Integrating runoff map of a spatially distributed model and thematic layers for identifying potential rainwater harvesting suitability sites using GIS techniques

Rainwater harvesting (RWH) is one of the major techniques that is investigated in the present study using Analytic Hierarchy Process (AHP) and Weighted Linear Combination (WLC) methods as two tools for decision-making, weighting and combining different thematic layers include land use, slope, drainage density and hydrological soil groups (HSG). The runoff map obtained by the distributed spatial-physical WetSpa model is considered as a useful layer that is integrated with other thematic layers in the geographic information system (GIS) environment for identifying RWH sites. Kakareza watershed (1132 km2) in Iran was selected as a study area to carry out the foregoing approach. The results showed that 256 km2 of the study area is good for RWH, 360 km2 is moderate and 516 km2 is poor. Thus, about 22.61% (256 km2) of Kakareza watershed is highly suitable for farm ponds. This article recommends the RWH suitable sites to a judicious decision for better water management in the area

Application of partial least squares regression and WetSpa model to determine factors controlling sediment yield in Chardavol watershed, Iran

This paper examines the effects of watershed complexity in terms of physiography and land use on the specific sediment yield of the Chardavol watershed (1012.946 km2) in Iran. First, specific sediment yield was simulated using spatially distributed hydrological WetSpa model, then the influential factors such as morphometric variables, land-use composition and pattern and soil properties of the watershed were calculated at the sub-watershed scale. Due to the inter-reliant of these watershed characteristics, a partial least squares regression (PLSR) was used to illustrate the relationship between the specific sediment yield and data of 15 selected watershed characteristics. The results showed that the land-use composition and soil properties had the maximum effects on the specific sediment yield and clarified 79% of the variation in the specific sediment yield. Regarding the availability of digital spatial database over the watershed, this simple PLSR procedure could be applied in different watersheds

Application of GIS-based data-driven models for groundwater potential mapping in Kuhdasht region of Iran

Water shortage and population growth in Iran rapidly diminish groundwater supplies. Thus, finding the techniques such as GIS that can be used as powerful tools in groundwater management, and predicting groundwater potential is required. The main objective of this study is to evaluate the efficiency of the statistical index (SI), frequency ratio (FR) weights of evidence (WoE) and evidential belief function (EBF) models for groundwater potential mapping at Kuhdasht region, Lorestan province, Iran. For this purpose, 12 groundwater influencing factors were considered in this investigation. From 171 available wells in the study area, 114 wells (67%) and 57 wells (33%) were used based on random selection in SI, FR, WoE and EBF models as training and validation data-sets, respectively. The area under the ROC curve (AUC) for SI, FR, WoE and EBF models was calculated as 91.8, 91, 93.6 and 93.3%, respectively. These curve values indicated that all four models have reasonably good accuracy in spatially predicting groundwater potential in this area

Flood hazard zoning in Yasooj region, Iran, using GIS and multi-criteria decision analysis

Flood is considered to be the most common natural disaster worldwide during the last decades. Flood hazard potential mapping is required for management and mitigation of flood. The present research was aimed to assess the efficiency of analytical hierarchical process (AHP) to identify potential flood hazard zones by comparing with the results of a hydraulic model. Initially, four parameters via distance to river, land use, elevation and land slope were used in some part of the Yasooj River, Iran. In order to determine the weight of each effective factor, questionnaires of comparison ratings on the Saaty's scale were prepared and distributed to eight experts. The normalized weights of criteria/parameters were determined based on Saaty's nine-point scale and its importance in specifying flood hazard potential zones using the AHP and eigenvector methods. The set of criteria were integrated by weighted linear combination method using ArcGIS 10.2 software to generate flood hazard prediction map. The inundation simulation (extent and depth of flood) was conducted using hydrodynamic program HEC-RAS for 50- and 100-year interval floods. The validation of the flood hazard prediction map was conducted based on flood extent and depth maps. The results showed that the AHP technique is promising of making accurate and reliable prediction for flood extent. Therefore, the AHP and geographic information system (GIS) techniques are suggested for assessment of the flood hazard potential, specifically in no-data regions

The effect of different sampling schemes on estimation precision of snow water equivalent (SWE) using geostatistics techniques in a semi-arid region of Iran

The aim of this study is to compare the effect of two sampling patterns: systematic sampling and Latin hypercube sampling (LHS), on estimation precision of snow water equivalent (SWE), and also comparing different geostatistics methods of kriging, cokriging and radial basin functions for mapping SWE. To achieve the study purpose, the semi-arid mountainous watershed of Sohrevard in Zanjan Province of Iran was selected. Snow depth in 150 points with systematic sampling and 150 points with LHS sampling and snow density in 18 points were randomly measured. In addition, SWE was calculated in the study area, and its map was derived based on both the sampling methods using geostatistical techniques. The results showed that the accuracy of the SWE map using LHS was higher than systematic sampling. According to the most statistical indicators, in both methods of sampling, accuracy of mapping using regular spline was better than other methods

Spatial prediction of flood-susceptible areas using frequency ratio and maximum entropy models

Modelling the flood in watersheds and reducing the damages caused by this natural disaster is one of the primary objectives of watershed management. This study aims to investigate the application of the frequency ratio and maximum entropy models for flood susceptibility mapping in the Madarsoo watershed, Golestan Province, Iran. Based on the maximum entropy and frequency ratio methods as well as analysis of the relationship between the flood events belonging to training group and the factors affecting on the risk of flooding, the weight of classes of each factor was determined in a GIS environment. Finally, prediction map of flooding potential was validated using receiver operating characteristic (ROC) curve method. ROC curve estimated the area under the curve for frequency ratio and the maximum entropy models as 74.3% and 92.6%, respectively, indicating that the maximum entropy model led to better results for evaluating flooding potential in the study area

Applicability of generalized additive model in groundwater potential modelling and comparison its performance by bivariate statistical methods

Groundwater is the most valuable natural resource in arid areas. Therefore, any attempt to investigate potential zones of groundwater for further management of water supply is necessary. Hence, many researchers have worked on this subject all around the world. On the other hand, the Generalized Additive Model (GAM) has been applied to environmental and ecological modelling, but its applicability to other kinds of predictive modelling such as groundwater potential mapping has not yet been investigated. Therefore, the main purpose of this study is to evaluate the performance of GAM model and then its comparison with three popular GIS-based bivariate statistical methods, namely Frequency Ratio (FR), Statistical Index (SI) and Weight-of-Evidence (WOE) for producing groundwater spring potential map (GSPM) in Lorestan Province Iran. To achieve this, out of 6439 existed springs, 4291 spring locations were selected for training phase and the remaining 2147 springs for model evaluation. Next, the thematic layers of 12 effective spring parameters including altitude, plan curvature, slope angle, slope aspect, drainage density, distance from rivers, topographic wetness index, fault density, distance from fault, lithology, soil and land use/land cover were mapped and integrated using the ArcGIS 10.2 software to generate a groundwater prospect map using mentioned approaches. The produced GSPMs were then classified into four distinct groundwater potential zones, namely low, moderate, high and very high classes. The results of the analysis were finally validated using the receiver operating characteristic (ROC) curve technique. The results indicated that out of four models, SI is superior (prediction accuracy of 85.4%) following by FR, GAM and WOE, respectively (prediction accuracy of 83.7, 77 and 76.3%). The result of groundwater spring potential map is helpful as a guide for engineers in water resources management and land use planning in order to select suitable areas to implement development schemes and also government entities

Modeling and assessing the effects of land use changes on runoff generation with the CLUE-s and WetSpa models

Land use change is an important determinant of hydrological processes and is known to affect hydrological parameters such as runoff volume, flood frequency, base flow, and the partitioning into surface flow and subsurface flow. The main objective of this research was to assess the magnitude of the effect of land use changes on runoff parameters, using the Baghsalian watershed in Iran as a case study site. At first, land use maps of years 1986 and 2012 were prepared using synthetic method, and then simulation was done based on land use changes in the 1986 to 2012 period. Land use map of year 2030 was simulated using CLUE-s model. Spatially distributed hydrological WetSpa model was used to simulate runoff at daily scale with land use maps of 1986, 2012, and 2030. Total volume of runoff, peak flow, and surface flow were compared. The accuracy of the WetSpa model simulation was assessed with the Nash-Sutcliffe efficiency, which had values of 0.61 and 0.56% for the calibration and validation dataset, respectively. The aggregation measure criterion was also calculated and had values of 64 and 62% for the calibration and validation periods, respectively. The main land use changes in Baghsalian watershed between 1986, 2012, and 2030 were the conversion of forest and rangeland to agriculture and residential land use types. Because of these conversions, simulated total runoff volume increased; and the rate of increase in surface runoff was larger than the rate of increase in subsurface runoff. In addition, surface and subsurface runoff increased in 2012 and 2030 compared to 1986 land use map, but the rate of increase of subsurface runoff was less than surface runoff.</p