Journal of Irrigation and Drainage Engineering

Soil erosion, more than any other factor, has more significant and direct impacts on a hydrological watershed in terms of environmental problems. After deriving the erosion hotspots, this study used them to investigate two watersheds, Hocking River Basin and Atwood Lake Basin, in Ohio. Each watershed was divided into $30\times 30\mathrm{m}$ grids, respectively, using the geographic information system (GIS), while the revised universal soil loss equation (RUSLE) was applied to estimate the soil erosion for each grid. Grid values of soil erosion estimates are ranked numerically from the lowest to the highest. Grids of soil erosion estimates equal to or greater than the top 5% value are defined as erosion hotspots to form the erosion hotspot image. Then, assigning individual parameters of land slope, soil type, and land use to be 1, to neutralize individual effects in the RUSLE modeling, three different erosion hotspot images were derived in a similar manner. Overlaying each of these three erosion hotspot images with the original erosion hotspot image, it was found that the land slope factor as a representative topography of the watershed has the most significant effect on erosion hotspots for both watersheds compared with soil types and land uses. Generally, the erosion estimate increases as the land slope increases, but the combination of soil type factor with land slope factor results in more effects on erosion hotspots in the Hocking River Basin than their counterparts in the Atwood Lake Basin. On the other hand, the combination of the land use factor with land slope factor has more effects on erosion hotspots in the Atwood Lake Basin than in the Hocking River Basin.

One of the main problems in the water management of irrigation canals is the control of water distribution among users’ outlets. This is because of the difficulty of measuring the removing flows correctly because they are highly variable in both time and space. To help solve this problem, a mathematical algorithm, the so-called canal monitoring algorithm, which determines the history of lateral extractions, is propounded. It uses the water depth measurements at checkpoints and the gate and other control device trajectories, which are implemented on the canal during a past period of time, and then obtains water withdrawals that happened at the outlets. The method also gives an estimation of the current state of the canal for model predictive control purposes. The algorithm solves the classical inverse problem, in which the unknowns are the parameters that define the flow rate trajectories of canal outlets, which are defined as piecewise functions of time in this paper. The algorithm is on the basis of the Gauss-Newton method and uses the complete Saint-Venant equations for the computation of the least-squared function. Numerical tests with excellent results have highlighted its computational efficiency, converging in a few iterations to the exact final results. These properties make the algorithm adequate to operate in real time. A laboratory canal test for verification shows accuracy in detecting water withdrawals at canal outlets when the Manning roughness coefficients are known. The test also reveals a functional relationship between the discharge removed and the empirical coefficients.

The time of concentration is an important parameter for predicting peak discharge at the basin outlet and for designing urban infrastructure facilities. In studying the hillslope response, employing hydraulic equations of flow, the shape of the hillslope geometry has often been assumed as rectangular and planar. However, natural hillslopes have complex topographies whose shapes are characterized by irregularly spaced contour lines. Recently, kinematic wave time of concentration has been derived for rectangular and curved parallel hillslopes. This paper extends this work to hillslopes of complex planform geometry, considering the degree of divergence or convergence of the hillslope. The extended formulation consists of only one equation that is valid for both divergent/convergent surfaces and for concave/convex hillslope profile, and is compared with the formulations for plane convergent and plane divergent surfaces previously introduced. Results are compared with those already available in the literature, which were obtained by using the nonlinear storage model applied to the same complex hillslopes.

The continuous increase in global population and simultaneous decrease in good-quality water resources emphasize the need of conjunctive use of groundwater and surface-water resources for irrigation. The optimal allocation of water resources can be achieved by employing an appropriate optimization technique. This paper presents an overview of the different programming techniques used for the conjunctive use planning and management of irrigated agriculture. Past papers on the applications of different programming techniques for the conjunctive use of different water sources are grouped into four categories: linear programming, nonlinear programming, dynamic programming, and genetic algorithms. Conclusions are provided based on this review, which could be useful for all stakeholders.

Flow routing is used to simulate or predict downstream hydrographs on the basis of the features of upstream flow hydrographs. This paper combines support vector regression (SVR) and the nondominated sorting genetic algorithm II (NSGAII) into a hybrid hydrologic routing model called SVR-NSGAII in this paper for the prediction of a downstream flow hydrograph in simple and compound channels. The SVR-NSGAII hydrologic routing predictions are compared with those from hydraulic models in simple and compound channels. This paper’s results indicate that the SVR-NSGAII predicts the downstream hydrograph flow in a simple and compound channel, with approximately 94 and 98% accuracy, respectively.

The aim of the present work is to propose an expeditive methodology derived from the one-dimensional (1D) entropy-based model to evaluate the water discharge in rough and smooth irrigation channels based on the knowledge of relative submergence. Recent studies have demonstrated that, for flow in the presence of high and intermediate roughness, corresponding to low flow depth generally, the entropy parameter seems to be dependent on the relative submergence. Whereas, in the case of very low roughness or smooth channels, the mean-to-maximum velocity ratio can be assumed constant at all water stages. Using detailed laboratory data, collected on smooth and rough flumes with different cross section geometries, the paper discusses the relationship existing between the entropy velocity ratio and the relative submergence to give an operative practical rule for water discharge computation and rating curve assessment in irrigation ditches. The comparison between observed and calculated discharges shows very low errors underlying the reliability of the proposed approach.

Quantification of long-term trends and magnitudes of actual crop evapotranspiration (ETc) and crop water productivity [CWP, also known as crop water use efficiency (CWUE)], especially in relation to interannual variation in climate, is critical to determine whether current crop, soil, and irrigation management practices are effective in water conservation and enhancing CWUE. This research quantified and mapped long-term spatio-temporal variability in CWUE, evapotranspiration water use efficiency (ETWUE) and environmental variables associated with it at regional scales for maize (Zea mays L.) and soybean [Glycine max (L.) Merr.] producing counties in Nebraska, from 1986 to 2009. Declining trends were observed in seasonal and annual reference (potential) evapotranspiration (ETref) and irrigated and rainfed maize and soybean ETc. About 15 and 64 mm reduction in seasonal and annual ETref, respectively, were observed from 1986 to 2009 with maximum reduction of 284 mm observed in Zone 4 (eastern subhumid region of Nebraska). A total reduction of 20, 50, 6.7, and 43 mm was observed in irrigated maize, rainfed maize, irrigated soybean, and rainfed soybean ETc, respectively. Analyses of the relationship between annual and seasonal ETref and all the meteorological variables on a large scale showed positive correlation with vapor pressure deficit (VPD), incoming solar radiation (Rs), and wind speed ($u$) with an $R^2$ of 0.85, 0.43, and 0.11, respectively; and inverse relationship with relative humidity (RH) ($R^2=0.51$). The authors found that the statewide decreasing trend in $T_{\text{avg}}$, $T_{\text{min}}$, $u$, and Rs collectively resulted in the overall reduction in ETref over the study area. Time series plots of CWUE and ETWUE were developed to observe potential spatial and temporal variability in CWUE and ETWUE. Counties with a relatively low mean CWUE in combination with low year-to-year consistency have been identified as areas with highest potential for improving CWUE. On a statewide scale, average increases of 34 and 32% were observed in irrigated and rainfed maize CWUE, respectively, and a 34% increase in maize ETWUE. Irrigated and rainfed soybean CWUE have increased by 29 and 33% from 1986 to 2009, respectively, whereas soybean ETWUE increased by 32%. The authors presented detailed spatio-temporal analyses of all the climatic variables that are used to evaluate CWP, which can be valuable to state and federal water management agencies and practitioners to evaluate long-term productivity indices of crop production and associated water productivity indices on large scales for various policy and management decisions as well as future planning and forecasting of crop productivity versus water demand and use, and associated analyses.

The hydrological and hydrogeological setting of a watershed, along with its spatial groundwater distribution, is very important for water resources management purposes. In addition, these factors are the bases for modeling applications. The Mires Basin, which is located on the Island of Crete, has marginal groundwater resources that are extensively used for agricultural activities and human consumption. A broad network of pumping stations was installed in 1984, and as a result productivity has risen at the price of an alarming drop of approximately 35 m in groundwater level during the last 30 years. This study reviews the hydrological and hydrogeological settings of the basin using the most recent available data, explains the declining groundwater level in terms of a statistical and a physically based approach depending on the basin’s groundwater balance, and presents the groundwater level spatial distribution. The latter is obtained by employing the Box-Cox normalization method to increase the accuracy of interpolation, and the recently proposed Spartan variogram function, which delivers improved spatial dependence inference.

Management of irrigation practices takes on a more-prominent role under drought conditions. Watershed-scale drought characterization is performed using cumulative density function (CDF)-based probabilistic drought indices in this case study. To investigate the role of hydrologic variables, either singly or in combination, copulas are used for multivariate joint cumulative density functions (CDFs) combined with graphical models for probabilistic drought classification. Adopting a multivariable, multiscalar approach in the proposed framework yields a drought index that allows for examining the roles of hydrologic variables on integrated drought assessment. The methodology is demonstrated using streamflow, precipitation, and soil-moisture anomalies to develop univariate and multivariate CDF-based indices at one-month, three-month, and six-month time scales to analyze the drought events over an Indiana watershed. Drought characterization varied across the univariate, bivariate, and trivariate drought models in the case study. The multivariate models were able to capture the early onset of drought events and persistence of the drought states, features that are contributed by different components of the hydrologic cycle. While short-term drought monitoring is facilitated by one-month models, threats to long-term water storage in the watershed can be assessed better with longer-time-scale models.

Recently presented climate change scenarios include increasing demand for water, due to both increase in temperature and variations in precipitation pattern. Since crop water requirements are related to climate and irrigation scheduling depends on crop evapotranspiration (ETc), it is crucial to have tools that allow the estimation of ETc in a reliable way. ETc is often calculated as the product of two factors, the reference evapotranspiration (ETo) and crop coefficient (Kc) values that convert ETo to ETc. This paper reviews Kc values, measured in different parts of the world and in different climates, with the aim to offer a practical tool for selecting the most appropriate Kc values for water balance irrigation scheduling, which result in more efficient irrigation. More than 100 scientific papers were studied and summarized in a report, accompanied by an extensive Kc database. The Kc report and database are available in the “Supplemental Data” section of this paper.