Assessment of LULC and climate change on the hydrology of Ashti Catchment,India using VIC model

The assessment of land use land cover (LULC) and climate change over the hydrology of a catchment has become inevitable and is an essential aspect to understand the water resources-related problems within the catchment. For large catchments, mesoscale models such as variable infiltration capacity (VIC) model are required for appropriate hydrological assessment. In this study, Ashti Catchment (sub-catchment of Godavari Basin in India) is considered as a case study to evaluate the impacts of LULC changes and rainfall trends on the hydrological variables using VIC model. The land cover data and rainfall trends for 40 years (1971–2010) were used as driving input parameters to simulate the hydrological changes over the Ashti Catchment and the results are compared with observed runoff. The good agreement between observed and simulated streamflows emphasises that the VIC model is able to evaluate the hydrological changes within the major catchment, satisfactorily. Further, the study shows that evapotranspiration is predominantly governed by the vegetation classes. Evapotranspiration is higher for the forest cover as compared to the evapotranspiration for shrubland/grassland, as the trees with deeper roots draws the soil moisture from the deeper soil layers. The results show that the spatial extent of change in rainfall trends is small as compared to the total catchment. The hydrological response of the catchment shows that small changes in monsoon rainfall predominantly contribute to runoff, which results in higher changes in runoff as the potential evapotranspiration within the catchments is achieved. The study also emphasises that the hydrological implications of climate change are not very significant on the Ashti Catchment, during the last 40 years (1971–2010).     

Assessment of surface runoff depth changes in Sǎrǎţel River basin,Romania using GIS techniques

Sǎrǎ?el River basin, which is located in Curvature Subcarpahian area, has been facing an obvious increase in frequency of hydrological risk phenomena, associated with torrential events, during the last years. This trend is highly related to the increase in frequency of the extreme climatic phenomena and to the land use changes. The present study is aimed to highlight the spatial and quantitative changes occurred in surface runoff depth in Sǎrǎ?el catchment, between 1990–2006. This purpose was reached by estimating the surface runoff depth assignable to the average annual rainfall, by means of SCS-CN method, which was integrated into the GIS environment through the ArcCN-Runoff extension, for ArcGIS 10.1. In order to compute the surface runoff depth, by CN method, the land cover and the hydrological soil classes were introduced as vector (polygon data), while the curve number and the average annual rainfall were introduced as tables. After spatially modeling the surface runoff depth for the two years, the 1990 raster dataset was subtracted from the 2006 raster dataset, in order to highlight the changes in surface runoff depth.     

Effects of historical and projected land use/cover change on runoff and sediment yield in the Netravati river basin,Western Ghats,India

In this study, the effects of changes in historical and projected land use land cover (LULC) on monthly streamflow and sediment yield for the Netravati river basin in the Western Ghats of India are explored using land use maps from six time periods (1972, 1979, 1991, 2000, 2012, and 2030) and the soil and water assessment tool (SWAT). The LULC for 2030 is projected using the land change modeller with the assumption of normal growth. The sensitivity analysis, model calibration, and validation indicated that the SWAT model could reasonably simulate streamflow and sediment yield in the river basin. The results showed that the spatial extent of the LULC classes of urban (1.80–9.96%), agriculture (31.38–55.75%), and water bodies (1.48–2.66%) increased, whereas that of forest (53.04–27.03%), grassland (11.17–4.41%), and bare land (1.09–0.16%) decreased from 1972 to 2030. The streamflow increased steadily (7.88%) with changes in LULC, whereas the average annual sediment yield decreased (0.028%) between 1972 and 1991 and increased later (0.029%) until 2012. However, it may increase by 0.43% from 2012 to 2030. The results indicate that LULC changes in urbanization and agricultural intensification have contributed to the increase in runoff, amounting to 428.65 and 58.67 mm, respectively, and sediment yield, amounting to 348 and 43 ton/km², respectively, in the catchment area from 1972 to 2030. The proposed methodology can be applied to other river basins for which temporal digital LULC maps are available for better water resource management plans.     

Shallow landslide susceptibility assessment under future climate and land cover changes: A case study from southwest China

There is no doubt that land cover and climate changes have consequences on landslide activity, but it is still an open issue to assess and quantify their impacts. Wanzhou County in southwest China was selected as the test area to study rainfall-induced shallow landslide susceptibility under the future changes of land use and land cover (LULC) and climate. We used a high-resolution meteorological precipitation dataset and frequency distribution model to analyse the present extreme and antecedent rainfall conditions related to landslide activity. The future climate change factors were obtained from a 4-member multi-model ensemble that was derived from statistically downscaled regional climate simulations. The future LULC maps were simulated by the land change modeller (LCM) integrated into IDRISI Selva software. A total of six scenarios were defined by considering the rainfall (antecedent conditions and extreme events) and LULC changes towards two time periods (mid and late XXI century). A physically-based model was used to assess landslide susceptibility under these different scenarios. The results showed that the magnitude of both antecedent effective recharge and event rainfall in the region will evidently increase in the future. Under the scenario with a return period of 100 years, the antecedent rainfall in summer will increase by up to 63% whereas the event rainfall will increase by up to 54% for the late 21st century. The most considerable changes of LULC will be the increase of forest cover and the decrease of farming land. The magnitude of this change can reach + 22.1% (forest) and –9.2% (farmland) from 2010 until 2100, respectively. We found that the negative impact of climate change on landslide susceptibility is greater than the stabilizing effect of LULC change, leading to an over decrease in stability over the study area. This is one of the first studies across Asia to assess and quantify changes of regional landslide susceptibility under scenarios driven by LULC and climate change. Our results aim to guide land use planning and climate change mitigation considerations to reduce landslide risk.     

Impact of city expansion on hydrological regime of Rispana Watershed,Dehradun, India

Rispana River flows through the heart of Dehradun, the capital city of Uttarakhand State, India. Uttarakhand had separated from Uttar Pradesh State in the year 2000; since then, Dehradun City has witnessed numerous changes. Both urban sprawl and densification were noticed, with around a 32% increase in population. The city had faced recurrent high runoff and urban flood situations in these last 2 decades. Therefore, the study was conducted to detect the change in land use/land cover (LULC), especially urbanization, through remote sensing data; and later to determine the impacts of such changes on the Rispana watershed hydrology. The LULC maps for the year 2003 and the 2017 were generated through supervised classification technique using the Landsat Series satellite datasets. The LULC change analysis depicted that mainly the urban settlement class increased with significant area among other classes from the year 2003–2017. It was noticed that majorly agriculture and fallow land (8.18 km², which is 13.52% of total watershed area) converted to urban, increasing the impervious area. Almost all the municipal wards, falling in the Rispana watershed, showed urbanization during the said period, with an increase of as high as 71%. The change in LULC or effect of urbanization on the hydrological response of the watershed was assessed using the most widely used Natural Resources Conservation Services Curve Number method. It was noticed that the area under moderated runoff potential (approx. 10.23 km²) steeply increased during the lean season, whereas, high runoff potential zones (5 km²) increased significantly under wet season. Therefore, it was concluded that an increase in impervious surface resulted in high runoff generation. Further, such LULC change along with climate might lead to high runoff within the watershed, which the present storm drainage network could not withstand. The situation generally led to urban floods and affected urban dwellers regularly. Therefore, it is critical to assess the hydrological impacts of LULC change for land use planning and water resource management. Furthermore, under the smart city project, the local government has various plans to improve present infrastructure; therefore, it becomes necessary to incorporate such observations in the policies.

     

An integrated object-based image analysis and CA-Markov model approach for modeling land use/land cover trends in the Sarab plain

The present paper is an attempt to integrate a semi-automated object-based image analysis (OBIA) classification framework and a cellular automata-Markov model to study land use/land cover (LULC) changes. Land use maps for the Sarab plain in Iran for the years 2000, 2006, and 2014 were created from Landsat satellite data, by applying an OBIA classification using the normalized difference vegetation index, salinity index, moisture stress index, soil-adjusted vegetation index, and elevation and slope indicators. The classifications yielded overall accuracies of 91, 93, and 94% for 2000, 2006, and 2014, respectively. Finally, using the transition matrix, the spatial distribution of land use was simulated for 2020. The results of the study revealed that the number of orchards with irrigated agriculture and dry-farm agriculture in the Sarab plain is increasing, while the amount of bare land is decreasing. The results of this research are of great importance for regional authorities and decision makers in strategic land use planning.     

Evaluation of the Soil Conservation Service curve number methodology using data from agricultural plots

The Soil Conservation Service curve number (SCS-CN) method, also known as the Natural Resources Conservation Service curve number (NRCS-CN) method, is popular for computing the volume of direct surface runoff for a given rainfall event. The performance of the SCS-CN method, based on large rainfall (P) and runoff (Q) datasets of United States watersheds, is evaluated using a large dataset of natural storm events from 27 agricultural plots in India. On the whole, the CN estimates from the National Engineering Handbook (chapter 4) tables do not match those derived from the observed P and Q datasets. As a result, the runoff prediction using former CNs was poor for the data of 22 (out of 24) plots. However, the match was little better for higher CN values, consistent with the general notion that the existing SCS-CN method performs better for high rainfall–runoff (high CN) events. Infiltration capacity (fc) was the main explanatory variable for runoff (or CN) production in study plots as it exhibited the expected inverse relationship between CN and fc. The plot-data optimization yielded initial abstraction coefficient (λ) values from 0 to 0.659 for the ordered dataset and 0 to 0.208 for the natural dataset (with 0 as the most frequent value). Mean and median λ values were, respectively, 0.030 and 0 for the natural rainfall–runoff dataset and 0.108 and 0 for the ordered rainfall–runoff dataset. Runoff estimation was very sensitive to λ and it improved consistently as λ changed from 0.2 to 0.03.     

Regional modelling of rainfall-induced runoff using hydrological model by incorporating plant cover effects: case study in Kelantan,Malaysia

The objective of this paper is to develop a spatial temporal runoff modelling of local rainfall patterns effect on the plant cover hilly lands in Kelantan River Basin. Rainfall interception loss based on leaf area index, loss/infiltration on the ground surface, and runoff calculation were considered as the main plant cover effects on the runoff volume. In this regard, a hydrological and geotechnical grid-based regional model (integrated model) was performed using Microsoft Excel^® and GIS framework system for deterministic modelling of rainfall-induced runoff by incorporating plant cover effects. The infiltration process of the current model was integrated with the precipitation distribution method and rainfall interception approach while the runoff analysis of integrated model was employed based on loss/infiltration water on the ground surface with consideration of water interception loss by canopy and the remaining surface water. In the following, the spatial temporal analysis of rainfall-induced runoff was performed using 10 days of hourly rainfall events at the end of December 2014 in Kelantan River Basin. The corresponding changes in pressure head and consequent rate of infiltration were calculated during rainfall events. Subsequently, flood volume is computed using local rainfall patterns, along with water interception loss and the remaining surface water in the study area. The results showed the land cover changes caused significant differences in hydrological response to surface water. The increase in runoff volume of the Kelantan River Basin is as a function of deforestation and urbanization, especially converting the forest area to agricultural land (i.e. rubber and mixed agriculture).     

Non-point source pollution of Wujiang River watershed in Guizhou Province, SW China

The amount of pollution from non-point sources flowing in the streams of the Wujiang River watershed in Guizhou Province, SW China, is estimated by a GIS-based method using rainfall, surface runoff and land use data. A grid of cells, 100 m in size, is laid over the landscape. For each cell, mean annual surface runoff is estimated from rainfall and percent land use, and expected pollutant concentration is estimated from land use. The product of surface runoff and concentration gives expected pollutant loading from that cell. These loadings are accumulated going downstream to give expected annual pollutant loadings in streams and rivers. By dividing these accumulated loadings by the similarly accumulated mean annual surface runoff, the expected pollutant concentration from non-point sources is determined for each location in a stream or river. Observed pollutant concentrations in the watershed are averaged at each sample point and compared to the expected concentrations at the same locations determined from the grid cell model. In general, annual non-point source nutrient loadings in the Wujiang River watershed are seen to be predominantly from the agricultural and meadow areas.     

Analyzing and modeling of a large river basin dynamics applying integrated cellular automata and Markov model

Historical and exact information about the land use/land cover change is very important for regional sustainable development. The aim of this paper is to determine the rapid changes in land use/land cover (LULC) pattern due to agriculture expansion, environmental calamities such as flood and government policies over Upper Narmada basin, India. Multi-temporal Landsat satellite images for years 1990, 2000, 2010 and 2015 were used to analyze and monitor the changes in LULC with an overall accuracy of more than 85%. Results revealed a potential decrease in natural vegetation (? 9.52%) due to the expansion of settlement (+ 0.52%) and cropland (+ 9.43%) from 1990 to 2015. In the present study, Cellular Automata and Markov (CA–Markov), an integrated tool was used to project the short-term LULC map of year 2030. The projected LULC (2030) indicated the expansion of built-up area along with the cropland and degradation in the vegetation area. The outcomes from the study can help as a guiding tool for protection of natural vegetation and the management of the built-up area. Additionally, it will help in devising the strategies to utilize every bit of land in the study area for decision makers.     

Rainfall-Runoff Modeling using Clustering and Regression Analysis for the River Brahmaputra Basin

In this research, k-means, agglomerative hierarchical clustering and regression analysis have been applied in hydrological real time series in the form of patterns and models, which gives the fruitful results of data analysis, pattern discovery and forecasting of hydrological runoff of the catchment. The present study compares with the actual field data, predicted value and validation of statistical yields obtained from cluster analysis, regression analysis with ARIMA model. The seasonal autoregressive integrated moving average (SARIMA) and autoregressive integrated moving average (ARIMA) models is investigated for monthly runoff forecasting. The different parameters have been analyzed for the validation of results with casual effects. The comparison of model results obtained by K-means & AHC have very close similarities. Result of models is compared with casual effects in the same scenario and it is found that the developed model is more suitable for the runoff forecasting. The average value of R² determined is 0.92 for eight ARIMA models. This shows more accuracy of developed ARIMA model under these processes. The developed rainfall runoff models are highly useful for water resources planning and development.     

Assessing the impacts of rainfall intensity and urbanization on storm runoff in an arid catchment

In the past few decades, rapid urbanization has occurred in many regions of the Kingdom of Saudi Arabia due to increasing population and urban development. Additionally, the effects of global warming on rainfall characteristics have been observed. This rapid change in urbanization and climate change has cause significant changes in the nature of land surfaces and rainfall patterns, which affect the runoff process and the amount of surface runoff during floods. This study investigated the effect of urbanization and rainfall intensity for Hafr Al-Batin watershed located in Saudi Arabia. For this purpose, a hydrologic model, HEC-HMS, was adopted to simulate the flow of different rainfall intesities and urbanization levels. Simulated results showed that for a 100-year storm, a 24-h duration, and an urbanization level of 80%, the peak flow was 213% higher than the estimated current peak and the runoff volume was 112% higher than the current runoff volume. These results show a strong linear correlation between the level of urbanization and both peak discharge and runoff volume. Furthermore, the results indicate that for short return periods, the peak flow is more sensitive to the level of urbanization compared to long periods.     

Assessment of land use land cover change impact on hydrological regime of a basin

The sustainability of water resources mainly depends on planning and management of land use; a small change in it may affect water yield largely, as both are linked through relevant hydrological processes, explicitly. However, human activities, especially a significant increase in population, in-migration and accelerated socio-economic activities, are constantly modifying the land use and land cover (LULC) pattern. The impact of such changes in LULC on the hydrological regime of a basin is of widespread concern and a great challenge to the water resource engineers. While studying these impacts, the issue that prevails is the selection of a hydrological model that may be able to accommodate spatial and temporal dynamics of the basin with higher accuracy. Therefore, in the present study, the capabilities of variable infiltration capacity hydrological model to hydrologically simulate the basin under varying LULC scenarios have been investigated. For the present analysis, the Pennar River Basin, Andhra Pradesh, which falls under a water scarce region in India, has been chosen. The water balance components such as runoff potential, evapotranspiration (ET) and baseflow of Pennar Basin have been simulated under different LULC scenarios to study the impact of change on hydrological regime of a basin. Majorly, increase in built-up (13.94% approx.) and decrease in deciduous forest cover (2.44%) are the significant changes observed in the basin during the last three decades. It was found that the impact of LULC change on hydrology is balancing out at basin scale (considering the entire basin, while routing the runoff at the basin outlet). Therefore, an analysis on spatial variation in each of the water balance components considered in the study was done at grid scale. It was observed that the impact of LULC is considerable spatially at grid level, and the maximum increase of 265 mm (1985–2005) and the decrease of 48 mm (1985–1995) in runoff generation at grid were estimated. On the contrary, ET component showed the maximum increase of 400 and decrease of 570 mm under different LULC change scenario. Similarly, in the base flow parameter, an increase of 70 mm and the decrease of 100 mm were observed. It was noticed that the upper basin is showing an increasing trend in almost all hydrological components as compared to the lower basin. Based on this basin scale study, it was concluded that change in the land cover alters the hydrology; however, it needs to be studied at finer spatial scale rather than the entire basin as a whole. The information like the spatial variation in hydrological components may be very useful for local authority and decision-makers to plan mitigation strategies accordingly.     

Impact of LULC change on the runoff,base flow and evapotranspiration dynamics in eastern Indian river basins during 1985–2005 using variable infiltration capacity approach

As a catchment phenomenon, land use and land cover change (LULCC) has a great role in influencing the hydrological cycle. In this study, decadal LULC maps of 1985, 1995, 2005 and predicted-2025 of the Subarnarekha, Brahmani, Baitarani, Mahanadi and Nagavali River basins of eastern India were analyzed in the framework of the variable infiltration capacity (VIC) macro scale hydrologic model to estimate their relative consequences. The model simulation showed a decrease in ET with 0.0276% during 1985–1995, but a slight increase with 0.0097% during 1995–2005. Conversely, runoff and base flow showed an overall increasing trend with 0.0319 and 0.0041% respectively during 1985–1995. In response to the predicted LULC in 2025, the VIC model simulation estimated reduction of ET with 0.0851% with an increase of runoff by 0.051%. Among the vegetation parameters, leaf area index (LAI) emerged as the most sensitive one to alter the simulated water balance. LULC alterations via deforestation, urbanization, cropland expansions led to reduced canopy cover for interception and transpiration that in turn contributed to overall decrease in ET and increase in runoff and base flow. This study reiterates changes in the hydrology due to LULCC, thereby providing useful inputs for integrated water resources management in the principle of sustained ecology.     

Integrated remote sensing and GIS for surface water development. Case study: Ras El Hekma area, northwestern coast of Egypt

The surface water development can help to address the growing demand for water resources and the effects of stormwater flooding on the local environment. The study area was chosen according to its special conditions where it represents one of the main headlands along the southern Mediterranean coast and receives amount of rainfall during the winter season. The main objective of this paper is to monitor and record data about the current surface water status as well as to have a systematic understanding of the water resources base in the study area, and this assessment will contribute in the exploitation of the surface water. The current research is integration between geomorphology, geology, remote sensing, and the applications of geographical information system. The total amount of annual rainfall and surface runoff are estimated (annual rainfall is 23.345 million m³ and surface runoff is 1.167 million m³). On the other hand, the surface runoff which has been resulted from one event (storm) is also estimated to be 483,000 m³/day. The present study introduce some recommendations; the cisterns should be established in the vicinities of the watersheds and on the downstream of the drainage basins to store water before draining to the sea, the dug should be in oolitic limestone to reduce drilling costs, the water reservoirs should be established to store large amount of surface water (from 2,000 to 3,000 m³). Dams are necessary to protect the agriculture activities from any flash hazard which is expected any time.     

Impacts of future climate and land cover changes on landslide susceptibility: regional scale modelling in the Val d’Aran region (Pyrenees,Spain)

It is widely accepted that future environmental changes will affect rainfall-induced shallow slides in high-mountain areas. In this study, the Val d’Aran region located in the Central Pyrenees was selected to analyze and quantify the impacts of land use and land cover (LULC) and climate changes on regional landslides susceptibility. We analyzed 26 climate models of the EURO-CORDEX database focussing on the future rainfall conditions. The IDRISI TerrSet software suite was used to create the future LULC maps. These two inputs were analyzed individually and in a combined way defining 20 different scenarios. All these scenarios were incorporated in a physically based stability model to compute landslides susceptibility maps. The results showed that both environmental conditions will considerably change in the future. The daily rainfall will increase between 14 and 26% assuming a return period of 100 years. This intensification of precipitation will produce an overall decrease of the stability condition in the study area. Regarding the LULC prediction, the forest area will significantly increase, while in particular grassland, but also shrubs decrease. As a consequence, the overall stability condition improves, because the root strength is higher in forest than in grassland and shrubs. When we analyzed the combined impacts, the results showed that the positive effect of LULC changes is larger than the negative influence of rainfall changes. Hence, when combining the two aspects in the future scenarios, the stability condition in the study area will improve.

     

Deforestation effects on soil properties,runoff and erosion in northern Iran

Improper cultivation practices are seriously degrading native forest ecosystems in northern Iran. Hence, the objectives of this study are to compare selected soil properties, runoff amount, erosion and also introducing equations to predict the runoff and soil erosion in three types of land use (forest, garden and cultivated). A simple portable rainfall simulator has been set in 90 random points to create experimental rainfall. Result showed that changes in natural forest led to a significant clay, organic carbon of soil, total N and antecedent soil moisture decrease and sand, pH and bulk density increasing. The rainfall runoff experiments indicate that runoff content of the natural forest soils was 35 % and respectively 38.45 % higher than the garden and cultivated land soils .This result could be related to the higher antecedent soil moisture in natural forest compared with the other land uses. According to the obtained results, garden soil erosion and cultivated land was 1.351 and respectively 1.587 times higher than the forest. The correlation matrix revealed that runoff content was positively correlated with antecedent soil moisture, bulk density and silt, and negatively with soil organic carbon, total N and sand. Also, soil organic carbon, total N, clay and sand showed negative correlation with soil erosion, while there is a positive correlation between erosion and silt, bulk density, pH and antecedent soil moisture. The results of multiple linear regression showed that runoff in forest, garden and cultivated land can be predicted with correlation coefficient of 0.637, 0.547 and 0.624, respectively. The correlation coefficients of 0.798, 0.628 and 0.560 in equations indicate their moderate potential in simulating soil erosion.     

鄄城县耕地保护问题与对策

2005年末,鄄城县土地更新调查显示耕地面积为66 741 hm2,根据预测规划期变化情况,最终确定2010年耕地保有量目标为66 681 hm2,2020年耕地保有量目标为66 986 hm2。该文总结了鄄城县历年来耕地数量和质量变化情况及其原因,分析存在的问题,预测耕地保护规模与目标,提出进一步加强鄄城县耕地保护的对策措施。     

不同林草系统对集水区水量平衡的影响研究

应用SWAT99.2模型(Soil and Water Assessment Tool),系统地研究了红壤丘岗集水区4种林草系统(自然草被、阔叶林、混交林和针叶林)的地表径流、根层渗漏、蒸发蒸腾、土壤蓄水量的时空特点,并用实测的地表径流对模型进行校正和验证,月地表径流的Nash-Sutcliffe模拟效率系数达到0.74,模拟值和观测值的决定系数达0.90。结果表明,降水的年内分配不均造成了径流、渗漏、土壤蓄水量月份之间的差异,年际间气象条件(特别是降水)的差异性导致了水量平衡支出项的年际差异,其中径流量和渗漏量受降水的影响最大,蒸发蒸腾量次之,土壤蓄水量的年变化量受降水的影响最小;林地能有效地减少区域的地表径流量,其中以阔叶林和混交林的效果最好;林地入渗性能大于草地;蒸发蒸腾量是林地水量平衡支出中最大的一项,且3种林地的蒸发蒸腾量均大于草地。水量平衡的预测结果显示,土地利用方式是区域短期水量平衡的主要影响因子。     

嫩江流域沼泽湿地景观变化及其水文驱动因素分析

借助ArcGIS空间分析工具,以嫩江流域1978年、1990年、2000年和2008年4期遥感湿地分布图为基础,采用SWAT (Soil and Water Assessment Tool)水文模型将嫩江流域划分为43个子流域,并以沼泽湿地类型为例,将各个子流域内降水和径流信息与湿地退化遥感信息作对比筛选,对全流域以及湿地面积减少严重所在子流域作进一步分析。另外,利用两期土地利用类型数据生成嫩江流域土地利用转移矩阵。结果表明:1978—2008年间嫩江流域沼泽湿地退化严重,尤其以1990—2000年间最为显著。这与流域内降水、径流的变化密切相关,并受到土地利用类型转化以及水利工程建设等人类活动的影响。其中,沼泽湿地面积变化与流域径流系数变化在0.01水平上呈极显著正相关,pearson相关系数为0.90。气候变化和人类活动影响下对湿地水文过程以及水资源的变化,导致湿地日益萎缩,对流域内湿地生态系统平衡产生了负面影响。