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Floodplain societies decide whether to protect themselves against floods (fight), live with floods (adapt), or adopt an approach that represents some combination of the two. The formation of a levee system is an important factor in determining whether a society fights or adapts to floods; however, these factors have been considered fixed boundaries in previous studies in human–flood interactions. We analyze a levee system transformation process covering the past century, from the indigenous ring-type levee system with floods to modern continuous levees against floods in the Kiso River basin in Japan by applying a historical sociohydrological approach. The results show degradation processes of the indigenous levee system and traditional communities alongside the installation of modern continuous levees, and a trade-off relationship was observed between the lengths of both. There are interactions between the levee systems and the human–water system through various water uses and different-scale components, and the dynamics within the region are connected to external socioeconomic trends through the installed modern levees and institutions.

Abstract Stable water isotopes in inland Antarctic ice cores are powerful paleoclimate proxies; however, their relationship with dynamical atmospheric circulations remains controversial. Using a water isotope climate model (MIROC5‐iso), we assessed the influence of the Last Glacial Maximum (LGM; ∼21,000 years ago) sea surface temperatures (SST) and sea ice (SIC) on Antarctic precipitation isotopes (δ18Op) through atmospheric circulation. The results revealed that the synoptic circulation mostly maintained southward moisture transport, reaching inland Antarctica. The steepened meridional SST gradient in the mid‐latitudes increased δ18Op in inland Antarctica with the enhanced baroclinic instability and synoptic moisture transport. In contrast, expanded SIC distribution decreased δ18Op over Antarctica by enhanced preferential removal of heavy isotopes during vapor transport due to the increased transport distance and enhanced surface cooling. These findings propose to use Antarctic ice cores to describe the southern hemisphere atmospheric circulation, represented by the westerly jets, during the LGM and other past climates.

The climate impact contribution of lakes to sustain the Green Sahara in the mid-Holocene (MH, 6000 years ago) is still under debate. To assess the lake-induced climate response over North Africa, we investigated the roles of western Sahara lakes and Megalake Chad using reconstructions of MH Sahara lake maps as surface boundary conditions for the isotope-enabled atmospheric model MIROC5-iso. Our results show that the western Sahara lakes pushed the West African monsoon northward and extended it eastward by expanding Megalake Chad. This lake–climate impact was caused by the cyclonic circulation response related to the weakened African Easterly Jet and enhanced Tropical Easterly Jet. According to the Budyko aridity index, the northwestern Sahara climate region shifted from hyper-arid to arid or semi-arid with the lake expansion. Moreover, precipitation scarcity could have been reduced by up to 13 % to sustain the semi-humid conditions. Such lake–climate impacts could alleviate Sahara aridity, relying on lake positions in the monsoon regions. Our findings are promising for understanding the contribution of lakes to sustaining the Green Sahara.

In this paper, we propose a method for regional analysis using image recognition technology based on deep learning and big data of street images captured by omnidirectional cameras on vehicles. Specifically, we first construct a classification method of regions based on street images using a pretrained deep learning model (VGG16) for image recognition as a feature extractor. Next, we develop a method to evaluate the landscape and safety of streets based on the ratio of street components (such as buildings, roads, fences, vegetations, sky, street lights) at each shooting point, which is calculated by semantic segmentation.

Global hydrological models that include human activities are powerful tools for assessing water availability and use at global and continental scales. Such models are typically applied at a spatial resolution of 30 arcmin (approximately 50 km). In recent years, some 5 arcmin (9 km) applications have been reported but with numerous technical challenges, including the validation of calculations for more than 1 × 106 grid cells and the conversion of simulation results into meaningful information relevant to water resource management. Here, the H08 global water resources model was applied in two ways to Kyushu island in Japan at a resolution of 1 arcmin (2 km), and the detailed results were compared. One method involved feeding interpolated global meteorological and geographic data into the default global model (GLB; in accordance with previous high-resolution applications). For the other method, locally derived boundary conditions were input to the localized model (LOC; this method can be easily extended and applied to other regions, at least across Japan). The results showed that the GLB cannot easily reproduce the historical record, especially for variables related to human activities (e.g., dam operation and water withdrawal). LOC is capable of estimating natural and human water balance components at daily timescales and providing reliable information for regional water resource assessment. The results highlight the importance of improving data preparation and modeling methods to represent water management and use in hyper-resolution global hydrology simulations.

Terrestrial surface water temperature is a key variable affecting water quality and energy balance, and thermodynamics and fluid dynamics are tightly coupled in fluvial and lacustrine systems. Streamflow generally plays a role in the horizontal redistribution of heat, and thermal exchange in lakes predominantly occurs in a vertical direction. However, numerical models simulate the water temperature for uncoupled rivers and lakes, and the linkages between them on a global scale remain unclear. In this study, we proposed an integrated modeling framework: Tightly Coupled framework for Hydrology of Open water Interactions in River–lake network (TCHOIR, read as “tee quire”). The objective is to simulate terrestrial fluvial and thermodynamics as a continuum of mass and energy in solid and liquid phases redistributed among rivers and lakes. TCHOIR uses high-resolution geographical information harmonized over fluvial and lacustrine networks. The results have been validated through comparison with in situ observations and satellite-based data products, and the model sensitivity has been tested with multiple meteorological forcing datasets. It was observed that the “coupled” mode outperformed the “river-only” mode in terms of discharge and temperature downstream of lakes; moreover, it was observed that seasonal and interannual variation in lake water levels and temperature are also more reliable in the “coupled” mode. The inclusion of lakes in the coupled model resulted in an increase in river temperatures during winter at midlatitudes and a decrease in temperatures during summer at high latitudes, which reflects the role of lakes as a form of large heat storage. The river–lake coupling framework presented herein provides a basis for further elucidating the role of terrestrial surface water in Earth's energy cycle.

This paper examines the possibility of impression evaluation based on gaze analysis of subjects and deep learning, using an example of evaluating street attractiveness in densely built-up wooden residential areas. Firstly, the relationship between the subjects' gazing tendency and their evaluation of street image attractiveness is analysed by measuring the subjects' gaze with an eye tracker. Next, we construct a model that can estimate an attractiveness evaluation result using convolutional neural networks (CNNs), combined with the method of gradient-weighted class activation mapping (Grad-CAM) - these in in visualizing which street components can contribute to evaluating attractiveness. Finally, we discuss the similarity between the subjects' gaze tendencies and activation heatmaps created by Grad-CAM.

Global-scale river models (GRMs) are core tools for providing consistent estimates of global flood hazard, especially in data-scarce regions. Due to former limitations in computational power and input datasets, most GRMs have been developed to use simplified representations of flow physics and run at coarse spatial resolutions. With increasing computational power and improved datasets, the application of GRMs to finer resolutions is becoming a reality. To support development in this direction, the suitability of GRMs for application to finer resolutions needs to be assessed. This study investigates the impacts of spatial resolution and flow connectivity representation on the predictive capability of a GRM, CaMa-Flood, in simulating the 2011 extreme flood in Thailand. Analyses show that when single downstream connectivity (SDC) is assumed, simulation results deteriorate with finer spatial resolution; Nash–Sutcliffe efficiency coefficients decreased by more than 50 % between simulation results at 10 km resolution and 1 km resolution. When multiple downstream connectivity (MDC) is represented, simulation results slightly improve with finer spatial resolution. The SDC simulations result in excessive backflows on very flat floodplains due to the restrictive flow directions at finer resolutions. MDC channels attenuated these effects by maintaining flow connectivity and flow capacity between floodplains in varying spatial resolutions. While a regional-scale flood was chosen as a test case, these findings should be universal and may have significant impacts on large- to global-scale simulations, especially in regions where mega deltas exist.These results demonstrate that a GRM can be used for higher resolution simulations of large-scale floods, provided that MDC in rivers and floodplains is adequately represented in the model structure.

Over recent decades, the global population has been rapidly increasing and human activities have altered terrestrial water fluxes to an unprecedented extent. The phenomenal growth of the human footprint has significantly modified hydrological processes in various ways (e.g. irrigation, artificial dams, and water diversion) and at various scales (from a watershed to the globe). During the early 1990s, awareness of the potential for increased water scarcity led to the first detailed global water resource assessments. Shortly thereafter, in order to analyse the human perturbation on terrestrial water resources, the first generation of large-scale hydrological models (LHMs) was produced. However, at this early stage few models considered the interaction between terrestrial water fluxes and human activities, including water use and reservoir regulation, and even fewer models distinguished water use from surface water and groundwater resources. Since the early 2000s, a growing number of LHMs have incorporated human impacts on the hydrological cycle, yet the representation of human activities in hydrological models remains challenging. In this paper we provide a synthesis of progress in the development and application of human impact modelling in LHMs. We highlight a number of key challenges and discuss possible improvements in order to better represent the human–water interface in hydrological models.

Water scarcity threatens a growing number of global catchments. Here, the authors examine how human interventions (HI) affected water scarcity between 1971 and 2010 and find that HI caused increases in the average duration and occurrence of water scarcity for 32% and 34% of the global population, respectively.

Evapotranspiration (ET) of Amazon forests is a main driver of regional climate patterns and an important indicator of ecosystem functioning. Despite its importance, the seasonal variability of ET over Amazon forests, and its relationship with environmental drivers, is still poorly understood. In this study, we carry out a water balance approach to analyse seasonal patterns in ET and their relationships with water and energy drivers over five sub-basins across the Amazon Basin. We used in situ measurements of river discharge, and remotely sensed estimates of terrestrial water storage, rainfall, and solar radiation. We show that the characteristics of ET seasonality in all sub-basins differ in timing and magnitude. The highest mean annual ET was found in the northern Rio Negro basin (∼ 1497 mm year−1) and the lowest values in the Solimões River basin (∼ 986 mm year−1). For the first time in a basin-scale study, using observational data, we show that factors limiting ET vary across climatic gradients in the Amazon, confirming local-scale eddy covariance studies. Both annual mean and seasonality in ET are driven by a combination of energy and water availability, as neither rainfall nor radiation alone could explain patterns in ET. In southern basins, despite seasonal rainfall deficits, deep root water uptake allows increasing rates of ET during the dry season, when radiation is usually higher than in the wet season. We demonstrate contrasting ET seasonality with satellite greenness across Amazon forests, with strong asynchronous relationships in ever-wet watersheds, and positive correlations observed in seasonally dry watersheds. Finally, we compared our results with estimates obtained by two ET models, and we conclude that neither of the two tested models could provide a consistent representation of ET seasonal patterns across the Amazon.

The assessment of water balance components using global hydrological models is subject to climate forcing uncertainty as well as to an increasing intensity of human water use within the 20th century. The uncertainty of five state-of-the-art climate forcings and the resulting range of cell runoff that is simulated by the global hydrological model WaterGAP is presented. On the global land surface, about 62 % of precipitation evapotranspires, whereas 38 % discharges into oceans and inland sinks. During 1971–2000, evapotranspiration due to human water use amounted to almost 1 % of precipitation, while this anthropogenic water flow increased by a factor of approximately 5 between 1901 and 2010. Deviation of estimated global discharge from the ensemble mean due to climate forcing uncertainty is approximately 4 %. Precipitation uncertainty is the most important reason for the uncertainty of discharge and evapotranspiration, followed by shortwave downward radiation. At continental levels, deviations of water balance components due to uncertain climate forcing are higher, with the highest discharge deviations occurring for river discharge in Africa (−6 to 11 % from the ensemble mean). Uncertain climate forcings also affect the estimation of irrigation water use and thus the estimated human impact of river discharge. The uncertainty range of global irrigation water consumption amounts to approximately 50 % of the global sum of water consumption in the other water use sector.

The Land Surface, Snow and Soil Moisture Model Intercomparison Project (LS3MIP) is designed to provide a comprehensive assessment of land surface, snow and soil moisture feedbacks on climate variability and climate change, and to diagnose systematic biases in the land modules of current Earth system models (ESMs). The solid and liquid water stored at the land surface has a large influence on the regional climate, its variability and predictability, including effects on the energy, water and carbon cycles. Notably, snow and soil moisture affect surface radiation and flux partitioning properties, moisture storage and land surface memory. They both strongly affect atmospheric conditions, in particular surface air temperature and precipitation, but also large-scale circulation patterns. However, models show divergent responses and representations of these feedbacks as well as systematic biases in the underlying processes. LS3MIP will provide the means to quantify the associated uncertainties and better constrain climate change projections, which is of particular interest for highly vulnerable regions (densely populated areas, agricultural regions, the Arctic, semi-arid and other sensitive terrestrial ecosystems). The experiments are subdivided in two components, the first addressing systematic land biases in offline mode (“LMIP”, building upon the 3rd phase of Global Soil Wetness Project; GSWP3) and the second addressing land feedbacks attributed to soil moisture and snow in an integrated framework (“LFMIP”, building upon the GLACE-CMIP blueprint).

When assessing global water resources with hydrological models, it is essential to know about methodological uncertainties. The values of simulated water balance components may vary due to different spatial and temporal aggregations, reference periods, and applied climate forcings, as well as due to the consideration of human water use, or the lack thereof. We analyzed these variations over the period 1901–2010 by forcing the global hydrological model WaterGAP 2.2 (ISIMIP2a) with five state-of-the-art climate data sets, including a homogenized version of the concatenated WFD/WFDEI data set. Absolute values and temporal variations of global water balance components are strongly affected by the uncertainty in the climate forcing, and no temporal trends of the global water balance components are detected for the four homogeneous climate forcings considered (except for human water abstractions). The calibration of WaterGAP against observed long-term average river discharge Q significantly reduces the impact of climate forcing uncertainty on estimated Q and renewable water resources. For the homogeneous forcings, Q of the calibrated and non-calibrated regions of the globe varies by 1.6 and 18.5 %, respectively, for 1971–2000. On the continental scale, most differences for long-term average precipitation P and Q estimates occur in Africa and, due to snow undercatch of rain gauges, also in the data-rich continents Europe and North America. Variations of Q at the grid-cell scale are large, except in a few grid cells upstream and downstream of calibration stations, with an average variation of 37 and 74 % among the four homogeneous forcings in calibrated and non-calibrated regions, respectively. Considering only the forcings GSWP3 and WFDEI_hom, i.e., excluding the forcing without undercatch correction (PGFv2.1) and the one with a much lower shortwave downward radiation SWD than the others (WFD), Q variations are reduced to 16 and 31 % in calibrated and non-calibrated regions, respectively. These simulation results support the need for extended Q measurements and data sharing for better constraining global water balance assessments. Over the 20th century, the human footprint on natural water resources has become larger. For 11–18% of the global land area, the change of Q between 1941–1970 and 1971–2000 was driven more strongly by change of human water use including dam construction than by change in precipitation, while this was true for only 9–13 % of the land area from 1911–1940 to 1941–1970.

The assessment of flood risk is important for policymakers to evaluate damage and for disaster preparation. Large population densities and high property concentration make cities more vulnerable to floods and having higher absolute damage per year. A number of major cities in the world suffer from flood inundation damage every year. In Japan, approximately USD 1 billion in damage occurs annually due to pluvial floods only. The amount of damage was typically large in large cities, but regions with lower population density tended to have more damage per capita. Our statistical approach gives the probability of damage following every daily rainfall event and thereby the annual damage as a function of rainfall, population density, topographical slope and gross domestic product. Our results for Japan show reasonable agreement with area-averaged annual damage for the period 1993–2009. We report a damage occurrence probability function and a damage cost function for pluvial flood damage, which makes this method flexible for use in future scenarios and also capable of being expanded to different regions.

Climate change and its impacts already pose considerable challenges for societies that will further increase with global warming (IPCC, 2014a, b). Uncertainties of the climatic response to greenhouse gas emissions include the potential passing of large-scale tipping points (e.g. Lenton et al., 2008; Levermann et al., 2012; Schellnhuber, 2010) and changes in extreme meteorological events (Field et al., 2012) with complex impacts on societies (Hallegatte et al., 2013). Thus climate change mitigation is considered a necessary societal response for avoiding uncontrollable impacts (Conference of the Parties, 2010). On the other hand, large-scale climate change mitigation itself implies fundamental changes in, for example, the global energy system. The associated challenges come on top of others that derive from equally important ethical imperatives like the fulfilment of increasing food demand that may draw on the same resources. For example, ensuring food security for a growing population may require an expansion of cropland, thereby reducing natural carbon sinks or the area available for bio-energy production. So far, available studies addressing this problem have relied on individual impact models, ignoring uncertainty in crop model and biome model projections. Here, we propose a probabilistic decision framework that allows for an evaluation of agricultural management and mitigation options in a multi-impact-model setting. Based on simulations generated within the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP), we outline how cross-sectorally consistent multi-model impact simulations could be used to generate the information required for robust decision making. Using an illustrative future land use pattern, we discuss the trade-off between potential gains in crop production and associated losses in natural carbon sinks in the new multiple crop- and biome-model setting. In addition, crop and water model simulations are combined to explore irrigation increases as one possible measure of agricultural intensification that could limit the expansion of cropland required in response to climate change and growing food demand. This example shows that current impact model uncertainties pose an important challenge to long-term mitigation planning and must not be ignored in long-term strategic decision making.

The effectiveness of population policy in reducing the combined impacts of population change and climate change on water resources is explored. One no-policy scenario and two scenarios with population policy assumptions are employed in combination with water availability under the SRES scenarios A1b, B1 and A2 for the impact analysis. The population data used are from the World Bank. The river discharges per grid of horizontal resolution 0.5° are obtained from the Total Runoff Integrating Pathways (TRIP) of the University of Tokyo, Japan. Unlike the population scenarios utilized in the SRES emission scenarios and the newest representative concentration pathways, the scenarios employed in this research are based, even after 2050, on country-level rather than regional-level growth assumptions. Our analysis implies that the heterogeneous pattern of population changes across the world is the dominant driver of water stress, irrespective of future greenhouse gas emissions, with highest impacts occurring in the already water-stressed low latitudes. In 2100, Africa, Middle East and parts of Asia are under extreme water stress under all scenarios. The sensitivity analysis reveals that a small reduction in populations over the region could relieve a large number of people from high water stress, while a further increase in population from the assumed levels (SC1) might not increase the number of people under high water stress considerably. Most of the population increase towards 2100 occurs in the already water-stressed lower latitudes. Therefore, population reduction policies are recommended for this region as a method of adaptation to the future water stress conditions. Population reduction policies will facilitate more control over their future development pathways, even if these countries were not able to contribute significantly to greenhouse gas (GHG) emission cuts due to economic constraints. However, for the European region, the population living in water-stressed regions is almost 20 times lower than that in the lower latitudes. For countries with high population momentum, the population policy scenario with fertility-reduction assumptions gained a maximum of 6.1 times the water availability in Niger and 5.3 times that in Uganda compared with the no-policy scenario. Most of these countries are in sub-Saharan Africa. These countries represent 24.5% of the global population in the no-policy scenario, and the scenario with fertility-reduction assumptions reduces it to 8.7% by 2100. This scenario is also effective in reducing the area under extreme water stress in these countries. However, the policy scenario with assumptions of population stabilization at the replacement fertility rate increases the water stress in high-latitude countries. Nevertheless, the impact is low due to the high per capita water availability in the region. This research is expected to widen the understanding of the combined impacts of climate change in the future and of the strategies needed to enhance the space for adaptation.

Anaplasma phagocytophilum, a member of the family Anaplasmataceae and the obligate intracellular bacterium that causes granulocytic anaplasmosis, resides in a host cell-derived vacuole. Bacterial proteins that localize to the A. phagocytophilum-occupied vacuole membrane (AVM) are critical host-pathogen interfaces. Of the few bacterial AVM proteins that have been identified, the domains responsible for AVM localization and the host cell pathways that they co-opt are poorly defined. APH0032 is an effector that is expressed and localizes to the AVM late during the infection cycle. Herein, the APH0032 domain that is essential for associating with host cell membranes was mapped. Immunofluorescent labeling of infected cells that had been differentially permeabilized confirmed that APH0032 is exposed on the AVM’s cytosolic face, signifying its potential to interface with host cell processes. SUMOylation is the covalent attachment of a member of the small ubiquitin-like modifier (SUMO) family of proteins to lysines in target substrates. Previous work from our laboratory determined that SUMOylation is important for A. phagocytophilum survival and that SUMOylated proteins decorate the AVM. Algorithmic prediction analyses identified APH0032 as a candidate for SUMOylation. Endogenous APH0032 was precipitated from infected cells using a SUMO affinity matrix, confirming that the effector co-opts SUMOylation during infection. APH0032 pronouncedly colocalized with SUMO1, but not SUMO2/3 moieties on the AVM. Ectopic expression of APH0032 in A. phagocytophilum infected host cells significantly boosted the bacterial load. This study delineates the first domain of any Anaplasmataceae protein that is essential for associating with the pathogen-occupied vacuole membrane, demonstrates the importance of APH0032 to infection, and identifies it as the second A. phagocytophilum effector that co-opts SUMOylation, thus underscoring the relevance of this post-translational modification to infection.

This paper proposes an improved method for converting a fine-resolution flow direction map into a coarse-resolution river network map for use in global river routing models. The proposed method attempts to preserve the river network structure of an original fine-resolution map in the upscaling procedure, as this has not been achieved with previous upscaling methods. We describe an improved method in which a downstream cell can be flexibly located on any cell in the river network map. The improved method preserves the river network structure of the original flow direction map and allows automated construction of river network maps at any resolution. Automated construction of a river network map is helpful for attaching sub-grid topographic information, such as realistic river meanderings and drainage boundaries, onto the upscaled river network map. The advantages of the proposed method are expected to enhance the ability of global river routing models by providing ways to more precisely represent surface water storage and movement.

This study employs the regional Community Multiscale Air Quality (CMAQ) model to examine seasonal and diurnal variations of boundary layer ozone (O3) over East Asia. We evaluate the response of model simulations of boundary layer O3 to the choice of chemical mechanisms, meteorological fields, boundary conditions, and model resolutions. Data obtained from surface stations, aircraft measurements, and satellites are used to advance understanding of O3 chemistry and mechanisms over East Asia and evaluate how well the model represents the observed features. Satellite measurements and model simulations of summertime rainfall are used to assess the impact of the Asian monsoon on O3 production. Our results suggest that summertime O3 over Central Eastern China is highly sensitive to cloud cover and monsoonal rainfall over this region. Thus, accurate simulation of the East Asia summer monsoon is critical to model analysis of atmospheric chemistry over China. Examination of hourly summertime O3 mixing ratios from sites in Japan confirms the important role of diurnal boundary layer fluctuations in controlling ground-level O3. By comparing five different model configurations with observations at six sites, the specific mechanisms responsible for model behavior are identified and discussed. In particular, vertical mixing, urban chemistry, and dry deposition depending on boundary layer height strongly affect model ability to capture observed behavior. Central Eastern China appears to be the most sensitive region in our study to the choice of chemical mechanisms. Evaluation with TRACE-P aircraft measurements reveals that neither the CB4 nor the SAPRC99 mechanisms consistently capture observed behavior of key photochemical oxidants in springtime. However, our analysis finds that SAPRC99 performs somewhat better in simulating mixing ratios of H2O2 (hydrogen peroxide) and PAN (peroxyacetyl nitrate) at flight altitudes below 1 km. The high level of uncertainty associated with O3 production in Central Eastern China poses a major problem for regional air quality management. This highly polluted, densely populated region would greatly benefit from comprehensive air quality monitoring and the development of model chemical mechanisms appropriate to this unique atmospheric environment.

To assess global water resources from the perspective of subannual variation in water availability and water use, an integrated water resources model was developed. In a companion report, we presented the global meteorological forcing input used to drive the model and six modules, namely, the land surface hydrology module, the river routing module, the crop growth module, the reservoir operation module, the environmental flow requirement module, and the anthropogenic withdrawal module. Here, we present the results of the model application and global water resources assessments. First, the timing and volume of simulated agriculture water use were examined because agricultural use composes approximately 85% of total consumptive water withdrawal in the world. The estimated crop calendar showed good agreement with earlier reports for wheat, maize, and rice in major countries of production. In major countries, the error in the planting date was ±1 mo, but there were some exceptional cases. The estimated irrigation water withdrawal also showed fair agreement with country statistics, but tended to be underestimated in countries in the Asian monsoon region. The results indicate the validity of the model and the input meteorological forcing because site-specific parameter tuning was not used in the series of simulations. Finally, global water resources were assessed on a subannual basis using a newly devised index. This index located water-stressed regions that were undetected in earlier studies. These regions, which are indicated by a gap in the subannual distribution of water availability and water use, include the Sahel, the Asian monsoon region, and southern Africa. The simulation results show that the reservoir operations of major reservoirs (>1 km3) and the allocation of environmental flow requirements can alter the population under high water stress by approximately −11% to +5% globally. The integrated model is applicable to assessments of various global environmental projections such as climate change.

To assess global water availability and use at a subannual timescale, an integrated global water resources model was developed consisting of six modules: land surface hydrology, river routing, crop growth, reservoir operation, environmental flow requirement estimation, and anthropogenic water withdrawal. The model simulates both natural and anthropogenic water flow globally (excluding Antarctica) on a daily basis at a spatial resolution of 1°×1° (longitude and latitude). This first part of the two-feature report describes the six modules and the input meteorological forcing. The input meteorological forcing was provided by the second Global Soil Wetness Project (GSWP2), an international land surface modeling project. Several reported shortcomings of the forcing component were improved. The land surface hydrology module was developed based on a bucket type model that simulates energy and water balance on land surfaces. The crop growth module is a relatively simple model based on concepts of heat unit theory, potential biomass, and a harvest index. In the reservoir operation module, 452 major reservoirs with >1 km3 each of storage capacity store and release water according to their own rules of operation. Operating rules were determined for each reservoir by an algorithm that used currently available global data such as reservoir storage capacity, intended purposes, simulated inflow, and water demand in the lower reaches. The environmental flow requirement module was newly developed based on case studies from around the world. Simulated runoff was compared and validated with observation-based global runoff data sets and observed streamflow records at 32 major river gauging stations around the world. Mean annual runoff agreed well with earlier studies at global and continental scales, and in individual basins, the mean bias was less than ±20% in 14 of the 32 river basins and less than ±50% in 24 basins. The error in the peak was less than ±1 mo in 19 of the 27 basins and less than ±2 mo in 25 basins. The performance was similar to the best available precedent studies with closure of energy and water. The input meteorological forcing component and the integrated model provide a framework with which to assess global water resources, with the potential application to investigate the subannual variability in water resources.

An optical particle counter (OPC) is used in conjunction with lidar measurements to examine the characteristics of the particle size distribution in cirrus cloud in the tropical tropopause layer (TTL) over Thailand where the TTL is defined as the height at which temperature is lower than −75°C in this paper. Of 11 OPC launches, cirrus cloud was detected at 10–15 km high on 7 occasions, cirrus was detected in the TTL in 6 cases, and simultaneous OPC and lidar measurements were made on two occasions. Comparison of lidar and OPC measurements reveal that the cloud heights of cirrus in the TTL varies by several hundred meters over distances of tens kilometers; hence the height is not always horizontally uniform. The mode radii of particles constituting the clouds are estimated by lidar and OPC measurements to be less than approximately 10 μm. The regression lines of the particle size distribution with and without cirrus cloud exhibit similar features at equivalent radii of