The Pros and Cons of Encouraging Shallow Groundwater Use through Controlled Drainage in a Salt-Impacted Irrigation Area

Encouraging shallow groundwater use through water table management or controlled drainage in irrigated areas can relief crop water stress under water shortage condition. But substituting fresh irrigation water with saline groundwater may speed up salinity buildup in the crop root zone, and consequently increase water use for salt leaching. With a proposed analytical model, this paper presents a case study demonstrating the effect of encouraging shallow groundwater use through controlled drainage on salt and water management in a semi-arid irrigation area in northwestern China. Based on the average rainfall condition, the model assumes that salt accumulates in the crop root zone due to irrigation and shallow groundwater use; till the average soil salinity reaches the crop tolerance level, leaching irrigation is performed and the drainage outlet is lowered to discharge the salt-laden leaching water. For the relatively salt tolerant crop–cotton in the study area, the predicted leaching cycle was as long as 751 days using the fresh water (with salinity of 0.5 g/L) irrigation only; it was shortened to 268 days when the water table depth was controlled at 2 m and 23% of the crop water requirement was contributed from the saline groundwater (with salinity of 4.43 g/L). The predicted leaching cycle was 140 days when the water table depth was controlled at 1.5 m and groundwater contribution was 41% of the crop water requirement; it was shortened to 119 days when the water table depth was controlled at 1.2 m and the groundwater contribution was 67% of the crop water requirements. So the benefit from encouraged shallow groundwater use through controlled drainage is obtained at the expense of shortened leaching cycle; but the shallow groundwater use by crops consists of a significant portion of crop water requirements, and the leaching cycle remains long enough to provide a time window for scheduled leaching in the off season of irrigation. Weighing the pros and cons of the encouraged shallow groundwater use may help plan irrigation and drainage practices to achieve higher water use efficiency in saline agricultural areas.     

Coupled Quantity-Quality Simulation-Optimization Model for Conjunctive Surface-Groundwater Use

Many water resources optimization problems involve conflicting objectives which the main goal is to find a set of optimal solutions on, or near to, Pareto front. In this study a multi-objective water allocation model was developed for optimization of conjunctive use of surface water and groundwater resources to achieve sustainable supply of agricultural water. Here, the water resource allocation model is based on simulation-optimization (SO) modeling approach. Two surrogate models, namely an Artificial Neural Network model for groundwater level simulation and a Genetic Programming model for TDS concentration prediction were coupled with NSGA-II. The objective functions involved: 1) minimizing water shortage relative to the water demand, 2) minimizing the drawdown of groundwater level, and 3) minimizing the groundwater quality changes. According to the MSE and R² criteria, the results showed that the surrogate models for prediction of groundwater level and TDS concentration performed favorably in comparison to the measured values at the number of observation wells. In Najaf Abad plain case study, the average drawdown was limited to 0.18 m and the average TDS concentration also decreased from 1257 mg/lit to 1229 mg/lit under optimal conditions.     

Model Based Assessment of Nitrate Pollution of Water Resources on a Federal State Level for the Dimensioning of Agro-environmental Reduction Strategies

The main goal of the project was to assess nitrogen pollution of surface waters and groundwater in the Federal State of North Rhine Westphalia (NRW), Germany. For this purpose the hydro(geo-)logical models GROWA-DENUZ/WEKU were coupled to the agro-economic model RAUMIS in order to assess the diffuse nitrogen loads and to approaches to determine the nitrogen loads from point sources. In this way the complex socio-economic interrelations and hydrological/hydrogeological interdependencies were simultaneously. The model network was applied consistently across the whole territory of NRW. At first the actual N inputs into groundwater and surface waters resulting from diffuse sources and point sources were assessed. For the relevant diffuse input pathways (groundwater runoff, drainage runoff and natural interflow) this was done in a spatial resolution of 100 m???100 m. In the case of point source inputs information from municipal waste water treatment plants, industrial effluents, rainwater sewers and combined sewer overflows has been considered. For NRW an actual total N input into surface waters of ca. 117.000 t???a^?1?N has been quantified. As the inputs via natural interflow (ca. 30 %), groundwater runoff (ca. 26 %) and drainage systems (ca. 18 %) hold the largest portion, it is evident that measures to control nitrate pollution have to focus on the inputs from diffuse sources. For this purpose, initially the development of the agrarian sector according to the Common Agricultural Policy, CAP until 2015 including supplementary measures and other impact factors has been analysed. The impact of this so-called baseline scenario 2015 was predicted for both, the diffuse N surpluses and the N pollution of groundwater and surface waters. It could be shown that the baseline projections for the agricultural sector through 2015 may lead to decrease of the diffuse N inputs into groundwater by ca. 13.500 t???a^?1?N and an overall decrease of the diffuse N inputs into surface waters by ca. 25.000 kg???ha^?1???a^?1?N. Based on the baseline scenario 2015 the additional N reduction to guarantee nitrate concentrations in groundwater below the EU-threshold value of 50 mg???l^?1 NO₃ was determined by means of a backward model calculation. This was done using the predicted nitrate concentrations in the leachate 2015 for the individual 100 m???100 m grids as starting points. In this way for the whole territory of NRW an additional N reduction beyond the baseline scenario 2015 of ca. 12.000 t???a^?1?N has been assessed. Model results indicate that additional N reduction measures don’t have to be implemented area-covering in order to be efficient, but in certain subareas only. It is suggested that in these subareas the available financial resources for the implementation of N reduction measures shall be used for individual, i.e. regionally adapted nitrate reduction measures.     

Application of NN-ARX Model to Predict Groundwater Levels in the Neishaboor Plain, Iran

There is no doubt that groundwater is an important and vital source of water supply in arid and semi-arid areas. Therefore, prediction of groundwater level fluctuations is necessary for planning conjunctive use in these areas. This research was aimed to predict groundwater levels in the Neishaboor plain using Neural Network – AutoRegressive eXtra input (NN-ARX) and Static-NN models. The NN-ARX model determines a nonlinear ARX model of a dynamic system by training a hidden layer neural network with the Levenberg-Marquardt algorithm. In this model the current outputs depend not only on the current inputs, but also on the inputs and outputs at the pervious time periods. The available observation wells in the study area were clustered according to their fluctuation behavior using the “Ward” method, which resulted in six areal zones. Then, for each cluster, an observation well was selected as its representative, and for each zone, values of monthly precipitation, temperature and groundwater extraction were estimated. The best input of the Static-NN model was identified using combination of Gamma Test and Genetic Algorithm. Also, Gamma Test is applied to identify the length of the training dataset. The results showed that the NN-ARX model was suitable and more practical. The performance indicators (R ²?=?0.97, RMSE?=?0.03 m, ME?=?--0.07 m and R ²?=?0.81, RMSE?=?0.35 m, ME?=?0.60 m, respectively for the best and worst performance of model) reveals the effectiveness of this model. Moreover, these results were compared with the results of a static-NN model using t-test, which showed the superiority of the NN-ARX over the static-NN.     

Soil Water Distribution and Movement in Layered Soils of a Dam Farmland

In soil profiles, special emphasis has been placed on the migration of agricultural chemicals spread intentionally or accidentally into deep soils or groundwater body. To prevent soil water pollution and estimate the magnitude of the hazard caused by these chemicals, it is necessary to know the processes controlling their movement from the soil surface, through the root zone and eventually to the water table. This paper deals with two-dimensional soil water distribution and movement in sloping layered soils of a dam farmland on the Loess Plateau of China. In the dam farmland, soil water content showed horizontal distribution corresponding to spatial patterns of the particle sizes. The soil water content of deeper soil was relatively stable compared with topsoil. Generally, rainfall infiltration was limited to 0.8 m in the study period. Funnel flows were found in the layered soils of the dam farmland after rainfall proving the existence of this phenomenon which was observed in simulation experiments and field observation by previous researches. In the study area, the wetting front was unstable due to the layered soils. The spatial correlation analysis of the soil water content showed water movement along the layers in the wetting process with 7 m day^???1 only on the first day after rainfall. On the vertical direction, the velocity of water movement was 0.3 m day^???1 on the first day after rainfall. The results indicated that the quantity of funnel flow increases with distance along the inclined interfaces in the dam farmland which can cause contamination of groundwater. Consequently, future studies should consider the funnel flow and the management of agriculture chemicals in dam farmlands.     

Interrelationships between Hydrology and Ecology in Fire Degraded Tropical Peat Swamp Forests

Interrelationships between hydrology and ecology are established for the Air Hitam Laut watershed in Jambi Province, Sumatra, Indonesia. The developed relational diagram shows how modelled regional groundwater levels and flooding patterns are related to the occurrence of different vegetation types in this endangered peatland watershed. In dry conditions when groundwater levels are deeper than 1 m below soil surface, fire disasters are unavoidable. When areas susceptible to fire actually burn and both vegetation and peat disappear, the total inundated area will expand with a factor five. In wet conditions with groundwater levels of more than 1 m above soil surface for a prolonged period of time, flooding creates lakes where no plant species can regrow. In the intermediate range, rehabilitation of different plant species is promising and is related to the actual hydrological regime.     

Estimation of Groundwater Recharge from the Rainfall and Irrigation in an Arid Environment Using Inverse Modeling Approach and RS

Quantifying recharge from agricultural areas is important to sustain long-term groundwater use, make intelligent groundwater allocation decisions, and develop on-farm water management strategies. The scarcity of data in many arid regions, especially in the Middle East, has necessitated the use of combined mathematical models and field observations to estimate groundwater recharge. This study was designed to assess the recharge contribution to groundwater from rainfall and irrigation return flow in the Mosian plain, west of Iran. The Inverse modeling approach and remote sensing technology (RS) were used to quantify the groundwater recharge. The recharge for steady–state conditions was estimated using the Recharge Package of MODFLOW. The land-use map for the research area was produced using remote sensing and satellite images technology. According to results, groundwater recharge from the rainfall and irrigation return flow was at the rate of 0.15 mm/day. The recharge to the groundwater from rainfall was about 0.08 mm/day (10.8 % of total rainfall). The average of groundwater recharge contribution in the study area was about 0.39 mm/day that include 15.2 % of the total water used in the irrigated fields. We can conclude that irrigation water is the most important resource of groundwater recharge in this area, consequently, it should be integrated into relevant hydrological models as the main source of groundwater recharge.     

污染物击穿防污屏障与地下水土污染防控研究进展

鉴于防污屏障是控制固废填埋场地下水土污染的重要结构,为评价防污屏障的服役寿命,分别针对重金属和有机污染物,总结了污染物在黏土屏障和复合屏障中的一维运移解析解,包括非线性吸附条件下污染物在黏土屏障中的一维扩散解、污染物在有缺陷膜复合屏障中的一维运移解和温度场作用下污染物在黏土屏障中的耦合运移解析解等。评价了污染物击穿防污屏障长历时过程超重力离心模型试验的可靠性。对运行了17 a的安徽某填埋场进行现场调查,发现氯离子运移最大深度达9 m,钠离子和COD的运移深度在3~4 m。总结和评价了地下水土污染控制的竖向屏障技术,认为土-膨润土系竖向隔离墙技术在我国具有广阔的应用前景,并对今后的研究进行展望。     

Incorporating Influences of Shallow Groundwater Conditions in Curve Number-Based Runoff Estimation Methods

Runoff generation process in any watershed is mainly affected by precipitation, land use and land cover, existing soil moisture conditions and losses. Shallow groundwater table conditions that occur in many regions are known to affect the soil moisture retention capacity, infiltration and ultimately the runoff. A methodology that links soil moisture capacity to the shallow groundwater table or High-Water Table (HWT) using a nonlinear functional relationship within a curve number (CN)-based runoff estimation method, is proposed and investigated using single and continuous event simulation models in this study. The relationship is used to obtain an adjusted CN that incorporates the effect of change in soil moisture conditions due to HWT. The CN defined for average conditions is replaced by this adjusted CN and is used for runoff estimation. A single event model that uses Soil Conservation Service (SCS) CN approach is used for evaluation of variations in runoff depths and peak discharges based on different HWT conditions. A real-life case study from central Florida region in the USA was adopted for application and evaluation of the proposed methodology. Results from the case study application of the models indicate that HWT conditions significantly influence the magnitudes of peak discharge by as much as 43% and runoff depth by 48% as the water table height reaches the land surface. The magnitudes of increases in peak discharges are specific to case study region and are dependent on the functional form of the relationship linking HWT and soil storage capacity. Also, for specific values of HWT, an equivalency between HWT-based CN and wet antecedent moisture condition (AMC)-based CN can be established.     

Application of Several Data-Driven Techniques for Predicting Groundwater Level

In this study, several data-driven techniques including system identification, time series, and adaptive neuro-fuzzy inference system (ANFIS) models were applied to predict groundwater level for different forecasting period. The results showed that ANFIS models out-perform both time series and system identification models. ANFIS model in which preprocessed data using fuzzy interface system is used as input for artificial neural network (ANN) can cope with non-linear nature of time series so it can perform better than others. It was also demonstrated that all above mentioned approaches could model groundwater level for 1 and 2 months ahead appropriately but for 3 months ahead the performance of the models was not satisfactory.     

Delineation of Groundwater Potential Zones of Coastal Groundwater Basin Using Multi-Criteria Decision Making Technique

Delineation of groundwater potential zones (GWPZ) has been performed for a coastal groundwater basin of eastern India. The groundwater potential zone index (GWPZI) map is generated by using Analytic Hierarchy Process (AHP) from different influencing features, e.g., Land Use/Land Cover (LU/LC), soil (S), geomorphology (GM), hydrogeology (HG), surface geology (SG), recharge rate (RR), drainage density (DD), rainfall (RF), slope (Sl), surface water bodies (SW), lineament density (LD), and Normalized Difference Vegetative Index (NDVI). Recharge rate values are estimated from hydrological water balance model. Overlay weighted sum method is used to integrate all thematic feature maps to generate GWPZ map of the study area. Four zones have been identified for the coastal groundwater basin [very good: 36.39 % (273.53 km², good: 43.57 % (327.47 km²), moderate: 18.27 % (137.30 km²), and poor: 1.77 % (13.27 km²)]. Areas in north to south-west and south-east direction show very good GWPZ due to the presence of low drainage density. GWPZ map and well yield values show good agreement. Sensitivity analysis reveals that exclusion/absence of rainfall and lineament density increases the poor groundwater potential zones. Omission of hydrogeology, soils, surface geology, and NDVI show maximum increase in good GWPZ. Obtained GWPZ map can be utilized effectively for planning of sustainable agriculture. This analysis demonstrates the potential applicability of the methodology for a general coastal groundwater basin.     

Exploring the Mechanism of Surface and Ground Water through Data-Driven Techniques with Sensitivity Analysis for Water Resources Management

The over extraction of groundwater in central-western and southwestern Taiwan has resulted in serious land subsidence for decades. For making countermeasures in response to land subsidence, this study collects long-term hydrological data to explore the relationships between surface water and groundwater in various monitoring stations, and then constructs one-month-ahead forecast models by using data-driven techniques for the water resources management of the Zhuoshui River basin in Taiwan. The results demonstrate that the constructed models can accurately forecast monthly groundwater levels. The sensitivity analysis is next conducted on the input variables of the constructed models by using the partial derivative method. The analysis results reveal that streamflow is a predominant factor for groundwater level variation, and therefore streamflow management made by the upstream weir of the river would influence groundwater level variations. This study further implements several scenario analyses based on the interactive mechanism between groundwater and surface water in response to future climatic conditions and weir discharge management, respectively. The results of scenario analyses indicate that the groundwater recharge zone spreads along the Zhuoshui River while lateral and vertical recharge sources would cause different quantities and distribution patterns of groundwater recharge. Besides, an increase in weir discharge would improve groundwater recharge quantities with groundwater level variations at 0.12 m and 0.06 m in wet and dry seasons, respectively. As a consequence, the operation of weir discharge would play an import role in sustainable development of water resources management in the study area.     

Understanding groundwater table using a statistical model

In this study, a statistical model was established to estimate the groundwater table using precipitation, evaporation, the river stage of the Liangduo River, and the tide level of the Yellow Sea, as well as to predict the groundwater table with easily measurable climate data in a coastal plain in eastern China. To achieve these objectives, groundwater table data from twelve wells in a farmland covering an area of 50 m × 150 m were measured over a 12-month period in 2013 in Dongtai City, Jiangsu Province. Trend analysis and correlation analysis were conducted to study the patterns of changes in the groundwater table. In addition, a linear regression model was established and regression analysis was conducted to understand the relationships between precipitation, evaporation, river stage, tide level, and groundwater table. The results are as follows:(1) The groundwater table was strongly affected by climate factors(e.g., precipitation and evaporation), and river stage was also a significant factor affecting the groundwater table in the study area( p 0.01, where p is the probability value).(2) The groundwater table was especially sensitive to precipitation. The significance of the factors of the groundwater table were ranked in the following descending order:precipitation, evaporation, and river stage.(3) A triple linear regression model of the groundwater table, precipitation, evaporation, and river stage was established. The linear relationship between the groundwater table and the main factors was satisfied by the actual values versus the simulated values of the groundwater table(R~2 = 0.841, where R~2 is the coefficient of determination).     

Risk-Based Evaluation for Meeting Future Water Demand of the Brahmaputra Floodplain Within Bangladesh

A risk-based evaluation is performed for meeting future water demands in the Brahmaputra Floodplain Area within Bangladesh (BFA). This evaluation is carried out using three risk-based performance indicators: reliability, resiliency and vulnerability. The vulnerability indicator has been redefined incorporating the aspect of a supply failure. The analysis includes the impacts of climate change on both water demands and resources, and the generation of synthetic flows of the Brahmaputra River using time series models. The simulated values of the indicators reveal that the expected demand of the BFA up to the year 2050 can be supplied with the proposed Brahmaputra Barrage inside Bangladesh under the ‘no change’ in climatic condition, provided that the groundwater remains usable. However, if groundwater becomes unusable due to widespread arsenic contamination and/or a climate change occurs, it would not be possible to meet the future water demand of the region with high reliability, moderate resiliency and low vulnerability.     

Integrated Approach for Identifying Suitable Sites for Rainwater Harvesting Structures for Groundwater Augmentation in Basaltic Terrain

Integrated hydrological, geophysical and groundwater modeling studies has been carried out for identification of suitable sites for rainwater harvesting structures for groundwater augmentation in RRCAT Campus, Indore, M.P. Based on these studies ten check dams, two contour bunds and one earthen bund were recommended on the existing stream channels and in valley fills respectively. Likely water impoundment on these structures was calculated keeping in view the length and width of stream channels. Based on these study a groundwater flow model using MODFLOW were carried out keeping in view the geologic and hydrologic conditions of the area. The net rechargeable impounded rain water from these structures to groundwater regime was calculated for monsoon seasons which varied from 20 % to 48 % and net enhancement of groundwater recharge from all structures would be around 0.11 mcm/year and the water level in the existing well would rise by 2–3 m above its present level for future Groundwater augmentation.     

Estimation of Groundwater Balance Using Soil-Water-Vegetation Model and GIS

This study concerns the development of a methodology using modern techniques of data generation (Modeling) and interpretation (GIS) to compute groundwater plausibly at regional scale, alternate to previously established norms. The approach is centered on quantitative estimation of two main parameters-input and output. GIS techniques along with soil vegetation model (CropSyst) have been demonstrated for the calculation of groundwater balance components. Using the developed methodology water resources of the Ludhiana district for the period between, 2000 and 2010 were estimated. The temporal changes in water balance components indicated that the major inputs to the hydrologic system are rainfall and canal water and the major out component are evapotranspiration (ET). Multi-annual (2000 to 2010) average of 719 mm rainfall, 88 mm canal water, 74 mm of groundwater inflow, with annual loss 974 mm as ET, caused 123 mm of net negative groundwater recharge in Ludhiana district. The annual computed rise/fall with the developed methodology closely matched the observed values.     

A Holistic System Approach to Understanding Underground Water Dynamics in the Loess Tableland: A Case Study of the Dongzhi Loess Tableland in Northwest China

The Loess Plateau in northwest China is one of the most water-scarce areas on Earth. In the loess tableland (LT), the underground water system is the most critical component of terrestrial ecology and the local economy. In this study, a new approach was developed to holistically simulate monthly and yearly underground hydrology in the LT, including the soil water reservoir (SWR) and the groundwater reservoir (GWR). The approach was applied to the Dongzhi Loess Tableland (DLT) to simulate SWR and GWR from 1981 to 2010 to capture the underground water dynamics. The results suggest a strong monthly variability of the SWR, with most time of a year having higher evapotranspiration than the precipitation infiltration, leading to a soil water deficit. The rainy season is the primary period for deep zone recharge, and the water balance of the GWR is generally positive from July to October and negative from November to the following June. In the DLT, The decrease in vertical recharge and increase in human extraction have led to a total groundwater level drawdown of 15.7 m and considerable spring attenuation with an annual ratio of 1.19 % over the past 30 years. If ground water withdraw rate remains the same as since 1981, the GWR will be depleted within approximately 100 years.     

Quantifying the Poorly Known Role of Groundwater in Agriculture: the Case of Cyprus

Agriculture in the Mediterranean region is constrained by limited water resources and in many countries irrigation demand exceeds the renewable water supply. This paper presents a comprehensive approach to (a) quantify the consumptive green (soil moisture provided by precipitation) and blue (irrigation) water use for crop production, (b) distinguish the contribution of groundwater to irrigation supply and (c) estimate groundwater over-abstraction. A spatiotemporally explicit soil water balance model, based on the FAO-56 dual crop coefficient approach, which includes the computation of evaporation losses of the different irrigation systems, was applied to the 5,760-km² area of the Republic of Cyprus for the agro-meteorological years 1995–2009. The model uses national agricultural statistics, community-level data from the agricultural census and daily data from 34 meteorological stations and 70 precipitation gauges. Groundwater over-abstraction is quantified per groundwater body, based on the sustainable abstraction rates specified in the Cyprus River Basin Management Plan, as prepared for the EU Water Framework Directive. It was found that, on average, total agricultural water use was 506 Mm³/year, of which 62 % is attributed to green water use and 38 % to blue water use. Groundwater contributed, on average, 81 % (151 Mm³/year) to blue water use and exceeded the recommended abstraction rates by 45 % (47 Mm³/year). Even though the irrigated area decreased by 18 % during the 2008 drought year, relative to the wettest year (2003), total blue water use decreased by only 1 %. The limited surface water supply during the driest year resulted in a 37 % increase in groundwater use, relative to the wettest year, and exceeded the sustainable abstraction rate by 53 % (55 Mm³/year). Overall, the model provides objective and quantitative outcomes that can potentially contribute to the improvement of water resource management in Mediterranean environments, in the light of climate change and expected policy reforms.     

潜水入渗补给研究进展

目前,对土壤水运移机理研究已从定性走向定量、从均质走向非均质。优先流是地下水入渗的普遍现象,在田间土壤水主要以捷径流方式入渗补给地下水。对优先流研究是潜水入渗补给研究的重点与难点之一,其主要方法为染色示踪与X射线成像和地质雷达技术。潜水入渗补给评价方法众多,且每种方法都有其适用条件。因此,综合采用示踪法、地下水位波动法、地中渗透仪法、零通量法和数值模拟法,相互对比验证,提高评价可靠性,是研究地下水入渗补给最有效的方法。     

A Wavelet-ANFIS Hybrid Model for Groundwater Level Forecasting for Different Prediction Periods

Artificial neural network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) have an extensive range of applications in water resources management. Wavelet transformation as a preprocessing approach can improve the ability of a forecasting model by capturing useful information on various resolution levels. The objective of this research is to compare several data-driven models for forecasting groundwater level for different prediction periods. In this study, a number of model structures for Artificial Neural Network (ANN), Adaptive Neuro-Fuzzy Inference System (ANFIS), Wavelet-ANN and Wavelet-ANFIS models have been compared to evaluate their performances to forecast groundwater level with 1, 2, 3 and 4 months ahead under two case studies in two sub-basins. It was demonstrated that wavelet transform can improve accuracy of groundwater level forecasting. It has been also shown that the forecasts made by Wavelet-ANFIS models are more accurate than those by ANN, ANFIS and Wavelet-ANN models. This study confirms that the optimum number of neurons in the hidden layer cannot be always determined by using a specific formula but trial-and-error method. The decomposition level in wavelet transform should be determined according to the periodicity and seasonality of data series. The prediction of these models is more accurate for 1 and 2 months ahead (for example RMSE?=?0.12, E?=?0.93 and R ²?=?0.99 for wavelet-ANFIS model for 1 month ahead) than for 3 and 4 months ahead (for example RMSE?=?2.07, E?=?0.63 and R ²?=?0.91 for wavelet-ANFIS model for 4 months ahead).