Data-scarce Catchment Research Articles

Modeling Multi-Event Non-Point Source Pollution in a Data-Scarce Catchment Using ANN and Entropy Analysis

Event-based runoff–pollutant relationships have been the key for water quality management, but the scarcity of measured data results in poor model performance, especially for multiple rainfall events. In this study, a new framework was proposed for event-based non-point source (NPS) prediction and evaluation. The artificial neural network (ANN) was used to extend the runoff–pollutant relationship from complete data events to other data-scarce events. The interpolation method was then used to solve the problem of tail deviation in the simulated pollutographs. In addition, the entropy method was utilized to train the ANN for comprehensive evaluations. A case study was performed in the Three Gorges Reservoir Region, China. Results showed that the ANN performed well in the NPS simulation, especially for light rainfall events, and the phosphorus predictions were always more accurate than the nitrogen predictions under scarce data conditions. In addition, peak pollutant data scarcity had a significant impact on the model performance. Furthermore, these traditional indicators would lead to certain information loss during the model evaluation, but the entropy weighting method could provide a more accurate model evaluation. These results would be valuable for monitoring schemes and the quantitation of event-based NPS pollution, especially in data-poor catchments.

Simulating Microbial Water Quality in Data-Scarce Catchments: an Update of the WQSAM Model to Simulate the Fate of Escherichia coli

Faecal-derived microbial pollution of fresh surface waters is a global problem. Water quality models can play an important role in the management of microbial pollution; however, most existing models are too complex and require a large amount of observed data for calibration, thereby excluding their use in data-scarce catchments. The Water Quality Systems Assessment Model (WQSAM) is a water quality water model structured on the concept of requisite simplicity, thereby limiting the complexity and data requirements of the model. Here, microbial water quality simulation functionality was added to WQSAM, with the aim of assessing whether a simplified representation of processes affecting microbial water quality is sufficiently accurate for purposes of water resource management. Simulations of microbial water quality were based on the inputs and fate of an indicator organism, Escherichia coli. Non-point source inputs were modelled by assigning microbial water quality ‘signatures’ to incremental flow components, whereas a similar signature was assigned to point source inputs. The instream fate of E. coli was based on a first-order rate equation, moderated by salinity and water temperature. The model was validated by application to the upper to middle Crocodile River Catchment, Mpumalanga, South Africa, for historical conditions. Model simulations were obtained that were representative of the variability of observed temperature, salinity and microbial water quality data. The simulations of E. coli were found to be most sensitive to the decay rate k 0. It is argued here that the uncertainty in model results due to the use of a relatively simple model structure would be no more, or even less that that due to the application of a complex model to a catchment with insufficient observed data for adequate model calibration.

Use of Landsat series data to analyse the spatial and temporal variations of land degradation in a dispersive soil environment: A case of King Sabata Dalindyebo local municipality in the Eastern Cape Province, South Africa

Land degradation as a result of inappropriate land use practices, such as overgrazing and cultivation on steep slopes, etc. is one of the major global environmental challenges. Specifically, land degradation threatens the productivity and sustainability of the natural environment, agriculture, and most importantly rural economies in most developing countries, particularly the sub-Saharan region. The main aim of this study was therefore, to assess the potential and strength of using the free or readily available Landsat series data in mapping degraded land areas at the King Sabata Dalindyebo local municipality in the Eastern Cape, South Africa (1984–2010). Data analysis was done using a robust non-parametric classification ensemble; Discriminant Analysis (DA). The results show that degraded areas vary over the years. For example, the results show that the year 1994 and 2004 incurred high degradation levels, when compared to the year 1984 and 2010. Moreover, the observed degradation significantly (α = 0.05) varies with soil type. The chromic acrisols have the highest levels of erosion (approx. 80% in 1984), when compared to humic-umbric acrisols (less than 10% for the entire period under study). It can also be observed that considerable part of degradation occurred in the northern part of the municipal district. Overall, the findings of this research underlines the importance and efficacy of multispectral Landsat series data-set in mapping and monitoring levels of land degradation in data-scarce catchments.

Glacier mass balance simulation using SWAT distributed snow algorithm

ABSTRACTApplication of a temperature-index melt model incorporated into the Soil and Water Assessment Tool (SWAT) is presented to simulate mass balance (MB) and equilibrium line altitude (ELA) of three glaciers. The snow accumulation/melt parameters were adjusted to glacierized and free glacier areas, respectively. The SWAT snow algorithm enabled us to consider spatial variation of snow parameters by elevation bands across the sub-basins, while in the previous studies using SWAT, the related parameters were constant for an entire basin. The results show slight improvement in runoff simulation and significant improvement in simulated MB when considering ELA in model calibration. The results showed that SWAT can be applied to simulate MB, vertical MB distribution and annual ELA, with light calibration efforts for data-scarce catchments. The accuracy of the results depends on the modelled area of ablation zone from which most of the meltwater is released.

Water availability and agricultural demand: An assessment framework using global datasets in a data scarce catchment, Rokel-Seli River, Sierra Leone

Abstract Study region The proposed assessment framework is aimed at application in Sub-Saharan Africa, but could also be applied in other hydrologically data scarce regions. The test study site was the Rokel-Seli River catchment, Sierra Leone, West Africa. Study focus We propose a simple, transferable water assessment framework that allows the use of global climate datasets in the assessment of water availability and crop demand in data scarce catchments. In this study, we apply the assessment framework to the catchment of the Rokel-Seli River in Sierra Leone to investigate the capabilities of global datasets complemented with limited historical data in estimating water resources of a river basin facing rising demands from large scale agricultural water withdrawals. We demonstrate how short term river flow records can be extended using a lumped hydrological model, and then use a crop water demand model to generate irrigation water demands for a large irrigated biofuels scheme abstracting from the river. The results of using several different global datasets to drive the assessment framework are compared and the performance evaluated against observed rain and flow gauge records. New hydrological insights We find that the hydrological model capably simulates both low and high flows satisfactorily, and that all the input datasets consistently produce similar results for water withdrawal scenarios. The proposed framework is successfully applied to assess the variability of flows available for abstraction against agricultural demand. The assessment framework conclusions are robust despite the different input datasets and calibration scenarios tested, and can be extended to include other global input datasets.

Evaluation of satellite-based rainfall products for hydrological modelling in Morocco

ABSTRACTSeveral satellite-based precipitation estimates are becoming available at a global scale, providing new possibilities for water resources modelling, particularly in data-sparse regions and developing countries. This work provides a first validation of five different satellite-based precipitation products (TRMM-3B42 v6 and v7, RFE 2.0, PERSIANN-CDR, CMORPH1.0 version 0.x) in the 1785 km2 Makhazine catchment (Morocco). Precipitation products are first compared against ground observations. Ten raingauges and four different interpolation methods (inverse distance, nearest neighbour, ordinary kriging and residual kriging with altitude) were used to compute a set of interpolated precipitation reference fields. Second, a parsimonious conceptual hydrological model is considered, with a simulation approach based on the random generation of model parameters drawn from existing parameter set libraries, to compare the different precipitation inputs. The results indicate that (1) all four interpolation methods, except the nearest neighbour approach, give similar and valid precipitation estimates at the catchment scale; (2) among the different satellite-based precipitation estimates verified, the TRMM-3B42 v7 product is the closest to observed precipitation, and (3) despite poor performance at the daily time step when used in the hydrological model, TRMM-3B42 v7 estimates are found adequate to reproduce monthly dynamics of discharge in the catchment. The results provide valuable perspectives for water resources modelling of data-scarce catchments with satellite-based rainfall data in this region.Editor M.C. Acreman; Associate editor N. Verhoest

Ungauged runoff simulation in Upper Manyame Catchment, Zimbabwe: Application of the HEC-HMS model

The Hydrologic Engineering Center Hydrologic Modelling System (HEC-HMS) model was applied to simulate runoff in the ten gauged and ungauged Upper Manyame subcatchments in Zimbabwe. Remote sensing and Geographic Information System techniques were used to determine the geometric and hydrologic parameters required for estimating model parameters. The Snyder Unit Hydrograph method was used for ungauged subcatchment simulations based on parameter transfer from gauged subcatchments. The Marimba and Mukuvisi subcatchments were considered as the gauged subcatchments based on data completeness for the simulation period (2004–2010). Before extrapolating the calibrated model setup to eight ungauged subcatchments, the feasibility of model parameter transferability was tested, using the proxy – catchment approach and evaluated using the Nash Sutcliffe (NSE) and Relative Volume Error (RVE) criterion. Results showed that the model successfully predicted gauged catchment runoff and peakflows for the calibration (Marimba NSE = 68%, RVE = 5.8%; Mukuvisi NSE = 64%, RVE = −8.9%) and validation (Marimba NSE = 61%, RVE = 8.1%; Mukuvisi NSE = 57%, RVE = 9.9%) periods. The study demonstrates the suitability of HEC-HMS for continuous runoff simulation in a complex watershed with numerous subcatchments and channel reaches. The ungauged subcatchments contribute to 51% of Upper Manyame Catchment's runoff. Ruwa and Lake Chivero subcatchments had the highest ungauged subcatchment contribution to Upper Manyame Catchment runoff (19% and 15% respectively). This work will have a significant contribution for the future development of water resources programs in Upper Manyame Catchment in particular and in other data-scarce catchments.

TOPMODEL for Streamflow Simulation of a Tropical Catchment Using Different Resolutions of ASTER DEM: Optimization Through Response Surface Methodology

The unavailability of proper hydrological data quality combined with the complexity of most physical based hydrologic models limits research on rainfall-runoff relationships, particularly in the tropics. In this paper, an attempt has been made to use different resolutions of DEM generated from freely available 30 m-based ASTER imagery as primary input to the topographically-based hydrological (TOPMODEL) model to simulate the runoff of a medium catchment located in the tropics. Response surface methodology (RSM) was applied to optimize the most sensitive parameters for streamflow simulation. DEM resolutions from 30 to 300 m have been used to assess their effects on the topographic index distribution (TI) and TOPMODEL simulation. It is found that changing DEM resolutions reduces the TOPMODEL simulation performance as the resolutions are varied from 30 to 300 m. The study concluded that the ASTER 30 m DEM can be used for reasonable streamflow simulation of a data scarce tropical catchment compared with the resampled DEMs.

A robust debris-flow and GLOF risk management strategy for a data-scarce catchment in Santa Teresa, Peru

The town of Santa Teresa (Cusco Region, Peru) has been affected by several large debris-flow events in the recent past, which destroyed parts of the town and resulted in a resettlement of the municipality. Here, we present a risk analysis and a risk management strategy for debris-flows and glacier lake outbursts in the Sacsara catchment. Data scarcity and limited understanding of both physical and social processes impede a full quantitative risk assessment. Therefore, a bottom-up approach is chosen in order to establish an integrated risk management strategy that is robust against uncertainties in the risk analysis. With the Rapid Mass Movement Simulation (RAMMS) model, a reconstruction of a major event from 1998 in the Sacsara catchment is calculated, including a sensitivity analysis for various model parameters. Based on the simulation results, potential future debris-flows scenarios of different magnitudes, including outbursts of two glacier lakes, are modeled for assessing the hazard. For the local communities in the catchment, the hazard assessment is complemented by the analysis of high-resolution satellite imagery and fieldwork. Physical, social, economic, and institutional vulnerability are considered for the vulnerability assessment, and risk is eventually evaluated by crossing the local hazard maps with the vulnerability. Based on this risk analysis, a risk management strategy is developed, consisting of three complementing elements: (i) standardized risk sheets for the communities; (ii) activities with the local population and authorities to increase social and institutional preparedness; and (iii) a simple Early Warning System. By combining scientific, technical, and social aspects, this work is an example of a framework for an integrated risk management strategy in a data scarce, remote mountain catchment in a developing country.

Snowmelt runoff modelling in data scarce Nuranang catchment of eastern Himalayan region

Snowmelt runoff modelling is very important tool to estimate the ice and snow induced runoff volume in the mountain basins. However, unavailability of data is a key challenge for snowmelt runoff modelling especially in the eastern Himalayan region. In this paper, an attempt has been made to apply the Windows-based Snowmelt Runoff Model (WinSRM) to estimate the snowmelt runoff from a small representative seasonally snow-covered eastern Himalayan catchment with high data scarcity located in Arunachal Pradesh. The 52km2 catchment, having very steep average slope with an elevation difference of more than 1800m from lowest to highest point, has been divided into three elevation zones. The satellite images of the catchment are acquired from Indian Remote Sensing Satellite IRS-P6 (LISS-III/AWiFS). Snow cover mapping is done using normalised difference snow index (NDSI) method. Snow depletion curves of each zone are generated from daily snow covered area percentage (SCA%) obtained by interpolating periodic SCA% determined from cloud free images, which is also a rarity in this region during the snow depletion season. A logarithmic relationship is established between SCA% and average mean air temperature (AMAT) to estimate the SCA% for validation period of 2004 for which cloud free IRS-P6 Satellite images were not available. The WinSRM model is calibrated using three years data of 2006, 2007, and 2009 for the depletion period and is validated for depletion period of 2004. It is shown that the SRM model can be used satisfactorily in such data scarce catchments of eastern Himalaya. The procedures adopted in this study to handle different limited data conditions and estimate some of the required model parameters are also explained in this paper.

Peer review report 1 On “Model signatures and aridity indices enhance the accuracy of water balance estimations in a data-scarce Eastern Mediterranean catchment”

Peer review report 1 On “Model signatures and aridity indices enhance the accuracy of water balance estimations in a data-scarce Eastern Mediterranean catchment”

Peer review report 2 On “Model signatures and aridity indices enhance the accuracy of water balance estimations in a data-scarce Eastern Mediterranean catchment”

Peer review report 2 On “Model signatures and aridity indices enhance the accuracy of water balance estimations in a data-scarce Eastern Mediterranean catchment”

An experiment to gauge an ungauged catchment: rapid data assessment and eco-hydrological modelling in a data-scarce rural catchment

We conducted a PUB (predictions in ungauged basins) experiment looking at hydrology and crop dynamics in the semi-arid rural Mod catchment in India. The experiment was motivated by the aims (a) to develop a coupled eco-hydrological model capable of analysing land-use strategies concerning crop water need, erosion protection, crop yield and resistivity against droughts and floods, and (b) to assess the feasibility of a strategy for collecting the necessary data in a data-scarce region. Our experiment combines parsimonious data assessment and eco-hydrological model coupling at the lower mesoscale. Linking bottom-up sampling of functionally representative soil classes and top-down regionalization based on spectral properties of the same resulted in a comprehensive distributed data basis for the model. A clear focus on the dominating processes and the catena as the organizing landscape element in the given environmental setting enabled this. We employed the WASA (Water Availability in Semi-Arid environments) model for uncalibrated process-based water balance modelling and integrated a crop simulation subroutine based on the SWAP (Soil Water Atmosphere Plant) model to account for crop dynamics, feedbacks and yield estimation. While we found the data assessment strategy and the hydrological model application largely feasible, in terms of its accounting for scale, processes and model concepts, the simulation of feedbacks with crops was problematic. Contributing to the PUB issue, more general conclusions are drawn concerning spatially-distributed structural information and uncalibrated modelling.Editor Z.W. Kundzewicz; Associate editor F. Hattermann

Addressing sources of uncertainty in runoff projections for a data scarce catchment in the Ecuadorian Andes

Future climate projections from general circulation models (GCMs) predict an acceleration of the global hydrological cycle throughout the 21st century in response to human-induced rise in temperatures. However, projections of GCMs are too coarse in resolution to be used in local studies of climate change impacts. To cope with this problem, downscaling methods have been developed that transform climate projections into high resolution datasets to drive impact models such as rainfall-runoff models. Generally, the range of changes simulated by different GCMs is considered to be the major source of variability in the results of such studies. However, the cascade of uncertainty in runoff projections is further elongated by differences between impact models, especially where robust calibration is hampered by the scarcity of data. Here, we address the relative importance of these different sources of uncertainty in a poorly monitored headwater catchment of the Ecuadorian Andes. Therefore, we force 7 hydrological models with downscaled outputs of 8 GCMs driven by the A1B and A2 emission scenarios over the 21st century. Results indicate a likely increase in annual runoff by 2100 with a large variability between the different combinations of a climate model with a hydrological model. Differences between GCM projections introduce a gradually increasing relative uncertainty throughout the 21st century. Meanwhile, structural differences between applied hydrological models still contribute to a third of the total uncertainty in late 21st century runoff projections and differences between the two emission scenarios are marginal.

Predicting aquifer response time for application in catchment modeling.

It is well established that changes in catchment land use can lead to significant impacts on water resources. Where land-use changes increase evapotranspiration there is a resultant decrease in groundwater recharge, which in turn decreases groundwater discharge to streams. The response time of changes in groundwater discharge to a change in recharge is a key aspect of predicting impacts of land-use change on catchment water yield. Predicting these impacts across the large catchments relevant to water resource planning can require the estimation of groundwater response times from hundreds of aquifers. At this scale, detailed site-specific measured data are often absent, and available spatial data are limited. While numerical models can be applied, there is little advantage if there are no detailed data to parameterize them. Simple analytical methods are useful in this situation, as they allow the variability in groundwater response to be incorporated into catchment hydrological models, with minimal modeling overhead. This paper describes an analytical model which has been developed to capture some of the features of real, sloping aquifer systems. The derived groundwater response timescale can be used to parameterize a groundwater discharge function, allowing groundwater response to be predicted in relation to different broad catchment characteristics at a level of complexity which matches the available data. The results from the analytical model are compared to published field data and numerical model results, and provide an approach with broad application to inform water resource planning in other large, data-scarce catchments.

Simulation of streamflow and sediment with the soil and water assessment tool in a data scarce catchment in the three gorges region, china.

The Three Gorges Region in China is currently subject to a large-scale land use change, which was induced by the construction of the Three Gorges Dam on the Yangtze River. The relocation of towns, villages, and agricultural areas is expected to affect the water balance and increase erosion rates and sediment yields in the affected catchments. Hydrologic and water quality models are frequently used to assess the impact of land use changes on water resources. In this study, the eco-hydrological Soil and Water Assessment Tool (SWAT) model is applied to the Xiangxi Catchment in the Three Gorges Region. This paper presents the calibration and validation of streamflow and sediment loads at Xingshan gauging station. The calibration of daily streamflow resulted in a satisfactory fit of simulated and observed data, which is indicated by Nash-Sutcliffe efficiency (NSE) values of 0.69 and 0.67 for the calibration (1981-1986) and validation (1988-1993) periods, respectively. In contrast, the model was not able to simulate the monthly average sediment loads correctly, as indicated by very low NSE values of 0.47 (calibration) and 0.08 (validation). This might be due to inadequate representation of spatial rainfall variability by the available climate stations, insufficient input data, uncertainties in the model structure, or uncertainties in the observed sediment loads. The discussion of these possible reasons for the incorrect prediction of sediment loads by SWAT reveals the need for further research in the field of hydrological and water quality modeling in China.

Baseflow prediction in a data-scarce catchment with Inselberg topography, Central Mozambique

This study aimed to improve the understanding of hydrological processes in a humid (sub)tropical area in Africa with Inselberg topography. Additionally, the study intended to develop an approach for selective discharge data acquisition to determine water availability for smallholder irrigation in similar data-scarce catchments. During the December 2012–August 2013 field campaign meteorological and river stage data were collected at the Messica catchment in Central Mozambique. The 220km2 catchment has an estimated 1000ha of irrigated land, developed by smallholder farmers. Baseflow in the perennial tributary streams on the slopes of a meta-sedimentary Inselberg is the source of irrigation water. The baseflow recession curve of one of these tributaries is analysed and the water balance of an average year was determined. Precipitation, potential evapotranspiration, actual evapotranspiration and discharge were estimated to be 1224, 1462, 949 and 266mm/year respectively. Differential gauging showed that the perennial tributaries gain water; the groundwater contribution increased with approximately 50% over two and a half month relative to the downstream discharge from March to May. In the downstream parts the groundwater contribution per metre stream length is between 30% and 100% higher compared to the upstream parts for two of the tributaries. Nevertheless, due to natural streambed infiltration and irrigation canals, discharge varies over the length of these tributaries. A rainfall–runoff model (HBV) was calibrated using the field data to examine the relation between precipitation characteristics and discharge at the start of the dry season. For precipitation scenarios with low and high intensity precipitation, discharges from June onwards were approximately similar in size according to the calibrated model. This suggest that discharge at the start of the dry season is mainly determined by total precipitation and the timing of precipitation (i.e. early or late in the wet season), not by individual rainfall events or rainfall intensity. It is concluded that the use of selective discharge measurements and low frequency precipitation measurements can effectively be used for water availability assessments in Inselberg catchments. Further research should be conducted to verify the validity of the used techniques in other humid sub-tropical Inselberg areas.

Development and application of a nitrogen simulation model in a data scarce catchment in South China

Abstract The Xitiaoxi catchment is one of the most important catchments in the Taihu Basin in southeastern China. It contributes a significant amount of surface runoff and nutrient to Taihu Lake. Understanding the nutrient cycling and identification of critical non-point source pollution in this catchment are therefore of primary importance. In this paper, the Xinanjiang-Nitrogen (XAJ-N) model, a conceptual model of nutrient mobilization and transport is developed by integration of the Xinanjiang rainfall–runoff model, the Integrated Nitrogen CAtchment (INCA) model and the Modified Universal Soil Loss Equation (MUSLE). It is implemented with the environmental modelling language PCRaster and estimates the water fluxes and nutrient loadings on a cell-by-cell basis in daily time steps. The model includes the nitrogen cycling processes of mineralization, leaching, fixation, volatilization, nitrification, denitrification and plant uptake. Nitrogen is assumed to be mobilized by surface runoff and groundwater. The model performance was verified by comparing simulated and measured daily discharge and nutrient loadings. The results showed a fairly good relationship between predicted and observed values. Due to the scarce observed data, the simulation results were also validated using an internal mass balance method and values from the literature. It showed that the modelling approach can be used as a tool to estimate the export of nutrient with a daily resolution at a catchment scale.

Use of soil moisture dynamics and patterns at different spatio-temporal scales for the investigation of subsurface flow processes

Abstract. Spatial patterns as well as temporal dynamics of soil moisture have a major influence on runoff generation. The investigation of these dynamics and patterns can thus yield valuable information on hydrological processes, especially in data scarce or previously ungauged catchments. The combination of spatially scarce but temporally high resolution soil moisture profiles with episodic and thus temporally scarce moisture profiles at additional locations provides information on spatial as well as temporal patterns of soil moisture at the hillslope transect scale. This approach is better suited to difficult terrain (dense forest, steep slopes) than geophysical techniques and at the same time less cost-intensive than a high resolution grid of continuously measuring sensors. Rainfall simulation experiments with dye tracers while continuously monitoring soil moisture response allows for visualization of flow processes in the unsaturated zone at these locations. Data was analyzed at different spacio-temporal scales using various graphical methods, such as space-time colour maps (for the event and plot scale) and binary indicator maps (for the long-term and hillslope scale). Annual dynamics of soil moisture and decimeter-scale variability were also investigated. The proposed approach proved to be successful in the investigation of flow processes in the unsaturated zone and showed the importance of preferential flow in the Malalcahuello Catchment, a data-scarce catchment in the Andes of Southern Chile. Fast response times of stream flow indicate that preferential flow observed at the plot scale might also be of importance at the hillslope or catchment scale. Flow patterns were highly variable in space but persistent in time. The most likely explanation for preferential flow in this catchment is a combination of hydrophobicity, small scale heterogeneity in rainfall due to redistribution in the canopy and strong gradients in unsaturated conductivities leading to self-reinforcing flow paths.

Implementation of a process-based catchment model in a poorly gauged, highly glacierized Himalayan headwater

Abstract. The paper presents a catchment modeling approach for remote glacierized Himalayan catchments. The distributed catchment model TACD, which is widely based on the HBV model, was further developed for the application in highly glacierized catchments on a daily timestep and applied to the Nepalese Himalayan headwater Langtang Khola (360 km2). Low laying reference stations are taken for temperature extrapolation applying a second order polynomial function. Probability based statistical methods enable bridging data gaps in daily precipitation time series and the redistribution of cumulated precipitation sums over the previous days. Snow and ice melt was calculated in a distributed way based on the temperature-index method employing calculated daily potential sunshine durations. Different melting conditions of snow and ice and melting of ice under debris layers were considered. The spatial delineation of hydrological response units was achieved by taking topographic and physiographic information from maps and satellite images into account, and enabled to incorporate process knowledge into the model. Simulation results demonstrated that the model is able to simulate daily discharge for a period of 10 years and point glacier mass balances observed in the research area with an adequate reliability. The simple but robust data pre-processing and modeling approach enables the determination of the components of the water balance of a remote, data scarce catchment with a minimum of input data.