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.

Effects of Elevated Air Temperatures on Soil Thermal and Hydrologic Processes in the Active Layer in an Alpine Meadow Ecosystem of the Qinghai-Tibet Plateau

In this study,effects of elevated air temperatures on thermal and hydrologic process of the shallow soil in the active layer were investigated. Open-top chambers(OTCs)were utilized to increase air temperatures 1-2℃ in OTC-1 and 3-5℃ in OTC-2 in the alpine meadow ecosystem on the Qinghai- Tibetan Plateau.Results show that the annual air temperatures under OTC-1 and OTC-2 were 1.21℃ and 3.62℃ higher than the Control,respectively.The entirely-frozen period of shallow soil in the active layer was shortened and the fully thawed period was prolonged with temperature increase.The maximum penetration depth and duration of the negative isotherm during the entirely-frozen period decreased, and soil freezing was retarded in the local scope of the soil profile when temperature increased.Meanwhile, the positive isotherm during the fully-thawed period increased,and the soil thawing was accelerated.Soil moisture under different manipulations decreased with the temperature increase at the same depth. During the early freezing period and the early fully- thawed period,the maximum soil moisture under the Control manipulation was at 0.2 m deep,whereas under OTC-1 and OTC-2 manipulations,the maximum soil moisture were at 0.4-0.5 m deep. These results indicate that elevated temperatures led to a decrease of the moisture in the surface soil.The coupled relationship between soil temperature and moisture was significantly affected by the temperature increase.During the freezing and thawing processes, the soil temperature and moisture under different manipulations fit the regression model given by the equationθV=a/{1+exp[b(TS+c)]}+d.

Intermediately Complex Models for the Hydrological Interactions in the Atmosphere-Vegetation-Soil System

This paper investigates the hydrological interactions in the atmosphere-evegetation-soil system by using the bucket model and several new simplified intermediately complex models. The results of mathematical analysis and numerical simulations show that these models, despite their simplicity, can very clearly reveal the essential features of the rather complex hydrological system of atmosphere-ecosystem-soil. For given atmospheric variables, these models clearly demonstrate multiple timescales, the ＂red shift＂ of response spectra, multi-equilibria and limit cycles, bifurcation, abrupt change, self-organization, recovery, ＂desertification＂, and chaos. Most of these agree with observations. Especially, the weakening of ＂shading effect＂ of living canopy and the wilted biomass might be a major mechanism leading to the desertification in a relatively short period due to overgrazing, and the desertification in a relatively long period or in climate of change might be due to both Charney＇s mechanism and the shading effect. These ideas could be validated with further numerical simulations. In the paper, some methods for improving the estimation of timescales in the soil water evolution responding to the forcing are also proposed.

Hydrological Services by Mountain Ecosystems in Qilian Mountain of China: A Review

Hydrological service is a hot issue in the current researches of ecosystem service, particularly in the upper reaches of mountain rivers in dry land areas, where the Qilian Mountain is a representative one. The Qilian Mountain, where forest, shrubland and grassland consist of its main ecosystems, can provide fresh water and many other ecosystem services, through a series of eco-hydrological process such as precipitation interception, soil water storage, and fresh water provision. Thus, monitoring water regulation and assessing the hydrological service of the Qilian Mountain are meaningful and helpful for the healthy development of the lower reaches of arid and semi-arid areas. In recent 10 years, hydrological services have been widely researched in terms of scale and landscape pattern, including water conservation, hydrological responses to afforestation and their ecological effects. This study, after analyzing lots of current models and applications of geographical information system（GIS） in hydrological services, gave a scientific and reasonable evaluation of mountain ecosystem in eco-hydrological services, by employing the combination of international forefronts and contentious issues into the Qilian Mountain. Assessments of hydrological services at regional or larger scales are limited compared with studies within watershed scale in the Qilian Mountain. In our evaluation results of forest ecosystems, it is concluded that long-term observation and dynamic monitoring of different types of ecosystem are indispensable, and the hydrological services and the potential variation in water supplement on regional and large scales should be central issues in the future research.v

Hydrological simulation approaches for BMPs and LID practices in highly urbanized area and development of hydrological performance indicator system

Urbanization causes hydrological change and increases stormwater runoff volumes, leading to flooding, erosion, and the degradation of instream ecosystem health. Best management practices （BMPs）, like detention ponds and infiltration trenches, have been widely used to control flood runoff events for the past decade. However, low impact development （LID） options have been proposed as an alternative approach to better mimic the natural flow regime by using decentralized designs to control stormwater runoff at the source, rather than at a centralized location in the watershed. For highly urbanized areas, LID stormwater management practices such as bioretention cells and porous pavements can be used to retrofit existing infrastructure and reduce runoff volumes and peak flows. This paper describes a modeling approach to incorporate these LID practices and the two BMPs of detention ponds and infiltration trenches in an existing hydrological model to estimate the impacts of BMPs and LID practices on the surface runoff. The modeling approach has been used in a parking lot located in Lenexa, Kansas, USA, to predict hydrological performance of BMPs and LID practices. A performance indicator system including the flow duration curve, peak flow frequency exceedance curve, and runoff coefficient have been developed in an attempt to represent impacts of BMPs and LID practices on the entire spectrum of the runoff regime. Results demonstrate that use of these BMPs and LID practices leads to significant stormwater control for small rainfall events and less control for flood events.

Complementary system-theoretic modelling approach for enhancing hydrological forecasting

Hydrologic models generally represent the most dominant processes since they are mere simplifications of physical reality and thus are subject to many significant uncertainties. As such, a coupling strategy is proposed. To this end, the coupling of the artificial neural network （ANN） with the Xin＇anjiang conceptual model with a view to enhance the quality of its flow forecast is presented. The approach uses the latest observations and residuals in runoff/discharge forecasts from the Xin＇anjiang model. The two complementary models （Xin＇anjiang ＆ ANN） are used in such a way that residuals of the Xin＇anjiang model are forecasted by a neural network model so that flow forecasts can be improved as new observations come in. For the complementary neural network, the input data were presented in a patterned format to conform to the calibration regime of the Xin＇anjiang conceptual model, using differing variants of the neural network scheme. The results show that there is a substantial improvement in the accuracy of the forecasts when the complementary model was operated on top of the Xin＇anjiang conceptual model as compared with the results of the Xin＇anjiang model alone.

Seasonal evolution of the englacial and subglacial drainage systems of a temperate glacier revealed by hydrological analysis

Englacial and subglacial drainage systems of temperate glaciers have a strong influence on glacier dynamics, glacier-induced floods, glacier-weathering processes, and runoff from glacierized drainage basins. Proglacial discharge is partly controlled by the geometry of the glacial drainage network and by the process of producing meltwater. The glacial-drainage system of some alpine glaciers has been characterized using a model based on proglacial discharge analysis. In this paper, we apply cross-correlation analysis to hourly hydro-climatic data collected from China＇s Hailuogou Glacier, a typical temperate glacier in Mt. Gongga, to study the seasonal status changes of the englacial and subglacial drainage systems by discharge-temperature （Q-T） time lag analy-sis. During early ablation season （April-May） of 2003, 2004 and 2005, the change of englacial and subglacial drainage system usually leads several outburst flood events, which are also substantiated by observing the leakage of supraglacial pond and cre-vasses pond water during field works in April, 2008. At the end of ablation season （October-December）, the glacial-drainage net-works become less hydro-efficient. Those events are evidenced by hourly hydro-process near the terminus of Hailuogou Glacier, and the analysis of Q-T time lags also can be a good indicator of those changes. However, more detailed observations or experi-ments, e.g. dye-tracing experiment and recording borehole water level variations, are necessary to describe the evolutionary status and processes of englacial and subglacial drainage systems evolution during ablation season.

Development and Field Evaluation of a Low-Cost Wireless Sensor Network System for Hydrological Monitoring of a Small Agricultural Watershed

Hydrological monitoring and real-time access to data are valuable for hydrological research and water resources management. In the recent decades, rapid developments in digital technology, micro-electromechanical systems, low power micro-sensing technologies and improved industrial manufacturing processes have resulted in retrieving real-time data through Wireless Sensor Networks (WSNs) systems. In this study, a remotely operated low-cost and robust WSN system was developed to monitor and collect real-time hydrologic data from a small agricultural watershed in harsh weather conditions and upland rolling topography of Southern Ontario, Canada. The WSN system was assembled using off-the-shelf hardware components, and an open source operating system was used to minimize the cost. The developed system was rigorously tested in the laboratory and the field and found to be accurate and reliable for monitoring climatic and hydrologic parameters. The soil moisture and runoff data for 7 springs, 19 summer, and 19 fall season rainfall events over the period of more than two years were successfully collected in a small experimental agricultural watershed situated near Elora, Ontario, Canada. The developed WSN system can be readily extended for the purpose of most hydrological monitoring applications, although it was explicitly tailored for a project focused on mapping the Variable Source Areas (VSAs) in a small agricultural watershed.

Development of Hydrological Model in the "Forestwater" System for Example in the Juniper Forests of Southern Kyrgyzstan

The article considers the issues of methodology and development of optimal model adapted for the ＂forest-water＂ system, for forecasting the rate of stream flow and for preventing mudflows, flood flows and soil flows in juniper forests of Kyrgyzstan, and also shows the dynamics of ecosystems＇ progress.

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.

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.

Comparative analysis of recent hydrological models and an attempt to generate new combined products for monitoring terrestrial water storage change

Hydrological models are crucial for characterizing large-scale water quantity variations and correcting GNSS reference station vertical displacements.We evaluated the robustness of multiple models,such as the Global Land Data Assimilation System (GLDAS),the Famine Early Warning System Network Land Data Assimilation System (FLDAS),the National Centers for Environmental Prediction (NCEP),and the WaterGAP Global Hydrology Model (WGHM).Inter-model and outer comparisons with Global Positioning System (GPS) coordinate time series,satellite gravity field Mascon solutions,and Global Precipitation Climatology Centre (GPCC) guide our assessment.Results confirm WGHM's 26% greater effectiveness in correcting nonlinear variations in GPS height time series compared to NCEP.In the Amazon River Basin,a 5-month lag between FLDAS,GLDAS,and satellite gravity results is observed.In eastern Asia and Australia,NCEP's Terrestrial Water Storage Changes (TWSC)-derived surface displacements correlate differently with precipitation compared to other models.Three combined hydrological models (H-VCE,H-EWM,and H-CVM) utilizing Variance Component Estimation (VCE),Entropy Weight Method (EWM),and Coefficient of Variation Method (CVM) are formulated.Correcting nonlinear variations with combined models enhances global GPS height scatter by 15%-17%.Correlation with precipitation increases by 25%-30%,and with satellite gravity,rises from 0.2 to 0.8 at maximum.The combined model eliminates time lag in the Amazon Basin TWSC analysis,exhibiting a four times higher signal-to-noise ratio than single models.H-VCE demonstrates the highest accuracy.In summary,the combined hydrological model minimizes discrepancies among individual models,significantly improving accuracy for monitoring large-scale TWSC.

Understanding and simulating of three-dimensional subsurface hydrological partitioning in an alpine mountainous area, China

Critical zone(CZ)plays a vital role in sustaining biodiversity and humanity.However,flux quantification within CZ,particularly in terms of subsurface hydrological partitioning,remains a significant challenge.This study focused on quantifying subsurface hydrological partitioning,specifically in an alpine mountainous area,and highlighted the important role of lateral flow during this process.Precipitation was usually classified as two parts into the soil:increased soil water content(SWC)and lateral flow out of the soil pit.It was found that 65%–88%precipitation contributed to lateral flow.The second common partitioning class showed an increase in SWC caused by both precipitation and lateral flow into the soil pit.In this case,lateral flow contributed to the SWC increase ranging from 43%to 74%,which was notably larger than the SWC increase caused by precipitation.On alpine meadows,lateral flow from the soil pit occurred when the shallow soil was wetter than the field capacity.This result highlighted the need for three-dimensional simulation between soil layers in Earth system models(ESMs).During evapotranspiration process,significant differences were observed in the classification of subsurface hydrological partitioning among different vegetation types.Due to tangled and aggregated fine roots in the surface soil on alpine meadows,the majority of subsurface responses involved lateral flow,which provided 98%–100%of evapotranspiration(ET).On grassland,there was a high probability(0.87),which ET was entirely provided by lateral flow.The main reason for underestimating transpiration through soil water dynamics in previous research was the neglect of lateral root water uptake.Furthermore,there was a probability of 0.12,which ET was entirely provided by SWC decrease on grassland.In this case,there was a high probability(0.98)that soil water responses only occurred at layer 2(10–20 cm),because grass roots mainly distributed in this soil layer,and grasses often used their deep roots for water uptake during ET.To improve the estimation of soil water dynamics and ET,we established a random forest(RF)model to simulate lateral flow and then corrected the community land model(CLM).RF model demonstrated good performance and led to significant improvements in CLM simulation.These findings enhance our understanding of subsurface hydrological partitioning and emphasize the importance of considering lateral flow in ESMs and hydrological research.

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.

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.

TIME SERIES NEURAL NETWORK MODEL FOR HYDROLOGIC FORECASTING

Time series analysis plays an important role in hydrologic forecasting,while the key to this analysis is to establish a proper model.This paper presents a time series neural network model with back propagation procedure for hydrologic forecasting.Free from the disadvantages of previous models,the model can be parallel to operate information flexibly and rapidly.It excels in the ability of nonlinear mapping and can learn and adjust by itself,which gives the model a possibility to describe the complex nonlinear hydrologic process.By using directly a training process based on a set of previous data, the model can forecast the time series of stream flow.Moreover,two practical examples were used to test the performance of the time series neural network model.Results confirm that the model is efficient and feasible.

Influence of Rainfall Run-off in Hydrologic Process on Non-Point Pollution

[Objective] This study aimed to study on influence of rainfall runoff on non-point pollution and to reduce the pollution through control of the contamination produced from rainfall runoff. [Method] In order to explore effective methods to decrease non-point pollution, we conducted analysis on hydrological process of rainfall runoff, interaction mechanism between the process and non-point pollutants, the influence on non-point pollution and hydrological model application in the research. [Result] It was proved that rainfall runoff was the main factor of non-point pollution. Control from source strengthened clearing and controlling of non-point pollutants on the ground. Growing plants in slope effectively reduced the scour and erosion of rainfall runoff on soil. The study became simple thanks for the hydrological process. [Conclusion] The research indicated that non-point pollution would be effectively reduced through control of rainfall runoff.

Simulation Study on the Alkalized-salinized Grassland Ecosystem in the Songnen Plain

Using Object-oriented design and a new programming language JAVA, a physically-based model was built to simulate the hydrological, alkalization/de-alkalization and salinization/desalinization processes in soil. Furthermore, a process-based model was built to evaluate the dynamics of four herbaceous ecosystems (including dynamics of above-ground biomass, below-ground biomass, and litter biomass), each dominated by Aneurolepidium chinense (Trin.) Kitag., Chloris virgata Sw., Puccinellia tenuiflora (Turcz.) Scribn. et Merr. and Suaeda glauca Bunge. This model is a daily-time step model, suitable for simulating hydrological, alkalization/de-alkalization and salinization/desalinization processes of heterogeneous soil, and growth dynamics of different grassland communities. With climatic data and experimental data of Changling Experimental Site in Jilin Province, the soil moisture content (in 1991, 1996, 1997 and 1998), soil salt concentration, exchangeable cation percentage and pH in soil and growth dynamics of these four sorts of grassland communities (in 1991) were simulated and the results were verified to be in accord with observed data.

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.