Localized heavy rainfall has caused severe damage in Japan, and land surface states (e.g., land surface temperature) are known to affect localized heavy rainfall. Thus, the introduction of a detailed initial land surface state is required for weather prediction using numerical meteorological models.In this study, we developed a method for estimating realistic land surface states based on a detailed land surface model, introducing solar radiation data based on geostationary meteorological satellites, rainfall data provided by the Japan Meteorological Agency (JMA), and detailed anthropocentric heat, and building height data.In this study, to provide atmospheric boundary conditions, the JMA meso-scale objective analysis data (5 km horizontal resolution) were used. For precipitation distribution, the Radar-Raingauge-Analyzed Precipitation data provided by JMA (1 km horizontal resolution) were used. For solar radiation distribution, solar radiation consortium data (1 km spatial resolution) were used.These data were introduced into a detailed land surface model called the Simple Biosphere model including Urban Canopy (SiBUC), which consists of green area, water body, and urban area sub-models. The calculation of each sub-model was carried out based on the heat, radiative, and water budget equations.The proposed method was applied to the Keihanshin region for 31 days from 09:00 JST on the August 1, 2018, within a domain of 480 km × 480 km and horizontal resolution of approximately 2 km. During validation, the maximum, minimum, and average roof surface temperatures for each day were extracted from the estimated and observed values to calculate the mean error, root mean squared error, and correlation coefficient. All daily maximum and minimum average roof temperature data showed a high correlation, with a coefficient exceeding 0.8.

Climate change may increase the frequency and intensity of extreme rainfall. For better water management in the future, it is essential to identify flood characteristics. Urban flood modeling is a general way to quantify the impact of floods on urban catchments. This research investigated the impact of changes in rainfall intensity-duration frequency (IDF) curves on flood characteristics in the urban area of Phnom Penh using the SWMM Model. The NSGA-II algorithm was used to auto-calibrate the SWMM model and obtain the parameter settings. The model was calibrated and validated by four rainfall events, and the results indicate the model performance is satisfactory, the Nash-Sutcliffe model's efficiency being between 0.658 and 0.915. A temporal decomposition model based on the ANN method was applied to create a monthly maximum next-day rainfall in Ho Chi Minh City and Can Tho from future daily rainfall data provided by five CORDEX models. The 2-, 5-, and 10-year (return period) IDF curves over the historical period between 1986-2005 in Phnom Penh City were regressed using the weighted average of sub-daily rainfall in Ho Chi Minh and Can Tho in a given return period. This operation was also used to construct IDF curves for a future period (2026-2045) based on regional climate model outputs. The alternating block method was used to generate a 7-hour time series and input in the SWMM model. Compared with the historical extreme rainfall events, future ones were expected to rainfall amount increase by 19.3mm, 27.8mm, 32.1mm for the 2, 5, and 10-year. The increase in surface runoff resulted in more overloaded conduits and nodes with overflows of 35.9%, 27.0%, and 15.6%, respectively. In all, 42 vulnerable hotspots and 32 pipes insufficient drainage pipes were identified, which will provide useful information for assessing future flooding in Phnom Penh City. 

In order to properly understand the climate conditions of a watershed, a proper evaluation of long-term observed data should first be determined. Trend analysis should be performed to determine if significant trends are present in the dataset. In this study, Mann-Kendall trend test was used to determine if significant trends can be detected in the climate parameters of Yongdam dam watershed. The annual, seasonal, and the monthly precipitation, and air temperature data from year 1943 to 2020 were used in this study. Results suggests that for a significant level of 0.05 (α = 0.05), the annual number of wet days is decreasing, and the average rainfall intensity during summer, and winter seasons are increasing, and decreasing, respectively. Therefore, based from the results of this study, though the number of wet days decreases, the increase in rainfall intensity during summer may result to frequent flooding; while the decrease in rainfall intensity may result to drier winter seasons in Yongdam dam watershed.This research was supported by the National Research Foundation of Korea (2018K1A3A1A05087901).

Global river ecosystems have been seriously threatened as a result of rapid socioeconomic development and climate change over the last several decades. Accordingly, developing a rational evaluation and management method becomes essential. The catchment of Lai Chi Wo (LCW) in Hong Kong, China, was chosen as the research area for applying a method for this study. The hydrology and fish assemblage at five stations in the LCW was collected. Then, we used the fish-based biotic integrity index (F-IBI) to evaluate river health. The results revealed that there are spatial variations of F-IBI from the LCW downstream to upstream. Such variations are compatible with human interference in the river downstream and upstream. Further, the results of assignment method and ratio methods showed similar results of ecological health in the LCW downstream. The regression analysis results also showed the appropriate range of environmental factors (water temperature, DO, turbidity, pH, water level) with F-IBI and the impact of environmental changes on living things. The study can provide a referable ecological health assessment criterion to river health evaluation, and enrich our eco-hydrology knowledge.

Typhoon Hagibis caused severe flood damages in the wide area of the eastern Japan. In the Ara River basin system, a widespread inundation was caused due to the levee collapse at 7 stations of the tributaries. On the other hand, there was no levee breach in the main stream, but it is shown that the water level of the Ara River exceeded designed high water level (H.W.L.). If the flooding of the Ara River occurs, it is expected to be accompanied the inundation in large area near Tokyo Metropolitan area, so it is very important to evaluate the flood risk. In this study, we examined the possibility of flooding in the Ara River due to the typhoon Hagibis. Specifically, we investigated whether flooding could have occurred due to differences in rainfall distribution in the river catchment area by the calculation based on runoff analysis and river flow analysis. We used the hindcast rainfall analyzed by the radar AMeDAS and the predicted rainfall by the Mesoscale Ensemble Prediction System (MEPS) developed by the Japan Meteorological Agency. Then, we conducted runoff analysis by using Rainfall-Runoff-Inundation (RRI) model and river flow analysis calculating 1-D unsteady flow using these two types of rainfall data. In order to reproduce the current conditions, the parameters of the calculation model were identified using hindcast rainfall, and then we calculated the discharge and the water level using these parameters and predicted rainfall data. As a result, we showed there were 22 km of sections where the calculated water level exceeded H.W.L., and in some sections the exceedance time exceeded 14 hours. In addition, we showed that the river discharge increased due to the difference in the rainfall distribution, and it is suggested the possibility that the water level may have increased compared to the current conditions.

To minimize the damage from extreme droughts which may be caused from the climate change, a range of measures to stabilize water supply have been established. These include water supply adjustment (rationing) and introduction to additional supply such as a conduit operation and the consideration of emergency capacity of reservoirs. In order to effectively execute various structural and non-structural drought response measures, it is necessary to establish the priorities of such measures and optimal operation plans according to the quantitatively measured drought resilience. In this study, an evaluation index S-day (water supply day) is proposed as a criterion for evaluating both structures’ and basins’ drought resilience capacities. S-day calculates the number of days that the system can endure during a drought and aims to reflect both the capacity of the facility as well as its water demand. In this study, a reservoir model was constructed including four reservoirs (Boryeong Dam, Daecheong Dam, Yongdam Dam, and Buan Dam) in the Geum River Basin, South Korea. As a result, reservoir capacity (reservoir response capacity) was more sensitive to the changes in the inflow (a range of return periods) than the drought response measures, and the degree of improvement was found to be the greatest in low water level (50% effective storage water) conditions. Especially, in the case of Boryeong Dam, it showed the effect of the conduit operation was the greatest. Finally, the structural drought response measures appeared to be more effective than the non-structural measures when establishing drought resilience in reservoirs.

Frequency and severity of drought tend to increase in several regions of the world including Korean Peninsula. IPCC AR5 (the 5^th Assessment Report of Intergovernmental Panel on Climate Change) projected that this tendency would be continued due to climate change. South Korea has suffered from droughts almost every year since 2006. Drought Monitoring and Early Warning System (DMEWS) supported by Korean government, was, therefore, developed in 2015 and has been operated since March, 2016.In DMEWS, drought monitoring and 1-, 2-, and 3-month outlook maps are provided in terms of meteorological, agricultural, and hydrological droughts. Drought condition is classified into four levels, ‘Concern’, ‘Caution’, ‘Severe’, and ‘Very Severe’. Hydrological drought is specifically based on whether municipal and industrial water supply conditions from water sources such as dams, reservoirs, rivers, groundwater, and so on, are sufficient to be supplied to 167 administrative regions. K-water has established the drought monitoring and forecasting system for hydrological drought analysis since the beginning of DMEWS. This paper introduced the techniques for hydrological drought forecasting of K-water and showed the evaluation results of the forecasting accuracy. Discharges of 113 inland mid-sized basins are calculated by using the quantitative weather forecasts, rainfall-runoff models, and ESP (Ensemble Streamflow Prediction). Then, the storages and flowrates of water sources are predicted. Finally, the drought conditions of water sources are determined from the drought criteria. Skill scores showed that hydrological drought early warning service was reliable in spite of the uncertainties from weather forecasts and models.

Over the last century, an incredible variation was observed in the global climate. The hydrological cycle and its available water resources are greatly influenced by climate change, and the consequences give rise to extreme natural disasters such as droughts. This study predicted the future drought in the South Han River basin using daily meteorological data generated from general circulation models (GCMs). With the recent development of the Shared Socioeconomic Pathway (SSP) scenario, Coupled Model Intercomparison Project (CMIP)6 GCMs are extensively used. This study used the Australian Community Climate and Earth System Simulator model (ACCESS-ESM1.5) for SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5. Two meteorological drought indices, namely, Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) were used to project meteorological drought status while a hydrological drought index, Standardized Streamflow Index (SDI), was used to identify the hydrological drought characteristics. The metrological data of GCMs were bias-corrected using quantile mapping method and the streamflow was obtained using Soil and Water Assessment Tool (SWAT). As a result, the drought occurrences in the South Han River basin were all different for all scenarios and those in SSP5-8.5 are the most serious. Therefore, it was concluded that the establishment of water resources planning and management for drought should consider the future climate projection.

Due to the the severity of droughts, national drought policy in South Korea has been established since 2017. Despite the important concept of the risk around the world, it is not included at the policy of South Korea. Since the drought risk assessment has developed into a conceptual model, the verification part of which remains insufficient. Therefore, this research conducts to develop the framework of drought risk on regional scale. In this proposed framework, risk consists of hazard, exposure, and capacity indicators. The hazard indicator calculated by a lack of precipitation for explaining the cause of droughts. The exposure indicator includes water demands which are the object by droughts. The capacity indicator is separate into the coping capacity for reducing and the adaptive capacity for addressing the damage. From three indicators, the drought risk index is calculated through data preprocessing and the weighting coefficient are computed with random values of 0.1 units. The Pearson correlation coefficient between the index and drought damage estimation is utilized to select the weighting coefficients for each region. The results from this study present drought risk index for every sub-basin in Korean Peninsula. Moreover using climate change scenarios, the future drought risk index are projected under RCP4.5 and RCP 8.5 in the 21st century.

To cope with droughts, estimating the appropriate drought frequency inflow has been an essential issue for the reservoir operation field. Parallel to the flood frequency analysis, drought frequency is estimated from the inverse function of the cumulative distribution function of design return periods by substituting the non-exceedance probability. Unlike floods, due to the long-lasting characteristics of drought, the autocorrelation term should be additionally considered. Therefore, K-water has developed two methods, using in practice; Cumulative Difference Method (CDM) and K-water Disaggregation Method (KDM). CDM is to subtract each frequency inflow estimated from the accumulated (e.g., 12 months) inflow from the target month, and the one month less accumulated (e.g., 11 months) inflow from the very next month of the target month. Also, KDM is to distribute the annual frequency inflow according to the sum of each month’s frequency flow. However, when using CDM, the frequency flow is estimated excessively large. Besides, a significant difference between the estimated frequency inflow using KDM and the observed inflow of the recent extreme drought was discovered. Therefore in this study, a linear regression-based model with autocorrelation term is used to distribute annual frequency inflow on a monthly scale. Then a total of four frequency analysis methods are compared and evaluated by applying them to the Chungju Dam basin. The results from this study would contribute to a more flexible response to drought by calculating a more reasonable amount of dam inflow considering the drought characteristics.

Many researchers used General Circulation Models (GCMs) to assess the future changes in precipitation. The Coupled Model Intercomparison Project (CMIP)6 represents a substantial expansion over CMIP5, in terms of the number of modeling groups participating, the number of future scenarios examined and the number of different experiments conducted. The Intergovernmental Panel on Climate Change (IPCC) Assessment Report (AR)5 featured four Representative Concentration Pathways (RCPs) that examined different possible future greenhouse gas emissions. The newer version of CMIP6 is called Socioeconomic Shared Pathway (SSP), each of SSPs result in similar 2100 radiative forcing levels as their predecessor in AR5. The uncertainty caused by changes in precipitation is the most important impact on water resource management. The uncertainty of GCM found in several studies focuses on conducting the assessment. As CMIP6 GCMs developed, it is essential to confirm the uncertainties of CMIP5 and CMIP6 from GCMs and future scenarios. This study compared the changes in precipitation by two pairs of CMIP5 GCMs and CMIP6 GCMs for the near (2025-2060) and far (2065–2100) futures relative to the historical precipitation (1970–2005) over South Korea. In the projection, the bias-corrected historical precipitations from CMIP5 and CMIP6 GCMs were compared with the observed precipitation at 22 observation stations and reliability ensemble averages to quantify the uncertainty of each scenario (RCP4.5&SSP2-4.5 and RCP8.5&SSP5-8.5). This study concluded that CMIP6 GCM improved over the CMIP5 GCM in the historical period. The changes in GCM ensemble precipitation were higher in the far future than in the near The uncertainty of precipitation was higher in RCPs scenarios of CMIP5 than in SSPs of CMIP6. This study contributes to improve the confidence of future projections of CMIP6 GCMs and understand the uncertainty of the SSP scenarios to RCPs.

This study analyses the multivariate dependence between socio-hydrological variables in the West African region. In this study, a copula function is derived and the maximum entropy of the copula function is determined. The mathematical framework upon which this study is based asserts that the total correlation between multiple variables is equal to the negative of the entropy of the copula function. Since different copula functions produce different correlations values, several copulas were tested to determine the most accurate fit using two goodness of fit tests i.e. Kolmogorov-Smirnov test and the Cramer von Mises test. The copulas used in this study were the Gumbel, Frank, Normal and Student’s t copulas. The aim of the study was to determine a more accurate correlation between social (i.e. population) and hydrological variables (i.e. runoff, temperature, and rainfall) to aid the establishment of flood and drought management. This has become necessitated by the fact that the population of Africa is the fastest growing in the world. The population of West Africa has increased five-fold since 1950 from 73 to 367 million people in 2015. In fact, Africa will account for nearly half of global population growth over the next two decades and West Africa alone for about 15%. West Africa’s population accounts for about 30% of Africa’s population .Thus water demand and dependence has exponentially grown particularly due to the lack of study and infrastructure to tackle this issue. From roughly 367 million people today it is expected to increase to almost 570 by 2035. It is expected that the study will show a significant correlation between the social and the hydrological variables because of the significant role humans play in the changes of hydrological variables and climate in general.

Most water resources are highly allocated in many regions of New Zealand. Demand for water has intensified over the past decades at a phenomenal rate. The critical period for managing water resources is in the summer months; stream flows and groundwater levels are at their lowest, and demand is highest for seasonal uses such as irrigation. Irrigation water is allocated with an emphasis on managing annual volumes, i.e. the total volume allowed to be extracted over an irrigation season (m³/year). Those annual volumes are often calculated using an arbitrary “daily irrigation system capacity”, which is considered to be appropriate to meet crop water demand. The system capacity is the minimum depth of water that an irrigation system must apply to be able to meet the plant water requirements without reducing yield. Due to soil water storage, the system capacity is less than the peak daily evapotranspiration requirement; however the key question is “how much less can it be”? What is often overlooked are the ramifications for how the system capacity is used in resource allocation. The total allocable resource from run-of-stream is determined to be an instantaneous flow rate (i.e. l/s). This total allocable resource must not be less than the cumulative sum of the system capacities for all water takes. Therefore, the system capacities determine the area that maybe irrigated from a resource.  We developed an approach to optimize the system capacity to ensure that the maximum possible area can be effectively irrigated so that the full economic benefits from the available resource can be captured. The results show that the optimized system capacities also reduce the annual water volumes, lower energy use and decrease drainage/potential nutrient losses. Accordingly, optimised system capacities enhance social, environmental and economic wellbeing and supports the creation of water resilient communities.

Gross primary production (GPP) is the largest carbon flux term from the atmosphere into terrestrial ecosystems and plays an important role in regulating the carbon balance of terrestrial ecosystems. GPP generation mainly depends on the photosynthesis of vegetation affected by solar radiation, precipitation, temperature, and so on. However, this effect varies greatly between different regions, especially in irrigated and non-irrigated areas. Irrigation activities not only provide sufficient water for crops in the irrigated area but also impose a cooling effect on the land surface, changing the hydrothermal conditions of plants, thus affecting the formation of GPP. GPP over the irrigated area is moreover a dominant source of crop yield, and Vast agricultural land is distributed in China. It is of great significance to study the influence of irrigation on the GPP over agricultural land in China to better understand the carbon balance in irrigated area and to ensure food security.

Hetao Irrigation District is not only one of the three outsize irrigation districts in China but also an important commodity grain base area. It is of great significance to predict and monitor agricultural drought accurately for risk management in the Hetao Irrigation District (HTID). The China Meteorological Administration Land Data Assimilation System (CLDAS) was used to evaluate the applicability of the Soil Moisture Active Passive (SMAP) dataset. The Soil Water Deficit Index (SWDI) and Percentage of Drought Week (PDW) were calculated to investigate the spatiotemporal evolution of agricultural drought in the HTID. The accuracy of SWDI was examined by comparing with the Atmospheric Water Deficit (AWD) that calculated based on the China Meteorological Assimilation Datasets for SWAT model (CMADS) dataset. The main results are as follows: (1) A good applicability of soil moisture produced by SMAP was demonstrated in the HTID. At the regional scale, temporal variation trends of soil moisture between SMAP and CLDAS was consistent and the mean correlation coefficient of the whole irrigation area was 0.65. At the grid scale, approximately 69% grids showed a high correlation (R > 0.5), which was mainly located in the southwestern and northeastern of the HTID. (2) Severe drought mainly occurred in three periods (from the end of April to the mid-May, from the end of July to the end of August and from the mid-September to mid-October, respectively) and concentrated in the southwest, middle and east of the HTID. The values of PDW during 2015–2016 increased slightly, implying a prolonged duration of drought events. (3) Except for topographical factors, the correlation between SWDI and AWD is very significant with half of the grids passing the significance test of 0.01, indicating that investigation of drought conditions in the HTID based on SWDI derived from SMAP is credible.

In this study, the Soil Water and Assessment Tool model and cellular automata model were used to construct the planting structure optimization model, which took the maximum crop water productivity (CWP), the maximum economic water productivity (EWP) and the maximum nutrient water productivity (NWP) as the objective function, respectively. The model was applied to the Heihe River Basin in the arid region of Northwest China to optimize the spatial distribution of six crops, namely corn, wheat, barley, canola, alfalfa and cotton.The results showed that under the premise of considering food security, the maximization of water productivity would lead to the reduction of corn planting area and the eastward shift of corn planting region.The maximization of EWP will also lead to a significant decrease in the proportion of wheat planting. But the proportion of barley and canola planted will increase significantly. After optimization, the planting proportion of cotton and alfalfa crops also increased, and the main planting region of cotton was changed to Ganzhou district. Compared with the original planting structure, the planting structure under the three optimization objectives can reduce the irrigation water demand of cultivated land and improve the water production of the basin, and the maximum CWP has the greatest water-saving intensity.

Realistic estimation of groundwater discharge during watershed module is essential. One of the watershed scale models that contain a tile drainage component is the Soil and Water Assessment Tool (SWAT) model. It is crucial to accurately simulate tile drains in hydrological models to predict hydrologic processes. The SWAT is a physically-based, semi-distributed, and process-oriented eco-hydrological model designed to predict discharge, sediment yield, nutrient, and pesticide loads for river basins over long periods. The tile drainage algorithms in SWAT have been refined over the years to improve the modeling of a tile-drained watershed. The latest releases of the SWAT model (SWAT2009 and SWAT2012) also incorporated the physically-based Hooghoudt (1940) and Kirkham (1957) tile drain equations as an alternative for tile flow simulation methods and a tool to design cost-effective and environment-friendly tile drain water management. When the water table is below the surface; ponded depressional depths are below a threshold, the Hooghoudt steady-state equation is used to compute drainage flux. To better understand its strengths and limitations, we conducted a rigorous review of published studies that have used the Hooghoudt and Kirkham tile drains equations into the SWAT to simulate tile flow and nitrate transported by tiles. The early SWAT model versions that are suitable for simulating tile flow are also reviewed to evaluate with the latest SWAT model. This review provides information on an evaluation of the Hooghoudt and Kirkham tile drains equation simulation by comparison to measured streamflow. This review pointed out that the Hooghoudt steady-state and Kirkham tile drain equations are a potential alternative to tile flow simulation methods and tile drainage design tools in SWAT.

Plastic film mulching is considered to be an effective field management measure, which can increase the temperature in the early stage of crop growth and reduce soil evaporation during the whole growth period, thus affecting crop yield. The large-scale use of plastic film inevitably increases the pressure on the environment. As a typical field-scale water-driven crop model, Aquacrop model can accurately simulate crop yield and crop evapotranspiration (ET) under different field management conditions. With the help of remote sensing inversion data, the model can overcome the heterogeneity of spatial distribution of meteorological, soil and crop species and the difficulty of data acquisition, and realize the regional application of the model. In this study, the Heihe River Basin in the arid region of Northwest China was taken as the study area. With the help of remote sensing data and ArcGIS software, the grid G-AquaCrop model was built to simulate the maize yield and evapotranspiration in the Heihe River Basin under the conditions of film mulching and no film mulching. Through the analysis of the changes of maize yield and evapotranspiration before and after film mulching, the suitable area for film mulching in the whole basin was given. The results showed that the simulated RMSE and NRMSE of the G-AquaCrop model for maize yield in the Heihe River Basin were 1.42 and 15.74 respectively. After film mulching, maize yield increased by 15.0% and ET decreased by 35% in Heihe River Basin. According to the change of production after film mulching, the maize yield can be improved to a certain extent in Suzhou, Jinta, Minle and Ganzhou. According to the change of ET after film mulching, ET can be reduced by at least 5% in Shandan, Minle, Ganzhou and Linze.

The dry-wet transition is of great importance for vegetation dynamics, however the response mechanism of vegetation variations is still unclear due to the complicated effects of climate change. As a critical ecologically fragile area located in the southeast Qinghai-Tibet Plateau, the Yarlung Zangbo River (YZR) basin, which was selected as the typical area in this study, is significantly sensitive and vulnerable to climate change. The standardized precipitation evapotranspiration index (SPEI) and the normalized difference vegetation index (NDVI) based on the GLDAS-NOAH products and the GIMMS-NDVI remote sensing data from 1982 to 2015 were employed to investigate the spatio-temporal characteristics of the dry-wet regime and the vegetation dynamic responses. The results showed that: (1) The spatio-temporal patterns of the precipitation and temperature simulated by the GLDAS-NOAH fitted well with those of the in-situ data. (2) During the period of 1982–2015, the whole YZR basin exhibited an overall wetting tendency. However, the spatio-temporal characteristics of the dry-wet regime exhibited a reversal phenomenon before and after 2000, which was jointly identified by the SPEI and runoff. That is, the YZR basin showed a wetting trend before 2000 and a drying trend after 2000; the arid areas in the basin showed a tendency of wetting whereas the humid areas exhibited a trend of drying. (3) The region where NDVI was positively correlated with SPEI accounted for approximately 70% of the basin area, demonstrating a similar spatio-temporal reversal phenomenon of the vegetation around 2000, indicating that the dry-wet condition is of great importance for the evolution of vegetation. (4) The SPEI showed a much more significant positive correlation with the soil water content which accounted for more than 95% of the basin area, implying that the soil water content was an important indicator to identify the dry-wet transition in the YZR basin.

Drought is one of the costliest natural hazards and the main factor of concern impacting crop growth in the arid Hexi Corridor in Northwest China. However, the inter-relationship between meteorological drought severity and crop yield is seldom studied across this region. In this study, two multi-scalar drought indices: the Standardized Precipitation Index (SPI) and the Standardized Precipitation-Evapotranspiration Index (SPEI) are employed to monitor the evolution of drought condition in the Hexi Corridor. We examined (a) the historical drought evolution of the Hexi Corridor since 1970s; (b) the possible future drought tendency under different RCP scenarios; and (c) the multi-scale correlation between crop yield and drought indices.