Ungauged River Basins Research Articles

Hydrological Modeling of an Ungauged River Basin Using SWAT Model for Water Resource Management Case of Kayanga River Upstream Niandouba Dam

Hydrological modeling of ungauged basins is important and imperative for policymakers and stakeholders in water management. The Kayanga river upstream from the Niandouba dam is subject to extreme pressure caused by natural and anthropogenic factors. The hydro system Niandouba Dam and Confluent Dam are used to providing water for the irrigated perimeters in Anambe. Since there is no data available to evaluate the water resources entering the Niandouba Dam, we used Soil and Water Assessment Tools (SWAT) to set up a hydrological model in the ungauged basin of Kayanga river upstream Niandouba dam. A regionalization approach has been used to predict the river discharge at Niandouba watershed upstream of the Niandouba dam. SWAT model has been calibrated from 01/01/2001 to 31/12/2001 and validated from 01/01/2002 to 31/12/2002, with a daily scale on the Koulountou watershed. During the calibration period, the criteria of goodness of fit are respectively 0.87 for Nash-Sutcliffe Efficiency coefficient (NSE), 0.87 for coefficient of determination (R2), -1.6% for Percent Bias (PBIAS) and 0.36 for Standard Deviation Ratio (RSR). In the validation period, we have found a Nash-Sutcliffe Efficiency coefficient (NSE) of 0.62, a coefficient of determination (R2) of 0.77, a Percent Bias (PBIAS) of +35.9%, Standard Deviation Ratio (RSR) of 0.62. These parameters have been used to generate flows at the entrance of the Niandouba Dam.

Semi-distributed parameter optimization and uncertainty assessment for an ungauged catchment of Deduru Oya Basin in Sri Lanka

ABSTRACTParameters are the key element in any hydrological model which govern the processes of water cycle. However, determining the most influential parameters and their ranges has certainly a challenging task for an ungauged river basin, where measurements related to hydrometeorological data and parameters are either too few or too poor in quality or not available at all. In this context, the aim of this research is to demonstrate a semi-distributed modelling approach and to optimize uncertainty assessment of model parameters in part of an ungauged river basin belongs to Deduru Oya Basin. Satellite retrieved weather data was used as input data and the model was run using SWAT water resources modelling tool. The parameters were optimized for the period of 2007–2011, using SUFI-2 inverse modelling approach. In local sensitivity analysis, out of the 43 parameters 14 were received as significant and out of them 4 were received as most sensitive with reference to the selected catchment. The model showed acceptable P values greater than 70% for 2007, 2008 and 2010 and lower R values that indicate lesser parameter uncertainty. The calibrated parameter ranges are also similar for the above 3 years. The key feature noticed in the final result was that the above 3 years have relatively similar seasonal rainfall pattern. Conversely, the model showed moderately acceptable P values, lesser than 60% for 2009 and 2011 where the annual rainfall pattern of the 2 years was comparatively different than its usual seasonal pattern. Moreover, the significant parameters identified by SUFI-2 have shown direct and indirect relationship with the physical properties and characteristics of the soil in the watershed.

Investigating the Sediment Yield Predictability in Some Italian Rivers by Means of Hydro-Geomorphometric Variables

In the present work, preliminary results are reported from an ongoing research study aimed at developing an improved prediction model to estimate the sediment yield in Italian ungauged river basins. The statistical correlations between a set of hydro-geomorphometric parameters and suspended sediment yield (SSY) data from 30 Italian rivers were investigated. The main question is whether such variables are helpful to explain the behavior of fluvial systems in the sediment delivery process. To this aim, a broad set of variables, simply derived from digital cartographic sources and available data records, was utilized in order to take into account all the possible features and processes having some influence on sediment production and conveyance. A stepwise regression analysis pointed out that, among all possibilities, the catchment elevation range (Hr), the density of stream hierarchical anomaly (Da), and the stream channel slope ratio (ΔSs) are significantly linked to the SSY. The derived linear regression model equation was proven to be satisfactory (r2-adjusted = 0.72; F-significance = 5.7 × 10−8; ME = 0.61), however, the percentage standard error (40%) implies that the model is still affected by some uncertainties. These can be justified, on one hand, by the wide variance and, on the other hand, by the quality of the observed SSY data. Reducing these uncertainties will be the effort in the follow-up of the research.

Monitoring Water Levels and Discharges Using Radar Altimetry in an Ungauged River Basin: The Case of the Ogooué

Radar altimetry is now commonly used for the monitoring of water levels in large river basins. In this study, an altimetry-based network of virtual stations was defined in the quasi ungauged Ogooué river basin, located in Gabon, Central Africa, using data from seven altimetry missions (Jason-2 and 3, ERS-2, ENVISAT, Cryosat-2, SARAL, Sentinel-3A) from 1995 to 2017. The performance of the five latter altimetry missions to retrieve water stages and discharges was assessed through comparisons against gauge station records. All missions exhibited a good agreement with gauge records, but the most recent missions showed an increase of data availability (only 6 virtual stations (VS) with ERS-2 compared to 16 VS for ENVISAT and SARAL) and accuracy (RMSE lower than 1.05, 0.48 and 0.33 and R² higher than 0.55, 0.83 and 0.91 for ERS-2, ENVISAT and SARAL respectively). The concept of VS is extended to the case of drifting orbits using the data from Cryosat-2 in several close locations. Good agreement was also found with the gauge station in Lambaréné (RMSE = 0.25 m and R2 = 0.96). Very good results were obtained using only one year and a half of Sentinel-3 data (RMSE < 0.41 m and R2 > 0.89). The combination of data from all the radar altimetry missions near Lamabréné resulted in a long-term (May 1995 to August 2017) and significantly improved water-level time series (R² = 0.96 and RMSE = 0.38 m). The increase in data sampling in the river basin leads to a better water level peak to peak characterization and hence to a more accurate annual discharge over the common observation period with only a 1.4 m3·s−1 difference (i.e., 0.03%) between the altimetry-based and the in situ mean annual discharge.

Assessment of a Simplified Connectivity Index and Specific Sediment Potential in River Basins by Means of Geomorphometric Tools

Sediment connectivity is a major topic in recent research because of its relevance in the characterization of the morphology of river systems and assessing of sediment transport and deposition. Currently, the connectivity indices found in the literature are generally dimensionless and need to be coupled with quantitative soil-loss data for land management and design purposes. In the present work, a simple methodology is proposed to assess two different indices, namely, the simplified connectivity index (SCI) and the specific sediment potential (SSP), based on geomorphometric tools that are commonly available in commercial and open-source geographic information system (GIS) platforms. The proposed metrics allows us to easily assess both the SCI and the SSP as functions of the estimated soil erosion per unit area of the catchment and of the inverse distance of each unit area from the river outlet, this distance being measured along the network path. The proposed indices have been devised to express, respectively, the potential sediment transfer ability and the sediment mass potentially available at a given section of the drainage network. In addition to other parameters used to describe the catchment characteristics potentially affecting the river sediment delivery capacity, the SCI and SSP indices can help to refine theoretical models in order to assess the sediment yield (SY) in ungauged river basins.

In vitro evaluation of cell signalling processes associated with the potential genotoxicity of metal oxide nanoparticles

The assessment of the mean annual runoff and its interannual variability in a basin is the first and fundamental task for several activities related to water resources management and water quality analysis. The scarcity of observed runoff data is a common problem worldwide so that the runoff estimation in ungauged basins is still an open question. In this context, the main aim of this work is to propose and test a simple tool able to estimate the probability distribution of the annual surface runoff in ungauged river basins in arid and semi-arid areas using a simplified Fu's parameterization of the Budyko's curve at regional scale. Starting from a method recently developed to derive the distribution of annual runoff, under the assumption of negligible inter-annual change in basin water storage, we here generalize the application to any catchment where the parameter of the Fu's curve is known. Specifically, we provide a closed-form expression of the annual runoff distribution as a function of the mean and standard deviation of annual rainfall and potential evapotranspiration, and the Fu's parameter. The proposed method is based on a first order Taylor expansion of the Fu's equation and allows calculating the probability density function of annual runoff in seasonally dry arid and semi-arid geographic context around the world by taking advantage of simple easy-to-find climatic data and the many studies with estimates of the Fu's parameter worldwide. The computational simplicity of the proposed tool makes it a valuable supporting tool in the field of water resources assessment for practitioners, regional agencies and authorities.

Analytical estimation of annual runoff distribution in ungauged seasonally dry basins based on a first order Taylor expansion of the Fu's equation

Abstract The assessment of the mean annual runoff and its interannual variability in a basin is the first and fundamental task for several activities related to water resources management and water quality analysis. The scarcity of observed runoff data is a common problem worldwide so that the runoff estimation in ungauged basins is still an open question. In this context, the main aim of this work is to propose and test a simple tool able to estimate the probability distribution of the annual surface runoff in ungauged river basins in arid and semi-arid areas using a simplified Fu's parameterization of the Budyko's curve at regional scale. Starting from a method recently developed to derive the distribution of annual runoff, under the assumption of negligible inter-annual change in basin water storage, we here generalize the application to any catchment where the parameter of the Fu's curve is known. Specifically, we provide a closed-form expression of the annual runoff distribution as a function of the mean and standard deviation of annual rainfall and potential evapotranspiration, and the Fu's parameter. The proposed method is based on a first order Taylor expansion of the Fu's equation and allows calculating the probability density function of annual runoff in seasonally dry arid and semi-arid geographic context around the world by taking advantage of simple easy-to-find climatic data and the many studies with estimates of the Fu's parameter worldwide. The computational simplicity of the proposed tool makes it a valuable supporting tool in the field of water resources assessment for practitioners, regional agencies and authorities.

Calibration of a large-scale hydrological model using satellite-based soil moisture and evapotranspiration products

Abstract. A considerable number of river basins around the world lack sufficient ground observations of hydro-meteorological data for effective water resources assessment and management. Several approaches can be developed to increase the quality and availability of data in these poorly gauged or ungauged river basins; among them, the use of Earth observations products has recently become promising. Earth observations of various environmental variables can be used potentially to increase knowledge about the hydrological processes in the basin and to improve streamflow model estimates, via assimilation or calibration. The present study aims to calibrate the large-scale hydrological model PCRaster GLOBal Water Balance (PCR-GLOBWB) using satellite-based products of evapotranspiration and soil moisture for the Moroccan Oum er Rbia River basin. Daily simulations at a spatial resolution of 5 × 5 arcmin are performed with varying parameters values for the 32-year period 1979–2010. Five different calibration scenarios are inter-compared: (i) reference scenario using the hydrological model with the standard parameterization, (ii) calibration using in situ-observed discharge time series, (iii) calibration using the Global Land Evaporation Amsterdam Model (GLEAM) actual evapotranspiration time series, (iv) calibration using ESA Climate Change Initiative (CCI) surface soil moisture time series and (v) step-wise calibration using GLEAM actual evapotranspiration and ESA CCI surface soil moisture time series. The impact on discharge estimates of precipitation in comparison with model parameters calibration is investigated using three global precipitation products, including ERA-Interim (EI), WATCH Forcing methodology applied to ERA-Interim reanalysis data (WFDEI) and Multi-Source Weighted-Ensemble Precipitation data by merging gauge, satellite and reanalysis data (MSWEP). Results show that GLEAM evapotranspiration and ESA CCI soil moisture may be used for model calibration resulting in reasonable discharge estimates (NSE values from 0.5 to 0.75), although better model performance is achieved when the model is calibrated with in situ streamflow observations. Independent calibration based on only evapotranspiration or soil moisture observations improves model predictions to a lesser extent. Precipitation input affects discharge estimates more than calibrating model parameters. The use of WFDEI precipitation leads to the lowest model performances. Apart from the in situ discharge calibration scenario, the highest discharge improvement is obtained when EI and MSWEP precipitation products are used in combination with a step-wise calibration approach based on evapotranspiration and soil moisture observations. This study opens up the possibility of using globally available Earth observations and reanalysis products of precipitation, evapotranspiration and soil moisture in large-scale hydrological models to estimate discharge at a river basin scale.

Runoff modeling of the Mara River using satellite observed soil moisture and rainfall

Hydrological models are essential in water resources management. However modeling in poorly gauged catchments is a big challenge. Recent studies have shown that satellite based hydrological and meteorological data has the potential of being part of the solution towards overcoming this challenge. In this study, we modify the conceptual lumped rainfall-runoff model by Meier et al. (2011) to simulate the runoff of the Mara River basin. The model is developed based on the relationships found between satellite observed soil moisture and rainfall and the measured runoff. It uses the satellite observed rainfall as the prime forcing, and the soil moisture to separate the fast surface runoff and slow base flow contributions. The soil moisture and rainfall products used in this research are the Advanced Scatterometer Soil Water Index (ASCAT SWI) and Tropical Rainfall Measurement Mission (TRMM) 3B42 v7 respectively. The performance of the model is evaluated for three sub-catchments defined by the Mara mines, Nyangores and Amala gauging stations along the Mara River. The Pearson correlation (r) for Mara mines Nyangores and Amala during calibration and (validation) were 0.54 (0.77), 0.67 (0.74), 0.125 (0.48) respectively. The model showed great potential for simulating dry season runoff, but needs further improvement to be able to reliably simulate wet season runoff. Nevertheless, this study demonstrates the potential role operational satellite based soil moisture and rainfall products can play in quantifying the available water resources particularly in the many un-gauged river basins across Africa.Keywords—ASCAT SWI, hydrological modeling, rainfall, runoff, soil moisture, TRMM 3B42 v7

Runoff modeling of the Mara River using satellite observed soil moisture and rainfall

Hydrological models are essential in water resources management. However modeling in poorly gauged catchments is a big challenge. Recent studies have shown that satellite based hydrological and meteorological data has the potential of being part of the solution towards overcoming this challenge. In this study, we modify the conceptual lumped rainfall-runoff model by Meier et al. (2011) to simulate the runoff of the Mara River basin. The model is developed based on the relationships found between satellite observed soil moisture and rainfall and the measured runoff. It uses the satellite observed rainfall as the prime forcing, and the soil moisture to separate the fast surface runoff and slow base flow contributions. The soil moisture and rainfall products used in this research are the Advanced Scatterometer Soil Water Index (ASCAT SWI) and Tropical Rainfall Measurement Mission (TRMM) 3B42 v7 respectively. The performance of the model is evaluated for three sub-catchments defined by the Mara mines, Nyangores and Amala gauging stations along the Mara River. The Pearson correlation (r) for Mara mines Nyangores and Amala during calibration and (validation) were 0.54 (0.77), 0.67 (0.74), 0.125 (0.48) respectively. The model showed great potential for simulating dry season runoff, but needs further improvement to be able to reliably simulate wet season runoff. Nevertheless, this study demonstrates the potential role operational satellite based soil moisture and rainfall products can play in quantifying the available water resources particularly in the many un-gauged river basins across Africa.Keywords—ASCAT SWI, hydrological modeling, rainfall, runoff, soil moisture, TRMM 3B42 v7

Artificial intelligence and geo-statistical models for stream-flow forecasting in ungauged stations: state of the art

Developing an accurate model for discharge estimation techniques of the ungauged river basin is a crucial challenge in water resource management especially in under-development regions. This article is a thorough review of the historical improvement stages of this topic to understand previous challenges that faced researchers, the shortfalls of methods and techniques, how researchers prevailed and what deficiencies still require solutions. This revision focuses on data-driven approaches and GIS-based methods that have improved the accuracy of estimation of hydrological variables, considering their advantages and disadvantages. Past studies used artificial intelligence and geo-statistical methods to forecast the runoff at ungauged river basins, and mapping the spatial distribution has been considered in this study. A recommendation for future research on the potential of a hybrid model utilizing both approaches is proposed and described.

Approach of Land Cover Based Asymptotic Curve Number Regression Equation to Estimate Runoff

AbstractThe Natural Resources Conservation Service‐Curve Number (NRCS‐CN) method has been used widely for estimation of direct runoff. However, the determination methods of CN values for land covers from the National Engineering Handbook Chapter 4 (NEH‐4) are inadequate due to uncertainty raised in determining the of the hydrologic soil group, which could change from reported soil survey data due to soil compaction and other human activities. To overcome these drawbacks, an asymptotic CN (ACN) regression equation for the relationship between measured streamflow and rainfall for gauged river basins (ACN‐RB) was developed and used in various studies. The ACN‐RB determines various CN values depending on the amount of rainfall in an event. The ACN‐RB has limitations in application to ungauged river basin because the ACN‐based CN values do not consider various land covers. Accordingly, 13 land cover‐based asymptotic CN regression equations (LC‐ACN‐REs) were developed and evaluated in this study by comparing estimated direct runoff with measured data. The estimated direct runoff using the LC‐ACN‐REs, which were classified as “standard types”, matched observed direct runoff well, as evidenced by a Nash‐Sutcliff efficiency (NSE) value of 0.78 for Jungrang A basin and a NSE value of 0.73 for Tancheon A basin. Copyright © 2016 John Wiley & Sons, Ltd.

STREAMFLOW PREDICTION IN UNGAUGED CATCHMENTS IN THE EAST COAST OF PENINSULAR MALAYSIA USING MULTIVARIATE STATISTICAL TECHNIQUES

The east coast of Peninsular Malaysia is one of the most vulnerable regions of Malaysia to hydrological disasters, which is believed to become more vulnerable due to climate change. Studies to have better understandings of the hydrological processes in the region are therefore, of paramount importance for disaster risk mitigation. However, unavailability of long-term river discharge data is one of the major constraints of hydrologic studies in the area. The major objective of this study is to predict river discharge in ungauged river basins in the study area. For this purpose, a set of multiple linear regression equations and exponential functions have been developed, which are expressed in the forms of multivariate equations. Available streamflow data along with other catchment characteristics from gauged catchments were used to develop the equations and were subsequently applied to the poorly gauged or ungauged catchments within the study area for prediction of streamflow. In this present study, 4 to 7 explanatory variables were selected as the input variables, which comprise of climatic, geomorphologic, geographic characteristics, soil properties, land use pattern and land cover of the area. Ten flow metrics as maximum, 0.05, 0.10, 0.25, 0.50, 0.75, 0.90, and 0.95, mean and minimum were therefore predicted. Thus, the results of the developed multivariate equations revealed the model to be capable of predicting the desired flow metrics at ungauged catchments in the area under consideration with reasonable accuracy.

Chemical and isotopic fingerprinting of small ungauged watershed: How far the hydrological functioning can be understood?

This study presents the ability of major/trace elements together with strontium isotopes to trace water origins at small scale at the outlet of a small watershed (Peyne, Hérault, France). Two small sub-basins draining distinct lithologies in their headwater (Plio-Villafranchian conglomerate versus Triassic gypsum-rich marls and dolomites) and the Miocene formations downstream are investigated. The Ca/Na vs. Mg/Na ratios and Ca/Sr vs. 87Sr/86Sr ratios allow the different facies that imprint the water signature to be identified, according to the hydrological conditions (low/high flows). Moreover, Sr isotopes evidence the two distinct Miocene facies, the sandy marls and the marine carbonates. The variation of the signature at the outlet of the basin allows identifying the main contributing compartments according to the hydrological conditions. This approach, based on a limited number of samples, highlights the potential of geochemical and isotopic tracers to define the contributing compartments to the runoff at the outlet of a basin. It thus could be considered as a potential alternative way to classical hydrological monitoring to delineate the main contributing areas during floods, especially in small ungauged river basins, where most of the devastating flash floods are recorded.

Advancing river modelling in ungauged basins using satellite remote sensing: the case of the Ganges–Brahmaputra–Meghna basin

ABSTRACTRiver modelling is the process of simulating the water flow dynamics of a stream network against time-varying boundary conditions. Such river models are often an important component of any flood forecasting system that forecasts river levels in flood-prone regions. However, large river basins such as the Ganges, Brahmaputra, and Meghna (GBM), Indus, Irrawaddy, Salween, Mekong, and Niger in the developing world are mostly ungauged as they lack the necessary and routine in situ measurements of river bed depth/slope, bathymetry (river cross section), flood plain mapping, and boundary condition flows for setting up of a river model. For such basins, proxy approaches relying primarily on remote-sensing data from space platforms may be the only way to overcome the lack of in situ data. In this study, we share our experience in setting up the one-dimensional River Analysis System model of the Hydrologic Engineering Center over the stream network of the GBM basin. Good-quality in situ measurements of river hydraulics (cross section, slope, flow) were available only for the basin's downstream and flood-prone region, which comprises 7% of the total basin area. For the remaining 93% of the basin area, data from the following satellite sensors were used to build a functional river model: (a) Shuttle Radar Topography Mission to derive river network and adjust river bed profiles; (b) Landsat–MODIS for updating river network and flow direction generated by elevation data; (c) radar altimetry data to build the depth versus width relationship at river locations; and (d) satellite precipitation-based hydrologic modelling of lateral flows into major rivers. We measured the success of our approach by systematically testing how well the basin-wide river model could simulate river-level dynamics at two measured downstream low-lying locations. This paper summarizes the key hurdles faced and offers a step-by-step ‘rule book’ approach to setting up river models for large ungauged river basins around the world. By following these rules in a systematic way, the root mean squared error for river-level simulation was reduced from 3 to 1 m. Such a guide can be useful for setting up river hydraulic models for flood forecasting systems in ungauged basins such as the Niger, Mekong, Irrawaddy, and Indus.

A fast mobile early warning system for water quality emergency risk in ungauged river basins

Environmental decision support system (EDSS) has become an important research topic in the fields of water environment protection and emergency early warning. Most existing systems require plenty of measured data, which are typically unavailable in ungauged basins. In order to develop an early warning system that can work with few measured data, a mobile environment decision support system (MEWSUB) for early warning and emergency assessment in ungauged river basins was developed. A one-dimensional water quality model was built for the system and the terrain module and pollutant module were developed for terrain digitization and pollutant release process data generation. MEWSUB can quickly create water quality model input files, simulate the temporal release of pollutants, and display the results in a dynamically rendered map and trend line diagram via HTML5. The system has been used successfully to support early warning efforts during accidents on several ungauged rivers in China.

A pan-African medium-range ensemble flood forecast system

Abstract. The African Flood Forecasting System (AFFS) is a probabilistic flood forecast system for medium- to large-scale African river basins, with lead times of up to 15 days. The key components are the hydrological model LISFLOOD, the African GIS database, the meteorological ensemble predictions by the ECMWF (European Centre for Medium-Ranged Weather Forecasts) and critical hydrological thresholds. In this paper, the predictive capability is investigated in a hindcast mode, by reproducing hydrological predictions for the year 2003 when important floods were observed. Results were verified by ground measurements of 36 sub-catchments as well as by reports of various flood archives. Results showed that AFFS detected around 70 % of the reported flood events correctly. In particular, the system showed good performance in predicting riverine flood events of long duration (> 1 week) and large affected areas (> 10 000 km2) well in advance, whereas AFFS showed limitations for small-scale and short duration flood events. The case study for the flood event in March 2003 in the Sabi Basin (Zimbabwe) illustrated the good performance of AFFS in forecasting timing and severity of the floods, gave an example of the clear and concise output products, and showed that the system is capable of producing flood warnings even in ungauged river basins. Hence, from a technical perspective, AFFS shows a large potential as an operational pan-African flood forecasting system, although issues related to the practical implication will still need to be investigated.

Multidisciplinary study of flash floods in the Caldera de Taburiente National Park (Canary Islands, Spain)

The national parks of the Canary Islands have specific environmental features that attract thousands of tourists every year. Most of the parks are located in mountainous areas, where hydrogeomorphic processes and their related hazards are frequent. The main aim of this study is to improve our understanding of the effects and frequency of these processes in an ungauged river basin located on the island of La Palma. In this river basin, the use of hydrological and hydraulic modelling based on classic data sources and flood risk analysis methods has important shortcomings because of a lack of or incomplete information. Here, we use palaeohydrological data from tree-ring analyses of disturbed trees as these appear to be the only reliable alternative. In addition, dendrogeomorphological data are compared with available meteorological and documental information to develop a multidisciplinary flash flood record. This is the first time that Pinus canariensis has been used in a dendrogeomorphological study we assess its suitability for the reconstruction of flash flood events. Such techniques have not been applied before in subtropical, tropical or equatorial areas. Tree-ring dating data were mostly obtained from 63 wounds from 54 trees from which two main types of post-damage tree response were identified: growth release and growth suppression. Injuries occurring in 1962 were especially relevant (affecting almost all the older trees) and also in 1997, with both presenting a large number of replications. Other injuries occurred in 1993, 2001, 2003, 2007 and 2009, obtaining a record from the dendrogeomorphological evidence. The data were compared with daily meteorological data and available documental sources in order to establish the most complete flash flood record possible. Our findings provide new insight into past flood events, their frequency–magnitude relationships, and climatic triggers, that can provide park managers with tools to reduce natural risks and their effects on visitors and infrastructure.

Earth Observation Based Assessment of the Water Production and Water Consumption of Nile Basin Agro-Ecosystems

The increasing competition for water resources requires a better understanding of flows, fluxes, stocks, and the services and benefits related to water consumption. This paper explains how public domain Earth Observation data based on Moderate Resolution Imaging Spectroradiometer (MODIS), Second Generation Meteosat (MSG), Tropical Rainfall Measurement Mission (TRMM) and various altimeter measurements can be used to estimate net water production (rainfall (P) > evapotranspiration (ET)) and net water consumption (ET > P) of Nile Basin agro-ecosystems. Rainfall data from TRMM and the Famine Early Warning System Network (FEWS-NET) RainFall Estimates (RFE) products were used in conjunction with actual evapotranspiration from the Operational Simplified Surface Energy Balance (SSEBop) and ETLook models. Water flows laterally between net water production and net water consumption areas as a result of runoff and withdrawals. This lateral flow between the 15 sub-basins of the Nile was estimated, and partitioned into stream flow and non-stream flow using the discharge data. A series of essential water metrics necessary for successful integrated water management are explained and computed. Net water withdrawal estimates (natural and humanly instigated) were assumed to be the difference between net rainfall (Pnet) and actual evapotranspiration (ET) and some first estimates of withdrawals—without flow meters—are provided. Groundwater-dependent ecosystems withdraw large volumes of groundwater, which exceed water withdrawals for the irrigation sector. There is a strong need for the development of more open-access Earth Observation databases, especially for information related to actual ET. The fluxes, flows and storage changes presented form the basis for a global framework to describe monthly and annual water accounts in ungauged river basins.

Water Level Fluctuations in the Congo Basin Derived from ENVISAT Satellite Altimetry

In the Congo Basin, the elevated vulnerability of food security and the water supply implies that sustainable development strategies must incorporate the effects of climate change on hydrological regimes. However, the lack of observational hydro-climatic data over the past decades strongly limits the number of studies investigating the effects of climate change in the Congo Basin. We present the largest altimetry-based dataset of water levels ever constituted over the entire Congo Basin. This dataset of water levels illuminates the hydrological regimes of various tributaries of the Congo River. A total of 140 water level time series are extracted using ENVISAT altimetry over the period of 2003 to 2009. To improve the understanding of the physical phenomena dominating the region, we perform a K-means cluster analysis of the altimeter-derived river level height variations to identify groups of hydrologically similar catchments. This analysis reveals nine distinct hydrological regions. The proposed regionalization scheme is validated and therefore considered reliable for estimating monthly water level variations in the Congo Basin. This result confirms the potential of satellite altimetry in monitoring spatio-temporal water level variations as a promising and unprecedented means for improved representation of the hydrologic characteristics in large ungauged river basins.