of losses due to extreme climate events and long-term climate adaptation requires climate informed decision-making. In the past few decades, several remote sensing and modeled-based Earth observations (EOs) have been developed to provide an unprecedented global overview and routine monitoring of climate and its impacts on vegetation and hydrologic conditions, with the goal of supporting informed decision-making. However, their usage in decision-making is particularly limited in climate-risk vulnerable and in situ data-scarce regions such as sub-Saharan Africa, due to lack of access to EOs. Here, we describe the Early Warning eXplorer (EWX), which was developed to address this crucial limitation and facilitate the application of EOs in decision-making, particularly in the food and water-insecure regions of the world. First, the EWX's core framework, which includes (i) the Viewer, (ii) GeoEngine, and (iii) Support Applications, is described. Then, a comprehensive overview of the Viewer, which is a web-based interface used to access EOs, is provided. This includes a description of (i) the maps and associated features to access gridded EO data and anomalies for different temporal averaging periods, (ii) time series graphs and associated features to access EOs aggregated over polygons such as administrative boundaries, and (iii) commonly used EOs served by the EWX that provide assessments of climate and vegetation conditions. Next, examples are provided to demonstrate how EWX can be used to monitor development, progression, spatial extent, and severity of climate-driven extreme events to support timely decisions related to mitigation of food insecurity and flooding impacts. Finally, the value of a regional implementation of EWX at the Regional Centre for Mapping of Resources for Development (RCMRD) in Nairobi, Kenya, is highlighted. Regional implementation of the EWX facilitates access to regionally focused EOs and their availability at polygon boundaries most relevant to the local decision-makers. Similar instances of EWX implemented in other regions, especially those susceptible to food and water security, will likely further enhance the application of EOs for informed decision-making.

Frontiers in Climate

Spectral matching techniques (SMTs) and automated cropland classification algorithms (ACCAs) for mapping croplands of Australia using MODIS 250-m time-series (2000–2015) data

Mapping croplands, including fallow areas, are an important measure to determine the quantity of food that is produced, where they are produced, and when they are produced (e.g. seasonality). Furthermore, croplands are known as water guzzlers by consuming anywhere between 70% and 90% of all human water use globally. Given these facts and the increase in global population to nearly 10 billion by the year 2050, the need for routine, rapid, and automated cropland mapping year-after-year and/or season-after-season is of great importance. The overarching goal of this study was to generate standard and routine cropland products, year-after-year, over very large areas through the use of two novel methods: (a) quantitative spectral matching techniques (QSMTs) applied at continental level and (b) rule-based Automated Cropland Classification Algorithm (ACCA) with the ability to hind-cast, now-cast, and future-cast. Australia was chosen for the study given its extensive croplands, rich history of agriculture, and yet nonexistent routine yearly generated cropland products using multi-temporal remote sensing. This research produced three distinct cropland products using Moderate Resolution Imaging Spectroradiometer (MODIS) 250-m normalized difference vegetation index 16-day composite time-series data for 16 years: 2000 through 2015. The products consisted of: (1) cropland extent/areas versus cropland fallow areas, (2) irrigated versus rainfed croplands, and (3) cropping intensities: single, double, and continuous cropping. An accurate reference cropland product (RCP) for the year 2014 (RCP2014) produced using QSMT was used as a knowledge base to train and develop the ACCA algorithm that was then applied to the MODIS time-series data for the years 2000–2015. A comparison between the ACCA-derived cropland products (ACPs) for the year 2014 (ACP2014) versus RCP2014 provided an overall agreement of 89.4% (kappa = 0.814) with six classes: (a) producer’s accuracies varying between 72% and 90% and (b) user’s accuracies varying between 79% and 90%. ACPs for the individual years 2000–2013 and 2015 (ACP2000–ACP2013, ACP2015) showed very strong similarities with several other studies. The extent and vigor of the Australian croplands versus cropland fallows were accurately captured by the ACCA algorithm for the years 2000–2015, thus highlighting the value of the study in food security analysis. The ACCA algorithm and the cropland products are released through http://croplands.org/app/map and http://geography.wr.usgs.gov/science/croplands/algorithms/australia_250m.html

International Journal of Digital Earth

The United States National Climate Assessment - Alaska Technical Regional Report

The Alaskan landscape is changing, both in terms of effects of human activities as a consequence of increased population, social and economic development and their effects on the local and broad landscape; and those effects that accompany naturally occurring hazards such as volcanic eruptions, earthquakes, and tsunamis. Some of the most prevalent changes, however, are those resulting from a changing climate, with both near term and potential upcoming effects expected to continue into the future. Alaska's average annual statewide temperatures have increased by nearly 4&deg;F from 1949 to 2005, with significant spatial variability due to the large latitudinal and longitudinal expanse of the State. Increases in mean annual temperature have been greatest in the interior region, and smallest in the State's southwest coastal regions. In general, however, trends point toward increases in both minimum temperatures, and in fewer extreme cold days. Trends in precipitation are somewhat similar to those in temperature, but with more variability. On the whole, Alaska saw a 10-percent increase in precipitation from 1949 to 2005, with the greatest increases recorded in winter. The National Climate Assessment has designated two well-established scenarios developed by the Intergovernmental Panel on Climate Change (Nakicenovic and others, 2001) as a minimum set that technical and author teams considered as context in preparing portions of this assessment. These two scenarios are referred to as the Special Report on Emissions Scenarios A2 and B1 scenarios, which assume either a continuation of recent trends in fossil fuel use (A2) or a vigorous global effort to reduce fossil fuel use (B1). Temperature increases from 4 to 22&deg;F are predicted (to 2070-2099) depending on which emissions scenario (A2 or B1) is used with the least warming in southeast Alaska and the greatest in the northwest. Concomitant with temperature changes, by the end of the 21st century the growing season is expected to lengthen by 15-25 days in some areas of Alaska, with much of that corresponding with earlier spring snow melt. Future projections of precipitation (30-80 years) over Alaska show an increase across the State, with the largest changes in the northwest and smallest in the southeast. Because of increasing temperatures and growing season length, however, increased precipitation may not correspond with increased water availability, due to temperature related increased evapotranspiration. The extent of snow cover in the Northern Hemisphere has decreased by about 10 percent since the late 1960s, with stronger trends noted since the late 1980s. Alaska has experienced similar trends, with a strong decrease in snow cover extent occurring in May. When averaged across the State, the disappearance of snow in the spring has occurred from 4 to 6 days earlier per decade, and snow return in fall has occurred approximately 2 days later per decade. This change appears to be driven by climate warming rather than a decrease in winter precipitation, with average winter temperatures also increasing by about 2.5&deg;F. The extent of sea ice has been declining, as has been widely published in both national and scientific media outlets, and is projected to continue to decline during this century. The observed decline in annual sea ice minimum extent (September) has occurred more rapidly than was predicted by climate models and has been accompanied by decreases in ice thickness and in the presence of multi-year ice. This decrease was first documented by satellite imagery in the late 1970s for the Bering and Chukchi Seas, and is projected to continue, with the potential for the disappearance of summer sea ice by mid- to late century. A new phenomenon that was not reported in previous assessments is ocean acidification. Uptake of carbon dioxide (CO2) by oceans has a significant effect on marine biogeochemistry by reducing seawater pH. Ocean acidification is of particular concern in Alaska, because cold sea water absorbs CO2 more rapidly than warm water, and a decrease in sea ice extent has allowed increased sea surface exposure and more uptake of CO2 into these northern waters. Ocean acidification will likely affect the ability of organisms to produce and maintain shell material, such as aragonite or calcite (calcium carbonate minerals structured from carbonate ions), required by many shelled organism, from mollusks to corals to microscopic organisms at the base of the food chain. Direct biological effects in Alaska further along the food chain have yet to be studied and may vary among organisms. Some of the potentially most significant changes to Alaska that could result from a changing climate are the effects on the terrestrial cryosphere - particularly glaciers and permafrost. Alaskan glaciers are changing at a rapid rate, the primary driver appearing to be temperature. Statewide, glaciers lost 13 cubic miles of ice annually from the 1950s to the 1990s, and that rate doubled in the 2000s. However, like temperature and precipitation, glacier ice loss is not spatially uniform; most glaciers are losing mass, yet some are growing (for example Hubbard Glacier in southeast Alaska). Alaska glaciers with the most rapid loss are those terminating in sea water or lakes. With this increasing rate of melt, the contribution of surplus fresh water entering into the oceans from Alaska's glaciers, as well as those in neighboring British Columbia, Canada, is approximately 20 percent of that contributed by the Greenland Ice Sheet. Permafrost degradation (that is, the thawing of ice-rich soils) is currently (2012) impacting infrastructure and surface-water availability in areas of both discontinuous and continuous ground ice. Over most of the State, the permafrost is warming, with increasing temperatures broadly consistent with increasing air temperatures. On the Arctic coastal plain of Alaska, permafrost temperatures showed some cooling in the 1950s and 1960s but have been followed by a roughly 5&deg;F increase since the 1980s. Many areas in the continuous permafrost zone have seen increases in temperature in the seasonally active layer and a decrease in re-freezing rates. Changes in the discontinuous permafrost zone are initially much more observable due to the resulting thermokarst terrain (land surface formed as ice rich permafrost thaws), most notable in boreal forested areas. Climate warming in Alaska has potentially broad implications for human health and food security, especially in rural areas, as well as increased risk for injury with changing winter ice conditions. Additionally, such warming poses the potential for increasing damage to existing water and sanitation facilities and challenges for development of new facilities, especially in areas underlain by permafrost. Non-infectious and infectious diseases also are becoming an increasing concern. For example, from 1999 to 2006 there was a statistically significant increase in medical claims for insectbite reactions in five of six regions of Alaska, with the largest percentage increase occurring in the most northern areas. The availability and quality of subsistence foods, normally considered to be very healthy, may change due to changing access, changing habitats, and spoilage of meat in food storage cellars. These and other trends and potential outcomes resulting from a changing climate are further described in this report. In addition, we describe new science leadership activities that have been initiated to address and provide guidance toward conducting research aimed at making available information for policy makers and land management agencies to better understand, address, and plan for changes to the local and regional environment. This report cites data in both metric and standard units due to the contributions by numerous authors and the direct reference of their data.

Alaska