Simulated River Discharge Research Articles

Land Cover and Climate Change Impact on River Discharge: Case Study of Upper Citarum River Basin

The Upper Citarum River Basin is the main catchment area of the Saguling Dam, the most upstream of three cascade dams in the Citarum River Basin. During the last 30 years, rapid economic development has led to an increase of water extraction and land conversion from green area to developed area. Also, evidence of climate change can clearly be seen from the climatological records of a number of climatology stations in this basin over the last few decades. In this study, the effect of anthropogenic and climate change in the Upper Citarum River Basin river discharge was simulated using the Sacramento Catchment Model. Historical river discharge, rainfall, climatology, and land cover from 1995 to 2009 were used for model calibration and verification. The multi-model mean monthly rainfall and the temperature projection taken from Coupled Model Intercomparison Project 5 (CMIP5) for the RCP6 and RCP8.5 climate change scenarios were statistically downscaled and used as input for a simulation of future river discharge from 2030 to 2050. The result showed that the combination of anthropogenic and climate change may result in a significant decrease of low flow in the Upper Citarum River Basin. This study underlines the importance of land cover and climate change factors for future infrastructure planning and management in the Upper Citarum River Basin.

Implementing northern peatlands in a global land surface model: description and evaluation in the ORCHIDEE high-latitude version model (ORC-HL-PEAT)

Abstract. Widely present in boreal regions, peatlands contain large carbon stocks because of their hydrologic properties and high water content, which makes primary productivity exceed decomposition rates. We have enhanced the global land surface model ORCHIDEE by introducing a hydrological representation of northern peatlands. These peatlands are represented as a new plant functional type (PFT) in the model, with specific hydrological properties for peat soil. In this paper, we focus on the representation of the hydrology of northern peatlands and on the evaluation of the hydrological impact of this implementation. A prescribed map based on the inventory of Yu et al. (2010) defines peatlands as a fraction of a grid cell represented as a PFT comparable to C3 grasses, with adaptations to reproduce shallow roots and higher photosynthesis stress. The treatment of peatland hydrology differs from that of other vegetation types by the fact that runoff from other soil types is partially directed towards the peatlands (instead of directly to the river network). The evaluation of this implementation was carried out at different spatial and temporal scales, from site evaluation to larger scales such as the watershed scale and the scale of all northern latitudes. The simulated net ecosystem exchanges agree with observations from three FLUXNET sites. Water table positions were generally close to observations, with some exceptions in winter. Compared to other soils, the simulated peat soils have a reduced seasonal variability in water storage. The seasonal cycle of the simulated extent of inundated peatlands is compared to flooded area as estimated from satellite observations. The model is able to represent more than 89.5 % of the flooded areas located in peatland areas, where the modelled extent of inundated peatlands reaches 0.83×106 km2. However, the extent of peatlands in northern latitudes is too small to substantially impact the large-scale terrestrial water storage north of 45∘ N. Therefore, the inclusion of peatlands has a weak impact on the simulated river discharge rates in boreal regions.

Modeling and simulation of river discharge using artificial neural networks

The study developed multiple artificial neural network models with the aim of establishing the most suitable non-linear discharge perdition model of Ibu River. A 12-year daily discharge of River Ibu gauged near Sagamu was obtained from the Ogun-Oshun River Basin Development Authority (OORBDA), Abeokuta Nigeria to model and simulate daily discharge. The back-propagation method was used in developing the artificial neural network model. The study revealed that only three artificial neural network (ANN) models out of fifteen developed, have overall results that are satisfactory for prediction, out of these, the model with the least error was used for validation. The results obtained with ANNs based on two hidden layers for 1-day ahead are better than those obtained by models with single layers. It was concluded that the general performance of ANN models depends solely on the data used. While it was recommended that additional basin characteristics such as slope, geology, morphology and surface roughness features should be included to obtain more robust river discharge models. Keywords: Artificial Neural Network, Hydrologic record, Prediction

Modeling Simulation of River Discharge of Loktak Lake Catchment in Northeast India

AbstractWater resources management requires an integrated approach between sustainability and catchment management to provide an enhanced understanding of usage options and environmental impacts. D...

Hydrological assessment of atmospheric forcing uncertainty in the Euro-Mediterranean area using a land surface model

Abstract. Physically consistent descriptions of land surface hydrology are crucial for planning human activities that involve freshwater resources, especially in light of the expected climate change scenarios. We assess how atmospheric forcing data uncertainties affect land surface model (LSM) simulations by means of an extensive evaluation exercise using a number of state-of-the-art remote sensing and station-based datasets. For this purpose, we use the CO2-responsive ISBA-A-gs LSM coupled with the CNRM version of the Total Runoff Integrated Pathways (CTRIP) river routing model. We perform multi-forcing simulations over the Euro-Mediterranean area (25–75.5∘ N, 11.5∘ W–62.5∘ E, at 0.5∘ resolution) from 1979 to 2012. The model is forced using four atmospheric datasets. Three of them are based on the ERA-Interim reanalysis (ERA-I). The fourth dataset is independent from ERA-Interim: PGF, developed at Princeton University. The hydrological impacts of atmospheric forcing uncertainties are assessed by comparing simulated surface soil moisture (SSM), leaf area index (LAI) and river discharge against observation-based datasets: SSM from the European Space Agency's Water Cycle Multi-mission Observation Strategy and Climate Change Initiative projects (ESA-CCI), LAI of the Global Inventory Modeling and Mapping Studies (GIMMS), and Global Runoff Data Centre (GRDC) river discharge. The atmospheric forcing data are also compared to reference datasets. Precipitation is the most uncertain forcing variable across datasets, while the most consistent are air temperature and SW and LW radiation. At the monthly timescale, SSM and LAI simulations are relatively insensitive to forcing uncertainties. Some discrepancies with ESA-CCI appear to be forcing-independent and may be due to different assumptions underlying the LSM and the remote sensing retrieval algorithm. All simulations overestimate average summer and early-autumn LAI. Forcing uncertainty impacts on simulated river discharge are larger on mean values and standard deviations than on correlations with GRDC data. Anomaly correlation coefficients are not inferior to those computed from raw monthly discharge time series, indicating that the model reproduces inter-annual variability fairly well. However, simulated river discharge time series generally feature larger variability compared to measurements. They also tend to overestimate winter–spring high flows and underestimate summer–autumn low flows. Considering that several differences emerge between simulations and reference data, which may not be completely explained by forcing uncertainty, we suggest several research directions. These range from further investigating the discrepancies between LSMs and remote sensing retrievals to developing new model components to represent physical and anthropogenic processes.

A global hydrological simulation to specify the sources of water used by humans

Abstract. Humans abstract water from various sources to sustain their livelihood and society. Some global hydrological models (GHMs) include explicit schemes of human water abstraction, but the representation and performance of these schemes remain limited. We substantially enhanced the water abstraction schemes of the H08 GHM. This enabled us to estimate water abstraction from six major water sources, namely, river flow regulated by global reservoirs (i.e., reservoirs regulating the flow of the world's major rivers), aqueduct water transfer, local reservoirs, seawater desalination, renewable groundwater, and nonrenewable groundwater. In its standard setup, the model covers the whole globe at a spatial resolution of 0.5° × 0.5°, and the calculation interval is 1 day. All the interactions were simulated in a single computer program, and all water fluxes and storage were strictly traceable at any place and time during the simulation period. A global hydrological simulation was conducted to validate the performance of the model for the period of 1979–2013 (land use was fixed for the year 2000). The simulated water fluxes for water abstraction were validated against those reported in earlier publications and showed a reasonable agreement at the global and country level. The simulated monthly river discharge and terrestrial water storage (TWS) for six of the world's most significantly human-affected river basins were compared with gauge observations and the data derived from the Gravity Recovery and Climate Experiment (GRACE) satellite mission. It is found that the simulation including the newly added schemes outperformed the simulation without human activities. The simulated results indicated that, in 2000, of the 3628±75 km3 yr−1 global freshwater requirement, 2839±50 km3 yr−1 was taken from surface water and 789±30 km3 yr−1 from groundwater. Streamflow, aqueduct water transfer, local reservoirs, and seawater desalination accounted for 1786±23, 199±10, 106±5, and 1.8±0 km3 yr−1 of the surface water, respectively. The remaining 747±45 km3 yr−1 freshwater requirement was unmet, or surface water was not available when and where it was needed in our simulation. Renewable and nonrenewable groundwater accounted for 607±11 and 182±26 km3 yr−1 of the groundwater total, respectively. Each source differed in its renewability, economic costs for development, and environmental consequences of usage. The model is useful for performing global water resource assessments by considering the aspects of sustainability, economy, and environment.

Improving drought simulations within the Murray-Darling Basin by combined calibration/assimilation of GRACE data into the WaterGAP Global Hydrology Model

Simulating hydrological processes within the (semi-)arid region of the Murray-Darling Basin (MDB), Australia, is very challenging specially during droughts. In this study, we investigate whether integrating remotely sensed terrestrial water storage changes (TWSC) from the Gravity Recovery And Climate Experiment (GRACE) mission into a global water resources and use model enables a more realistic representation of the basin hydrology during droughts. For our study, the WaterGAP Global Hydrology Model (WGHM), which simulates the impact of human water abstractions on surface water and groundwater storage, has been chosen for simulating compartmental water storages and river discharge during the so-called ‘Millennium Drought’ (2001–2009). In particular, we test the ability of a parameter calibration and data assimilation (C/DA) approach to introduce long-term trends into WGHM, which are poorly represented due to errors in forcing, model structure and calibration. For the first time, the impact of the parameter equifinality problem on the C/DA results is evaluated. We also investigate the influence of selecting a specific GRACE data product and filtering method on the final C/DA results. Integrating GRACE data into WGHM does not only improve simulation of seasonality and trend of TWSC, but also it improves the simulation of individual water storage components. For example, after the C/DA, correlations between simulated groundwater storage changes and independent in-situ well data increase (up to 0.82) in three out of four sub-basins. Declining groundwater storage trends - found mainly in the south, i.e. Murray Basin, at in-situ wells - have been introduced while simulated soil water and surface water storage do not show trends, which is in agreement with existing literature. Although GRACE C/DA in MDB does not improve river discharge simulations, the correlation between river storage simulations and gauge-based river levels increases significantly from 0.15 to 0.52. By adapting the C/DA settings to the basin-specific characteristics and reducing the number of calibration parameters, their convergence is improved and their uncertainty is reduced. The time-variable parameter values resulting from C/DA allow WGHM to better react to the very wet Australian summer 2009/10. Using solutions from different GRACE data providers produces slightly different C/DA results. We conclude that a rigorous evaluation of GRACE errors is required to realistically account for the spread of the differences in the results.

Streamflow and Sediment Yield Prediction for Watershed Prioritization in the Upper Blue Nile River Basin, Ethiopia

Inappropriate use of land and poor ecosystem management have accelerated land degradation and reduced the storage capacity of reservoirs. To mitigate the effect of the increased sediment yield, it is important to identify erosion-prone areas in a 287 km2 catchment in Ethiopia. The objectives of this study were to: (1) assess the spatial variability of sediment yield; (2) quantify the amount of sediment delivered into the reservoir; and (3) prioritize sub-catchments for watershed management using the Soil and Water Assessment Tool (SWAT). The SWAT model was calibrated and validated using SUFI-2, GLUE, ParaSol, and PSO SWAT-CUP optimization algorithms. For most of the SWAT-CUP simulations, the observed and simulated river discharge were not significantly different at the 95% level of confidence (95PPU), and sources of uncertainties were captured by bracketing more than 70% of the observed data. This catchment prioritization study indicated that more than 85% of the sediment was sourced from lowland areas (slope range: 0–8%) and the variation in sediment yield was more sensitive to the land use and soil type prevailing in the area regardless of the terrain slope. Contrary to the perception of the upland as an important source of sediment, the lowland in fact was the most important source of sediment and should be the focus area for improved land management practice to reduce sediment delivery into storage reservoirs. The research also showed that lowland erosion-prone areas are typified by extensive agriculture, which causes significant modification of the landscape. Tillage practice changes the infiltration and runoff characteristics of the land surface and interaction of shallow groundwater table and saturation excess runoff, which in turn affects the delivery of water and sediment to the reservoir and catchment evapotranspiration.

Water resources management using the WRF-Hydro modelling system: Case-study of the Tono dam in West Africa

Water resources are a major source of economic development for most West African (WA) countries. There is, however inadequate information on these resources for the purposes of planning, decision-making and management. This paper explores the potential for using a state of the art hydrological model (WRF-Hydro) in a fully coupled (i.e. land surface hydrology-atmosphere) mode to assess these water resources, particularly the Tono basin in Ghana. The WRF-Hydro model is an enhanced version of the Weather Research and Forecasting model (WRF) which allows simulating river discharge. A 2-domain configuration is chosen: an outer domain at 25km horizontal resolution encompassing the West African Region and an inner domain at 5km horizontal resolution centered on the Tono basin. The infiltration partition parameter and Manning’s roughness parameter were calibrated to fit the WRF-Hydro simulated discharge with the observed data. The simulations were done from 1999 to 2003, using 1999 as a spin-up period. The results were compared with TRMM precipitation, CRU temperature and available observed hydrological data. The WRF-Hydro model captured the attributes of the “observed” streamflow estimate; with Nash-Sutcliff efficiency (NSE) of 0.78 and Pearson’s correlation of 0.89. Further validation of model results is based on using the output from the WRF-Hydro model as input into a water balance model to simulate the dam levels. WRF-Hydro has shown the potential for use in water resource planning (i.e. with respect to streamflow and dam level estimation). However, the model requires further improvement with respect to calibration of model parameters (e.g. baseflow and saturated hydraulic conductivity) considering the effect of the accumulation of model bias in dam level estimation.

Impact of vegetation dynamics on hydrological processes in a semi-arid basin by using a land surface-hydrology coupled model

Land surface models (LSMs) are widely used to understand the interactions between hydrological processes and vegetation dynamics, which is important for the attribution and prediction of regional hydrological variations. However, most LSMs have large uncertainties in their representations of eco-hydrological processes due to deficiencies in hydrological parameterizations. In this study, the Community Land Model version 4 (CLM4) LSM was modified with an advanced runoff generation and flow routing scheme, resulting in a new land surface-hydrology coupled model, CLM-GBHM. Both models were implemented in the Wudinghe River Basin (WRB), which is a semi-arid basin located in the middle reaches of the Yellow River, China. Compared with CLM, CLM-GBHM increased the Nash Sutcliffe efficiency for daily river discharge simulation (1965–1969) from −0.03 to 0.23 and reduced the relative bias in water table depth simulations (2010–2012) from 32.4% to 13.4%. The CLM-GBHM simulations with static, remotely sensed and model-predicted vegetation conditions showed that the vegetation in the WRB began to recover in the 2000s due to the Grain for Green Program but had not reached the same level of vegetation cover as regions in natural eco-hydrological equilibrium. Compared with a simulation using remotely sensed vegetation cover, the simulation with a dynamic vegetation model that considers only climate-induced change showed a 10.3% increase in evapotranspiration, a 47.8% decrease in runoff, and a 62.7% and 71.3% deceleration in changing trend of the outlet river discharge before and after the year 2000, respectively. This result suggests that both natural and anthropogenic factors should be incorporated in dynamic vegetation models to better simulate the eco-hydrological cycle.

Intercomparison of global river discharge simulations focusing on dam operation—multiple models analysis in two case-study river basins, Missouri–Mississippi and Green–Colorado

We performed an intercomparison of river discharge regulated by dams under four meteorological forcings among five global hydrological models for a historical period by simulation. This is the first global multimodel intercomparison study on dam-regulated river flow. Although the simulations were conducted globally, the Missouri–Mississippi and Green–Colorado Rivers were chosen as case-study sites in this study. The hydrological models incorporate generic schemes of dam operation, not specific to a certain dam. We examined river discharge on a longitudinal section of river channels to investigate the effects of dams on simulated discharge, especially at the seasonal time scale. We found that the magnitude of dam regulation differed considerably among the hydrological models. The difference was attributable not only to dam operation schemes but also to the magnitude of simulated river discharge flowing into dams. That is, although a similar algorithm of dam operation schemes was incorporated in different hydrological models, the magnitude of dam regulation substantially differed among the models. Intermodel discrepancies tended to decrease toward the lower reaches of these river basins, which means model dependence is less significant toward lower reaches. These case-study results imply that, intermodel comparisons of river discharge should be made at different locations along the river's course to critically examine the performance of hydrological models because the performance can vary with the locations.

Evaluation of the SWAT model performance for simulating river discharge in the Himalayan and tropical basins of Asia

Abstract This study evaluated the Soil and Water Assessment Tool (SWAT) model performance for 11 basins located in two contrasting climatic regions of Asia: the Himalayan and the Southeast Asian tropics. A large variation existed among the case study basins in relation to basin size (330–78,529 km2), topography (377–4,310 metres above sea level) and annual rainfall (1,273–2,500 mm). Performance of the model was evaluated using R2 and wR2 for a low discharge event; Nash–Sutcliffe efficiency (NSE), R2 and RMSE-observation standard deviation ratio (RSR) for high discharge events; and NSE, R2, PBIAS, RSR, NSErel and wR2 for the overall hydrographs. SWAT was found to be suitable for both climatic regions but yielded better performance in the Himalayan basins (NSE 0.72–0.81 at calibration) compared to the tropical basins (NSE 0.36–0.72 at calibration). Although most of the models underperformed in either low or high discharge events, a few of those remaining showed a balance between the extremes, proving that it is possible to achieve a balanced hydrograph with the SWAT model. The consistency of model performance across numerous Himalayan and tropical basins in the area confirmed the versatility and reliability of SWAT as a hydrological model and suitable tool for water resources planning and management.

The effect of satellite-derived surface soil moisture and leaf area index land data assimilation on streamflow simulations over France

Abstract. This study evaluates the impact of assimilating surface soil moisture (SSM) and leaf area index (LAI) observations into a land surface model using the SAFRAN–ISBA–MODCOU (SIM) hydrological suite. SIM consists of three stages: (1) an atmospheric reanalysis (SAFRAN) over France, which forces (2) the three-layer ISBA land surface model, which then provides drainage and runoff inputs to (3) the MODCOU hydro-geological model. The drainage and runoff outputs from ISBA are validated by comparing the simulated river discharge from MODCOU with over 500 river-gauge observations over France and with a subset of stations with low-anthropogenic influence, over several years. This study makes use of the A-gs version of ISBA that allows for physiological processes. The atmospheric forcing for the ISBA-A-gs model underestimates direct shortwave and long-wave radiation by approximately 5 % averaged over France. The ISBA-A-gs model also substantially underestimates the grassland LAI compared with satellite retrievals during winter dormancy. These differences result in an underestimation (overestimation) of evapotranspiration (drainage and runoff). The excess runoff flowing into the rivers and aquifers contributes to an overestimation of the SIM river discharge. Two experiments attempted to resolve these problems: (i) a correction of the minimum LAI model parameter for grasslands and (ii) a bias-correction of the model radiative forcing. Two data assimilation experiments were also performed, which are designed to correct random errors in the initial conditions: (iii) the assimilation of LAI observations and (iv) the assimilation of SSM and LAI observations. The data assimilation for (iii) and (iv) was done with a simplified extended Kalman filter (SEKF), which uses finite differences in the observation operator Jacobians to relate the observations to the model variables. Experiments (i) and (ii) improved the median SIM Nash scores by about 9 % and 18 % respectively. Experiment (iii) reduced the LAI phase errors in ISBA-A-gs but had little impact on the discharge Nash efficiency of SIM. In contrast, experiment (iv) resulted in spurious increases in drainage and runoff, which degraded the median discharge Nash efficiency by about 7 %. The poor performance of the SEKF originates from the observation operator Jacobians. These Jacobians are dampened when the soil is saturated and when the vegetation is dormant, which leads to positive biases in drainage and/or runoff and to insufficient corrections during winter, respectively. Possible ways to improve the model are discussed, including a new multi-layer diffusion model and a more realistic response of photosynthesis to temperature in mountainous regions. The data assimilation should be advanced by accounting for model and forcing uncertainties.

Impact of climate variability and streamflow alteration on groundwater contribution to the base flow of the Lower Zab River (Iran and Iraq)

Overall water resources evaluations including groundwater contributions to river flow are critical for assessing climate change and drought impacts on basin hydrological responses. By utilising precipitation, daily stream flow and simulated river discharge alteration data, this study introduces a simple but comprehensive methodology to better understand the potential impact of river regulation coupled with climate variability and drought on groundwater involvement. The Lower Zab River basin in northern Iraq has been selected as a representative case study to demonstrate the new methodology. Three of the most commonly used base flow separation methods were assessed: Eckhardt algorithm, flow duration curve and Chapman filtering algorithm. In addition, the indicators of hydrologic alteration method and the reconnaissance drought index have been applied. The results demonstrated that some of the underground water responds to precipitation events. A noticeable increase in groundwater contribution has been observed during the hydrological years between 1998–2001 and 2006–2008 as a result of a sharp decline in the average precipitation. However, the opposite has been observed during the hydrological year 1987, which impacted negatively on the basin water resources availability. The reservoir release through the dry periods causes the observed variations in base flow index (BFI) values between the pre- and post-river damming time periods. Considering the BFI long-term seasonal variation, index values started to rise in April and reached their maximum by the end of June. A steady decline has been recorded between August and September.

Climate change impact assessment on mountain snow hydrology by water and energy budget-based distributed hydrological model

A water and energy budget-based distributed hydrological model with improved snow physics (WEB-DHM-S) was applied to elucidate the impact of climate change on mountain snow hydrology in the Shubuto River basin, Hokkaido, Japan. The simulated spatial distribution of snow cover was evaluated using the Moderate Resolution Imaging Spectroradiometer (MODIS) 8-day maximum snow-cover extent (MOD10A2) product, which revealed the model’s capability for capturing the spatiotemporal variations in snow cover within the study area. Four Atmosphere Ocean General Circulation Models (AOGCMs) were selected and the SRESA1B emission scenario of the Intergovernmental Panel on Climate Change was used to describe climate predictions in the basin. All AOGCMs predict a future decrease in snowmelt contribution to total discharge 11–22% and an average decrease in SWE of 36%, with a shift in peak SWE by 4–14 days. The shift in runoff regime is broadly consistent between the AOGCMs with snowmelt-induced peak discharge expected to occur on average about two weeks earlier in the future hydrological year. The warming climate will drive a shift in runoff regime from a combined rainfall- and snowmelt-driven regime to one with a reduced contribution from snowmelt. The results of the study revealed that the model could be successfully applicable on the basin scale to simulate river discharge and snow processes and to investigate the effect of climate change on hydrological processes. This research contributes to improve the understanding of basin hydrological responses and the pace of change associated with climate variability.

Assimilation of Gridded GRACE Terrestrial Water Storage Estimates in the North American Land Data Assimilation System

AbstractThe objective of the North American Land Data Assimilation System (NLDAS) is to provide best-available estimates of near-surface meteorological conditions and soil hydrological status for the continental United States. To support the ongoing efforts to develop data assimilation (DA) capabilities for NLDAS, the results of Gravity Recovery and Climate Experiment (GRACE) DA implemented in a manner consistent with NLDAS development are presented. Following previous work, GRACE terrestrial water storage (TWS) anomaly estimates are assimilated into the NASA Catchment land surface model using an ensemble smoother. In contrast to many earlier GRACE DA studies, a gridded GRACE TWS product is assimilated, spatially distributed GRACE error estimates are accounted for, and the impact that GRACE scaling factors have on assimilation is evaluated. Comparisons with quality-controlled in situ observations indicate that GRACE DA has a positive impact on the simulation of unconfined groundwater variability across the majority of the eastern United States and on the simulation of surface and root zone soil moisture across the country. Smaller improvements are seen in the simulation of snow depth, and the impact of GRACE DA on simulated river discharge and evapotranspiration is regionally variable. The use of GRACE scaling factors during assimilation improved DA results in the western United States but led to small degradations in the eastern United States. The study also found comparable performance between the use of gridded and basin-averaged GRACE observations in assimilation. Finally, the evaluations presented in the paper indicate that GRACE DA can be helpful in improving the representation of droughts.

Numerical simulations of river discharges, nutrient flux and nutrient dispersal in Jakarta Bay, Indonesia

The present application of numerical modelling techniques provides an overview of river discharges, nutrient flux and nutrient dispersal in Jakarta Bay. A hydrological model simulated river discharges with a total of 90 to 377m3s−1 entering Jakarta Bay. Daily total nitrogen and total phosphorus loads ranged from 40 to 174tons and 14 to 60tons, respectively. Flow model results indicate that nutrient gradients are subject to turbulent mixing by tides and advective transport through circulation driven by wind, barotropic and baroclinic pressure gradients. The bulk of nutrient loads originate from the Citarum and Cisadane rivers flowing through predominantly rural areas. Despite lower nutrient loads, river discharges from the urban area of Jakarta exhibit the highest impact of nutrient concentrations in the near shore area of Jakarta Bay and show that nutrient concentrations were not only regulated by nutrient loads but were strongly regulated by initial river concentrations and local flow characteristics.

On the Use of Hydrological Models and Satellite Data to Study the Water Budget of River Basins Affected by Human Activities: Examples from the Garonne Basin of France

Natural and anthropogenic forcing factors and their changes significantly impact water resources in many river basins around the world. Information on such changes can be derived from fine scale in situ and satellite observations, used in combination with hydrological models. The latter need to account for hydrological changes caused by human activities to correctly estimate the actual water resource. In this study, we consider the catchment area of the Garonne river (in France) to investigate the capabilities of space-based observations and up-to-date hydrological modeling in estimating water resources of a river basin modified by human activities and a changing climate. Using the ISBA--MODCOU and SWAT hydrological models, we find that the water resources of the Garonne basin display a negative climate trend since 1960. The snow component of the two models is validated using the moderate-resolution imaging spectroradiometer snow cover extent climatology. Crop sowing dates based on remote sensing studies are also considered in the validation procedure. Use of this dataset improves the simulated evapotranspiration and river discharge amounts when compared to conventional data. Finally, we investigate the benefit of using the MAELIA multi-agent model that accounts for a realistic agricultural and management scenario. Among other results, we find that changes in crop systems have significant impacts on water uptake for agriculture. This work constitutes a basis for the construction of a future modeling framework of the sociological and hydrological system of the Garonne river region.

Modelling the effect of riparian vegetation restoration on sediment transport in a human‐impacted Brazilian catchment

AbstractSoil erosion threatens both soil and water resources and has increased globally because of the removal of natural vegetation and the intensification of existing agriculture. Brazil is privileged by a large proportion of natural vegetation and abundant freshwater. Recently, modifications of the Brazilian Forest Act (BFA) have been approved, which offer landowners that had committed illegal riparian deforestation in the past amnesty from reforestation, and further reductions of riparian protected areas are currently discussed. Here, we used the Soil and Water Assessment Tool to simulate river discharge and sediment exports in a typical human‐impacted Brazilian catchment, the Rio das Mortes catchment. By restoring the riparian vegetation according to the BFA and ignoring amnesties to land owners, the current annual sediment export of the catchment of 0·830 t ha−1 was reduced by 29·4% according to our model. Further, simulated reforestation twice the size demanded by the BFA resulted in a 31·4% reduction of the current sediment export. However, reforestation of a 5‐m homogeneous riparian corridor only, as currently discussed in the Federal Brazilian State of São Paulo, reduced sediment exports by only 23·8%, not considering expected additional erosion due to deforestation outside the simulated reforested 5‐m corridor. Our study is the first catchment‐wide assessment of the role of riparian vegetation in preventing soil erosion in Brazil. Its results support intensive reforestation efforts of the riparian zone and point to substantial negative effects of further reductions of the protected riparian corridor width and amnesties from reforestation to land owners. Copyright © 2016 John Wiley & Sons, Ltd.

Climate change and its impacts on river discharge in two climate regions in China

Abstract. Understanding the heterogeneity of climate change and its impacts on annual and seasonal discharge and the difference between median flow and extreme flow in different climate regions is of utmost importance to successful water management. To quantify the spatial and temporal heterogeneity of climate change impacts on hydrological processes, this study simulated river discharge in the River Huangfuchuan in semi-arid northern China and in the River Xiangxi in humid southern China. The study assessed the uncertainty in projected discharge for three time periods (2020s, 2050s and 2080s) using seven equally weighted GCMs (global climate models) for the SRES (Special Reports on Emissions Scenarios) A1B scenario. Climate projections that were applied to semi-distributed hydrological models (Soil Water Assessment Tools, SWAT) in both catchments showed trends toward warmer and wetter conditions, particularly for the River Huangfuchuan. Results based on seven GCMs' projections indicated changes from −1.1 to 8.6 °C and 0.3 to 7.0 °C in seasonal temperature and changes from −29 to 139 % and −32 to 85 % in seasonal precipitation in the rivers Huangfuchuan and Xiangxi, respectively. The largest increases in temperature and precipitation in both catchments were projected in the spring and winter seasons. The main projected hydrologic impact was a more pronounced increase in annual discharge in the River Huangfuchuan than in the River Xiangxi. Most of the GCMs projected increased discharge in all seasons, especially in spring, although the magnitude of these increases varied between GCMs. The peak flows were projected to appear earlier than usual in the River Huangfuchuan and later than usual in the River Xiangxi, while the GCMs were fairly consistent in projecting increased extreme flows in both catchments with varying magnitude compared to median flows. For the River Huangfuchuan in the 2080s, median flow changed from −2 to 304 %, compared to a −1 to 145 % change in high flow (Q05 exceedance threshold). For the River Xiangxi, low flow (Q95 exceedance threshold) changed from −1 to 77 % and high flow changed from −1 to 62 %, while median flow changed from −4 to 23 %. The uncertainty analysis provided an improved understanding of future hydrologic behavior in the watershed. Furthermore, this study indicated that the uncertainty constrained by GCMs was critical and should always be considered in analysis of climate change impacts and adaptation.