Analysing the Potential Impact of Climate Change on the Hydrological Regime of the Upper Benue River Basin (North Cameroon)

In this study, we analyse the climate variability in the Upper Benue basin and assess its potential impact on the hydrology regime under two different greenhouse gas emission scenarios. The hydrological regime of the basin is more vulnerable to climate variability, especially precipitation and temperature. Observed hydroclimatic data (1950-2015) was analysed using a statistical approach. The potential impact of future climate change on the hydrological regime is quantified using the GR2M model and two climate models: HadGEM2-ES and MIROC5 from CMIP5 under RCP 4.5 and RCP 8.5 greenhouse gas emission scenarios. The main result shows that precipitation varies significantly according to the geographical location and time in the Upper Benue basin. The trend analysis of climatic parameters shows a decrease in annual average precipitation across the study area at a rate of -0.568 mm/year which represents about 37 mm/year over the time 1950-2015 compared to the 1961-1990 reference period. An increase of 0.7°C in mean temperature and 14% of PET are also observed according to the same reference period. The two climate models predict a warming of the basin of about 2°C for both RCP 4.5 and 8.5 scenarios and an increase in precipitation between 1% and 10% between 2015 and 2100. Similarly, the average annual flow is projected to increase by about +2% to +10% in the future for both RCP 4.5 and 8.5 scenarios between 2015 and 2100. Therefore, it is primordial to develop adaptation and mitigation measures to manage efficiently the availability of water resources.

Integrated Hydrological Modeling of the Godavari River Basin in Maharashtra Using the SWAT Model: Streamflow Simulation and Analysis

Hydrological modeling plays a crucial role in efficiently managing water resources and understanding the hydrologic behavior of watersheds. This study aims to simulate daily streamflow in the Godavari River Basin in Maharashtra using the Soil and Water Assessment Tool (SWAT). SWAT is a process-based hydrological model used to predict water balance components, sediment levels, and nutrient contamination. In this research, we used integrated remote sensing and GIS data, including Digital Elevation Models (DEM), land use and land cover (LULC) maps, soil maps, and observed precipitation and temperature data, as input for developing the SWAT model to assess surface runoff in this large river basin. The Godavari River Basin under study was divided into 25 sub-basins, comprising 151 hydrological response units categorized by unique land cover, soil, and slope characteristics using the SWAT model. The model was calibrated and validated against observed runoff data for two time periods: 2003-2006 and 2007-2010 respectively. Model performance was assessed using the Nash-Sutcliffe efficiency (NSE) and the coefficient of determination (R2). The results show the effectiveness of the SWAT2012 model, with R2 value of 0.84 during calibration and 0.86 during validation. NSE values also ranged from 0.84 during calibration to 0.85 during validation. These findings enhance our understanding of surface runoff dynamics in the Godavari River Basin under study and highlight the suit-ability of the SWAT model for this region.

Initiatives to clarify mechanisms of hydrological evolution in human-influenced Yellow River Basin

Significant changes in water cycle elements/processes have created serious challenges to regional sustainability and high-quality development in the Yellow River Basin in China.It is necessary to investigate the impacts of climate change and human activities on hydrological evolution and disaster risk from a holistic perspective of the basin.This study developed initiatives to clarify the mechanisms of hydrological evolution in the human-influenced Yellow River Basin.The proposed research method includes:(1)a tool to simulate multiple factors and a multi-scale water cycle using a grid-based spatiotemporal coupling approach,and(2)a new algorithm to separate the responses of the water cycle to climate change and human impacts,and de-couple the eco-environmental effects using artificial intelligence techniques.With this research framework,key breakthroughs are expected to be made in the understanding of the impacts of land cover change on the water cycle and blue/green water redirection.The outcomes of this research project are expected to provide theoretical support for ecological protection and water governance in the basin.

Effect of sand-fixing vegetation on the hydrological regulation function of sand dunes and its practical significance

Soil water content is a key controlling factor for vegetation restoration in sand dunes.The deep seepage and lateral migration of water in dunes affect the recharge process of deep soil water and groundwater in sand dune ecosystems.To determine the influence of vegetation on the hydrological regulation function of sand dunes,we examined the deep seepage and lateral migration of dune water with different vegetation coverages during the growing season in the Horqin Sandy Land,China.The results showed that the deep seepage and lateral migration of water decreased with the increase in vegetation coverage on the dunes.The accumulated deep seepage water of mobile dunes(vegetation coverage<5%)and dunes with vegetation coverage of 18.03%,27.12%,and 50.65%accounted for 56.53%,51.82%,18.98%,and 0.26%,respectively,of the rainfall in the same period.The accumulated lateral migration of water in these dunes accounted for 12.39%,6.33%,2.23%,and 7.61%of the rainfall in the same period.The direction and position of the dune slope affected the soil water deep seepage and lateral migration process.The amounts of deep seepage and lateral migration of water on the windward slope were lower than those on the leeward slope.The amounts of deep seepage and lateral migration of water showed a decreasing trend from the bottom to the middle and to the top of the dune slope.According to the above results,during the construction of sand-control projects in sandy regions,we suggest that a certain area of mobile dunes(>13.75%)should be retained as a water resource reservoir to maintain the water balance of artificial fixed dune ecosystems.These findings provide reliable evidence for the accurate assessment of water resources within the sand dune ecosystem and guide the construction of desertification control projects.

Elucidating Dominant Factors Affecting Land Surface Hydrological Simulations of the Community Land Model over China

In order to compare the impacts of the choice of land surface model(LSM)parameterization schemes,meteorological forcing,and land surface parameters on land surface hydrological simulations,and explore to what extent the quality can be improved,a series of experiments with different LSMs,forcing datasets,and parameter datasets concerning soil texture and land cover were conducted.Six simulations are run for the Chinese mainland on 0.1°×0.1°grids from 1979 to 2008,and the simulated monthly soil moisture(SM),evapotranspiration(ET),and snow depth(SD)are then compared and assessed against observations.The results show that the meteorological forcing is the most important factor governing output.Beyond that,SM seems to be also very sensitive to soil texture information;SD is also very sensitive to snow parameterization scheme in the LSM.The Community Land Model version 4.5(CLM4.5),driven by newly developed observation-based regional meteorological forcing and land surface parameters(referred to as CMFD_CLM4.5_NEW),significantly improved the simulations in most cases over the Chinese mainland and its eight basins.It increased the correlation coefficient values from 0.46 to 0.54 for the SM modeling and from 0.54 to 0.67 for the SD simulations,and it decreased the root-mean-square error(RMSE)from 0.093 to 0.085 for the SM simulation and reduced the normalized RMSE from 1.277 to 0.201 for the SD simulations.This study indicates that the offline LSM simulation using a refined LSM driven by newly developed observation-based regional meteorological forcing and land surface parameters can better model reginal land surface hydrological processes.

Hydrological Processes in a Small Research Watershed under Forest Coverage in the Coast of Chiapas, Mexico

In the hydrological watershed, some natural processes take place in which the interaction of water, soil, climate and vegetation favors the capture of water. The present study aimed to evaluate preliminary information regarding the hydrological response and the water balance in a small research watershed with tropical forest cover (15°01'44''N and 92°13'55''W, 471 m, 2.3 has). Events of precipitation, direct runoff, infiltration rate and baseflow were performed. The amount, duration and intensity of rainfall events were recorded with the use of a pluviograph. Surface runoff was quantified with an established gauging station, an H-type gauging device and a horizontal mechanical gauging limnograph. Runoff base flow was measured at the gauging station using the volume-time method. Infiltration was measured using a triple ring infiltrometer, taking two measurements in the upper part and two in the lower part of the microbasin. Evapotranspiration was measured with the amount of rainfall entering and runoff leaving the watershed. In the study period, annual rainfall of 4417.6 mm distributed over 181 events were recorded;about 70% of the storms showed lower intensities at 20 mm·h-1. The total runoff was 345.8 mm caused by half of the rainfall events, which represents 7.8% of the total rain;77% of runoff events showed lower sheets of 5 mm and an average specific rate of 20.7 L·s-1·ha-1 with a maximum of 113.6 L·s-1·ha-1. Three runoff events were greater than 20.1 mm and caused the 22.5% of the total runoff depth in the study period showing the equilibrium conditions in the hydrological response of the forest. Water outputs like baseflow was 669.5 mm. In this way, 90% of the rainfall is infiltrated every year in the micro-watershed, which shows the importance of the plant cover in the hydrological regulation and the groundwater recharge.

Intensity Estimation of Extreme Meteorological and Hydrological Factors Induced by Tropical Cyclones Affecting Hong Kong

Hong Kong is often affected by tropical cyclones.The Hong Kong observatory issues warning signals based on the impact of tropical cyclones on the region.The joint frequency analysis of tropical cyclones in Hong Kong can provide a scientific basis for disaster reduction and prevention and post-disaster reconstruction of tropical cyclones.First,the maximum hourly mean wind speed(W),warning signal duration(D),maximum sea level(L),and total rainfall(R)of each tropical cyclone that affected Hong Kong from 1985 to 2019 are selected and fitted using the Gumbel,Weibull,Pearson type 3,and lognormal distributions.Then,bivariate copula functions,such as the Clayton,Frank,Gumbel-Hougaard,and Gaussian copulas,are applied to construct the joint probability models of W,D,L,and R,respectively.The joint return periods of W and D and those of L and R are defined as the meteorological and hydrological intensities of tropical cyclones,respectively.The results show that the joint return periods are good indicators of the comprehensive effect of the meteorological and hydrological intensities of tropical cyclones.No necessary correlation between meteorological and hydrological intensities of tropical cyclones exists.The meteorological and hydrological intensities of tropical cyclones show an upward trend in recent years.

Dimensioning Urban Drainage Systems in Housing Subdivisions in the Amazon Using Different Hydrological Models

Hydrological studies for sizing urban drainage systems in the Amazon have often been neglected and little investigated for rainwater projects. This research evaluated alternative hydrological models used in sizing urban drainage network projects in subdivisions with subsidized houses in the Amazonian region in Brazil. Statistical tests of these models were performed for both original and alternative scenarios. The methodological steps we conducted as follows: 1) evaluate the dimensioning of infrastructure project networks, considering two case studies contemplated by the Calha Norte Program (CNP) in the state of Amapá;2) test the statistical significance of the dimensioning of network diameters (α < 0.05), considering a) benchmark project (MD or M1) approved by the Ministry of Defense;b) determination of concentration time (Ct) and rainfall intensity-duration-frequency (IDF) relationships, as well as estimating diameters using alternative models. The results indicated a significant influence on the diameters of the projected rainfall networks (p < 0.05), suggesting that alternative models predicted more unfavorable flow peaks than the original model. We conclude that the benchmarking model underestimated the diameter of the project compared to alternative models, which means the optimized Ct parameter significantly impacts dimensioning estimates in rainwater projects in these Amazonian municipalities. This suggests that underestimated parameters in MD may cause inefficiency in the stormwater system projects in future similar scenarios.

Anthropogenic activity,hydrological regime,and light level jointly influence temporal patterns in biosonar activity of the Yangtze finless porpoise at the junction of the Yangtze River and Poyang Lake,China

Under increasing anthropogenic pressure,species with a previously contiguous distribution across their ranges have been reduced to small fragmented populations.The critically endangered Yangtze finless porpoise(Neophocaena asiaeorientalis asiaeorientalis),once commonly observed in the Yangtze River-Poyang Lake junction,is now rarely seen in the river-lake corridor.In this study,static passive acoustic monitoring techniques were used to detect the biosonar activities of the Yangtze finless porpoise in this unique corridor.Generalized linear models were used to examine the correlation between these activities and anthropogenic impacts from the COVID-19 pandemic lockdown and boat navigation,as well as environmental variables,including hydrological conditions and light levels.Over approximately three consecutive years of monitoring(2020–2022),porpoise biosonar was detected during 93%of logged days,indicating the key role of the corridor for finless porpoise conservation.In addition,porpoise clicks were recorded in 3.80%of minutes,while feeding correlated buzzes were detected in 1.23%of minutes,suggesting the potential existence of localized,small-scale migration.Furthermore,both anthropogenic and environmental variables were significantly correlated with the diel,lunar,monthly,seasonal,and annual variations in porpoise biosonar activities.During the pandemic lockdown period,porpoise sonar detection showed a significant increase.Furthermore,a significant negative correlation was identified between the detection of porpoise click trains and buzzes and boat traffic intensity.In addition to water level and flux,daylight and moonlight exhibited significant correlations with porpoise biosonar activities,with markedly higher detections at night and quarter moon periods.Ensuring the spatiotemporal reduction of anthropogenic activities,implementing vessel speed restrictions(e.g.,during porpoise migration and feeding),and maintaining local natural hydrological regimes are critical factors for sustaining porpoise population viability.

Artificial Intelligence Technique in Hydrological Forecasts Supporting for Water Resources Management of a Large River Basin in Vietnam

Hydrological forecasting plays an important role in water resource management, supporting socio-economic development and managing water-related risks in river basins. There are many flow forecasting techniques that have been developed several centuries ago, ranging from physical models, physics-based models, conceptual models, and data-driven models. Recently, Artificial Intelligence (AI) has become an advanced technique applied as an effective data-driven model in hydrological forecasting. The main advantage of these models is that they give results with compatible accuracy, and require short computation time, thus increasing forecasting time and reducing human and financial effort. This study evaluates the applicability of machine learning and deep learning in Hanoi water level forecasting where it is controlled for flood management and water supply in the Red River Delta, Vietnam. Accordingly, SANN (machine learning algorithm) and LSTM (deep learning algorithm) were tested and compared with a Physics-Based Model (PBM) for the Red River Delta. The results show that SANN and LSTM give high accuracy. The R-squared coefficient is greater than 0.8, the mean squared error (MSE) is less than 20 cm, the correlation coefficient of the forecast hydrology is greater than 0.9 and the level of assurance of the forecast plan ranges from 80% to 90% in both cases. In addition, the calculation time is much reduced compared to the requirement of PBM, which is its limitation in hydrological forecasting for large river basins such as the Red River in Vietnam. Therefore, SANN and LSTM are expected to help increase lead time, thereby supporting water resource management for sustainable development and management of water-related risks in the Red River Delta.

Recent advances in hydrology studies under changing permafrost on the Qinghai-Xizang Plateau

Due to the great influences of both climate warming and human activities,permafrost on the Qinghai-Xizang Plateau(QXP)has been undergoing considerable degradation.Continuous degradation of plateau permafrost dramatically modifies the regional water cycle and hydrological processes,affecting the hydrogeological conditions,and ground hydrothermal status in cold regions.Permafrost thawing impacts the ecological environment,engineering facilities,and carbon storage functions,releasing some major greenhouse gases and exacerbating climate change.Despite the utilization of advanced research methodologies to investigate the changing hydrological processes and the corresponding influencing factors in permafrost regions,there still exist knowledge gaps in multivariate data,quantitative analysis of permafrost degradation's impact on various water bodies,and systematic hydrological modeling on the QXP.This review summarizes the main research methods in permafrost hydrology and elaborates on the impacts of permafrost degradation on regional precipitation distribution patterns,changes in surface runoff,expansion of thermokarst lakes/ponds,and groundwater dynamics on the QXP.Then,we discuss the current inadequacies and future research priorities,including multiple methods,observation data,and spatial and temporal scales,to provide a reference for a comprehensive analysis of the hydrological and environmental effects of permafrost degradation on the QXP under a warming climate.

Hydrologic Response to Future Climate Change in the Dulong-Irra-waddy River Basin Based on Coupled Model Intercomparison Project 6

Within the context of the Belt and Road Initiative(BRI)and the China-Myanmar Economic Corridor(CMEC),the Dulong-Ir-rawaddy(Ayeyarwady)River,an international river among China,India and Myanmar,plays a significant role as both a valuable hydro-power resource and an essential ecological passageway.However,the water resources and security exhibit a high degree of vulnerabil-ity to climate change impacts.This research evaluates climate impacts on the hydrology of the Dulong-Irrawaddy River Basin(DIRB)by using a physical-based hydrologic model.We crafted future climate scenarios using the three latest global climate models(GCMs)from Coupled Model Intercomparison Project 6(CMIP6)under two shared socioeconomic pathways(SSP2-4.5 and SSP5-8.5)for the near(2025-2049),mid(2050-2074),and far future(2075-2099).The regional model using MIKE SHE based on historical hydrologic processes was developed to further project future streamflow,demonstrating reliable performance in streamflow simulations with a val-idation Nash-Sutcliffe Efficiency(NSE)of 0.72.Results showed that climate change projections showed increases in the annual precip-itation and potential evapotranspiration(PET),with precipitation increasing by 11.3%and 26.1%,and PET increasing by 3.2%and 4.9%,respectively,by the end of the century under SSP2-4.5 and SSP5-8.5.These changes are projected to result in increased annual streamflow at all stations,notably at the basin’s outlet(Pyay station)compared to the baseline period(with an increase of 16.1%and 37.0%at the end of the 21st century under SSP2-4.5 and SSP5-8.5,respectively).Seasonal analysis for Pyay station forecasts an in-crease in dry-season streamflow by 31.3%-48.9%and 22.5%-76.3%under SSP2-4.5 and SSP5-8.5,respectively,and an increase in wet-season streamflow by 5.8%-12.6%and 2.8%-33.3%,respectively.Moreover,the magnitude and frequency of flood events are pre-dicted to escalate,potentially impacting hydropower production and food security significantly.This research outlines the hydrological response to future climate change during the 21st century and offers a scientific basis for the water resource management strategies by decision-makers.

Hydrological Process Factors Analysis of Heihe River Mountain Basin Based on GIS

Hydrological process factors are a reflection of the physical mechanism of basin hydrology,which can provide important basis for the use and protection of water resources.Taking Heihe River Mountain Basin as the study area,the hydrological simulation was made based on SWAT-GIS integrated model platform.The calculation methods of hydrological process factors using SWAT model were described based on the simulation results of runoff from 1990 to 2000.Hydrological process factors in the study area were analyzed by using GIS technology.The spatial and temporal characteristics of precipitation,runoff,infiltration,evapotranspiration and snowmelt in the basin were calculated and analyzed.

Light-absorbing Particles in Snow and Ice: Measurement and Modeling of Climatic and Hydrological impact

Light absorbing particles（LAP, e.g., black carbon, brown carbon, and dust） influence water and energy budgets of the atmosphere and snowpack in multiple ways. In addition to their effects associated with atmospheric heating by absorption of solar radiation and interactions with clouds, LAP in snow on land and ice can reduce the surface reflectance（a.k.a., surface darkening）, which is likely to accelerate the snow aging process and further reduces snow albedo and increases the speed of snowpack melt. LAP in snow and ice（LAPSI） has been identified as one of major forcings affecting climate change, e.g.in the fourth and fifth assessment reports of IPCC. However, the uncertainty level in quantifying this effect remains very high. In this review paper, we document various technical methods of measuring LAPSI and review the progress made in measuring the LAPSI in Arctic, Tibetan Plateau and other mid-latitude regions. We also report the progress in modeling the mass concentrations, albedo reduction, radiative forcing, and climatic and hydrological impact of LAPSI at global and regional scales. Finally we identify some research needs for reducing the uncertainties in the impact of LAPSI on global and regional climate and the hydrological cycle.

Modelling Hydrological Consequences of Climate Change—Progress and Challenges

The simulation of hydrological consequences of climate change has received increasing attention from the hydrology and land-surface modelling communities. There have been many studies of climate-change effects on hydrology and water resources which usually consist of three steps： （1） use of general circulation models （GCMs） to provide future global climate scenarios under the effect of increasing greenhouse gases, （2） use of downscaling techniques （both nested regional climate models, RCMs, and statistical methods） for ＂downscaling＂ the GCM output to the scales compatible with hydrological models, and （3） use of hydrologic models to simulate the effects of climate change on hydrological regimes at various scales. Great progress has been achieved in all three steps during the past few years, however, large uncertainties still exist in every stage of such study. This paper first reviews the present achievements in this field and then discusses the challenges for future studies of the hydrological impacts of climate change.

Atmospheric hydrological budget with its effects over Tibetan Plateau

Based on 1961-2000 NCEP/NCAR monthly mean reanalysis datasets, vapor transfer and hydrological budget over the Tibetan Plateau are investigated. The Plateau is a vapor sink all the year round. In summer, vapor is convergent in lower levels (from surface to 500 hPa) and divergent in upper levels (from 400 to 300 hPa), with 450 hPa referred to as level of non-divergence. Two levels have different hydrologic budget signatures: the budget is negative at the upper levels from February to November, i.e., vapor transfers from the upper levels over the plateau; as to the lower, the negative (positive) budget occurs during the winter (summer) half year. Evidence also indicates that Tibetan Plateau is a 'vapor transition belt', vapor from the south and the west is transferred from lower to upper levels there in summer, which will affect surrounding regions, including eastern China, especially, the middle and lower reaches of the Yangtze. Vapor transfer exerts significant influence on precipitation in summertime months. Vapor transferred from the upper layers helps humidify eastern China, with coefficient -0.3 of the upper budget to the precipitation over the middle and lower reaches of the Yangtze (MLRY); also, vapor transferred from east side (27.5 o -32.5 o N) of the upper level has remarkable relationship with precipitation, the coefficient being 0.41. The convergence of the lower level vapor has great effects on the local precipitation over the plateau, with coefficient reaching 0.44, and the vapor passage affects the advance and retreat of the rainbelt. In general, atmospheric hydrologic budget and vapor transfer over the plateau have noticeable effects on precipitation of the target region as well as the ambient areas.

Response of snow hydrological processes to a changing climate during 1961 to 2016 in the headwater of Irtysh River Basin, Chinese Altai Mountains

With changing climatic conditions and snow cover regime, regional hydrological cycle for a snowy basin will change and further available surface water resources will be redistributed. Assessing snow meltwater effect on runoff is the key to water safety, under climate warming and fast social-economic developing status. In this study, stable isotopic technology was utilized to analyze the snow meltwater effect on regional hydrological processes, and to declare the response of snow hydrology to climate change and snow cover regime, together with longterm meteorological and hydrological observations, in the headwater of Irtysh River, Chinese Altai Mountains during 1961-2015. The average δ^(18) O values of rainfall, snowfall, meltwater, groundwater and river water for 2014–2015 hydrological year were-10.9‰,-22.3‰,-21.7‰,-15.7‰ and-16.0‰, respectively.The results from stable isotopes, snow melting observation and remote sensing indicated that the meltwater effect on hydrological processes in Kayiertesi River Basin mainly occurred during snowmelt supplying period from April to June. The contribution of meltwater to runoff reached 58.1% during this period, but rainfall, meltwater and groundwater supplied 49.1%, 36.9% and 14.0% of water resource to annual runoff, respectively. With rising air temperature and increasing snowfall in cold season, the snow water equivalent(SWE) had an increasing trend but the snow cover duration declined by about one month including 13-day delay of the first day and 17-day advancement of the end day during 1961–2016. Increase in SWE provided more available water resource. However, variations in snow cover timing had resulted in redistribution of surface water resource, represented by an increase of discharge percentage in April and May, and a decline in Juneand July. This trend of snow hydrology will render a deficit of water resource in June and July when the water resource demand is high for agricultural irrigation and industrial manufacture.

Simulations of a Hydrological Model as Coupled to a Regional Climate Model

Considering a detailed hydrologic model in the land surface scheme helps to improve the simulation of regional hydro-climatology. A hydrologic model, which includes spatial heterogeneities in precipitation and infiltration, is constructed and incorporated into the land surface scheme BATS. Via the coupled-model (i.e., a regional climate model) simulations, the following major conclusions are obtained: the simulation of surface hydrology is sensitive to the inclusion of heterogeneities in precipitation and infiltration; the runoff ratio is increased after considering the infiltration heterogeneity, a result which is more consistent with the observations of surface moisture balance over humid areas; the introduction of the parameterization of infiltration heterogeneity can have a greater influence on the regional hydro-climatology than the precipitation heterogeneity; and the consideration of the impermeable fraction for the region reveals some features that are closer to the trend of aridification over northern China.

Systematic Hydrological Evaluation of the Noah-MP Land Surface Model over China

We evaluate water budget components-namely,soil moisture,runoff,evapotranspiration,and terrestrial water storage (TWS)-simulated by the Noah land surface model with multi-parameterization options (Noah-MP) in China,a large geographic domain challenging for hydrological modeling due to poor observational data and a lack of one single parameterization that can fit for complex hydrological processes.By comparing the model simulations with multi-source reference data,we show that Noah-MP can generally reproduce the overall spatiotemporal patterns of runoff and evapotranspiration over six major river basins,with the annual correlation coefficients generally greater than 0.8 and the Nash-Sutcliffe model efficiency coefficient exceeding 0.5.Among the six basins evaluated,the best model performance is seen over the Huaihe River basin.The temporal trend of the modeled TWS anomalies agrees well with GRACE (Gravity Recovery and Climate Experiment) observations,capturing major flood and drought events in different basins.Experiments with 12 selected physical parameterization options show that the runoff parameterization has a stronger impact on the simulated soil moisture-runoff-evapotranspiration relationships than the soil moisture factor for stomatal resistance schemes,a result consistent with previous studies.Overall,Noah-MP driven by GLDAS forcing simulates the hydrological variables well,except for the Songliao basin in northeastern China,likely because this is a transitional region with extensive freeze-thaw activity,while representations of human activities may also help improve the model performance.

Application of Radar-Measured Rain Data in Hydrological Processes Modeling during the Intensified Observation Period of HUBEX

On the basis of Digital Elevation Model data, the raster flow vectors, watershed delineation, and spatial topological relationship are generated by the Martz and Garbrecht method for the upper area of Huangnizhuang station in the Shihe Catchment with 805 km2 of area, an intensified observation field for the HUBEX/GAME Project. Then, the Xin’anjiang Model is applied for runoff production in each grid element where rain data measured by radar at Fuyang station is utilized as the input of the hydrological model. The elements are connected by flow vectors to the outlet of the drainage catchment where runoff is routed by the Muskingum method from each grid element to the outlet according to the length between each grid and the outlet. The Nash-Sutcliffe model efficiency coefficient is 92.41% from 31 May to 3 August 1998, and 85.64%, 86.62%, 92.57%, and 83.91%, respectively for the 1st, 2nd, 3rd, and 4th flood events during the whole computational period. As compared with the case where rain-gauge data are used in simulating the hourly hydrograph at Huangnizhuang station in the Shihe Catchment, the index of model efficiency improvement is positive, ranging from 27.56% to 69.39%. This justifies the claim that radar-measured data are superior to rain-gauge data as inputs to hydrological modeling. As a result, the grid-based hydrological model provides a good platform for runoff computation when radar-measured rain data with highly spatiotemporal resolution are taken as the input of the hydrological model.