scholarly journals Simplicity versus complexity in modelling groundwater recharge in Chalk catchments

2002 ◽  
Vol 6 (5) ◽  
pp. 927-937 ◽  
Author(s):  
R. B. Bradford ◽  
R. Ragab ◽  
S. M. Crooks ◽  
F. Bouraoui ◽  
E. Peters

Abstract. Models of varying complexity are available to provide estimates of recharge in headwater Chalk catchments. Some measure of how estimates vary between different models can help guide the choice of model for a particular application. This paper compares recharge estimates derived from four models employing input data at varying spatial resolutions for a Chalk headwater catchment (River Pang, UK) over a four-year period (1992-1995) that includes a range of climatic conditions. One model was validated against river flow data to provide a measure of their relative performance. Each model gave similar total recharge for the crucial winter recharge period when evaporation is low. However, the simple models produced relatively lower estimates of the summer and early autumn recharge due to the way in which processes governing recharge especially evaporation and infiltration are represented. The relative uniformity of land use, soil types and rainfall across headwater, drift-free Chalk catchments suggests that complex, distributed models offer limited benefits for recharge estimates at the catchment scale compared to simple models. Nonetheless, distributed models would be justified for studies where the pattern and amount of recharge need to be known in greater detail and to provide more reliable estimates of recharge during years with low rainfall. Keywords: Chalk, modelling, groundwater recharge

2009 ◽  
Vol 40 (2-3) ◽  
pp. 167-176 ◽  
Author(s):  
I. Bärlund ◽  
K. Rankinen ◽  
M. Järvinen ◽  
E. Huitu ◽  
N. Veijalainen ◽  
...  

Inorganic nitrogen loading was simulated using two dynamic catchment scale models, Integrated Nutrients in Catchments–Nitrogen (INCA-N) and the Generalized Watershed Loading Functions (GWLF). The simulated N loading was compared to a standard method to calculate annual loading using measured discharge and discharge-weighted concentrations. The main aim of the study was to compare these three estimation approaches with regards to their performance in hydrologically variable years in a small headwater catchment in southern Finland. Inter-annual variability of INCA-N and GWLF was compared with measured inorganic N concentrations at the catchment outlet. In years where snow melt dominates the annual discharge pattern all methods gave concurrent annual loading estimates. However, the loading estimates differ between the studied methods in years where large rainfall events in late summer or autumn dominate the annual discharge pattern, or when the model was not able to reproduce the spring discharge maximum properly. The results suggest that both models can be useful tools in estimating dissolved inorganic nitrogen loading from a catchment under changing climate conditions, providing that the key influencing driver, hydrology, is well captured.


2017 ◽  
Vol 21 (5) ◽  
pp. 2579-2594 ◽  
Author(s):  
Hidayat Hidayat ◽  
Adriaan J. Teuling ◽  
Bart Vermeulen ◽  
Muh Taufik ◽  
Karl Kastner ◽  
...  

Abstract. Wetlands are important reservoirs of water, carbon and biodiversity. They are typical landscapes of lowland regions that have high potential for water retention. However, the hydrology of these wetlands in tropical regions is often studied in isolation from the processes taking place at the catchment scale. Our main objective is to study the hydrological dynamics of one of the largest tropical rainforest regions on an island using a combination of satellite remote sensing and novel observations from dedicated field campaigns. This contribution offers a comprehensive analysis of the hydrological dynamics of two neighbouring poorly gauged tropical basins; the Kapuas basin (98 700 km2) in West Kalimantan and the Mahakam basin (77 100 km2) in East Kalimantan, Indonesia. Both basins are characterised by vast areas of inland lowlands. Hereby, we put specific emphasis on key hydrological variables and indicators such as discharge and flood extent. The hydroclimatological data described herein were obtained during fieldwork campaigns carried out in the Kapuas over the period 2013–2015 and in the Mahakam over the period 2008–2010. Additionally, we used the Tropical Rainfall Measuring Mission (TRMM) rainfall estimates over the period 1998–2015 to analyse the distribution of rainfall and the influence of El-Niño – Southern Oscillation. Flood occurrence maps were obtained from the analysis of the Phase Array type L-band Synthetic Aperture Radar (PALSAR) images from 2007 to 2010. Drought events were derived from time series of simulated groundwater recharge using time series of TRMM rainfall estimates, potential evapotranspiration estimates and the threshold level approach. The Kapuas and the Mahakam lake regions are vast reservoirs of water of about 1000 and 1500 km2 that can store as much as 3 and 6.5 billion m3 of water, respectively. These storage capacity values can be doubled considering the area of flooding under vegetation cover. Discharge time series show that backwater effects are highly influential in the wetland regions, which can be partly explained by inundation dynamics shown by flood occurrence maps obtained from PALSAR images. In contrast to their nature as wetlands, both lowland areas have frequent periods with low soil moisture conditions and low groundwater recharge. The Mahakam wetland area regularly exhibits low groundwater recharge, which may lead to prolonged drought events that can last up to 13 months. It appears that the Mahakam lowland is more vulnerable to hydrological drought, leading to more frequent fire occurrences than in the Kapuas basin.


2007 ◽  
Vol 4 (3) ◽  
pp. 1369-1406 ◽  
Author(s):  
M. Firat

Abstract. The use of Artificial Intelligence methods is becoming increasingly common in the modeling and forecasting of hydrological and water resource processes. In this study, applicability of Adaptive Neuro Fuzzy Inference System (ANFIS) and Artificial Neural Network (ANN) methods, Generalized Regression Neural Networks (GRNN) and Feed Forward Neural Networks (FFNN), for forecasting of daily river flow is investigated and the Seyhan catchment, located in the south of Turkey, is chosen as a case study. Totally, 5114 daily river flow data are obtained from river flow gauges station of Üçtepe (1818) on Seyhan River between the years 1986 and 2000. The data set are divided into three subgroups, training, testing and verification. The training and testing data set include totally 5114 daily river flow data and the number of verification data points is 731. The river flow forecasting models having various input structures are trained and tested to investigate the applicability of ANFIS and ANN methods. The results of ANFIS, GRNN and FFNN models for both training and testing are evaluated and the best fit forecasting model structure and method is determined according to criteria of performance evaluation. The best fit model is also trained and tested by traditional statistical methods and the performances of all models are compared in order to get more effective evaluation. Moreover ANFIS, GRNN and FFNN models are also verified by verification data set including 731 daily river flow data at the time period 1998–2000 and the results of models are compared. The results demonstrate that ANFIS model is superior to the GRNN and FFNN forecasting models, and ANFIS can be successfully applied and provide high accuracy and reliability for daily River flow forecasting.


1961 ◽  
Vol 41 (1) ◽  
pp. 124-133 ◽  
Author(s):  
J. A. Robertson

The Newdale Soil Association of Manitoba consists of a number of genetic soil types which are the result of local variations in relief, drainage and vegetation. Seven of these soil types were examined in the field and studied in the laboratory in an attempt to relate their characteristics to the factors responsible for their formation.It was found that the depth of the solum of these soils increased the farther down the slope the soil occurred, because of greater amounts of water entering the soil and the resultant cooler, moister soil climate. The per cent of exchangeable hydrogen also followed this trend. Where local soil-climatic conditions favoured the invasion of trees into the grassland area, the soils exhibited considerable degradation. This was revealed by the marked clay illuviation, the greater per cent of exchangeable hydrogen and the lower amount of organic carbon in the soils found under tree vegetation. Internal drainage had an important influence on the type of soil developed in the depressional areas.


Author(s):  
Ionuț Minea ◽  
Oana Elena Chelariu

Abstract Regional water resource management plans include various scenarios related to the anomalies and trends of hydro-climatic parameters. Two methods are used for the identification of the anomalies and trends associated with high flow (annual and seasonal) of the rivers in Eastern Romania, namely the quantile perturbation method (QPM) and the partial trend method (PMT). These methods were selected due to the fact that they are suitable for data sets which do not rely on restrictive statistical assumption as common parametric and nonparametric trend tests do. For six of the nine stations analyzed, the decreasing trend in high extremes for annual high flow based on the PTM is the same as the annual trend obtained with the QPM. Using the PI index (associated with PTM) for the estimation of trend intensity, values between −2.280 and −9.015 m3/s were calculated for the decreasing trend of the annual high flow and between +1,633 m3/s (in autumn) and −9.940 m3/s (in summer) for the seasonal high flow. The results obtained on the anomalies and trends of high river flow may represent a starting point in the analysis of the evolution of water resources and their effective management.


2019 ◽  
Vol 11 (4) ◽  
pp. 1072 ◽  
Author(s):  
Xin Jin ◽  
Yanxiang Jin ◽  
Xufeng Mao

Land use/cover change (LUCC) affects canopy interception, soil infiltration, land-surface evapotranspiration (ET), and other hydrological parameters during rainfall, which in turn affects the hydrological regimes and runoff mechanisms of river basins. Physically based distributed (or semi-distributed) models play an important role in interpreting and predicting the effects of LUCC on the hydrological processes of river basins. However, conventional distributed (or semi-distributed) models, such as the soil and water assessment tool (SWAT), generally assume that no LUCC takes place during the simulation period to simplify the computation process. When applying the SWAT, the subject river basin is subdivided into multiple hydrologic response units (HRUs) based on the land use/cover type, soil type, and surface slope. The land use/cover type is assumed to remain constant throughout the simulation period, which limits the ability to interpret and predict the effects of LUCC on hydrological processes in the subject river basin. To overcome this limitation, a modified SWAT (LU-SWAT) was developed that incorporates annual land use/cover data to simulate LUCC effects on hydrological processes under different climatic conditions. To validate this approach, this modified model and two other models (one model based on the 2000 land use map, called SWAT 1; one model based on the 2009 land use map, called SWAT 2) were applied to the middle reaches of the Heihe River in northwest China; this region is most affected by human activity. Study results indicated that from 1990 to 2009, farmland, forest, and urban areas all showed increasing trends, while grassland and bare land areas showed decreasing trends. Primary land use changes in the study area were from grassland to farmland and from bare land to forest. During this same period, surface runoff, groundwater runoff, and total water yield showed decreasing trends, while lateral flow and ET volume showed increasing trends under dry, wet, and normal conditions. Changes in the various hydrological parameters were most evident under dry and normal climatic conditions. Based on the existing research of the middle reaches of the Heihe River, and a comparison of the other two models from this study, the modified LU-SWAT developed in this study outperformed the conventional SWAT when predicting the effects of LUCC on the hydrological processes of river basins.


2003 ◽  
Vol 48 (10) ◽  
pp. 127-134 ◽  
Author(s):  
S.M. Dunn ◽  
N. Chalmers ◽  
M. Stalham ◽  
A. Lilly ◽  
B. Crabtree ◽  
...  

Legislation to control abstraction of water in Scotland is limited and for purposes such as irrigation there are no restrictions in place over most of the country. This situation is set to change with implementation of the European Water Framework Directive. As a first step towards the development of appropriate policy for irrigation control there is a need to assess the current scale of irrigation practices in Scotland. This paper presents a modelling approach that has been used to quantify spatially the volume of water abstractions across the country for irrigation of potato crops under typical climatic conditions. A water balance model was developed to calculate soil moisture deficits and identify the potential need for irrigation. The results were then combined with spatial data on potato cropping and integrated to the sub-catchment scale to identify the river systems most at risk from over-abstraction. The results highlight that the areas that have greatest need for irrigation of potatoes are all concentrated in the central east-coast area of Scotland. The difference between irrigation demand in wet and dry years is very significant, although spatial patterns of the distribution are similar.


2017 ◽  
Vol 21 (7) ◽  
pp. 3325-3352 ◽  
Author(s):  
Christa Kelleher ◽  
Brian McGlynn ◽  
Thorsten Wagener

Abstract. Distributed catchment models are widely used tools for predicting hydrologic behavior. While distributed models require many parameters to describe a system, they are expected to simulate behavior that is more consistent with observed processes. However, obtaining a single set of acceptable parameters can be problematic, as parameter equifinality often results in several behavioral sets that fit observations (typically streamflow). In this study, we investigate the extent to which equifinality impacts a typical distributed modeling application. We outline a hierarchical approach to reduce the number of behavioral sets based on regional, observation-driven, and expert-knowledge-based constraints. For our application, we explore how each of these constraint classes reduced the number of behavioral parameter sets and altered distributions of spatiotemporal simulations, simulating a well-studied headwater catchment, Stringer Creek, Montana, using the distributed hydrology–soil–vegetation model (DHSVM). As a demonstrative exercise, we investigated model performance across 10 000 parameter sets. Constraints on regional signatures, the hydrograph, and two internal measurements of snow water equivalent time series reduced the number of behavioral parameter sets but still left a small number with similar goodness of fit. This subset was ultimately further reduced by incorporating pattern expectations of groundwater table depth across the catchment. Our results suggest that utilizing a hierarchical approach based on regional datasets, observations, and expert knowledge to identify behavioral parameter sets can reduce equifinality and bolster more careful application and simulation of spatiotemporal processes via distributed modeling at the catchment scale.


Water ◽  
2019 ◽  
Vol 11 (9) ◽  
pp. 1790 ◽  
Author(s):  
Muhammad Afzal ◽  
Ragab Ragab

Although the climate change projections are produced by global models, studying the impact of climatic change on water resources is commonly investigated at catchment scale where the measurements are taken, and water management decisions are made. For this study, the Frome catchment in the UK was investigated as an example of midland England. The DiCaSM model was applied using the UKCP09 future climate change scenarios. The climate projections indicate that the greatest decrease in groundwater recharge and streamflow was projected under high emission scenarios in the 2080s. Under the medium and high emission scenarios, model results revealed that the frequency and severity of drought events would be the highest. The drought indices, the Reconnaissance Drought Index, RDI, Soil Moisture Deficit, SMD and Wetness Index, WI, predicted an increase in the severity of future drought events under the high emission scenarios. Increasing broadleaf forest area would decrease streamflow and groundwater recharge. Urban expansion could increase surface runoff. Decreasing winter barley and grass and increasing oil seed rape, would increase SMD and slightly decrease river flow. Findings of this study are helpful in the planning and management of the water resources considering the impact of climate and land use changes on variability in the availability of surface and groundwater resources.


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